literature review on women empowerment

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Revisiting the Impact Evaluation of Women’s Empowerment: A MCDM-Based Evaluation Indicator Selection Framework Proposal

• Original Research
• Open access
• Published: 31 January 2024
• Volume 172 , pages 121–145, ( 2024 )

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• Nihan Yıldırım   ORCID: orcid.org/0000-0002-6279-3849 1 &
• Fatma Köroğlu   ORCID: orcid.org/0000-0002-3367-1308 1  

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Women’s empowerment programs play a critical role in achieving the United Nations’ (UN’s) sustainable development goal of “Gender Equality”. However, non-profit organizations (NPOs) running women’s empowerment (WE) programs face challenges in monitoring, assessing, and evaluating the social impact (SI) and program performance due to the lack of solid guidelines. This study aims to analyze the impact and outcome evaluation indicators of WE programs by providing a quantitative tool. A multi-criteria decision-making (MCDM) model is proposed to identify and prioritize the performance indicators by utilizing Fuzzy TOPSIS (FTOPSIS) and Fuzzy AHP (FAHP) in a combined methodology. Results validated the identification and classification of the indicators by their importance and viability. In a qualitative study with NPOs working on WE in Turkey, social impact and outcome evaluation indicators are defined and ranked by criteria set in the proposed combined MCDM framework. The study aims to contribute to the theoretical frameworks and practices on social impact and outcome evaluation of women’s empowerment.

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1 Introduction

The economic empowerment of women and girls is a process whereby women and girls experience transformation in power and agency, as well as economic advancement (Pereznieto & Taylor, 2014 ). Social intervention programs in WE gained momentum as an urgent issue in the social economy agenda towards contributing to the Sustainable Development Goal (SDG) “No. 5 Gender Equality” of the UN with an emphasis on all women and girls’s economic empowerment. UN linked WE with “sense of self-worth”, “right to have access to opportunities and resources”, “right to have the power to control their own lives, both within and outside the home”, and “ability to influence the direction of social change to create a more just social and economic order, nationally and internationally” (IOM, 2017 ). The vital connection between economic and gender-based inequality often adversely impacts women’s well-being (Hughes, 2015 ), especially in male-dominant communities where women are mostly limited to household activities. Therefore, the analysis of WE is essential for any social work-related context (Basimatory et al., 2023 ; Sell & Minot, 2018 ).

In literature and practice, women’s economic empowerment projects are discussed in a large spectrum varying from the role of microfinance institutions (Rehman et al., 2020 ) to agricultural production (Johnson et al., 2018 ) and entrepreneurial activities (Karki & Xheneti, 2018 ) which can be empowering only if they can eliminate the limitation brought by gender roles. The change in women’s marginalization in the labor market cannot be overpassed on the way to WE (Güney-Frahm, 2018 ). NPOs play a considerable role in these efforts due to insufficient support from the government and society with patriarchal norms (Gupta, 2021 ). In Turkey as a developing country, women’s labor participation rate in 2022 was 37.3%, strikingly lower than OECD countries (64.8%) (OECD, 2020 ). The employment rate of women of working age was also much lower (35.5%) than OECD average (62.5%) (OECD, 2020 ). Many NPOs and their stakeholders work toward women’s economic empowerment to improve these rates in Turkey; however, they face performance-related challenges primarily due to inefficient monitoring and evaluation of their projects’ outputs, outcomes, and SIs.

SI refers to a logical chain starting with organizational inputs, leading to outputs, outcomes, and societal impacts (Ebrahim & Rangan, 2010 ). NPOs and practitioners must assess social interventions to maximize resource utilization and stakeholder satisfaction. SI program execution demands performance reporting and monitoring with contextual indicators for timely corrective and preventive actions. NPOs often struggle in measurement design at project inception, due to flawed theory of change (ToC) and inappropriate indicators (Güner, 2021 ). Furthermore, the existing frameworks like MEAL and SRI lack context-specific indicators, while costly SI consultancy services and templates prove inefficient without real-time program data.

Effective Social Impact Measurement (SIM) demands robust indicators (Alexander et al., 2010 ). For social entrepreneurs and enterprises, the lack of shared metrics hampers planning, stakeholder communication (Nicholls, 2009 ), and gaining support (Bengo et al., 2016 ). Local capacity for community-level SIMs is essential (Bice, 2020 ), requiring tailored indicators. However, the literature review reveals a scarcity of research on selecting performance indicators for women’s empowerment. Glennerster et al. ( 2018 ) listed the “varying meaning of empowerment in different contexts” and “prioritizing outcome measures” among the challenges in measuring women’s and girls’ empowerment. For the former, using findings from formative research is suggested for selecting or developing context-specific, locally tailored indicators to complement empowerment indicators with more standard ones. The literature review also revealed the MCDM methods are underutilized in SIM indicator selection, and few research employ them for ranking SI indicators in women’s economic empowerment.

In brief, despite the richness of research streams regarding women’s empowerment policies (Tirka Widanti, 2023 ) and WE indicators, literature gaps persist in two key areas: (1) lacking quantitative frameworks for selecting WE indicators across different contexts, necessitating the application of MCDM models to enhance consistency and validity through sensitivity analysis, mitigating expert subjectivity (Bengo et al., 2016 ); (2) underutilization of MCDM techniques for prioritizing SIM indicators, despite their widespread use in related domains such as ranking organizations based on their SI (Amrita et al., 2018 ; Bengo et al., 2020 ; Dzunic et al., 2018 ).

Following this suggestion, this paper aims to contribute to the WE theory and practice by providing context-specific indicator lists and rankings for WE programs. By this aim, we proposed a quantitative MCDM model for SIM in WE, with an application on Turkish WE programs, utilizing the expert opinions of program implementers and Non-governmental organization (NGO) experts gathered through interviews and surveys. The findings have the potential to offer guidance to program designers, implementers, and evaluators, focusing on indicators directly impacting women’s economic empowerment and contributing to the achievement of the UN’s 5th SDG—Gender Equality. Additionally, the proposed MCDM model for indicator selection aids NGOs in aligning indicators with the Theory of Change and context-based outcomes (Bice, 2020 ).

The study primarily defines the 17 performance indicators based on the data gathered through interviews with experts from 11 WE NGOs in Turkey. Surveys with 12 WE program executors (Key Informants) and experts enabled the evaluation of the importance (weights) of each criterion (measurability, attainability, relevance, replicability, and usability in various contexts) by Fuzzy AHP. Followingly, the Fuzzy TOPSIS method ranked and prioritized the indicators by using the weighted criteria obtained from FAHP. The results are validated through the consistency check and sensitivity analysis and ensure the robustness of the methodology. Finally, the discussion of the results provided a thorough understanding of the indicators along with the theoretical and practical implications and policy recommendations.

The following sections present a literature review on SIM, indicators and measurement of women’s empowerment, and MCDM methods. After introducing the methodological flow, the paper proceeds with the findings from the FTOPSIS—FAHP applications for prioritizing the indicators. The final section presents the concluding remarks with a discussion of the results.

2 Literature Review on Social Impact Measurement and Women’s Empowerment Indicators

2.1 social impact and social impact measurement.

SI is “the consequences to human populations of any public and private actions altering how people work, live, play, relate to one another, organize to meet their needs, and generally act as a member of society.” (Burdge & Vanclay, 1996 ). The SIM as a tool for validating the contributions to social goals transformed into a non-dismissible part of policy formation for many institutions, from business corporations to NPOs (Becker, 2001 ). NPOs are increasingly expected to prove their SI, hence to assure their sponsors of the results for enabling the continuity of funds from their present and future donors (Arvidson & Lyon, 2014 ). However, the need for SIM arises from the requirement of satisfying the funders and those NPOs’ self-evaluation (Arvidson & Lyon, 2014 ). NPOs’ recognition of their social value and benefits that the stakeholders perceive is highly critical (Polonsky et al., 2016 ).

However, challenges in practicing SIM, such as varying assumptions of project members and consultants about social value or the lack of a shared understanding, often undermine the quality of SIM and utilization of the improvement opportunities (Vanclay et al., 2015 ). Inappropriate or non-contextual indicators hinder the validity of impact measurement while the dilemma of “what to do” versus “how to do” misguides the design of the SIM process, shifting the sole focus from outcomes to the outputs. Also, the SI is a new topic among practitioners in Turkey, with limited examples and resources (Güner & Keskin, 2021 ). Lack of expertise in designing the SIM process has always been a significant barrier in social projects (Social Impact Task Force, 2000 ). Köroğlu and Yıldırım ( 2023 ) also highlighted this challenge in the context of SIM processes of NGO-led WE projects in Turkey.

2.2 Determinants and Indicators of Women’s Empowerment

The concept of empowerment has a multi-dimensional focus on “resources” (control over physical, financial, human, and intellectual resources (Kabeer, 1999 )), “the agency” (having the capacity and freedom to make individual life choices implies agencies (Desai, 2010 ; Sen, 2009 )), and achievement (the functioning constituted by agencies and resources together) (Basumatary et al., 2023 ; Sell & Minot, 2018 ). Proper impact assessment methods, indicators, and appropriate project execution strategies are critical for the success of WE projects.

Women’s empowerment is an inspiring but also challenging concept for monitoring and evaluation specialists (Bishop & Bowman, 2014 ):

It is inspiring to consider the potential for evaluation to illustrate and support truly transformational but often hidden changes.

It is challenging from the measurement perspective—an abstract and contested concept boasting a range of sometimes-dry definitions causing failure in capturing its transformational elements.

In this context, Landig ( 2011 ) analyzed the effectiveness of 3 EU-funded WE projects in Turkey and pointed out these projects aiming to increase the number of women in the workforce became more successful when evaluated and monitored. The possible interventions of an agency empowering a social group were categorized by Rowlands ( 1997 ) into four power types: (1) empowerment as a choice (power to do)—domain-specific autonomy and household decision-making; (2) empowerment as control (power over)—control over personal decisions; (3) empowerment as change (power from within)—changing aspects in one’s life (communal level) and communal belonging; and (4) empowerment in a community (power with)—changing aspects in one’s life (individual level). Referring to Rowland’s ( 1997 ) typology, Pereznieto and Taylor ( 2014 ) and Carter et al. ( 2014 ) categorized WE into four dimensions being referred to as “change outcomes” in WE interventions:

Power within the knowledge, individual capabilities, sense of entitlement, self-esteem, and self-belief to make changes in their lives, including learning skills to get a job or start an enterprise.

Power to economic decision-making within their household, community, and local economy (including markets), not just in areas being traditionally regarded as women’s realm, but extending to areas being traditionally regarded as men’s realm.

Power over access to and control over financial, physical, and knowledge-based assets, including access to employment and income-generation activities.

Power with the ability to organize with others to enhance economic activity and rights.

In Rowlands' typology, some proposed indicators of empowerment in general were also introduced by Ibrahim and Alkire ( 2007 ). In evaluating WE, Carter et al. ( 2014 ) noted quantitative methods emphasize 'power-to,' and qualitative methods offer broader insights.

The United Nations Foundation’s (UNF’s) guidance on Measuring Women’s Economic Empowerment classifies the outcomes of WE programs as direct, intermediate, and indirect (Buvinic & Furst-Nichols, 2013 ). Though these topics are widely acknowledged as primary determinants of WE, at the first step, a ToC should be mapped to select the most appropriate indicators for a reliable measurement strategy tailored to specific empowerment interventions (Glennerster &Takavarasha, 2013 ; Glennerster et al., 2018).

Though it is essential to use interventions and domain-specific measures in the empowerment context, the measures include a core set of concepts (Alkire, 2005 ; Glennerster et al., 2018 ). Three determinants (psychological patterns of society, family, and women) affect six indicators ((1) education, (2) educational freedom, (3) economic contribution, (4) economic freedom, (5) household management and decision-making, (6) perceived status within the household and health)) directly influencing WE status (Sharma & Bansal, 2017 ). Some primarily available measurement frameworks with indicators or measures of women's economic empowerment are the International Center for Research on Women’s (ICRW) modules (Golla et al., 2011 ), Women’s Empowerment in Agriculture Index (WEAI) (Malapit et al., 2019 ), or the guide of Glennerster et al. ( 2018 ) prepared for NPO usage. However, in academic studies, we have not found studies significantly fitting this problem’s context. International organizations like UNF, World Bank, GroW, and Oxfam also provided a list of WE topics (Aletheia et al., 2017 ; Alkire et al., 2013 ; Buvinic & Furst-Nichols, 2013 ; Bishop & Bowman, 2014 ; Golla et al., 2011 ; Laszlo & Grantham, 2017 ; Lombardini et al., 2017 , Glennerster et al., 2018 ):

Women’s access to and control over resources, including income and assets;

Participation in important decisions at the personal, household, and community level;

Control over reproductive health and fertility choices;

Subjective well-being and happiness; mobility;

Time use and sharing domestic work;

Freedom from violence;

Community and political participation;

Well-being outcomes in domains like education, health, and labor;

Women claiming and enjoying their rights;

Being able to make decisions about the direction of their lives;

Beginning to access power denied to them.

Recently, Basumatary et al. ( 2023 ) constructed a Women’s Empowerment Index (WEI) for handloom weavers (HW), adopting 25 indicators from Oxford Poverty and Human Development (OPHI), the Women’s Empowerment in Agriculture Index (Alkire et al., 2013 ); and the Women’s Empowerment Index for self-help groups women by Roy et al. ( 2018 ), in seven domains: economic empowerment, household empowerment, participation in the political and social sphere, health, involvement in fertility-related decisions, media, and leisure time/time allocation. However, like many other WE indices, this study gives the domains and indicators equal weight.

2.3 Women’s Empowerment Indicators Selection

The literature is wide regarding the frameworks used for measuring WE, such as the study of Roy et al. ( 2018 ), which proposed an index for measuring WE in India. Similarly, Naranayan et al. proposed a methodology for developing an index for WE in the nutrition context in India, where they selected the indicators via factor analysis and normative lenses (2019). A Ghana study measured employment's impact on WE by considering objective and subjective indicators derived from the literature and applying regression for the results (2020). Nevertheless, even though the computation process was systematical, the selection or ranking of the indicators lacked an analytical approach. Amrita et al. ( 2018 ) assessed women entrepreneurship projects’ performance indicators with Fuzzy AHP, however, it was also limited to the entrepreneurship context.

As Richardson ( 2018 ) suggested, research practices measuring WE lack an analytical approach for minimizing human judgment while considering the criteria and a measurement model for constructed indicator selection. In this regard, this study aims to fill this gap by proposing an MCDM model for WE indicator selection that can be applied to various projects or programs. The following section further reveals our findings regarding the rare application of quantitative methodologies, such as MCDM methods, for selecting and ranking indicators in the WE context.

3 Literature Review on Multi-criteria Decision-Making Approaches in Indicator Selection

Numerous studies employ MCDM approaches in various contexts: for instance, Ozkaya et al. ( 2021 ) in science, technology, and innovation indicators of countries; Mavi ( 2014 ) in ranking entrepreneurial universities’ indicators using Fuzzy TOPSIS and Fuzzy AHP; Anand et al. ( 2017 ) in evaluating sustainability indicators in smart cities with Fuzzy AHP; Singh et al. ( 2022 ) in construction safety with Fuzzy TOPSIS; Pansare et al. ( 2023 ) in reconfigurable manufacturing systems with a hybrid Fuzzy TOPSIS-Fuzzy AHP approach; Rao ( 2021 ) utilizing DEMATEL-ANP-based Method (DANP) for assessing sustainability indicators through corporate social responsibility reports in Taiwan; and Jiang et al. ( 2020 ) employing Z-DEMATEL in identifying key performance indicators in hospital management. Additional methods like Fuzzy DEMATEL, Fuzzy ANP, and MOORA are also evident, particularly in the shipbuilding industry (Gavalas et al., 2022 ).

MCDM methods also find extensive use in SIM. For instance, Dzunic et al. ( 2018 ) employed Entropy to rank SIs and TOPSIS to rate social enterprises in the context of people who parted from society. Stankovic et al. ( 2021 ) used an integrated approach with Entropy and Preference Ranking Organization Method for the Enrichment of Evaluations (PROMETHEE). Lamata et al. ( 2018 ) created an MCDM framework using AHP and TOPSIS to help investors decide the superior company in corporate social responsibility. Rafiaani et al. ( 2020 ) applied TOPSIS to rank SI indicators in Carbon capture and utilization (CCU). Bengo et al. ( 2020 ) introduced a Naive-scoring-based framework for SIM approaches. Adhikhari et al. ( 2023 ) evaluated WE across various domains using AHP and TOPSIS, though limited to measurement rather than indicator selection or ranking. Some studies opt for fuzzy extensions of AHP and TOPSIS due to their ability to tackle the challenges of traditional methods by bringing a realistic solution to complicated decision problems (Dang et al., 2019 ).

MCDM methodologies have demonstrated their ability to aid stakeholders in pinpointing and reaching a consensus on sustainable solutions across various sectors (Buchholz et al., 2009 ). However, adopting an MCDM method has pros and cons, with the choice of a method determining the outcomes. Multi-criteria methods encompass various categories, including weighting, ordinal approaches, utility function-based techniques, relationship handling, and methods centered around measuring proximity to an ideal alternative (Gomes & Gomes, 2014 ). Fuzzy TOPSIS and Fuzzy AHP are chosen for the proposed framework in this study. This choice stems from TOPSIS's distinctive advantages, such as reduced complexity in both data collection and computation processes, ease of utilization, and the comprehensibility of its logical foundation, aligning with human decision-making (Velasquez & Hester, 2013 ). Besides, TOPSIS identifies alternatives, eliminating units across criteria while normalizing values (Manivannan & Kumar, 2016 ). Predefined weights in TOPSIS rank alternatives based on proximity to ideal and anti-ideal solutions. An alternative exhibiting greater proximity to the ideal solution and greater distance from the anti-ideal solution is accorded a higher ranking (Jaini & Utyuzhnikov, 2016 ). Nonetheless, considering fuzzy logic’s ability to handle data vagueness and assign weights for criteria and alternatives (Chen, 2000 ), Fuzzy TOPSIS is chosen. Similarly, Fuzzy AHP is favored over conventional AHP, deploying fuzzy theory and fuzzy numbers to mitigate reliance on expert judgment (Figueiredo, et al., 2021 ). AHP relies on a reductionist approach reminiscent of Newtonian and Cartesian thought, wherein the problem is dissected into progressively smaller components until a precise and scalable level of analysis is achieved. AHP also necessitates the involvement of experts, who engage in pairwise comparisons of similar criteria to establish priorities for ranking the alternatives (Mathew et al., 2020 ). However, this also brings a deficiency caused by its reliability to experts (Ali et al., 2017 ). Therefore, Fuzzy AHP is preferred for this study because it deploys fuzzy theory concepts in hierarchical structure analysis using fuzzy numbers instead of real numbers (Figueiredo, et al., 2021 ).

Despite the significant potential contribution of such integrated methodology, no study utilized the Fuzzy MCDM methods in exploring the importance and priority of WE indicators. In the Scopus Publication Database, we searched for the following query matching the keywords corresponding to the concepts of our research question “Women Empowerment”, “indicator(s)”, “evaluation/assessment/measurement”, and combined them with the methodological keywords being “multi-criteria/multi-attribute decision making” and “fuzzy” (excluding the exact method name, such as AHP or TOPSIS to prevent researcher bias). The search query returned no publications in Scopus Database, as shown in Fig.  1 .

Screenshot of the Search Result in Scopus Database

Even when we limited the query to exclude the keyword “Fuzzy”, the Scopus database still did not include any publications. When the query is revised by replacing the MCDM/MADM keywords with the specific methods of AHP or TOPSIS, the database cannot find any matches. Therefore, this paper can potentially contribute to this methodological gap in the WE indicator ranking literature. The following sections introduce the combined methods in detail.

3.1 Fuzzy AHP

The Analytic Hierarchy Process (AHP), as introduced by Saaty ( 1990 ), serves as a valuable and pragmatic tool intergrating qualitative and quantitative elements into the decision-making process. However, it often faces criticism due to its reliance on a discrete scale ranging from 1 to 9, which proves inadequate in addressing the uncertainty and ambiguity inherent in determining the priorities of various attributes (Choudhary & Shankar, 2012 ). FAHP was developed to better the extent of the decision-makers’ piece of knowledge and prevent the risks of hidden uncertainty embedded in traditional AHP, which does not resemble how humans think (Kahraman et al., 2003 ). In addition, linguistic terms are used by fuzzy set theory for the representation of the decision-maker’s preferences (Awasthi et al., 2011 ). Accordingly, during the application of FAHP, the fuzzy triangular set is selected at first with the linguistic representations, which can be observed in Sect.  4.2 . The methodology being described by Dang et al. ( 2019 ) was used in this study. The steps after the linguistic terms selection start with the pairwise comparison matrix:

\(\tilde{d}_{ij}^{k}\) represents the  k th decision-makers’ preference of the ith criteria over the  j th criteria. If several decision-makers are evaluating their judgment, then an average preference for pairwise comparison matrices for all criteria would be as follows:

Chang and Yang ( 2011 ) suggest using the geometric mean of these numbers to avoid extreme values and to better deal with the reciprocal numbers:

where \(\widetilde{{r_{i} }}\) is the fuzzy geometric mean and \(\widetilde{{d_{ij} }}\) represents the decision-maker’s preference of the i th criteria over the j th criteria. Later, fuzzy weights of the criterion ( \(w_{i} )\) are calculated as below:

Finally, average and normalized weight criteria are calculated. \(M_{i}\)  is the average, and  \(N_{i}\)  is the normalized weight criteria.

To check the consistency, the fuzzy numbers denoted as M = (l, m, u) are defuzzied to crisp numbers (Kwong & Bai, 2003 ) as the following equation.

Then, the consistency ratio (CR) is calculated below using the random index (RI) shown in Table  1 (Golden et al., 1989 ).

3.2 Fuzzy TOPSIS Method

TOPSIS is a method proposed by Hwang and Yoon ( 1981 ) to solve MCDM problems by obtaining the alternative with the shortest distance from the positive ideal solution and the longest distance from the negative ideal solution; the positive ideal solution consists of the best (highest) values for positive criteria and the best (lowest) values for negative criteria. However, similar to what was mentioned in the previous sections, a fuzzy extended version of TOPSIS was proposed by Chen ( 2000 ) to overcome the problem of vague and uncertainty in human thinking, which eventually influence decision-making processes (Sadoughi et al., 2012 ).

Chen's ( 2000 ) methodology is used in this paper. FTOPSIS starts with constructing the group of decision-makers and building the criteria set. This method utilizes the linguistic variable sets to evaluate the alternatives based on criteria. Then, it follows the steps below, applying the Eqs.  1 – 8 (where \(\tilde{X}ij^{K}\) is the rating weight while \(\tilde{W}j^{K}\) is the importance weight among k decision-makers). Considering we have m alternatives, n measures, and k decision-makers, the fuzzy multi-criteria group decision-making problem would be the following matrix:

where \(A_{1}\) , \(A_{2}\) , …, \(A_{n}\) are alternative (indicator in our case) to be selected or prioritized, \(C_{1}\) , \(C_{2}\) ,…, \(C_{n}\) are evaluation measure or criteria. Furthermore, \(\tilde{X}_{ij}\) stands for the value of importance degree of alternative \(A_{i}\) based on \(C_{j}\) by evaluator k. The average value method is used for integrating the fuzzy performance score \(\tilde{X}_{ij}\) of k evaluators. Moreover, \(\tilde{X}_{ij}^{k}\) indicates a degree of alternative \(A_{i}\) based on \(C_{j}\) by evaluator k; a,b,c are the fuzzy numbers:

The initial collected data to address variations in measurement units and scales within MCDM problems must be normalized. In this study, the linear normalization technique is used, based on the following equation where \(\tilde{R}\) is a normalized fuzzy decision matrix.

If j is benefit criteria: \(c_{j}^{ + } = {\text{max}}_{i} c_{ij}\) while if j is a cost criterion: \(a_{j}^{ - } = {\text{min}}_{i} a_{ij}\) .

With the consideration of various weights being attended to each indicator, a weighted normalized decision matrix is obtained by multiplying the importance weight of criteria by the normalized fuzzy decision matrix, which is shown as \(\tilde{V}\) below:

As positive triangular fuzzy numbers are between zero and one, fuzzy ideal solution and negative fuzzy solution are calculated as below:

Then comes the step of computing the distance of each alternative with positive fuzzy ideal solution ( \(d_{i}^{ + } )\) and negative fuzzy ideal solution ( \(d_{i}^{ - } )\) :

Further, \(d(\tilde{v}_{a} ,\tilde{v}_{b} )\) represents the distance between two fuzzy numbers if \(\tilde{v}_{ij}\)  =  (a,b,c):

Finally, the closeness coefficient enables ranking all alternatives and the selection of the best alternative. The way to calculate the closeness coefficient of each alternative is below:

\(CC_{i}\) indicates the extent of the proximity of alternatives to the optimal solution and distance from the negative ideal solution. Hence, higher values of \(CC_{i}\) signify stronger performances of alternatives.

4 A Combined MCDM Framework Propos for the Women Empowerment Program Performance

4.1 building the mcdm model.

In the first phase, potential SI indicators for women's economic empowerment projects were identified through data collected via semi-structured key informant interviews (KIIs) with representatives from 11 Women NPOs in Turkey. These organizations included SistersLab, We Need to Talk, Flying Broom Association, Wtech, IDEMA, Red Pepper, KA.DER, Yaşamda Kadın ve Sanat Derneği, Ortak Yaşamı Geliştirme Vakfı, KAPI, and Yanındayız Derneği. Most interviewees were women with moderate experience in SIM, serving as project managers or co-founders. Informed consent was obtained at the outset of the interviews. Two interviewers conducted the KIIs through Zoom, each lasting approximately 40 min. They independently transcribed the interviews, coded the statements, and subsequently compared and merged the codes. The consistency in coding between the two interviewers obviated the need for an interrater reliability test, such as the Fleiss Kappa Statistic (Fleiss et al., 2003 ), which typically yields an “excellent” score of “ = 1”. As a result, these indicators were defined and used as the second-level criteria set within the MCDM framework. In the second phase, we developed an MCDM framework for evaluating these indicators based on a literature review. Subsequently, structured Expert Interviews (EIs) were conducted as online surveys with a new group of 12 decision-makers. This group consisted of 9 employees from Women's Empowerment NPOs from the initial list, 1 independent SI analyst, and 2 researchers involved in SIM. The final phase involved the application of MCDM methods, The methodological flow of the MCDM study is provided in Fig.  2 .

Methodological flow of the MCDM study for indicator evaluation

Following a literature review assessing the appropriateness and practicality of indicators drawn from EI findings, we established a relevant criteria set, forming the first level of the FAHP hierarchy. In their FTOPSIS application to evaluate health, safety, and environment performance indicators, Sadoughi et al. ( 2012 ) based criteria on the SMART framework (specific, measurable, attainable, realistic, and time-sensitive) during the FTOPSIS application, while Schwemlein et al. ( 2016 ) suggested indicators should be measurable, reliable, available, sensitive, and valid. Accordingly, “measurability” necessitates quantifiability (Dale & Beyeler, 2001 ), “reliability” ensures consistent results from the same group, day, and method, eliminating evaluator bias, and “validity” underscores relevance to the topic (WHO, 1997 ). During EIs, criteria indicative of an indicator’s importance in various frameworks were defined as follows: measurability (C1), attainability (C2), relevance (C3), reliability (C4), and alignment with multiple SI frameworks (C5). These criteria align with Fuzzy AHP's methodological requirements regarding the number of criteria and levels. Russo and Camanho’s ( 2015 ) analysis of AHP literature suggested using seven or fewer criteria and alternatives for optimal consistency and redundancy in AHP. They also claimed previous AHP models predominantly featured one to three layers, with a two-level structure being the most common. The proposed framework in Fig.  3 adheres to these principles, maintaining a criterion count below seven and employing a two-level hierarchy.

4.2 Application of MCDM Methods

This study combined the FAHP and FTOPSIS methods for evaluating the performance indicators of WE projects. Besides, sensitivity analysis and consistency check proved the validity of the proposed framework. Collecting the data, we conducted a survey with 12 experts, asking them to weigh the 5 criteria based on their importance and to evaluate 17 indicators by the 5 criteria.

12 decision-makers include 9 WE NGOs’ employees, 1 independent SI analyst, and 2 experienced researchers in the market research industry who are also involved in SIM. In the first part of the survey, criteria were rated using the linguistic variables Nurani et al. ( 2017 ) adapted in their study for Fuzzy AHP, and the Fuzzy number set in Table  2 is applied. In the second part of the survey, where the decision-makers rated the indicators based on the criteria, the scale in Table  3 with the relevant linguistic terms (Zahari & Abdullah, 2012 ) are adapted.

The FAHP process went from building the pairwise comparison matrix to the weighted normalization fuzzy decision matrix (Eqs.  1 – 7 ). Table 4 shows the final weights from the geometric means of all decision-makers’ ratings for the criteria. The criteria weights were 0.205, 0.233, 0.278, 0.138 and 0.145, respectively.

To test the validity of the method, Eqs.  8 – 9 are applied. Since the consistency rate is 2.9% as seen in Table  5 , which is lower than 10%, we confirmed the findings’ consistency. We accepted the calculated weights in Fuzzy AHP as appropriate for ranking the indicators.

With the criteria weights being obtained through Fuzzy AHP, the Fuzzy TOPSIS process started. Through Eq.  10 , the decision matrix is constructed based on the 12 decision-makers’ evaluation of indicators. Following the steps described in Eqs.  11 – 17 , the closeseness coefficients (CCi) and rankings of indicators are obtained as presented in Table  6 . A2, A3, and A4 are ranked among the top three indicators.

Eventually “number of employed or business starter beneficiaries”, “type of jobs”, “the revenue increase in the beneficiaries’ existing businesses,” and “number of beneficiaries who promoted in their jobs after the project” are resulted to be the most significant indicators. On the other hand, “positive change in beneficiaries’ view of their body”, “increase in mental well-being”, and “prevention of domestic violence during the project” occurred as indicators with a lower weight in women's economic empowerment programs in Turkey.

4.3 Sensitivity Analysis

The sensitivity analysis is a critical step of the AHP-based indicator ranking studies to test the proposed frameworks' wellness (Amrita et al., 2018 ). It is also crucial to understand the sensitivity of the results towards the changes in weights of the criteria (Perçin, 2012 ) by validating the MCDM frameworks and providing clear directions for improving the consensus and consistency among the respondents to the research tools.

Perçin ( 2012 ) measured the sensitivity in a FTOPSIS-FAHP integrated study by setting 10 cases. Five cases adapt the maximum weight for the first and random values of calculated weights for other criteria. The first criteria take the lowest weights for the last five cases while others change. We applied the same model by inserting the weights from FAHP to the model, though we used 8 cases due to the lower number of criteria, as given in Appendix 1.

Figures  4 and 5 show A2 increases in the 4th case and reaches the top in the 6th case, resulting from the C5 receiving the highest weight. The fifth case had the lowest value in C5, and A2 was the second-best ranked, showing its strong perception as the recommended indicator in many SI frameworks. Other indicators’ rankings did not change significantly; however, A1 showed high sensitivity to the relevance criteria (C3), occurring in case 5 and case 8, where the C3 took its highest weights, and measurability had the lowest. On the other hand, A1 kept obtaining one of the best ranks and can be counted as better than more than half of the other criteria. Still, it indicates the criteria measurability and relevance are critical in changing some of the results. In other words, an indicator may not be the most relevant factor to measure women’s economic empowerment even though it is highly measurable. This reveals an important finding on prioritizing indicators while measuring the success of those projects in the most realistic way.

Sensitivity analysis of FAHP-FTOPSIS (CCi)

Sensitivity analysis of FAHP-FTOPSIS (Ranking)

5 Discussion

In SIM and performance evaluation processes of social programs and projects, measurement frameworks including well-designed indicators play a critical role in defining the theory of change and monitoring the performance during and after the implementation phase. The utilization of advanced indicator design and selection methods significantly enhances the effectiveness of performance management within social programs. Nevertheless, within various social intervention initiatives, such as WE programs, both implementers and funders encounter difficulties when constructing evaluation frameworks, particularly in the realm of indicator design being tailored to context-based SIM. Referring to Bice ( 2020 ) and Taylor ( 2004 ), who pointed out the importance of context-based evaluation of social intervention, this paper provides a methodology and presents an application for a context-specific ranking of indicators from the case of women’s economic empowerment programs of NPOs in Turkey. In this way, this study also serves to overcome the “prioritizing outcome measures” and “the varying meaning of empowerment in different contexts” challenges being raised by Glennerster et al. ( 2018 ) in WE measurement. As recommended by these authors, we employed the insights derived from formative research to select or develop locally customized indicators and questions. This approach aimed to augment the context-specific empowerment indicators with standardized ones, addressing the challenges at hand. In addition, aligned with the concerns and needs about ToC alignment, the proposed methodology offers an expert-based view of expected and actual outcomes as inputs to the indicator set.

The field study with experts and key informants revealed employment status and conditions, knowledge and skills, psychological resources, awareness and act on gender equality and roles, and child-care conditions are part of women's economic empowerment. The mentioned topics also align with the framed indicators directly influencing the status of WE reported by Sharma and Bansal ( 2017 ). The child-care conditions can be matched with household management, employment with economic contribution, and financial freedom. Findings from the study do not include any indicator about “educational freedom” and “physical health” (mental well-being indicator can be argued for being categorized within the health category). The findings also revealed economic indicators (such as “the number of employed or business starter beneficiaries”, “the revenue increase in beneficiaries’ existing businesses”, etc.) occurred as the most critical indicators. In assessing indicators related to gained soft skills and mental well-being within the context of women’s economic empowerment projects in Turkey, this study yielded lower scores. This finding raises the discussion on the priority of economic obstacles in WE from a developing country context, which is expected to be an input to further studies. This insight is poised to serve as valuable input for future studies. Moreover, though the commonly used indicator “the number of beneficiaries who participated in the project” can be good in output measurement, it did not receive a high rank for SIM.

Referring to Rowland’s ( 1997 ) typology and categories of Pereznieto and Taylor ( 2014 ) and Carter et al. ( 2014 ), we can also discuss the ranking of WE indicators being revealed by this study based on their agency practice types. The study unveiled indicators ranking within the top seven (1st–7th) primarily pertain to economic aspects. Specifically, indicators A2, A3, and A4 focus on employment, while indicators A12, A14, and A15 are centered around income increase. These indicators are associated with the "power over" dimension, which pertains to individuals' ability to access and control financial, physical, and knowledge-based assets, including opportunities for employment and income-generation activities. On the other hand, A1, A10, A6, A8, and A11 which are a part of the “power within” dimensions of empowerment are listed in the middle ranks (8th–12th) from FTOPSIS results. The indicators being ranked between 11 and 18th are about “power to” and “power over” practices, being associated with the well-being of women and inclusivity being achieved by empowerment. Based on this categorization, it is evident social indicators related to empowerment, particularly those involving power over resources, agencies, and achievements, hold a comparatively higher degree of significance and priority for social programs. The process of empowering women to uncover their “power within” follows “power over” dimensions in these rankings. However, one might notice the aspects related to “power to” and “power with” are given lower priority, except for entrepreneurship. The mentioned classification can be observed in Appendix 2.

For methodological discussion, in practice, indicator rankings or importance levels are determined by naive methods such as expert scoring or weighted scoring models by a few experts, which raises the subjectivity and consistency problem. Despite their notable advantages, which include the elimination of qualitative expert evaluations for performance indicators and provision of relativity and consistency checks to expert opinions, MCDM tools have been infrequently employed in SI and outcome evaluation frameworks of social projects. Being one of the few studies, Rafiaani et al. ( 2020 ) used TOPSIS to rank the SI indicators and criteria for better SIM. Moreover, Amrita et al. ( 2018 ) applied FAHP to evaluate performance indicators of women’s entrepreneurship projects. Since there is no previous study on MCDM usage for evaluating performance indicators in WE projects (at least to our knowledge), especially in the context of Turkey, we applied an exploratory approach by interviewing experts to create an indicator list from scratch. Therefore, ratings of these indicators were the first attempt of rater experts in this domain, which raised the precise rating concern that Kabir and Hasin ( 2012 ) underlined. Overcoming this issue, we applied FTOPSIS, differing from Rafiaani et al. ( 2020 ). Furthermore, our approach not only expands upon the methodological framework introduced by Amrita et al. ( 2018 ) by incorporating the FTOPSIS-FAHP integrated approach but also broadens the scope to encompass an evaluation of indicators of overall women’s economic empowerment projects. This represents a valuable contribution to the field of MCDM studies within the context of SIM.

6 Conclusion

In conclusion, this paper delved into the realm of performance indicators within an evaluation framework, aiming to enhance their utilization across various stages of women’s economic empowerment interventions, from the initial design of ToC to ongoing monitoring and follow-up and ultimately to post-implementation phase involving measurement and final evaluation. Despite this valuable concept, SI has been in practice since the eighteenth century with remarkable developments within the last decades (Becker, 2001 ); the literature regarding quantitative approaches assisting indicator selection for WE projects is thin. Being motivated to contribute to stated significance of designing robust indicator sets based on project or program context in the literature, we aimed to propose an MCDM framework utilizing FAHP and FTOPSIS approaches. The literature was reviewed regarding WE indicators and their selection processes, MCDM methods used for indicator selection, and SIM contexts. Accordingly, 11 NGOs were interviewed to achieve a list of indicators commonly used in Turkey's context. The sampling from Turkey is valuable here as it presents a case of a developing and conservative country. Later, considering 12 decision-makers’ evaluations based on the criteria derived from literature, a ranking of indicators was provided. In this domain, study findings revealed the “number of beneficiaries” often used in output is insufficient to provide a robust measure of the project’s SI. The improvement of social skills, self-confidence, mental well-being, awareness of gender roles, view of their bodies, and prevention of domestic violence during the projects occurred as secondary indicators of impact on women’s economic empowerment. Indicators like number of beneficiaries employed, who started a business, got a promotion, type of jobs provided, and increase in revenues of their existing jobs received higher scores, enabling the representation of the intervening project’s success.

Through applying our proposed indicator selection model to Turkish WE NGOs, our findings not only shed light on enhancing performance evaluation but also made valuable contributions to context-specific processes associated with SIM of WE. One of the main contributions is providing a quantitative model to be adapted to any ToC on the way to designing an effective indicator set to facilitate the SIM processes. The second main contribution is the application of MCDM methods and their fuzzy extensions in this domain, which have been overlooked in the literature for SIM frameworks and scorecards. Even though MCDM has been utilized in several studies for evaluating SI, the gap in usage for indicator selection was apparent, especially in the context of WE. The proposed framework enabled the elimination of the subjectivity of the practitioners and the bias of the single advisor, consultant, or manager in assigning importance to SI indicators. Sensitivity analysis also provided a validity test for the appropriateness of the rankings. Each indicator is evaluated by five criteria: measurability, attainability, relevance, replicability, and usability in various contexts. In its current form, the indicator set and their importance weights can be applied to social output and impact evaluation processes of WE NGOs in Turkey. It may also serve as an analytical approach to design the ToC and MEAL frameworks with validated output indicators. Also, the proposed data collection and MCDM framework are valuable due to the context-based variety of WE programs, their outcomes, and the need for indicator-ToC alignment.

Here we must note the indicators and their corresponding ranking in this study for SIM in WE programs should be regarded as a proposed list. The content and prioritization of these indicators cannot be definitively determined without being integrated into the ToC which is specific to the evaluated social program or project (Glennerster & Takavarasha, 2013 ; Glennerster et al., 2018 ). The evaluators and program executors should design the indicators based on projects’ or programs’ goals; this tool may guide them through that process. The proposed and validated MCDM methodology for indicator selection and ranking is also adaptable to SI and program performance evaluations from various contexts. We also underline the focus was women’s economic empowerment in our study; future studies should be extended beyond economic empowerment, and should also deal with the empowerment of reproduction and maternal health indicators as previously discussed by reproduction research and feminist literature (such as Hudson et al., 2019 ; Thompson, 2005 ). Moreover, women’s empowerment measures from different frameworks (UNF, IRIW, etc.) can be benchmarked and merged by the indicators introduced in this study to provide a more consolidated approach to WE measures. Another important future research topic is to categorize and discuss the ranked indicators in Rowland’s ( 1997 ) typology for elaborating on the interventions to extend the agency dimension and resources. Other MCDM methods such as VIKOR and Data Enveloping can also be applied to the framework for delivering cross-validation on the results. Comparison of the indicator ranks can enable evaluators to understand further the cross-country or cross-regional differences among WE priorities as an input to social intervention programs and policies towards UN’s SDG No. 5: Gender Equality.

Adhikari, D., Gazi, K. H., Giri, B. C., Azizzadeh, F., & Mondal, S. P. (2023). Empowerment of women in India as different perspectives based on the AHP-TOPSIS inspired multi-criterion decision making method. Results in Control and Optimization, 12 , 100271.

Google Scholar  

Aletheia, D., Koolwal, G., Annan, J., Falb, K., & Goldstein, M. (2017). Measuring Women’s Agency. World Bank Policy Research Working Paper no. 8148, pp. 34–35. http://documents.worldbank.org/curated/en/333481500385677886/Measuring-womens-agency .

Alexander, J., Brudney, J. L., & Yang, K. (2010). Introduction to the symposium: Accountability and performance measurement—The evolving role of nonprofits in the hollow state. Nonprofit and Voluntary Sector Quarterly, 39 (4), 565–570.

Ali, S., Lee, S. M., & Jang, C. M. (2017). Determination of the most optimal on-shore wind farm site location using a GIS-MCDM methodology: Evaluating the case of South Korea. Energies, 10 (12), 2072.

Alkire, S. (2005). Subjective quantitative studies of human agency. Social Indicators Research, 74 (1), 217–260. https://doi.org/10.1007/s11205-005-6525-0

Article   Google Scholar  

Alkire, S., Meinzen-Dick, R., Peterman, A., Quisumbing, A., Seymour, G., & Vaz, A. (2013). The women’s empowerment in agriculture index. World Development, 52 , 71–91. https://doi.org/10.1016/j.worlddev.2013.06.007)

Amrita, K., Garg, C. P., & Singh, S. (2018). Modelling the critical success factors of women entrepreneurship using fuzzy AHP framework. Journal of Entrepreneurship in Emerging Economies, 10 (1), 81–116.

Anand, A., Rufuss, D. D. W., Rajkumar, V., & Suganthi, L. (2017). Evaluation of sustainability indicators in smart cities for India using MCDM approach. Energy Procedia, 141 , 211–215.

Arvidson, M., & Lyon, F. (2014). Social impact measurement and non-profit organisations: Compliance, resistance, and promotion. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 25 (4), 869–886.

Awasthi, A., Chauhan, S. S., & Omrani, H. (2011). Application of fuzzy TOPSIS in evaluating sustainable transportation systems. Expert Systems with Applications, 38 (10), 12270–12280.

Basumatary, K., Devi, M., Basumatary, S., Mwchahary, S., & Basumatary, I. R. (2023). Women’s empowerment index for handloom weavers in Assam, India. Humanities and Social Sciences Letters, 11 (2), 167–178.

Becker, H. A. (2001). Social impact assessment. European Journal of Operational Research, 128 (2), 311–321.

Bengo, I., Arena, M., And, A. G., & Calderini, M. (2016). Indicators and metrics for social business: A review of current approaches. Journal of Social Entrepreneurship, 1 (2), 1–24. https://doi.org/10.1080/19420676.2015.1049286by

Bengo, I., Chiodo, V., & Tosi, V. (2020). Measuring a blended performance: Managerial insights from the field of impact entrepreneurship. Entrepreneurship-Contemporary Issues . https://doi.org/10.5772/intechopen.94441

Bice, S. (2020). The future of impact assessment: Problems, solutions and recommendations. Impact Assessment and Project Appraisal, 38 (2), 104–108. https://doi.org/10.1080/14615517.2019.1672443

Article   MathSciNet   Google Scholar  

Bishop, D., & Bowman, K. (2014). Still learning: A critical reflection on 3 years of measuring women’s empowerment in Oxfam. Gender & Development, 22 (2), 253–269. https://doi.org/10.1080/13552074.2014.920993

Buchholz, T., Rametsteiner, E., Volk, T. A., & Luzadis, V. A. (2009). Multi criteria analysis for bioenergy systems assessments. Energy Policy, 37 (2), 484–495.

Burdge, R. J., & Vanclay, F. (1996). Social impact assessment: A contribution to the state of the art series. Impact Assessment, 14 (1), 59–86.

Buvinic, M., & Furst-Nichols, R. (2013). “Measuring women’s economic empowerment: Companion to a roadmap for promoting women’s economic empowerment.” United Nations Foundation and Exxon Mobil Foundation. http://womeneconroadmap.org/sites/default/files/Measuring%20Womens%20Econ%20Emp_FINAL_06_09_15.pdf

Carter, J., Byrne, S., Schrader, K., Kabir, H., Bashaw Uraguchi, Z., Pandit, B., Manandhar, B., Barileva, M., Pijls, N., & Fendrich, P. (2014). Learning about women’s empowerment in the context of development projects: Do the figures tell us enough? Gender & Development, 22 (2), 327–349. https://doi.org/10.1080/13552074.2014.920986

Chang, K. F., & Yang, H. W. (2011). A study of cosmetic bundle by utilizing a fuzzy analytic hierarchy process (AHP) to determine preference of product attributes toward customer value. African Journal of Business Management, 5 (22), 8728–8739.

Chen, C.-T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114 (1), 1–9. https://doi.org/10.1016/s0165-0114(97)00377-1

Choudhary, D., & Shankar, R. (2012). An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India. Energy , 42 (1), 510–521.

Dale, V. H., & Beyeler, S. C. (2001). Challenges in the development and use of ecological indicators. Ecological Indicators, 1 (1), 3–10.

Dang, V. T., Wang, J., & Dang, W. V. T. (2019). An integrated fuzzy AHP and fuzzy TOPSIS approach to assess sustainable urban development in an emerging economy. International Journal of Environmental Research and Public Health, 16 (16), 2902.

PubMed   PubMed Central   Google Scholar  

Desai, M. A. (2010). Hope in hard times: Women’s empowerment and human development. Retrieved from UNDP-HDRO Occasional Papers No. 2010/14.

Džunić, M., Stanković, J., & Janković-Milić, V. (2018). Multi-criteria approach in evaluating contribution of social entrepreneurship to the employment of socially-excluded groups. Technological and Economic Development of Economy, 24 (5), 1885–1908.

Ebrahim, A., & Rangan, V. K. (2010). The limits of nonprofit impact: A contingency framework for measuring social performance, Working Paper 10-099, Harvard Business School.

Figueiredo, K., Pierott, R., Hammad, A. W., & Haddad, A. (2021). Sustainable material choice for construction projects: a life cycle sustainability assessment framework based on BIM and Fuzzy-AHP. Building and Environment, 196 , 107805.

Fleiss, J. L., Levin, B., & Paik, M. C. (2003). Statistical methods for rates and proportions (3rd ed.). Wiley.

Social Impact Task Force, (2000). Enterprising communities: Wealth beyond welfare.  A report to the Chancellor of the Exchequer from the Social Investment Task Force, October .

Gavalas, D., Syriopoulos, T., & Tsatsaronis, M. (2022). Assessing key performance indicators in the shipbuilding industry; an MCDM approach. Maritime Policy & Management, 49 (4), 463–491.

Glennerster, R., Walsh, C., & Diaz-Martin, L. (2018). A practical guide to measuring women’s and girls’ empowerment in impact evaluations, Department for International Development. Abdul Lateef Jameel Poverty Action Lab, Report. Retrieved 18 Jan 2022 from https://www.povertyactionlab.org/sites/default/files/research-resources/practical-guide-to-measuring-womens-and-girls-empowerment-in-impact-evaluations.pdf

Glennerster, R., & Kudzai, T. (2013). Running randomized evaluations: A practical guide . Princeton University Press.

Golden, B. L., Wasil, E. A., & Harker, P. T. (1989). The analytic hierarchy process. Applications and Studies, Berlin, Heidelberg, 2 (1), 1–273.

Golla, A.-M., Malhotra, A., Nanda, P., Mehra, R., Kes, A., Jacobs, K., & Namy, S. (2011). Understanding and measuring women’s economic empowerment. International Center for Research on Women. https://www.icrw.org/publications/understanding-andmeasuring-womens

Gomes, L., & Gomes, C. (2014). Tomada de decisão gerencial–enfoque multicritério. 5. a edição-Editora Atlas.

Güner, D. & Keskin, E. (2021). IMECE summit shaping the features 2021, Social impact panel, March 18–19th 2021, IMECE.

Güney-Frahm, I. (2018). A new era for women? Some reflections on blind spots of ICT-based development projects for women’s entrepreneurship and empowerment. Gender, Technology and Development, 22 (2), 130–144.

Gupta, M. (2021). Role of NGOs in women empowerment: Case studies from Uttarakhand, India. Journal of Enterprising Communities: People and Places in the Global Economy, 15 (1), 26–41.

Hudson, N., Baldwin, K., Herbrand, C., Buhler, N., & Daly, I. (2019). Reproduction research: From complexity to methodological innovation. Methodological Innovations . https://doi.org/10.1177/2059799119829427

Hughes, C., Bolis, M., Fries, R., & Finigan, S. (2015). Women’s economic inequality and domestic violence: Exploring the links and empowering women. Gender & Development, 23 (2), 279–297.

Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple attribute decision making: Methods and applications a state-of-the-art survey. Lecture Notes in Economics and Mathematical Systems, vol. 186, pp. 58–191. https://doi.org/10.1007/978-3-642-48318-9_3

Ibrahim, S., & Alkire, S. (2007). Agency and empowerment: A proposal for the internationally comparable indicators. Retrieved from OPHI Working Paper No.04.

IOM UN Migration (2017). Empowering Caribbean women through migration. Retrieved Feb 2023 from https://rosanjose.iom.int/en/blogs/empowering-caribbean-women-through-migration#:~:text=The%20United%20Nations%20developed%20five,outside%20the%20home%3B%20and%20their

Jaini, N. I., & Utyuzhnikov, S. V. (2016). Critical criterion analysis for multi-criteria decision making. International Journal of Applied Physics and Mathematics, 6 (3), 129.

Jiang, S., Shi, H., Lin, W., & Liu, H. C. (2020). A large group linguistic Z-DEMATEL approach for identifying key performance indicators in hospital performance management. Applied Soft Computing, 86 , 105900.

Johnson, N., Balagamwala, M., Pinkstaff, C., Theis, S., Meinsen-Dick, R., & Agnes, Q. (2018). How do agricultural development projects empower women? Linking strategies with expected outcomes. Journal of Gender, Agriculture and Food Security (agri-Gender), 3 (302-2019–3652), 1–19.

Kabeer, N. (1999). Resources, agency, achievements: Reflections on the measurement of women’s empowerment. Development and Change, 30 (3), 435–464. https://doi.org/10.1111/1467-7660.00125

Kabir, G., & Hasin, A. (2012). Comparative analysis of TOPSIS and Fuzzy TOPSIS for the evaluation of travel website service quality. International Journal for Quality Research, 6 , 169–185.

Kahraman, C., Cebeci, U., & Ulukan, Z. (2003). Multi-criteria supplier selection using fuzzy AHP. Logistics Information Management, 16 (6), 382–394.

Karki, S. T., & Xheneti, M. (2018). Formalizing women entrepreneurs in Kathmandu, Nepal: Pathway towards empowerment? International Journal of Sociology and Social Policy., 38 (7–8), 526–541.

Köroğlu, F., & Yıldırım, N. (2023). Social impact & project performance measurement methods and challenges in practice: A study on women empowerment NGOs.  Journal of Business & Economics Review (JBER) ,  7 (4).

Kwong, C. K., & Bai, H. (2003). Determining the importance weights for the customer requirements in QFD using a fuzzy AHP with an extent analysis approach. Iie Transactions, 35 (7), 619–626.

Lamata, M. T., Liern, V., & Pérez-Gladish, B. (2018). Doing good by doing well: A MCDM framework for evaluating corporate social responsibility attractiveness. Annals of Operations Research, 267 (1), 249–266.

MathSciNet   Google Scholar  

Landig, J. M. (2011). Bringing women to the table: European Union funding for women’s empowerment projects in Turkey. In  Women’s studies international forum , vol. 34(3) (pp. 206–219). Pergamon.

Laszlo, S., & Grantham, K. (2017). “Measurement of women’s economic empowerment in GrOW projects: Inventory and user guide.” McGill University GrOW Working Paper, December 2017.

Lombardini, S., Bowman, K., & Garwood, R. (2017). A ‘How-To’ guide to measuring women’s empowerment: Sharing experience from oxfam’s impact evaluations. Oxfam. https://policy-practice.oxfam.org.uk/publications/a-how-to-guide-to-measuring-womens-empowerment-sharing experience-from-oxfams-i-620271.

Malapit, H., Quisumbing, A., Meinzen-Dick, R., Seymour, G., Martinez, E. M., Heckert, J., & Team, S. (2019). Development of the project-level women’s empowerment in agriculture index (pro-WEAI). World Development, 122 , 675–692.

Manivannan, R., & Kumar, M. P. (2016). Multi-response optimization of Micro-EDM process parameters on AISI304 steel using TOPSIS. Journal of Mechanical Science and Technology, 30 , 137–144.

Mathew, M., Chakrabortty, R. K., & Ryan, M. J. (2020). A novel approach integrating AHP and TOPSIS under spherical fuzzy sets for advanced manufacturing system selection. Engineering Applications of Artificial Intelligence, 96 , 103988.

Mavi, R. K. (2014). Indicators of entrepreneurial university: Fuzzy AHP and Fuzzy TOPSIS approach. Journal of the Knowledge Economy, 5 (2), 370–387.

Nicholls, A. (2009). We do good things, don’t We?: ‘Blended value accounting’ in social entrepreneurship. Accounting Organizations and Society, 34 (6–7), 755–769.

Nurani, A. I., Pramudyaningrum, A. T., Fadhila, S. R., Sangadji, S., & Hartono, W. (2017). Analytical hierarchy process (AHP), fuzzy AHP, and TOPSIS for determining bridge maintenance priority scale in Banjarsari, Surakarta. International Journal of Science and Applied Science: Conference Series, 2 (1), 60.

OECD, (2020). Economic empowerment of women statistics, Retrieved from https://stats.oecd.org/Index.aspx?DataSetCode=LFS_SEXAGE_I_Reconomic-empowerment/ ) or International Food Policy

Ozkaya, G., Timor, M., & Erdin, C. (2021). Science, technology and innovation policy indicators and comparisons of countries through a hybrid model of data mining and MCDM methods. Sustainability, 13 (2), 694.

Pansare, R., Yadav, G., & Nagare, M. R. (2023). A hybrid framework to prioritize the performance metrics of reconfigurable manufacturing system (RMS) using fuzzy AHP–TOPSIS method. The International Journal of Advanced Manufacturing Technology, 124 (3–4), 863–885.

Perçin, S. (2012). Bulanık AHS ve TOPSIS Yaklaşımının Makine Teçhizat Seçimine Uygulanması. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 21 (1), 169–184.

Pereznieto, P., & Taylor, G. (2014). A review of approaches and methods to measure economic empowerment of women and girls. Gender & Development, 22 (2), 233–251. https://doi.org/10.1080/13552074.2014.920976

Polonsky, M. J., Grau, L. S., & McDonald, S. (2016). Marketing intelligence & planning. Bradford, 34 (1), 80–98. https://doi.org/10.1108/MIP-11-2014-0221

Rafiaani, P., Dikopoulou, Z., Van Dael, M., Kuppens, T., Azadi, H., Lebailly, P., & Van Passel, S. (2020). Identifying social indicators for sustainability assessment of CCU technologies: A modified multi-criteria decision making. Social Indicators Research, 147 (1), 15–44.

Rao, S. H. (2021). A hybrid MCDM model based on DEMATEL and ANP for improving the measurement of corporate sustainability indicators: A study of Taiwan high speed rail. Research in Transportation Business & Management, 41 , 100657.

Rehman, H., Moazzam, D. A., & Ansari, N. (2020). Role of microfinance institutions in women empowerment: A case study of Akhuwat, Pakistan. South Asian Studies, 30 (1), 166–178.

Richardson, R. A. (2018). Measuring women’s empowerment: A critical review of current practices and recommendations for researchers. Social Indicators Research, 137 (2), 539–557.

Rowlands, J. (1997). Questioning empowerment: Working with women in honduras . Humanities Press International.

Roy, C., Chatterjee, S., & Dutta Gupta, S. (2018). Women empowerment index: Construction ofa tool to measure rural women empowerment level in India. Available at SSRN 3357543.

Russo, R., & Camanho, R. (2015). Criteria in AHP: A systematic review of literature. Procedia Computer Science . https://doi.org/10.1016/j.procs.2015.07.081

Saaty, T. L. (1990). An exposition of the AHP in reply to the paper “remarks on the analytic hierarchy process.” Management Science, 36 (3), 259–268.

Sadoughi, S., Yarahmadi, R., Taghdisi, M. H., & Mehrabi, Y. (2012). Evaluating and prioritizing of performance indicators of health, safety, and environment using fuzzy TOPSIS. African Journal of Business Management, 6 (5), 2026–2033.

Schwemlein, S., Cronk, R., & Bartram, J. (2016). Indicators for monitoring water, sanitation, and hygiene: A systematic review of indicator selection methods. International Journal of Environmental Research and Public Health, 13 (3), 333.

Sell, M., & Minot, N. (2018). What factors explain women’s empowerment? Decision-making among small-scale farmers in Uganda. Women’s Studies International Forum, 71 , 46–55.

Sen, A. (2009). The idea of justice . Harvard University Press.

Sharma, G., & Bansal, S. (2017). Determinants and indicators of women empowerment: A walk through psychological patterns and behavioural implications. Research Journal of Business Management., 11 , 15–27. https://doi.org/10.3923/rjbm.2017.15.27

Singh, A., Misra, S. C., Kumar, V., & Kumar, U. (2022). Identification and ordering of safety performance indicators using fuzzy TOPSIS: A case study in Indian construction company. International Journal of Quality & Reliability Management, 39 (1), 77–114.

Stanković, J. J., Marjanović, I., Papathanasiou, J., & Drezgić, S. (2021). Social, economic and environmental sustainability of port regions: Mcdm approach in composite index creation. Journal of Marine Science and Engineering, 9 (1), 74.

Taylor, C. N., Goodrich, C. G., & Bryan, C. H. (2004). Social assessment: Theory, process and techniques (3rd ed.). Social Ecology Press.

Thompson, C. (2005). Making parents: The ontological choreography of reproductive technologies . MIT Press.

Tirka Widanti, N. P. (2023). Gender equality issues and women’s empowerment policies from 2000 to 2022: A bibliometric analysis. Public Policy & Administration/viesoji Politika Ir Administravimas, 22 (2), 238–251.

Vanclay, F., Esteves, A. M., Aucamp, I., & Franks, D. M. (2015). Social impact assessment: Guidance for assessing and managing the social impacts of projects. Report by University of Groningen. Fargo ND: International Association for Impact Assessment.

Velasquez, M., & Hester, P. T. (2013). An analysis of multi-criteria decision making methods mission creep view project systemic thinking view project an analysis of multi-criteria decision making methods. International Journal of Operational Research, 10 , 56–66.

World Health Organization. (1997). Selecting reproductive health indicators: A guide for district managers . WHO.

Zahari, N. I. N., & Abdullah, M. L. (2012). Evaluation of sustainable development indicators with fuzzy TOPSIS based on subjective and objective weights. IIUM Engineering Journal, 13 (1), 67–71.

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Acknowledgements

This study is a product of the Social Impact Analysis of BPFC Project Nr 9801 funded by the sponsorship of IDEMA International and hosted by ITUNOVA TTO A. Ş. (Istanbul Technical University Technology Transfer Office) in 2022. We thank all the organizations for their collaboration and support.

Open access funding provided by the Scientific and Technological Research Council of Türkiye (TÜBİTAK).

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Appendix 1 Sensitivity analysis—cases for assigning criteria values

Appendix 2 indicators’ rankings and classifications by power typology* and categories.

*Based on typologies by Rowland ( 1997 ), Pereznieto and Taylor ( 2014 ) and Carter et al. ( 2014 )

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Yıldırım, N., Köroğlu, F. Revisiting the Impact Evaluation of Women’s Empowerment: A MCDM-Based Evaluation Indicator Selection Framework Proposal. Soc Indic Res 172 , 121–145 (2024). https://doi.org/10.1007/s11205-023-03302-7

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Women empowerment in reproductive health: a systematic review of measurement properties

• Maryam Vizheh   ORCID: orcid.org/0000-0002-8281-3405 1 , 2 ,
• Salut Muhidin   ORCID: orcid.org/0000-0002-7780-8580 2 ,
• Zahra Behboodi Moghadam   ORCID: orcid.org/0000-0002-4708-3590 1 &
• Armin Zareiyan   ORCID: orcid.org/0000-0002-6983-0569 3  

BMC Women's Health volume  21 , Article number:  424 ( 2021 ) Cite this article

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Introduction

There is a considerable dearth of official metrics for women empowerment, which is pivotal to observe universal progress towards Sustainable Development Goals 5, targeting "achieve gender equality and empower all women and girls.” This study aimed to introduce, critically appraise, and summarize the measurement properties of women empowerment scales in sexual and reproductive health.

A comprehensive systematic literature search through several international electronic databases, including PubMed, Scopus, Embase, ProQuest, and Science Direct was performed on September 2020, without a time limit. All studies aimed to develop and validate a measurement of women empowerment in sexual and reproductive health were included. The quality assessment was performed through a rating scale addressing the six criteria, including: a priori explicit theoretical framework, evaluating content validity, internal consistency, and factor analysis to assess structural validity.

Of 5234 identified studies, fifteen were included. The majority of the studies were conducted in the United States. All studies but one used a standardized measure. Total items of each scale ranged from 8 to 23. The most common domains investigated were decision-making, freedom of coercion, and communication with the partner. Four studies did not use any conceptual framework. The individual agency followed by immediate relational agency were the main focus of included studies. Of the included studies, seven applied either literature review, expert panels, or empirical methods to develop the item pool. Cronbach's alpha coefficient reported in nine studies ranged from α = 0.56 to 0.87. Most of the studies but three lack reporting test–retest reliability ranging r = 0.69–0.87. Nine studies proved content validity. Six criteria were applied to scoring the scales, by which nine of fifteen articles were rated as medium quality, two rated as poor quality, and four rated as high quality.

Most scales assessed various types of validity and Internal consistency for the reliability. Applying a theoretical framework, more rigorous validation of scales, and assessing the various dimensions of women empowerment in diverse contexts and different levels, namely structural agency, are needed to develop effective and representing scales.

Peer Review reports

Recognition and measurement of women empowerment are critical for global development and human rights [ 1 ]. This was accentuated as the Sustainable Development Goal (SDG 5), which targets to "achieve gender equality and empower all women and girls” [ 1 ].

Although the growing body of literature addresses the impact of women empowerment on reproductive outcomes, it is only recently that reproductive empowerment was explicitly distinguished as a distinct dimension of empowerment itself [ 2 , 3 ]. Edmeades et al. (2018) proposed the following definition of reproductive empowerment according to a recently developed framework: “Both a transformative process and an outcome, whereby individuals expand their capacity to make informed decisions about their reproductive lives, amplify their ability to participate meaningfully in public and private discussions related to sexuality, reproductive health, and fertility, and act on their preferences to achieve desired reproductive outcomes, free from violence, retribution or fear” [ 2 ].

Reproductive and sexual empowerment is critical because, in many contexts, intimate relationships frequently occur between individuals with vastly unequal power. In many cultures, normative expectations toward gendered heterosexual sex roles and gender inequalities negatively influence women’s sexual power and restrict their ability to negotiate sexual matters with male partners [ 4 ].

The literature review showed that scales of women empowerment in reproductive health, especially in the past years, concentrated more on “power”, where power structures limit women’s sexual and reproductive health capabilities. These measures such as Sexual Assertiveness Scale [ 5 ], The Sexual Relationship Power Scale [ 6 ], and the Sexual Pressure Scale [ 7 , 8 ], mainly addressed the experience of pressure and coercion regarding sexual activity, sexual desires, HIV/AIDS (Human immunodeficiency virus/Acquired immunodeficiency syndrome) risk and prevention, and STD (sexually transmitted diseases) prevention to better capture the gender norms and dynamics shaping women’s sexual decisions and outcomes. The recent measures, on the other hand, recognize “choice” as a critical component of empowerment. Kabeer's foundational work on women's empowerment in the early 2000s, and then developing a framework by World Bank [ 9 , 10 ], introduced decision-making and exercise of choice as the components of the agency. These concepts were used commonly to design scales of women empowerment measurements such as Sexual and reproductive empowerment [ 11 ], Reproductive Decision-making Agency [ 12 ], Women’s and Girls’ Empowerment in Sexual and Reproductive health (WGE-SRH) [ 13 ], aimed to assess women’s agency in decision making over vital sexual and reproductive health matters.

The lack of standardized terminology and measurements of women reproductive empowerment in addition to the conceptual ambiguity have directly influenced implications for its measure. Consequently, there is considerable variability in the association between reproductive empowerment and health outcomes. This restrains policymakers and authorities from planning effective interventions to improve reproductive empowerment or reproductive outcomes [ 3 ].

Although it is suggested that gender-based control in hetro-sexual relationships is correlated with sexual and reproductive consequences [ 14 ], there is a considerable dearth of official metrics for women empowerment, which is pivotal to observe progress towards SDG 5 [ 1 ]. Demand for developing standard measurements of women empowerment would be more highlighted given that adequate data for 80% of indicators to monitor SDG5 is lacking, often due to the absence of valid measures [ 15 ]. This study aimed to introduce, critically appraise, and summarize the quality of the women empowerment’s measurement properties in sexual and reproductive health.

Conceptual framework

In this review, we applied the Kabeer framework where conceives empowerment as the ability of exercise choice consisting of three inter-related dimensions including (1) resources, defined as not only access to but the future claims to material, human and social resources; (2) agency, including decision making, negotiation, deception, manipulation, subversion and resistance; and (3) achievements encompasses well-being outcomes which are sexual and reproductive health [ 9 ]. We also used the conceptual framework of women reproductive empowerment proposed by Edmeades, Mejia, and Sebany (2018). Within this approach, reproductive empowerment results from the interaction of three interrelated, multi-level processes: voice, choice, and power. Voice indicates women’s capacity to exercise their reproductive goals, interests, and desires and have meaningful participation in reproductive decision making. Choice implies the ability of women to make a meaningful contribution to reproductive decisions.Power indicates the ability to shape the process of reproductive decision-making by exerting power over others [ 3 ]. Power operates at multiple levels, including couple level, families level, and expanding to the community and societal levels [ 13 ].

Combining both frameworks, we sought psychometric assessment studies that had chosen any of the abovementioned concepts and considered sexual and reproductive health as the main outcome.

Study design and search strategy

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 16 ] were used to conduct the current review. A comprehensive literature search was carried out to identify women empowerment scales used in sexual and reproductive health and their properties. The first author (M.V) performed the systematic review on September 2020, in several international electronic databases, including PubMed, Scopus, Embase, ProQuest, and Science Direct, without a time limit. Various search strategies involving keywords, index/subject terms, and Medical Subject Headings (MeSH) terms were used. A brief sample of keywords included: (women, female, girls) AND (reproduction, sexual, family planning, family planning services, fertility, contraception, birth spacing, birth intervals) AND (empowerment, power, agency, decision-making, autonomy, coercion, choice, negotiation, mobility) AND (measurement, scale, instrument, tool, questionnaire, indicator) AND (psychometric, validity, validation study, reliability, reproducibility of results). Moreover, Google Scholar and the references of the included articles were reviewed manually.

Inclusion and exclusion criteria

All studies aimed to develop a new scale or adapt an existing scale and reported the results of the reliability and validity testing were included in this research. Studies that developed and validated a women empowerment scale but the primary outcome were not the sexual and reproductive health were excluded. Moreover, studies that used a new scale without performing a psychometric analysis were excluded, too. Studies published in a language other than English and non-peer-reviewed reports, books, and dissertations, were excluded.

Outcome of interest

In the aim of this review, the construct of interest is “women reproductive empowerment” the population of interest is “women and girls”, the type of scale of interest is “all” either self-report questionnaire or interviewer-administered, and “all” measurement properties were evaluated in the review.

Data extraction

The first author (M.V) screened all titles and abstracts from the search results. After identifying all relevant articles, full texts were reviewed by all authors. Two authors (M.V and A.Z) contributed to extracting the data from the included studies. Characteristics of the study samples and scales and the measurement properties were extracted. The qualitative data analysis was chosen to synthesize data in this study for two reasons. First, we found a large degree of heterogeneity between studies by examining the study characteristics, including population features, methods of determining construct validity, different domains addressed in scales, etc. Second, considering the purpose of this study to introduce, critically appraise, and summarize the measurement properties of relevant scales, the authors decided not to use quantitative data analysis, which has little implication.

Assessment of methodological quality

Assessing the methodological quality of included studies was performed by two authors (M.V and A.Z) separately. Both authors discussed the ranking system to ensure its accuracy. The differences between them, either in data extraction or quality rating, were solved by another author, Z.BM.

Methodological quality was evaluated through three dimensions, including the developments of items, validity, and reliability. To evaluate item development, we assessed whether a literature review, empirical study, or expert panel were conducted to develop the measurement. Assessing reliability focused on whether internal consistency and test–retest reliability were determined. Validity was assessed by examining the methods used to determine content validity (the degree to which the content scale reflects the construct); structural validity (the degree to which the scores on the scale represent the dimensionality of the construct); internal construct validity (the consistency between scales and hypothesis); and external construct validity (whether measures of constructs strongly correlate or minimally correlate with one another in the hypothesized way” (Table 2 ) [ 17 , 18 ].

A rating scale applied in some systematic reviews was used to evaluate the quality of the scales’ measurement properties [ 17 , 19 ]. Six criteria were the basis of the scoring, including whether studies used a priori explicit theoretical framework; assessed the content validity; assessed the internal reliability scores (α > 0.7), determined the structural validity using exploratory factor analysis; determined the internal construct validity through confirmatory factor analyses; and assessed the external construct validity or not. The scores on each item range from 0 (none of all six criteria were fulfilled) to 6 (all of six criteria were fulfilled). The total score of study ≤ 2 interprets as poor quality; 3–4 means medium quality, and the total score ≥ 5 is considered high quality (Table 3 ).

Study characteristics

The search strategy yielded 5234 relevant records. Finally, 62 full texts were reviewed, of which 15 separate scales were identified (Fig.  1 ).

PRISMA flow diagram of study process

Ambiguous scales that measured the components, dimensions, or subscales of women empowerment but did not fit in our framework and original search strategy were excluded to consistently adhere to our conceptual framework (n = 46). Another full text aimed at the psychometric analysis of Reproductive Agency Scale 17 (RAS-17), composing pregnancy-specific and non-pregnancy-specific agency items among Qatari and non-Qatari women with a normal pregnancy [ 20 ], was excluded to achieve the maximum homogeneity of the results. Some scales such as the Survey-Based Women’s Empowerment (SWPER) Index and Composite Women’s Empowerment Index (CWEI) have been developed to measure women empowerment [ 21 , 22 ]; however, they did not include in this review because they were not applicable in sexual or reproductive health.

A detailed description of the included scales is shown in Table 1 . The results revealed that included articles did not represent diverse geographical areas. The majority of studies (8/15) were conducted in the United States [ 5 , 6 , 7 , 8 , 23 , 24 , 25 , 26 ]. Two were done in Nepal [ 12 , 27 ], one in Spain [ 28 ], and the rest of the studies (4/15) were carried out in African countries [ 13 , 29 , 30 , 31 ]. The sample size varied from 235 to 4674 in primary studies and 111,368 in one study using the Demographic and Health Surveys (DHS). The age of participants ranged between 16 and 71. The items of each scale ranged from 8 to 23. The target population in studies were as following: three studies (3/15) included adolescents and young adults (15–24 years) [ 11 , 29 , 30 ], three (3/15) were carried out on young women aged 16–29 [ 7 , 8 , 25 ]; one conducted in young women 20–35 years [ 12 ]; six studies (6/15) aimed to assess women in reproductive age defined as those aged 15 to 49 years [ 5 , 6 , 13 , 26 , 27 , 31 ]. Two studies extended the age group of participants beyond 45 years; in one study, women at the ages of 15 to 60 [ 24 ]; and in another, women ages 18 to 71 were included [ 32 ].

The most common domains of women empowerment in reproductive health that had been measured were: freedom from coercion, decision-making, communication with the partner, choice, control, autonomy, and ability to negotiate. “Kabeer’s framework of empowerment” was applied as the empowerment framework in two studies (2/15) [ 11 , 31 ]; “The theory of gender and power” developed by Connell in four studies (4/15) [ 6 , 24 , 29 , 30 ]; and “Sex scripts” (gender-stereotypical expectations to engage in sexual behavior) was used in two studies (2/15) [ 7 , 8 ]. Moreover, the “Reproductive empowerment framework” developed by Edmeades et al. (2018) and “General conceptualization of assertiveness based on human rights to autonomy”, each one was used in one study [ 12 ]. The “World Bank’s Empowerment Framework” and “The sexual and health empowerment framework” developed by the authors were used in a study conducted by Moreau et al. [ 13 ]; whereas the rest of the studies did not apply any specific empowerment framework.

Reliability and validity testing

Of the included studies, seven applied either literature review, or expert panels, or empirical method to develop the item pool (Table 2 ). Adequate internal consistency defined as the alpha > 0.7 was reported in nine studies (9/15). However, in four studies, poor internal consistency (α < 0.70) was seen. Two studies also did not report internal consistency. Most of the studies but three lack reporting test–retest reliability. Nine studies proved content validity. Six criteria were applied to score scales by which nine of fifteen articles were rated as medium quality, two rated as poor quality, and four rated as high quality (Table 3 ).

Summary of included measures

Sexual and reproductive empowerment scale.

Sexual and Reproductive Empowerment Scale is a 23-item questionnaire developed and validated by Upadhyay et al. (2020) and aimed to assess the latent construct of sexual and reproductive empowerment among a national sample of American males and females adolescents and young adults (AYAs) aged 15–24 years. This scale contains the following domains: comfort talking with a partner (three questions); choice of partners, marriage, and children (three questions); parental support (4 questions); sexual safety (4 questions); self-love (4 questions); the sense of future (2 questions); and sexual pleasure (3 questions). The total score could range from 0 to 92. The items can be self-administered, and on average, AYAs could answer all items in less than 2 min. The baseline results demonstrated that sexual and reproductive empowerment was associated with access to sexual and reproductive health services and information, and also at 3-month follow-up was moderately associated with the use of desired contraceptive methods. In contrast to most reproductive empowerment measures, this scale can also be used among men and boys [ 11 ].

Reproductive Autonomy Scale

As a multi-dimensional scale, Reproductive Autonomy Scale (RAS) was developed and validated in the USA to measure “reproductive autonomy” among women. This scale is comprised of 14 items and three subscales. Reproductive autonomy was defined as women’s power to decide about and exercise control on issues related to using contraception, pregnancy, and childbearing. The participants were selected from the family planning and abortion facilities in the United States. Three subscales of the scales were freedom from coercion (five questions), communication (five questions), and decision-making (four questions). The study found a reverse association between freedom from coercion and communication subscales with unprotected sex [ 24 ].

Reproductive decision-making agency

Hinson et al. (2019) developed and validated the reproductive decision-making agency scale among Nepalese women aged 15–49. The 17-item scale attempts to measure women’s decision-making over reproductive behaviors in three domains, including women’s agency in using family planning methods, agency in choosing the method of family planning, and agency in choosing the time of getting pregnant. In this study, women whose husbands or other relatives rather than themselves mainly made decisions on reproductive behaviors were considered the lowest agency. In contrast, women reporting sole or joint decision makingwere categorized as the medium and high agency, respectively. The scale’s scores varied between three and nine, the higher scores representing the higher agency. This scale can be applied to assess a range of reproductive outcomes, particularly those related to reproductive control.

Women’s and Girls’ Empowerment in Sexual and Reproductive health (WGE-SRH)

WGE-SRH was developed by Moreau, Karp, et al. (2020) in three African countries, Ethiopia, Uganda, and Nigeria, to provide a cross-cultural scale. This 21-items scale attempts to assess the existence of choice and exercise of choice across the three domains related to sex, using contraception, and pregnancy. Participant’s agreement or disagreement with each item scored from 1 to 10. The results showed that women who indicated higher scores on the contraceptive choice subscale are more likely to use contraception. Moreover, higher scores on the sexual exercise scale were associated with a higher possibility of volitional sex [ 13 ].

A short-form Reproductive Coercion Scale (RCS)

This 5-item measure was derived from the Reproductive Coercion Scale (RCS) by McCauley et al. (2017). The scale was validated in two longitudinal randomized controlled trials conducted on young English- or Spanish-speaking women aged 16–29 in the USA. These five questions constructed two subscales: pregnancy coercion (three items) and condom manipulation (two items). Items include dichotomous (yes/no) answers. The short form of scale was useful in recognizing women who endorse low levels of reproduction coercion. This scale is particularly sensitive to identifying women who experience less common forms and multiple forms of reproduction coercion. Furthermore, this scale would provide a rapid assessment of reproductive coercion in clinics.

Sexual Assertiveness Scale (SAS)

SAS was developed to measure women’s understanding over the three subscales of assertiveness regarding initiation of sex, refusal of sex, and prevention of sexually transmitted disease/pregnancy (STD-P) with a regular partner. It comprises 18 items rated on a 5-point response format with anchors of 0 (Never) and 4 (Always). The higher scores on the scale, the higher sexual assertiveness is predicted. The SAS was developed and validated in a sample of young American women ages 16–29. After 6 and 12 months intervals, test–retest reliabilities were assessed [ 5 ].

Spanish version of Hurlbert Index of Sexual Assertiveness

Antos-Iglesias and Carlos Sierra (2010) adapted the Hurlbert Index of Sexual Assertiveness (Hurlbert, 1991) among the Spanish community. The psychometric analysis was conducted among 400 Spanish men and 453 women who had a partner for at least six months. The original scale was composed of 25 items, ranging from 1 (Never) to 5 (Always). The total scores were between 0 to 100. The higher scores represent the higher sexual assertiveness. The exploratory and confirmatory factor analyses identified a 19-item structure with two correlated factors (Initiation and No shyness/Refusal). Six items from the original version were eliminated. Finally, the Spanish version showed satisfactory psychometric characteristics [ 32 ].

Sexual Assertiveness Questionnaire (SAQ)

SAQ was derived from the Sexual Assertiveness Scale (Morokoff and colleagues, 1997) by Loshek and Terrell (2014) to provide a scale that does not include the condom insistence. The underlying hypothesis was although the sexual assertiveness scale encompasses condom insistence, it might not be administered to women at all life stages or in various kinds of relationships. The final scale comprises 18 items and three subscales, including the ability to initiate and communicate across desired sex, the ability to refuse unwanted sex, and the ability to talk about sexual history and risk. Response choices included a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree). The results demonstrate satisfactory psychometric properties [ 26 ].

Sexual Pressure Scale (SPS)

This 19-items scale aimed to measure gender-stereotypical expectations engaging in sexual behaviors. This study hypothesized that sexual pressure is associated with HIV sexual risk behavior. Scale composed of five factors: Condom Fear, Sexual Coercion, Women’s Sex Role, Men Expect Sex, and Show Trust. Higher sexual pressure was identified through a higher score. The SPS can be used to assess to what extent adherence to gender-stereotypical expectations may limit women’s sexual choices and lead to adverse consequences, such as being less assertive in communicating their desire to reduce risk and being more likely to be engaged in sex with men who are at the higher risk of HIV [ 7 ].

Sexual Pressure Scale for Women-Revised (SPSW-R)

Jones and Gulick (2009) revised the sexual pressure scale (Jones, 2006) to improve its reliability. The study was carried out on a sample of young adult urban women. The reliability and confirmatory factor analysis using structural equation modeling resulted in 18 items with higher reliability than the original scale. After eliminating the Condom Fear factor, a 4-factor model encompassing Show trust, Women’s sex role, Men expect sex, and Sexual coercion was remained [ 8 ].

Sexual Relationship Power Scale (SRPS)

This measure was designed by Pulerwitz et al. (2000) to address interpersonal power in sexual decision-making. SRPS consists of 23 items and two subscales, Relationship Control (RC) and Decision-Making Dominance (DM). RC subscale encompasses fifteen,and DM is composed of eight questions. The totalscore was ranged from 8 to 24. Lower scores on SRPS were associated with higher physical violence and lower consistent use of a condom [ 6 ].

Sexual Relationship Power Scale (SRPS) among adolescent girls and young women (AGYW)

This scale was derived from the Relationship Control subscale of the SRPS and then validated among AGYW who were at the risk of HIV in Kenya. The original subscale consisted of 15 items. A modified scale was extracted after removing three items related to condom use, resulting in 12 items in total. Participants were asked to express to what extent they agree or disagree with each item on a 4-point Likert scale. The results showed that AGYW with higher relationship power were less likely to experience sexual violence and more likely to use a condom and have knowledge of partner’s HIV status [ 29 ].

Sexual Relationship Power equity (SRP equity)

SRP equity is a South African adaptation of the Sexual Relationship Power, originally developed by Pulerwitz et al. in 2000 [ 6 ]. Over the community-based cohorts, 235 young men and women aged 16–24 years completed this questionnaire. Follow-up study performed six months later. The original SRPS consists of 13 questions. Participants answered on a 4-point Likert scale for each item, ranging from (‘strongly agree’ to ‘strongly disagree’). Higher scores representing greater equity in sexual relationship power. Finally, a 8-item scale for women and a 9-item scale for men were constructed. SRP equity was associated with higher education and no recent partner violence [ 30 ].

Women Autonomy Measurement Scale

This scale was developed by Bhandari et al. (2014) to provide a validated scale for measuring Nepalese women’s autonomy as one of the predictors of using maternal health care services. The 23 items were answered on a 3-point scale anchored with zero (not necessary), one (useful not essential), and two (essential). Three subscales, including decision-making autonomy, financial autonomy, and freedom of movement, constitute the scale. The Autonomy Measurement Scale showed appropriate psychometric characteristics and introduced a valid and standard scale for assessing women’s autonomy in developing countries [ 27 ].

Women’s Empowerment on Demographic and Health Surveys: indicators for health dimension

Using Demographic and Health Surveys (DHS) from nineteen countries in four African regions, a scale composed of 26 indicators was developed to assess different dimensions of women empowerment, including economic, socio-cultural, education, and health. Access to healthcare composes distance, money, and permission. For instance, items such as: whether women have the “access” or “financial constraints” to make beneficial health choices were included. If women reported difficulties accessing healthcare services, they were assigned a 0 score; otherwise, women were scored 1. This scale provided region-specific indicators of women empowerment in Sub-Saharan Africa [ 31 ].

To the best of our knowledge, this is the first review that systematically appraised and summarized the measurement properties of validated women empowerment scales in sexual and reproductive health and also assessed the methodological quality of the included studies. The study results contributed to present a comprehensive picture of the main developments in women reproductive empowermentmeasuresments. Although women empowerment is a broad concept with various domains at different levels, few validated scales exist to measure them. Some domains such as decision-making, freedom of coercion, and communication with a partner were measured more often, whereas others got less attention. It is possibly because most studies concentrated on the individual agency and agency within intimate partnerships (i.e., immediate relational agency). Various domains assessed in the included studies may represent the complex and multi-faceted nature of women empowerment [ 23 ]. On the other hand, distant agency focusing on structural empowerment received less attention. Only one study evaluated women's empowerment at the structural level [ 31 ]. In this study, Asaolu et al. (2018) investigated healthcare access as a significant contributor to women’s empowerment. The healthcare domain included three variables of distance, money, and permission [ 31 ]. They hypothesized that social norms hindering women from going out without somebody’s companionship, financial constraints, farther distance, poor road conditions, or unreliable/no transportation could influence women’s access to healthcare [ 31 ]. Women empowerment is a multi-level concept, and social and structural obstacles hinder many women from exercising agency beyond the barriers they face in their marriages or families. Researchers highlighted the importance of embedding the macro-level factors in the definition and measurement of women empowerment [ 33 ]. Many factors at the various intrapersonal, interpersonal, and ecological levels determine the degree that a woman is empowered [ 33 ]. Social, economic, and cultural systems that operate at the uppermost level play an essential role in shaping the parameters of empowerment in specific contexts. For instance, availability and accessibility of health services, women’s position in the society, the level of power that women can impose in their relationships with their male partners, and cultural expectations of women, effectively influence women empowerment regardless of their individual or household characteristics. Thus, designing scales to measure these structural factors is crucial to understanding reproductive empowerment [ 3 ].

All included studies except one used standardized measures that can be applied in other contexts. Comparing women empowerment across the countries would be possible through standardized scales such as autonomy, decision-making, and communication with a partner [ 34 ]. Although standards measures are more likely to compare various populations in different cultures, context-specific scales can provide opportunities to reflect women’s lived experiences in contexts in which they live and also allow us to compare the status of their empowerment with peers [ 35 ]. In studies that adapted a scale in the new context, some items were removed or substituted by others, indicating the contextual spirit of women empowerment and this fact that dominant beliefs, practices, and values can influence women empowerment. So, probably factors constituting the women empowerment are not similar in different contexts [ 36 , 37 ]. However, exploring how women in other countries experience empowerment is possible through adapting the existing scales in other contexts to compare women’s situations across the countries.

Sexual Relationship Power Scale and sexual assertiveness scale were most examined as three studies used each of these scales. All included studies focused on women and girls who were in a sexual relationship. Although this enables using scales that measure household, family-in-law, and financial issues of family and capturing the power balance between girls and women and their sexual partners, none of the studies address the never-married women highlighting a gap in developing suitable scales for assessing girls, singles, widows and never-married women. Some studies included men, providing a comparison between women and men's attitudes over women empowerment.

It should be mentioned that all included studies were based on cross-sectional data, limiting the assessment of temporal ordering. A significant concept of women empowerment is the process, emphasizing the changes from one state to another over time [ 10 ]. Women’s levels of power can transform over time [ 28 ]. Thus, considering changes in the state of women empowerment over time is vital.

Assessing the scales' quality showed that content validity, construct validity, and internal consistency were the most common properties evaluated. Just three studies assessed test–retest reliability. Consequently, their stability to apply to other contexts is doubtful. Rigorous psychometric assessment of the scales is vital. Because poor validity and reliability can endanger the risk of correct evaluation and diagnosis of scales, consequently leading to misinterpretation and inaccurate research findings [ 38 ]. In this review, most of the studies achieved moderate or high quality, indicating the appropriate methodology. It appears that the geographic distribution of validated scales is limited to the USA and some African countries. The lack of administration of these scales across various contexts could lead to inadequate external validity [ 39 ].

These findings give insights to develop new scales covering more domains of women reproductive empowerment or validate the currently available measurements in various settings on diverse samples.

Limitations

This systematic review's main focus was finding quantitative measures of women empowerment in sexual and reproductive health, so studies that characterize scales and domains without reporting the development and psychometric analysis were not included. Another limitation of this study is publication bias as the inclusion criteria just considered peer-reviewed articles and excluded gray literature, non-peer-reviewed reports, books, and dissertations. Additionally, including only articles in English may lead to language bias.

Some dimensions, namely the structural dimension of women empowerment, are being ignored in the existing scales. Including the diverse populations and samples to develop and refine women empowerment’s measurements would facilitate measuring variations in the contexts in which reproductive empowerment is evolved. This study highlighted the necessity of designing and developing comprehensive measures to address the various dimensions of women reproductive empowerment at different levels and in diverse contexts.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available as all data are included in the manuscript body, but are available from the corresponding author on reasonable request.

Pryor EC, Seck PA. Improving gender data is essential for progress on equity and empowerment. SSM-Popul Health. 2019;9:100494.

Article   Google Scholar  

Dmeades J, Mejia C, Parsons J, Sebany ME. A conceptual framework for reproductive empowerment: empowering individuals and couples to improve their health (background paper). Washington, DC: International Center for Research on Women; 2018.

Google Scholar  

Edmeades J, Hinson L, Sebany M, Murithi L. A conceptual framework for reproductive empowerment: empowering individuals and couples to improve their health (brief). Washington, DC: International Center for Research on Women; 2018.

Crissman HP, Adanu RM, Harlow SD. Women’s sexual empowerment and contraceptive use in Ghana. Stud Fam Plan. 2012;43(3):201–12.

Morokoff PJ, Quina K, Harlow LL, Whitmire L, Grimley DM, Gibson PR, et al. Sexual Assertiveness Scale (SAS) for women: development and validation. J Pers Soc Psychol. 1997;73(4):790.

Article   CAS   Google Scholar  

Pulerwitz J, Gortmaker SL, DeJong W. Measuring sexual relationship power in HIV/STD research. Sex Roles. 2000;42(7–8):637–60.

Jones R. Reliability and validity of the sexual pressure scale. Res Nurs Health. 2006;29(4):281–93.

Jones R, Gulick E. Reliability and validity of the Sexual Pressure Scale for Women-revised. Res Nurs Health. 2009;32(1):71–85.

Kabeer N. Resources, agency, achievements: reflections on the measurement of women’s empowerment. Dev Change. 1999;30(3):435–64.

Malhotra A, Schuler SR. Women’s empowerment as a variable in international development. Meas Empower Cross Discip Perspect. 2005;1(1):71–88.

Upadhyay UD, Danza PY, Neilands TB, Gipson JD, Brindis CD, Hindin MJ, et al. Development and validation of the sexual and reproductive empowerment scale for adolescents and young adults. J Adolesc Health. 2020;68:86–94.

Hinson L, Edmeades J, Murithi L, Puri M. Developing and testing measures of reproductive decision-making agency in Nepal. SSM Popul Health. 2019;9:100473.

Moreau C, Karp C, Wood SN, Galadanci H, Kibira SPS, Makumbi F, et al. Reconceptualizing women’s and girls’ empowerment: a cross-cultural index for measuring progress toward improved sexual and reproductive health. Int Perspect Sex Reprod Health. 2020;46:187–98.

Hameed W, Azmat SK, Ali M, Sheikh MI, Abbas G, Temmerman M, et al. Women’s empowerment and contraceptive use: the role of independent versus couples’ decision-making, from a lower middle income country perspective. PLoS ONE. 2014;9(8):e104633.

Raj A. Gender Empowerment Index: a choice of progress or perfection. Lancet Glob Health. 2017;5(9):e849–50.

Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009;62(10):e1–34.

Cyril S, Smith BJ, Renzaho AM. Systematic review of empowerment measures in health promotion. Health Promot Int. 2016;31(4):809–26.

PubMed   Google Scholar  

Mokkink LB, Prinsen C, Patrick DL, Alonso J, Bouter LM, de Vet H, et al. COSMIN methodology for systematic reviews of patient-reported outcome measures (PROMs). User Manual. 2018;78:1.

Cyril S, Oldroyd JC, Renzaho A. Urbanisation, urbanicity, and health: a systematic review of the reliability and validity of urbanicity scales. BMC Public Health. 2013;13(1):513.

Yount KM, James-Hawkins L, Rahim HFA. The Reproductive Agency Scale (RAS-17): development and validation in a cross-sectional study of pregnant Qatari and non-Qatari Arab Women. BMC Pregnancy Childbirth. 2020;20(1):1–15.

Ewerling F, Lynch JW, Victora CG, van Eerdewijk A, Tyszler M, Barros AJ. The SWPER index for women’s empowerment in Africa: development and validation of an index based on survey data. Lancet Glob Health. 2017;5(9):e916–23.

Batool SS, Batool SA. Construction and validation of composite Women’s Empowerment Index (CWEI). J Arts Soc Sci. 2018;5(2):1–38.

Upadhyay UD, Gipson JD, Withers M, Lewis S, Ciaraldi EJ, Fraser A, et al. Women’s empowerment and fertility: a review of the literature. Soc Sci Med. 2014;115:111–20.

Upadhyay UD, Dworkin SL, Weitz TA, Foster DG. Development and validation of a reproductive autonomy scale. Stud Fam Plan. 2014;45(1):19–41.

McCauley HL, Silverman JG, Jones KA, Tancredi DJ, Decker MR, McCormick MC, et al. Psychometric properties and refinement of the reproductive coercion scale. Contraception. 2017;95(3):292–8.

Loshek E, Terrell HK. The development of the Sexual Assertiveness Questionnaire (SAQ): a comprehensive measure of sexual assertiveness for women. J Sex Res. 2015;52(9):1017–27.

Bhandari TR, Dangal G, Sarma PS, Kutty V. Construction and validation of a Women’s Autonomy Measurement Scale with reference to utilization of maternal health care services in Nepal. J Nepal Med Assoc. 2014;52(195):925–34.

Santoso MV, Kerr RB, Hoddinott J, Garigipati P, Olmos S, Young SL. Role of women’s empowerment in child nutrition outcomes: a systematic review. Adv Nutr. 2019;10(6):1138–51.

Pulerwitz J, Mathur S, Woznica D. How empowered are girls/young women in their sexual relationships? Relationship power, HIV risk, and partner violence in Kenya. PLoS ONE. 2018;13(7):e0199733.

Closson K, Dietrich JJ, Beksinska M, Gibbs A, Hornschuh S, Smith T, et al. Measuring sexual relationship power equity among young women and young men South Africa: implications for gender-transformative programming. PLoS ONE. 2019;14(9):e0221554.

Asaolu IO, Alaofè H, Gunn JK, Adu AK, Monroy AJ, Ehiri JE, et al. Measuring women’s empowerment in sub-Saharan Africa: exploratory and confirmatory factor analyses of the demographic and health surveys. Front Psychol. 2018;9:994.

Santos-Iglesias P, Sierra JC. Hurlbert Index of Sexual Assertiveness: a study of psychometric properties in a Spanish sample. Psychol Rep. 2010;107(1):39–57.

Diamond-Smith N, Treleaven E, Murthy N, Sudhinaraset M. Women’s empowerment and experiences of mistreatment during childbirth in facilities in Lucknow, India: results from a cross-sectional study. BMC Pregnancy Childbirth. 2017;17(2):1–13.

Kishor S, Subaiya L. Understanding women’s empowerment: a comparative analysis of Demographic and Health Surveys (DHS) data. Pharr: Macro International; 2008.

Mumtaz Z, Salway S. Understanding gendered influences on women’s reproductive health in Pakistan: moving beyond the autonomy paradigm. Soc Sci Med. 2009;68(7):1349–56.

James-Hawkins L, Peters C, VanderEnde K, Bardin L, Yount KM. Women’s agency and its relationship to current contraceptive use in lower-and middle-income countries: a systematic review of the literature. Glob Public Health. 2018;13(7):843–58.

Rayan D. Empowerment and poverty reduction: a sourcebook. Washington, DC: The World Bank; 2002.

Book   Google Scholar  

Bautista MAC, Nurjono M, Lim YW, Dessers E, Vrijhoef HJ. Instruments measuring integrated care: a systematic review of measurement properties. Milbank Q. 2016;94(4):862–917.

Akey TM, Marquis JG, Ross ME. Validatieon of scores on the psychological empowerment scale: a measure of empowerment for parents of children with a disability. Educ Psychol Measur. 2000;60(3):419–38.

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This article is a part of the PhD thesis of the first author supported and granted by Tehran University of Medical Sciences, Tehran, Iran.

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Vizheh, M., Muhidin, S., Behboodi Moghadam, Z. et al. Women empowerment in reproductive health: a systematic review of measurement properties. BMC Women's Health 21 , 424 (2021). https://doi.org/10.1186/s12905-021-01566-0

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Women’s empowerment and fertility: A review of the literature

Ushma d. upadhyay.

a Advancing New Standards in Reproductive Health (ANSIRH), Bixby Center for Global Reproductive Health, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1330 Broadway, Suite 1100, Oakland, CA 94612, United States

g Women’s Health & Empowerment Center of Expertise, University of California Global Health Institute, United States

Jessica D. Gipson

b Department of Community Health Sciences, Fielding School of Public Health, University of California, Los Angeles, 650 Charles E. Young Drive South, CHS 46-071B, Los Angeles, CA 90095-1772, United States

Mellissa Withers

c UCLA Center for the Study of Women, Box 957222, Public Affairs 1500, Los Angeles, CA 90095-7222, United States

Shayna Lewis

e UCSF/UC Hastings Consortium on Law, Science and Health Policy, University of California Hastings College of the Law, 200 McAllister St., San Francisco, CA 94102, United States

Erica J. Ciaraldi

Ashley fraser.

d Bixby Center for Population, Health and Sustainability, School of Public Health, University of California, Berkeley, 17 University Hall, Berkeley, CA 94720, United States

Megan J. Huchko

f San Francisco General Hospital, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 50 Beale St, Suite 1200, San Francisco, CA 94105, United States

Ndola Prata

Women’s empowerment has become a focal point for development efforts worldwide and there is a need for an updated, critical assessment of the existing evidence on women’s empowerment and fertility. We conducted a literature review on studies examining the relationships between women’s empowerment and several fertility-related topics. Among the 60 studies identified for this review, the majority were conducted in South Asia ( n = 35) and used household decision-making as a measure of empowerment ( n = 37). Overall, the vast majority of studies found some positive associations between women’s empowerment and lower fertility, longer birth intervals, and lower rates of unintended pregnancy, but there was some variation in results. In many studies, results differed based on the measure of empowerment used, sociopolitical or gender environment, or sub-population studied. This article is one of the first evaluations of the literature assessing the relationships between women’s empowerment and fertility. We identify several key issues that merit further investigation.

1. Introduction

Over the last two decades, women’s empowerment has become a focus for development efforts worldwide. In 2000, 189 countries signed on to the eight Millennium Development Goals, which included a commitment to promoting gender equality and empowering women (MDG3) ( United Nations, 2000 ).

Since then, several scholars have attempted to synthesize existing knowledge on women’s empowerment and international development. In the only review that focused on reproductive-related outcomes, published over a decade ago, Blanc (2001) synthesized the research examining the role of gender-based power in sexual relationships and its impact on reproductive health. Malhotra et al. (2002) summarized the most promising methods to measure and analyze women’s empowerment and provided a review of empirical studies from the fields of economics, sociology, anthropology, and demography. In 2008, Kishor and Subaiya (2008) provided data on the distribution and correlates of women’s empowerment in 23 countries documenting the wide variation in levels of decision-making power and gender-equitable attitudes.

Recently, the World Bank devoted the World Development Report (2012) to the theme of Gender Equality and Development. The report argues that the success of global development efforts hinges on gender equality and recommends public policies that promote gender equity as a means of ensuring economic growth.

At the same time that these efforts aimed to improve the status of women globally, support for family planning—an integral component in transforming women’s lives—waned ( Cleland et al., 2006 ; Crossette, 2005 ). The recent London Summit on Family Planning brought renewed attention to the importance of family planning as a means of reducing fertility and expanding the options available to women beyond reproduction ( Carr et al., 2012 ).

This literature review builds on previous reviews of women’s empowerment, by focusing specifically on research that examines its associations with fertility. To guide our work we use a definition and conceptualization of women’s empowerment based on Kabeer’s (1999 ; 2001) : “the expansion of people’s ability to make strategic life choices in a context where this ability was previously denied to them.” Within this definition, two central components of empowerment are the agency and the resources needed to exercise life choices. This definition allows a broader conceptualization than interpersonal sexual relationship power.

We conducted literature searches using PubMed, POPLINE, and Web of Science search engines in May 2013. Searches were conducted by using the following individual and combined keywords (and MeSH terms in PubMed): fertility, family size, ideal family size, birth intervals, birth/birth spacing, induced abortion, reproductive health, unplanned pregnancy, unintended pregnancy, parturition, birth, pregnancy, pregnancy spacing/intervals, and childbearing, published from January 1990 to December 2012. This initial search resulted in 6259 articles in PubMed, 3578 in POPLINE, and 4508 in Web of Science, for a total of 14,345 articles, including duplicates among the three databases ( Fig. 1 ).

Flow chart of literature search.

We evaluated each article against our inclusion criteria based on the title and abstract. To be included, studies must have: 1) been in English, 2) used quantitative analysis, 3) used observational or experimental study design, 4) analyzed data from low- or middle-income countries as defined by the World Bank, 5) examined one or more of the searched fertility topics, 6) examined “women’s empowerment” either as an independent or dependent variable and described how it is measured. To meet the last criterion, an article had to include, either in its theoretical framework or stated research objective, the intention to examine women’s empowerment, women’s autonomy, women’s status, or a closely related construct that fit within our definition of women’s empowerment ( Kabeer, 2001 ). Based on the research that demonstrates the distinction empirically (e.g., Hindin, 2000 ) and general theoretical consensus ( Caldwell, 1986 ; Jejeebhoy, 1995 ; Mason, 1986 ), education may contribute to women’s empowerment but is a distinct construct; therefore, studies that examined women’s education or literacy in their own right were not included in this review. However, studies that conceptualized education as one form of empowerment, and/or used education as a proxy for empowerment were included. In order to limit the scope of this review, abstracts were further screened to exclude studies focused on the following topics: family planning and contraception (without also focusing on fertility), sexually transmitted infections, HIV/AIDS, and maternal, infant and child health. References from key articles were hand-searched to ensure that our review included all pertinent studies. This step allowed for the inclusion of book chapters, reports, and gray literature. This process resulted in 263 articles.

We then compiled a list of articles and abstracted data on the study design, study sample, measures of empowerment, independent variables, dependent variable(s), and results. This process eliminated 203 articles that did not meet the specified criteria, resulting in 60 reviewed articles. We first describe the measures of empowerment used in the studies. We then summarize the characteristics of the articles and synthesize the findings by topic. Dependent variables were considered positively associated with independent variables based on statistical tests conducted by the original authors at the significance level they determined. We conclude with a discussion of the ongoing challenges for the design, measurement and analysis of studies in this inherently complex area of investigation and make recommendations for future studies on empowerment and fertility.

3.1. Measures of women’s empowerment

We identified 19 domains of women’s empowerment in the reviewed studies and for each, provided specific examples of how the studies operationalized empowerment ( Table 1 ). While the majority of the 60 studies assessed empowerment across multiple domains, 4 studies examined only one domain. In over two-thirds ( n = 47) of the studies, multidimensionality was determined through the use of composite or sum scores, indices, factor analysis and multi-item scales, while the remaining 17 studies used individual items to represent empowerment.

Domains of women’s empowerment used in the reviewed studies.

Women’s participation in household decision-making was the most common measure of women’s empowerment, used in 37 articles. Typically researchers created an index representing the number of household decisions in which a woman participates (e.g., decisions about personal healthcare, buying children’s clothes, visiting relatives, and purchasing land). There was substantial variation in how these indices were developed. Some papers included decisions in which the woman has some say (joint or sole decision-making), while others counted only those decisions in which the woman has final say. Some included both major and minor decisions, while others included only major decisions, excluding day-to-day household decisions and those within women’s traditional purview.

The next most commonly assessed empowerment domain was women’s mobility, with 27 articles including this domain. This was determined by creating an index for the number of locations women can visit within their community, such as the market, movie theater, or health clinic, and outside of her community, such as her natal home. Some papers counted only locations where she was able to visit alone or without permission ( Al Riyami and Afifi, 2003a , 2003b ; Jejeebhoy, 1991 ).

Certain domains were more relevant and therefore, more commonly used in some regions. For example, the mobility index was more common in studies conducted in South Asia than in other regions.

The studies used a mix of both context-specific and standardized measures. Context-specific measures were used in some studies (e.g., Lee-Rife, 2010 ; Upadhyay and Hindin, 2005 ) to reflect locally-defined dimensions of women’s status, whereas other studies employed measures that are applicable in all contexts, such as items that assess a woman’s gender attitudes and beliefs. Among the articles, 25 conducted primary data collection and developed contextually-specific empowerment measures. For example, Upadhyay and Hindin (2005) used a locally defined measure of empowerment—whether the woman, her house and children were “well-kept” as a measure of empowerment based on findings from qualitative interviews. Singh et al. (2002) used whether the woman believes in the Parda system (wearing a veil). Context-specific measures are more likely to reflect women’s lived experiences, and the characteristics or opportunities in women’s lives that may make them more ‘empowered’ in comparison to their peers ( Mumtaz and Salway, 2009 ). However, standardized measures allow for comparisons across study settings. Nineteen studies in our review used Demographic and Health Survey (DHS) standardized measures, most commonly, the household decision-making index.

Some authors used sociodemographic variables as controls, while others used them as proxies for women’s status. For example, Woldemicael (2009) used women’s educational attainment, employment, household economic status and rural/urban residence as proxies for women’s status. Variables were not always clearly defined as either sociodemographic controls or measures of women’s empowerment. In such cases, it was difficult to make conclusions about effects that were found.

The study population influenced the type of empowerment domain or measure used. Three-quarters of the studies focused on currently married women ( n = 44, 73%), enabling the use of measures involving the household, finances, and in-laws. Over a quarter ( n = 16) of the articles included ever married women, including widows and divorcees. None of the articles included never-married women. Among all of the articles, 21 included data from men and women and of these, only one included matched couples—that is, both the male and female married partners.

Twelve studies incorporated community-level or aggregated contextual measures ( Aghajanian, 1992 ; Balk, 1994 ; Bhattacharya, 1998 , 2006 ; Hirschman and Guest, 1990 ; Kravdal, 2001 ; Malhotra et al., 1995 ; Pallitto and O’Campo, 2005 ; Sanderson, 2001 ; Sanderson and Dubrow, 2000 ; Vlassoff, 1991 ; Wasim, 2002 ). Contextual factors at the community-level ( Table 1 , #20) included gender-specific and community-level socio-demographic factors measured through study-specific instruments and aggregate DHS data. For example, while the authors did not include individual-level empowerment data, Malhotra et al. (1995) used measures of women’s status relative to men to capture the external, community-level factors influencing empowerment.

As indicated in Table 1 , some studies incorporated other measures of women’s empowerment (e.g., control by partner or family, gender attitudes or beliefs of woman or partner, exposure to public life, aspirations). Although less represented among the reviewed studies, several of these domains are noted by scholars such as Kabeer (2001) as important elements of women’s empowerment.

3.2. Findings by fertility-related topic

Of the 60 reviewed studies, the majority ( n = 25, 42%) collected primary data, including surveys designed to examine women’s empowerment. Many used large nationally-representative databases ( n = 19, 32%), and the same number used existing data from DHS or World Fertility Surveys ( n = 19, 32%). Most ( n = 54, 90%) used cross-sectional study designs while the remaining used repeated cross-sectional, panel data, or longitudinal designs.

Studies with primary data collection tended to be smaller and aimed to assess women’s empowerment and its impact on reproductive outcomes. Examples include the Survey of Women’s Status and Fertility in Nigeria ( Kritz et al., 2000 ), Women’s Reproductive Choices and Behaviors conducted in Madhya Pradesh, India ( Lee-Rife, 2010 ), and the Status of Women and Fertility survey in five Asian countries ( Mason and Smith, 2000 ). Several of these employed mixed methods—using both qualitative and quantitative methods to focus on issues within specific communities or villages (e.g., Bates et al., 2007 ; Vlassoff, 1991 ). These studies tended to be of high quality and usually made special effort to interpret and synthesize the findings.

Other studies with primary data collection relied on samples from subpopulations such as a village ( Vlassoff, 1991 ) or slum ( Pande et al., 2011 ). Four primary data collection studies were designed to evaluate the impact of microcredit, employment generation, or other non-governmental organization projects on the empowerment of women ( Amin et al., 1995 ; Feldman et al., 2009 ; Mahmud, 1991 ; Steele et al., 1998 ).

Other national datasets used included the Oman National Health Survey 2000 ( Al Riyami and Afifi, 2003a , 2003b ), fertility and family planning surveys (e.g., Hogan et al., 1999 ; Speizer et al., 2005 ), and census data (e.g., Aghajanian, 1992 ; Bhattacharya, 2006 ; Hirschman and Guest, 1990 ; Malhotra et al., 1995 ; Wasim, 2002 ).

The majority of studies were from South Asia ( n = 35, 58%), possibly because some of the earliest conceptualizations were developed in this region ( Bhatt, 1989 ; Dyson and Moore, 1983 ; Vlassoff, 1982 ). Almost one-fifth were from sub-Saharan Africa ( n = 10, 17%), and one-tenth from the Near East and Eurasia ( n = 5, 8%). The fewest studies were in Latin America ( n = 4, 7%) and East Asia ( n = 1, 2%); articles from these regions may be more often published in major regional languages, rather than in English. One study compiled data from multiple countries across South and East Asia and four others compiled data from multiple developing countries worldwide ( Fig. 2 ).

Distribution of articles by region ( n = 60).

Many of the articles reviewed examined multiple fertility-related topics. The majority examined number of children ( n = 38, 63%) or fertility preferences ( n = 18, 30%) as topics ( Fig. 3 ).

Distribution of articles by fertility topic. Note: studies may include multiple topics.

3.2.1. Number of children

We reviewed 38 articles that examined women’s empowerment and the number of children they have had. Most studies ( n = 29) analyzed the number of children either ever born or born within a specific period for individual women ( Adak and Bharati, 2011 ; Al Riyami and Afifi, 2003a , 2003b ; Ali et al., 1995 ; Ali and Sultan, 1999 ; Amin et al., 1995 ; Audinarayana, 1997 ; Balk, 1994 ; Bates et al., 2007 ; Goni and Saito, 2010 ; Gwako, 1997 ; Hari, 1991 ; Hindin, 2000 ; Hirschman and Guest, 1990 ; Jejeebhoy, 1991 ; Jin, 1995 ; Kabir et al., 2005a , 2005b ; Khan and Raeside, 1997 ; Kravdal, 2001 ; Larsen and Hollos, 2003 ; Manzoor and Mahmood, 1993 ; Muhammad and Fernando, 2010 ; Sathar and Kazi, 1997a ; Singh et al., 2002 ; Steele et al., 1998 ; Upadhyay and Karasek, 2012 ; Vlassoff, 1991 ; Yabiku et al., 2010 ). Five studies looked at district-level ( Aghajanian, 1992 ; Bhattacharya, 1998 , 2006 ; Malhotra et al., 1995 ; Wasim, 2002 ), and four at country-level ( Abadian, 1996 ; Sanderson, 2001 ; Sanderson and Dubrow, 2000 ; Wickrama and Lorenz, 2002 ) fertility rates.

Most studies tested multiple measures of empowerment and found an inverse relationship between number of children and at least one empowerment measure. Only three studies failed to find any significant association between number of children and women’s empowerment measures ( Adak and Bharati, 2011 ; Jejeebhoy, 1991 ; Yabiku et al., 2010 ).

Ten studies found significant inverse associations between women’s empowerment and number of children ( Audinarayana, 1997 ; Bhattacharya, 1998 , 2006 ; Hari, 1991 ; Hindin, 2000 ; Jin, 1995 ; Kabir et al., 2005a , 2005b ; Khan and Raeside, 1997 ; Manzoor and Mahmood, 1993 ) while 22 yielded a combination of significant inverse findings and non-significant associations suggesting that the relationship across all empowerment domains is not always consistent or clear ( Abadian, 1996 ; Aghajanian, 1992 ; Al Riyami and Afifi, 2003a , 2003b ; Ali et al., 1995 ; Ali and Sultan, 1999 ; Amin et al., 1995 ; Balk, 1994 ; Bates et al., 2007 ; Booth and Duvall, 1981 ; Goni and Saito, 2010 ; Gwako, 1997 ; Hirschman and Guest, 1990 ; Kravdal, 2001 ; Larsen and Hollos, 2003 ; Malhotra et al., 1995 ; Muhammad and Fernando, 2010 ; Sanderson, 2001 ; Sanderson and Dubrow, 2000 ; Singh et al., 2002 ; Steele et al., 1998 ; Vlassoff, 1991 ; Wasim, 2002 ; Wickrama and Lorenz, 2002 ). For example, Abadian (1996) used the 1992 World Demographic Report on 54 countries to analyze whether three empowerment measures: female age at marriage, age difference between spouses, and female secondary education were associated with total fertility rates. Women’s mean age at marriage ( β = −0.157, p < .05) and secondary education ( β = 0.039, p < .05) were negatively associated with total fertility rates when controlling for family planning effort scores and infant mortality rates. However, no significant associations were found between spousal age difference and total fertility rates. Abadian explains this lack of effect may be because mean spousal age difference is strongly associated with female age at marriage. In another example, Balk’s study (1994) of about 5000 women in 218 rural villages in Bangladesh found, as expected, that mobility was inversely associated with total number of children ever borndboth when looking at village-level ( β = −0.435, p < .01) and individual-level variables ( β = −0.213, p < .001). However, other measures of women’s decision-making power were not significantly associated with fertility. Balk argues that proxy measures of women’s status, such as education and occupation, are less likely than direct measures to adequately measure the association between women’s status and fertility.

Three studies found both positive and inverse associations between empowerment measures and fertility ( Amin et al., 1995 ; Sathar and Kazi, 1997b ; Upadhyay and Karasek, 2012 ). Sathar and Kazi (1997b) who analyzed data from 1036 Pakistani women found that freedom to make household purchases was negatively correlated ( β = −0.101, p < .001; β = −0.136, p < .001), while economic autonomy ( β = 0.068, p < 001; β = 0.167, p < .001) was positively correlated, with both recent and cumulative fertility and mobility was positively correlated with births within the last five years ( β = 0.052, p < .001) but negatively correlated with cumulative fertility ( β = −0.093, p < .001). In another example of unexpected findings, Upadhyay and Karasek (2012) examined the effect of women’s empowerment on ideal family size and achievement of desired fertility among over 8500 matched couples in four sub-Saharan African countries using DHS data. In Namibia greater household decision-making and in Zambia a belief in women’s right to refuse sex were associated with having more children than desired (Odds Ratio (OR) 2.3, 95 percent confidence interval [95% CI] = 1.01–5.34, p < =.05 and OR = 1.4, 95% CI = 1.01–2.02, p < .05 respectively). The authors explain this paradox by concluding that in these countries it may be that more empowered women fulfilled social expectations of high fertility, although they personally desired smaller families.

3.2.2. Fertility preferences

We reviewed 18 articles that examined fertility preferences, such as ideal family size and spousal communication around desired fertility ( Amin et al., 1995 ; El-Zeini, 2008 ; Goni and Saito, 2010 ; Hindin, 2000 ; Hogan et al., 1999 ; Isiugo-Abanihe, 1994 ; Jin, 1995 ; Kritz et al., 2000 ; Mason and Smith, 2000 ; McAllister et al., 2012 ; Moursund and Kravdal, 2003 ; Pande et al., 2011 ; Speizer et al., 2005 ; Steele et al., 1998 ; Upadhyay and Karasek, 2012 ; Vlassoff, 1991 ; Woldemicael, 2009 ; Zafar, 1996 ). All of these studies found that at least some women’s empowerment variables were positively associated with the ability to make fertility decisions and increased spousal communication, but many found significant positive and negative findings, depending upon the context and measures of empowerment used.

All seven studies examining women’s empowerment and desire for more children found a significant inverse association for at least some measures of women’s empowerment, but most also had some non-significant findings ( Hogan et al., 1999 ; Kritz et al., 2000 ; Moursund and Kravdal, 2003 ; Steele et al., 1998 ; Upadhyay and Karasek, 2012 ; Vlassoff, 1991 ; Woldemicael, 2009 ). For example, Steele et al. (1998) found that women’s household decision-making was negatively associated with a desire for more children ( β = −0.24, p < .001), but no association was found with their degree of mobility.

The two contextual-level studies that examined the relationship between women’s empowerment and the desire for more children had inconsistent findings between individual and community-level measures. Moursund and Kravdal (2003) used data from the 1998–99 India National Family Health Survey for 60,382 married women who had at least one child to examine the relationship between women’s autonomy and wanting no more children. At the individual-level, a higher score on the mobility index was associated with wanting no more children ( β = 0.04, p < .05). However, at the community-level, the results suggested that women who lived in areas with higher mobility ( β = −0.57, p < 001) were less likely to report wanting to stop childbearing. The authors could not explain the desire for higher fertility among women in areas where they have considerable freedom of movement. Kritz et al. (2000) examined the desire for more children using data from married women from five regional/tribal groups in Nigeria. Higher decision-making and household financial contributions of individual women were not associated with desire for more children after controlling for regional gender equity and ethnic group. However, when the communities were grouped into low, medium, and high gender equity areas, some interesting differences were noted. In areas of low and medium gender equity, measures of women’s autonomy, such as higher decision-making, some primary education, secondary education, women’s higher financial contribution to the household (in relation to her husband), and labor force participation were positively associated with the desire for no more children. However, in areas of high gender equity, no significant associations were found between women’s autonomy measures and the desire for no more children. Taken together, these contextual-level studies suggest that the context in which women live may be more influential than their own specific level of empowerment.

Seven studies examined women’s empowerment effects on ideal family size preferences ( El-Zeini, 2008 ; Isiugo-Abanihe, 1994 ; McAllister et al., 2012 ; Upadhyay and Karasek, 2012 ; Vlassoff, 1991 ; Woldemicael, 2009 ; Zafar, 1996 ). All found that at least some measures of women’s empowerment were positively associated with smaller ideal family size preferences but all also had non-significant associations and significant negative associations. For example, Woldemicael (2009) demonstrated that women who reported their husbands had all the decision-making power regarding small or large household purchases were more likely to desire large families (five or more children) compared to women who had at least some say in household decisions (OR = 1.39, p < .05; OR = 1.27, p < .05). As expected, women who reported that wife-beating is not justified were less likely to want large families than those who reported that wife-beating was justified (OR = 0.74, p < .01). However, women who reported their husbands had the final decision-making autonomy on whether they could visit family or friends were unexpectedly less likely to desire large families compared to women who reported decision-making autonomy with regard to visiting family or friends (OR = 0.70, p < .05).

Three studies assessed women’s empowerment and ability to make fertility decisions ( Gwako, 1997 ; Jin, 1995 ; Mason and Smith, 2000 ) and all found significant positive associations. Two studies examined the impact of empowerment on husband-wife communication about fertility intentions or preferences ( Hindin, 2000 ; Hogan et al., 1999 ) and found significant positive associations between women’s status variables and couple communication. In Hindin’s study (2000) using Zimbabwe DHS data from 3701 women, those who had no say over household purchases (OR = 0.61, p < .001) were less likely to have discussed their desired number of children with their partners, even after controlling for women’s status variables (e.g., work status, education, literacy). Hogan et al. (1999) examined the effect of women’s empowerment on the likelihood of spousal communication around preferred family size in Ethiopia. Among both urban and rural women, higher age at first marriage (rural OR = 1.65, p < .05; urban OR = 1.59, p < .05), literacy (rural OR = 2.52, p < .05; urban OR = 3.05, p < .05), and involvement in domestic decisions (rural OR = 1.31, p < .05; urban OR = 1.26, p < .05) were associated with increased odds of discussing family size preferences with their husbands.

3.2.3. Birth intervals

Seven studies examined associations between women’s empowerment and birth intervals ( Al Riyami and Afifi, 2003a , 2003b ; Feldman et al., 2009 ; Fricke and Teachman, 1993 ; Isvan, 1991 ; Nath et al., 1999 ; Upadhyay and Hindin, 2005 ) but two report the same findings using the same dataset and analyses ( Al Riyami and Afifi, 2003a , 2003b ). Among the six unique studies, five found significant associations, despite measuring birth spacing differently. Two studies examined the length of the first birth interval (period between marriage and first birth) ( Fricke and Teachman, 1993 ; Nath et al., 1999 ), another examined the length of the most recent closed birth interval (period between two most recent births) ( Al Riyami and Afifi, 2003a , 2003b ), another examined the length of the most recent open birth interval (period between last birth and interview date) ( Isvan, 1991 ), and the remaining two studies examined the length of the birth interval during a specified observation period ( Feldman et al., 2009 ; Upadhyay and Hindin, 2005 ).

Three studies found that greater household decision-making power was associated with longer birth intervals ( Al Riyami and Afifi, 2003a , 2003b ; Nath et al., 1999 ; Upadhyay and Hindin, 2005 ). However, Upadhyay and Hindin (2005) also found that, in the Philippines, women’s status variables, specifically older age at first birth (Hazard ratio (HR) = 1.10, p < .01) and whether the woman works for pay (HR = 1.29, p < .05), shortened birth intervals.

Fricke and Teachman (1993) examined first birth intervals in Nepal, finding that women who had more autonomy in choosing a spouse (OR = 2.41, p < .05) and who were married at age 19 or older had shorter first birth intervals (OR = 4.14, p < .001). The authors concluded that having a choice in one’s spouse and being older foster couple closeness and intimacy, thereby contributing to a shorter interval to first birth.

Feldman et al. (2009) was the one birth interval study that did not find significant associations. This intervention study in Mexico examined the effect of participation in a conditional cash-transfer program on women’s autonomy and its subsequent effect on birth intervals. While the program increased women’s autonomy among participants compared to controls, there was no differential effect on the length of birth intervals, the authors hypothesize, perhaps because the cash-transfer program allowed men to reduce migration for work and remain home, thus driving fertility up to the same levels as the controls.

3.2.4. Unintended pregnancy

Five articles addressed women’s empowerment and unintended pregnancy, finding inconsistent effects. In an analysis of 1200 women from urban and rural areas of the Philippines, Williams, et al. (2000) explored the effects of several domains of women’s agency (i.e., women’s income, education, degree of comfort in discussing sex with husband, and fatalism regarding fertility) on the likelihood of an unintended pregnancy. For rural women, women’s income was associated with a lower likelihood of unwanted pregnancy (ORs = 0.52–0.59 across models), whereas those indicating a higher degree of fertility fatalism were associated with higher odds of an unwanted pregnancy (OR = 2.77). The effects of other domains for rural women and for urban women were not significant or only marginally significant.

Pallitto and O’Campo (2005) examined the relationships between gender inequality, intimate partner violence (IPV), and unintended pregnancy using DHS data from Colombia. They found that women living in municipalities where men exhibit high levels of patriarchal control and high rates of IPV were more likely to experience an unintended pregnancy; however, none of the aggregated autonomy or status variables were significantly associated with unintended pregnancy.

Using life history data from Madhya Pradesh, India, Lee-Rife (2010) conducted an analysis examining the cumulative influence of reproductive events including unwanted or mistimed pregnancy, on several dimensions of empowerment: mobility, financial discretion, violence, and threats of abandonment/homelessness. Reproductive events were associated with the violence dimension only. Women with more mistimed pregnancies were less likely to experience recent violence after controlling for initial empowerment, sociodemographic characteristics, and other covariates.

Two additional analyses used DHS data to examine the relationships between women’s autonomy and unintended pregnancy among married, pregnant women in the Philippines ( Abada and Tenkorang, 2012 ) and in Bangladesh ( Rahman, 2012 ). Abada and Tenkorang (2012) used measures from the 2003 Philippines National Demographic and Health Survey to examine household autonomy and sexual decision-making autonomy, finding that higher household and sexual decision-making autonomy were associated with lower odds of unwanted pregnancy (RR: .458 and .588, respectively). There were no significant effects found, however, for mistimed pregnancies. Moreover, there was an interaction with age, such that older, more autonomous women were more likely to report unwanted pregnancies.

In Rahman’s (2012) analysis, women’s autonomy was assessed according to whether women reported having any say in five household decisions (health care, large household purchases, household purchases for daily needs, visits to family or relatives, and child health care). In multivariate models controlling for sociodemographic characteristics, women with higher autonomy scores were less likely to report an unintended (mistimed or unwanted) pregnancy (OR = 0.84).

3.2.5. Abortion

Only two articles examined the relationship between women’s empowerment and abortion, both focusing on India. The aforementioned analysis by Lee-Rife (2010) of women’s life history data in India (where abortion is legal) indicated that, after controlling for initial empowerment conditions and other covariates, women with more abortions were nearly four times as likely to experience recent violence. The author suggested that women may seek abortion as a means of preventing a child from being born into a violent household, or may suffer a violent response from a husband who disagrees with the use of abortion to regulate fertility.

In Agrawal’s (2012) analysis, women’s autonomy was measured with questions on household decision-making and ability to make decisions regarding money and mobility. Although the effect sizes are somewhat attenuated by the inclusion of sociodemographic and fertility-related variables (e.g., sex composition of living children), the effect of women’s autonomy on the reporting of an abortion persisted—women who reported ‘high’ and ‘medium’ levels of autonomy were significantly more likely to report ever having an abortion (AOR: 1.20 and 1.15, respectively), as compared to women with ‘low’ levels of autonomy. The authors discuss how sociocultural differences across Indian states inform these findings, yet there is limited attention to how women’s autonomy may interact with other factors in predicting abortion, such as son preference or sex composition of children.

4. Discussion

4.1. summary of findings.

Overall, empowerment was inversely associated with number of children in the majority of studies, although many studies also found no association between some indicators of women’s empowerment and number of children. Studies that used multiple and multidimensional measures of empowerment were more likely to find consistent associations, highlighting the importance of choosing appropriate measures that better approximate women’s empowerment.

Empowerment was also demonstrated to be positively associated with fertility preferences, such as the ideal number of children and desire for no more children. When empowerment was measured as higher spousal communication around fertility and women’s reported fertility decision-making ability, they were more likely to be associated with the desire for fewer children. While all of these studies found that at least some women’s empowerment variables were positively associated with fertility preferences, the associations were less consistent than with number of children. Many found significant positive and negative findings, depending upon the measure used and the level of the measure (e.g., individual and/or community-level). These inconsistent findings call attention to the need to better understand the indicators that best approximate empowerment in each study setting ( Moursund and Kravdal, 2003 ; Upadhyay and Karasek, 2012 ).

Together, the birth interval studies suggest that household decision-making power lengthens birth intervals, but certain aspects of women’s empowerment contribute to shorter birth intervals. As women attempt to reconcile opportunities such as education and work with childbearing, birth intervals may become shorter. For example, two studies found that older age at first birth was associated with shorter birth intervals, suggesting that these women may be trying to “catch up” with other women and one also found that working for pay shortened birth intervals ( Fricke and Teachman, 1993 ; Upadhyay and Hindin, 2005 ).

The few studies assessing the relationship between empowerment and unintended pregnancy found inverse associations and non-significant effects (e.g., Pallitto and O’Campo, 2005 ). Similar to the complexities inherent in measuring women’s empowerment, pregnancy intention is also a nuanced, multidimensional, and culturally-defined construct ( Santelli et al., 2003 ). The literature has yet to comprehensively address the extent to which the perceived ability to control fertility (the ‘calculus of conscious choice’) ( Coale, 1973 ) and the labeling of pregnancies as ‘unwanted’ or ‘unintended’ is itself an indicator of women’s agency or empowerment. The scarcity of studies on the relationships between empowerment and both unintended pregnancy and abortion is remarkable and an area for future research.

There are three limitations to acknowledge. First, it is possible that relevant studies were omitted if they used different terms to describe empowerment than those included in our search criteria. Second, we omitted articles in non-English languages that undoubtedly add to the theory and current knowledge in this area. This may explain why few studies in Latin America were identified. Third, since this review emphasizes breadth over depth; interesting study-specific issues, such as the interactive effects of particular sociodemographic characteristics or context-specific measures, were not highlighted.

4.2. Selecting appropriate measures of empowerment

Certain measures of women’s empowerment, such as household decision-making, are used much more frequently than other measures. The household decision-making domain was one of the earliest ways of operationalizing women’s empowerment ( Dyson and Moore, 1983 ) and formed the basis of empowerment items incorporated into the standard questionnaire of the DHS ( Kishor and Subaiya, 2008 ). Other domains, such as mobility, appeared frequently due to the predominance of studies from South Asia where mobility is considered a key indicator of women’s empowerment. Although the repeated use of specific measures across study settings facilitates global comparisons, continued work is needed to determine the relevance and validity of these measures, especially in lesser studied settings ( Agarwala and Lynch, 2006 ; Mumtaz and Salway, 2009 ). Further research should also test innovative and infrequently used measures of women’s empowerment (e.g., exposure to public life, aspirations) as listed in Table 1 .

Another measurement issue concerns the use of proxy measures to represent women’s empowerment. Women’s education, for example, is a marker of numerous influences and processes – family socioeconomic status, family investment in a daughter’s social development, sufficient mobility to attend school, and exposure to new ‘worldviews’ ( Jejeebhoy, 1995 ). While some studies simply controlled for women’s education, others used it as a proxy for women’s empowerment or women’s status ( Al Riyami and Afifi, 2003a , 2003b ; Hindin, 2000 ; Upadhyay and Hindin, 2005 ; Woldemicael, 2009 ). When proxy measures (e.g., education, employment, economic status) were included alongside other measures of women’s empowerment, researchers often found independent effects suggesting that they exert their influence in different ways ( Woldemicael, 2009 ). Future research could, either through the study design or the analysis phase, tease apart the individual contributions of education—and other sociodemographic characteristics—and women’s empowerment, as well as assess their synergistic influences. Such research would help disentangle complex causal pathways and better direct subsequent research and intervention efforts ( Upadhyay and Karasek, 2012 ).

More fundamentally, defining and appropriately operationalizing women’s empowerment remains a challenge. Studies examining the effect of empowerment across settings and populations found differential effects of measures across subgroups or settings, even within the same country or region (e.g., Hogan et al., 1999 ). The “well-kept” measure in the Philippines ( Upadhyay and Hindin, 2005 ) exemplifies the unique capabilities of qualitative research methods in constructing locally-relevant measures and testing the validity of existing measures. Qualitative research is also critical in identifying the multiple dimensions of women’s empowerment and illustrating the ways in which women may be more empowered within certain domains of their lives, as compared to others ( Gipson and Hindin, 2007 ). The multidimensionality of women’s empowerment likely contributed to some of the null and counterintuitive effects of empowerment measures in this review, emphasizing the importance of further refinement and conceptualization of women’s empowerment measures, as well as the incorporation of statistical techniques (e.g., multilevel and structural equation modeling) to better capture this complex, latent construct in quantitative analyses. Multidimensional measures of women’s empowerment that represent a single domain sometimes improve explanatory power ( Agarwala and Lynch, 2006 ). For example, empowerment measured by several items representing involvement in fertility and/or family planning decisions was consistently associated with fertility (e.g., Gwako, 1997 ; Jin, 1995 ; Pande et al., 2011 ). Lastly, considerable variation in the operationalization of empowerment measures likely affects what can be learned from the comparison of measures across studies. For example, the household decision-making measures can be constructed to examine ‘sole’ versus ‘joint’ decision-making, or to determine whether women had ‘any’ say in these household decisions, each of which may produce different estimates when examining relationships with reproductive outcomes ( DeRose and Ezeh, 2010 ). Moreover, the chosen constructions of these measures may also reflect biases on the part of the researchers in what defines women’s empowerment in a particular setting and if these constructions are even an appropriate or worthwhile goal ( Mumtaz and Salway, 2009 ). Further investigations of the linkages between women’s empowerment and health outcomes will continue to benefit from these debates and discussions, particularly those that draw on developments and insights gained from diverse multi-disciplinary perspectives.

4.3. Study design considerations for future research

This review revealed key issues that affect our ability to understand the linkages between and the conclusions drawn from existing studies on women’s empowerment and fertility. We suggest ways in which subsequent studies could advance this area of investigation.

First, there is a predominance of studies from South Asia. While the persistence of norms and practices that subjugate South Asian girls and women (e.g., sex-selective abortion and child marriage) warrant continued attention, other regions, like East Asia and Latin America, are minimally represented in this review. The gravitation towards certain research settings narrows our understanding of the linkages between women’s empowerment and fertility when comparing studies globally, as well as when attempting to understand the unique relationships and mechanisms within each region.

Additionally, most studies in this review included only currently married women and no studies included never married women as a focus of study. Although this review focuses on fertility-related topics that, in many settings, are most likely to occur within the context of marriage, including unmarried women in subsequent studies could illuminate interactions between women’s empowerment and relationship status on fertility-related outcomes. Similarly, few studies include matched couples or male perspectives on women’s empowerment. Collecting information from both partners provides the opportunity to account and control for men’s characteristics and fertility desires within the same models, as well as to assess couple concordance regarding reproductive intentions.

Beyond the inclusion of male partners, more studies are needed that account for the influence of communities and broader, sociopolitical forces on women’s empowerment and fertility outcomes. Several reviewed studies found synergistic or countervailing influences of individual and community-level measures of women’s empowerment on reproductive outcomes (e.g., Balk, 1994 ; Kritz et al., 2000 ; Pallitto and O’Campo, 2005 ). Although limited, these studies demonstrate the need to incorporate multiple levels of analysis to examine how social environment shapes the construction of empowerment and its relationship to fertility. Related to this, multilevel modeling could also be harnessed to shed light on the complex interactions between women’s empowerment, operating at the individual level and gender equity, operating at levels higher than the individual ( Malhotra, 2012 ).

We identified only a few studies that evaluated interventions aimed to mediate the relationship between women’s empowerment and reproductive health, which were almost entirely focused on credit programs (e.g., Amin et al., 1995 ; Feldman et al., 2009 ; Steele et al., 1998 ). Other types of interventions aimed at fostering women’s empowerment merit further investigation, especially given the ongoing empowerment programs being implemented by organizations such as the Population Council and the International Center for Research on Women.

Finally, the majority of the studies in this review relied on cross-sectional data, which limits our understanding of the linkages between women’s empowerment and fertility. Cross-sectional data does not allow us to map causal pathways nor determine the direction of causality – i.e., how does women’s empowerment cause changes in fertility outcomes? These relationships may also work in the opposite direction, such that fertility outcomes may cause changes in women’s empowerment, or be mutually influencing. Even when the measurement of empowerment precedes an outcome (e.g., subsequent fertility), we are still unable to establish causality in the absence of controls for external, concurrent secular changes that are also likely to influence these relationships. Longitudinal designs are needed to better reflect the process of women’s empowerment and to determine the causal mechanisms and mediating factors that may facilitate or hinder women’s empowerment ( Malhotra et al., 2002 ). As noted by Lee-Rife (2010) , the significant and independent effects found for women’s initial empowerment conditions (i.e., between marriage and first birth) highlight the importance of examining the “trajectory” and the dynamic nature of women’s empowerment across the life course and in response to reproductive events.

5. Conclusion

Improvements in the status and empowerment of women is central to progress in global development efforts and, perhaps more importantly, to the achievement of equitable treatment and representation of the 3.5 billion women in the world. Understanding individual women’s experience of empowerment and its effects is a crucial early step in making major advances in gender equity at the society level, and in achieving the Millennium Development Goal of promoting gender equality and empowering women. This review is one of the few efforts to provide an overview of quantitative studies assessing the relationships between women’s empowerment and fertility. It is our hope that this review serves as a resource to researchers, practitioners, and policymakers to help shape directions for future research and programmatic efforts.

Acknowledgments

This research was supported by the University of California Global Health Institute (UCGHI) Women’s Health and Empowerment Center of Expertise. U. Upadhyay’s participation was supported by the Advancing New Standards in Reproductive Health (ANSIRH) program at University of California, San Francisco (UCSF). J. Gipson’s participation was supported by NIH Grant #1K01HD067677. A. Fraser and N. Prata’s participation was supported by the Bixby Center for Population, Health and Sustainability, University of California, Berkeley. S. Lewis’ work on this paper was initiated while she was at the ANSIRH Program at UCSF. E. Ciaraldi’s participation was supported by the the Bixby Center on Population and Reproductive Health in the Fielding School of Public Health. M. Huchko’s participation was supported by UCSF-CTSI Grant Number KL2 RR024130. The authors thank Stephanie Blount for assistance with initial literature searches and Sheila Desai for reviewing the draft.

• Abada T, Tenkorang EY. Women’s autonomy and unintended pregnancies in the Philippines. J. Biosoc. Sci. 2012; 44 :703–718. [ PubMed ] [ Google Scholar ]
• Abadian S. Women’s autonomy and its impact on fertility. World Dev. 1996; 24 :1793–1809. [ Google Scholar ]
• Adak DK, Bharati P. Position of women in the Ladiya society: demographic perspectives. Coll. Antropol. 2011; 35 :319–324. [ PubMed ] [ Google Scholar ]
• Agarwala R, Lynch SM. Refining the measurement of women’s autonomy: an international application of a multi-dimensional construct. Soc. Forces. 2006; 84 :2077–2098. [ Google Scholar ]
• Aghajanian A. Status of women and fertility in Iran. J. Comp. Fam. Stud. 1992; 23 :361–374. [ Google Scholar ]
• Agrawal S. The sociocultural context of family size preference, ideal sex composition, and induced abortion in India: findings from India’s national family health surveys. Health Care Women Int. 2012; 33 :986–1019. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Al-Riyami AA, Afifi M. Determinants of women’s fertility in Oman. Saudi Med. J. 2003a; 24 :748–753. [ PubMed ] [ Google Scholar ]
• Al Riyami A, Afifi M. Women empowerment and marital fertility in Oman. J. Egypt Public Health Assoc. 2003b; 78 :55. [ PubMed ] [ Google Scholar ]
• Ali SM, Siyal HB, Sultan M. Women’s empowerment and reproductive choices. Pak. Dev. Rev. 1995; 34 (1):137–150. [ PubMed ] [ Google Scholar ]
• Ali SM, Sultan M. Socio-cultural constraints and women’s decision-making power regarding reproductive behaviour. Pak. Dev. Rev. 1999:689–696. [ Google Scholar ]
• Amin R, Hill RB, Li Y. Poor women’s participation in credit-based self-employment: the impact on their empowerment, fertility, contraceptive use, and fertility desire in rural Bangladesh. Pak. Dev. Rev. 1995; 34 :93–120. [ Google Scholar ]
• Audinarayana N. The effects of status of women on fertility in an urban setting of Tamil Nadu. Indian J. Soc. Work. 1997; 58 :542–556. [ Google Scholar ]
• Balk D. Individual and community aspects of women’s status and fertility in rural Bangladesh. Popul. Stud. 1994; 48 :21–45. [ Google Scholar ]
• Bates LM, Maselko J, Schuler SR. Women’s education and the timing of marriage and childbearing in the next generation: evidence from rural Bangladesh. Stud. Fam. Plan. 2007; 38 :101–112. [ PubMed ] [ Google Scholar ]
• Bhatt E. Toward empowerment. World Dev. 1989; 17 :1059–1065. [ Google Scholar ]
• Bhattacharya PC. Determinants of fertility in three north Indian states: caste, female autonomy and economic development. Can. J. Dev. Stud. Rev. Can. d’études Du. dév. 1998; 19 :37–53. [ Google Scholar ]
• Bhattacharya PC. Economic development, gender inequality, and demographic outcomes: evidence from India. Popul. Dev. Rev. 2006; 32 :263. [ Google Scholar ]
• Blanc AK. The effect of power in sexual relationships on sexual and reproductive health: an examination of the evidence. Stud. Fam. Plann. 2001; 32 :189–213. [ PubMed ] [ Google Scholar ]
• Booth A, Duvall D. Sex roles and the link between fertility and employment. Sex. Roles. 1981; 7 :847–856. [ PubMed ] [ Google Scholar ]
• Caldwell JC. Routes to low mortality in poor countries. Popul. Dev. Rev. 1986; 12 :171–220. [ PubMed ] [ Google Scholar ]
• Carr B, Gates MF, Mitchell A, Shah R. Giving women the power to plan their families. Lancet. 2012; 380 :80–82. [ PubMed ] [ Google Scholar ]
• Cleland J, Bernstein S, Ezeh A, Faundes A, Glasier A, Innis J. Family planning: the unfinished agenda. Lancet. 2006; 368 :1810–1827. [ PubMed ] [ Google Scholar ]
• Coale A. The Population Debate: Dimensions and Perspectives. United Nations, New York: 1973. The Demographic Transition. [ Google Scholar ]
• Crossette B. Reproductive health and the millennium development goals: the missing link. Stud. Fam. Plann. 2005; 36 :71–79. [ PubMed ] [ Google Scholar ]
• DeRose LF, Ezeh AC. Decision-making patterns and contraceptive use: evidence from Uganda. Popul. Res. Policy Rev. 2010; 29 :423–439. [ Google Scholar ]
• Dyson M, Moore M. On kinship structure, female autonomy, and demographic behaviour in India. Popul. Dev. Rev. 1983; 9 :35–60. [ Google Scholar ]
• El-Zeini LO. The path to replacement fertility in Egypt: acceptance, preference, and achievement. Stud. Fam. Plan. 2008; 39 :161–176. [ PubMed ] [ Google Scholar ]
• Feldman BS, Zaslavsky AM, Ezzati M, Peterson KE, Mitchell M. Contraceptive use, birth spacing, and autonomy: an analysis of the Oportunidades program in rural Mexico. Stud. Fam. Plan. 2009; 40 :51–62. [ PubMed ] [ Google Scholar ]
• Fricke T, Teachman JD. Writing the names: marriage style, living arrangements, and first birth interval in a Nepali society. Demography. 1993; 30 :175–188. [ PubMed ] [ Google Scholar ]
• Gipson JD, Hindin MJ. ‘Marriage means having children and forming your family, so what is the need of discussion?’ – communication and negotiation of childbearing preferences among Bangladeshi couples. Cult. Health & Sex. 2007; 9 :185–198. [ PubMed ] [ Google Scholar ]
• Goni MA, Saito O. Fertility decline and women’s status: a micro data analysis of the role of non-governmental organizations (NGOs) in Bangladesh. Int. NGO J. 2010; 5 :88–101. [ Google Scholar ]
• Gwako EL. Conjugal power in rural Kenya families: its influence on women’s decisions about family size and family planning practices. Sex. Roles. 1997; 36 :127–147. [ PubMed ] [ Google Scholar ]
• Hari M. Modernisation, status of women and fertility. J. Fam. Welf. 1991; 37 :62–67. [ Google Scholar ]
• Hindin M. Women’s autonomy, women’s status and fertility-related behavior in Zimbabwe. Popul. Res. Policy Rev. 2000; 19 :255–282. [ Google Scholar ]
• Hirschman C, Guest P. Multilevel models of fertility determination in four Southeast Asian countries: 1970 and 1980. Demography. 1990; 27 :369–396. [ PubMed ] [ Google Scholar ]
• Hogan DP, Berhanu B, Hailemariam A. Household organization, women’s autonomy, and contraceptive behavior in southern Ethiopia. Stud. Fam. Plan. 1999; 30 :302–314. [ PubMed ] [ Google Scholar ]
• Isiugo-Abanihe UC. The socio-cultural context of high fertility among Igbo women. Int. Sociol. 1994; 9 :237–258. [ PubMed ] [ Google Scholar ]
• Isvan NA. Productive and reproductive decisions in Turkey: the role of domestic bargaining. J. Marriage Fam. 1991; 53 :1057–1070. [ Google Scholar ]
• Jejeebhoy S. Women’s Education, Autonomy, and Reproductive Behaviour: Experience from Developing Countries. Clarendon Press; Oxford: 1995. p. 328. [ Google Scholar ]
• Jejeebhoy SJ. Women’s status and fertility: successive cross-sectional evidence from Tamil Nadu, India, 1970-80. Stud. Fam. Plann. 1991; 22 :217–230. [ PubMed ] [ Google Scholar ]
• Jin H. A study of rural women’s decision-making power on reproduction and fertility. Chin. J. Popul. Sci. 1995; 7 :241–257. [ PubMed ] [ Google Scholar ]
• Kabeer N. Resources, agency, achievements: reflections on the measurement of women’s empowerment. Dev. Change. 1999; 30 :435–464. [ Google Scholar ]
• Kabeer N. Discussing Women’s Empowerment—Theory and Practice. Novum Grafiska AB; Stockholm: 2001. Reflections on the Measurement of Women’s Empowerment. [ Google Scholar ]
• Kabir A, Ibrahim QI, Kawsar LA. Relationships between factors affecting contraception and fertility in Bangladesh. Int. Q. Community Health Educ. 2005a; 24 :45–53. [ PubMed ] [ Google Scholar ]
• Kabir MA, Khan M, Kabir M, Rahman M, Patwary M. Impact of woman’s status on fertility and contraceptive use in Bangladesh: evidence from Bangladesh demographic and health survey, 1999-2000. J. Fam. Welf. 2005b; 51 :1. [ Google Scholar ]
• Khan H, Raeside R. Factors affecting the most recent fertility rates in urban-rural Bangladesh. Soc. Sci. Med. 1997; 44 :279–289. [ PubMed ] [ Google Scholar ]
• Kishor S, Subaiya L. Comparative Report. Macro International Inc.; Calverton, Maryland: 2008. Understanding Women’s Empowerment: a Comparative Analysis of Demographic and Health Surveys (DHS) Data. http://www.measuredhs.com/pubs/pdf/CR20/CR20.pdf . [ Google Scholar ]
• Kravdal Ø. Main and interaction effects of women’s education and status on fertility: the case of Tanzania. Eur. J. Popul./Rev. Eur. De. Démogr. 2001; 17 :107–135. [ Google Scholar ]
• Kritz M, Makinwa-Adebusoye P, Gurak D. The role of gender context in shaping reproductive behaviour in Nigeria. In: Presser H, Sen G, editors. Female Empowerment and Demographic Processes: Moving Beyond Cairo. Oxford University Press; London: 2000. pp. 239–260. [ Google Scholar ]
• Larsen U, Hollos M. Women’s empowerment and fertility decline among the Pare of Kilimanjaro region, Northern Tanzania. Soc. Sci. Med. 2003; 57 :1099–1115. [ PubMed ] [ Google Scholar ]
• Lee-Rife SM. Women’s empowerment and reproductive experiences over the lifecourse. Soc. Sci. Med. 2010; 71 :634–642. [ PubMed ] [ Google Scholar ]
• Mahmud S. Current contraception among programme beneficiaries. Bangladesh Dev. Stud. 1991; 19 :35–61. [ PubMed ] [ Google Scholar ]
• Malhotra A. Fertility and Empowerment Work Paper Series 001-2012-ICRW-FE. International Center for Research on Women; 2012. Remobilizing the Gender and Fertility Connection: the Case for Examining the Impact of Fertility Control and Fertility Declines on Gender Equality; p. 38. [ Google Scholar ]
• Malhotra A, Schuler SR, Boender C. Measuring Women’s Empowerment as a Variable in International Development. Washington, DC: 2002. p. 58. http://hdr.undp.org/docs/network/hdr_net/GDI_GEM_Measuring_Womens_Empowerment.pdf . [ Google Scholar ]
• Malhotra A, Vanneman R, Kishor S. Fertility, dimensions of patriarchy, and development in India. Popul. Dev. Rev. 1995; 21 :281–305. [ Google Scholar ]
• Manzoor K, Mahmood N. An attempt to measure female status in Pakistan and its impact on reproductive behaviour [with Comments] Pak. Dev. Rev. 1993; 32 :917–930. [ PubMed ] [ Google Scholar ]
• Mason KO. The status of women: conceptual and methodological issues in demographic studies. Sociol. Forum. 1986; 1 :284–300. [ Google Scholar ]
• Mason KO, Smith HL. Husbands’ versus wives’ fertility goals and use of contraception: the influence of gender context in five Asian countries. Demography. 2000; 37 :299–311. [ PubMed ] [ Google Scholar ]
• McAllister L, Gurven M, Kaplan H, Stieglitz J. Why do women have more children than they want? Understanding differences in women’s ideal and actual family size in a natural fertility population. Am. J. Hum. Biol. 2012; 24 :786–799. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Moursund A, Kravdal Ø. Individual and community effects of women’s education and autonomy on contraceptive use in India. Popul. Stud. 2003; 57 :285–301. [ PubMed ] [ Google Scholar ]
• Muhammad A, Fernando R. Status of women and fertility in Pakistan. Can. Stud. Popul. 2010; 37 :1–23. [ Google Scholar ]
• Mumtaz Z, Salway S. Understanding gendered influences on women’s reproductive health in Pakistan: moving beyond the autonomy paradigm. Soc. Sci. Med. 2009; 68 :1349–1356. [ PubMed ] [ Google Scholar ]
• Nath DC, Land KC, Goswami G. Effects of the status of women on the first-birth interval in Indian urban society. J. Biosoc. Sci. 1999; 31 :55–69. [ PubMed ] [ Google Scholar ]
• Pallitto CC, O’Campo P. Community level effects of gender inequality on intimate partner violence and unintended pregnancy in Colombia: testing the feminist perspective. Soc. Sci. Med. 2005; 60 :2205–2216. [ PubMed ] [ Google Scholar ]
• Pande RP, Falle TY, Rathod S, Edmeades J, Krishnan S. ‘If your husband calls, you have to go’: understanding sexual agency among young married women in urban South India. Sex. Health. 2011; 8 :102–109. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Rahman M. Women’s autonomy and unintended pregnancy among currently pregnant women in Bangladesh. Maternal Child. Health J. 2012:1–9. [ PubMed ] [ Google Scholar ]
• Sanderson SK. An evolutionary interpretation of fertility decline: new evidence. Popul. Environ. 2001; 22 :555–563. [ Google Scholar ]
• Sanderson SK, Dubrow J. Fertility decline in the modern world and in the original demographic transition: testing three theories with cross-national data. Popul. Environ. 2000; 21 :511–537. [ Google Scholar ]
• Santelli J, Rochat R, Hatfield-Timajchy K, Gilbert B, Curtis K, Cabral R, et al. The measurement and meaning of unintended pregnancy. Perspect. Sex. Reprod. Health. 2003; 35 :94–101. [ PubMed ] [ Google Scholar ]
• Sathar Z, Kazi S. Women’s Autonomy, Livelihood and Fertility: a Study of Rural Punjab. 1997a (Chapter 4) [ Google Scholar ]
• Sathar ZA, Kazi S. Women’s Autonomy, Livelihood and Fertility: A Study of Rural Punjab. Pakistan Institute of Development Economics; Islamabad: 1997b. Marriage, Fertility, and Contraception. [ Google Scholar ]
• Singh K, Singh K, Singh B, Pathak A. Impact of education and autonomy on fertility of women in Eastern Uttar Pradesh. Demogr. India. 2002; 31 :223–234. [ Google Scholar ]
• Speizer IS, Whittle L, Carter M. Gender relations and reproductive decision making in Honduras. Int. Fam. Plan. Perspect. 2005; 31 :131–139. [ PubMed ] [ Google Scholar ]
• Steele F, Amin S, Naved RT, Division PCPR. The Impact of an Integrated Micro-credit Program on Women’s Empowerment and Fertility Behavior in Rural Bangladesh. The Population Council, Policy Research Division; 1998. [ Google Scholar ]
• United Nations . United Nations General Assembly Resolution 55/2. United Nations; New York: 2000. United Nations Millennium Declaration. http://www.un.org/millennium/declaration/ares552e.pdf . [ Google Scholar ]
• Upadhyay UD, Hindin MJ. Do higher status and more autonomous women have longer birth intervals? Results from Cebu, Philippines. Soc. Sci. Med. 2005; 60 :2641–2655. [ PubMed ] [ Google Scholar ]
• Upadhyay UD, Karasek D. Women’s empowerment and ideal family size: an examination of DHS empowerment measures in sub-Saharan Africa. Int. Perspectives Sex. Reproductive Health. 2012; 38 :78–89. [ PubMed ] [ Google Scholar ]
• Vlassoff C. The status of women in rural India: a village study. Soc. Action. 1982; 32 :380–407. [ PubMed ] [ Google Scholar ]
• Vlassoff C. Progress and stagnation: changes in fertility and women’s position in an Indian village. Popul. Stud. 1991; 46 :195–212. [ Google Scholar ]
• Wasim MP. Status of women indicators, infant mortality rate and birth rate: a study of high Crude birth rate districts of Pakistan. Indian Econ. Rev. 2002:117–134. [ Google Scholar ]
• Wickrama K, Lorenz FO. Women’s status, fertility decline, and women’s health in developing countries: direct and indirect influences of social status on health. Rural. Sociol. 2002; 67 :255–277. [ Google Scholar ]
• Williams L, Sobieszczyk T, Perez A. Couples’ views about planning fertility in the Philippines*. Rural. Sociol. 2000; 65 :484–514. [ Google Scholar ]
• Woldemicael G. Women’s autonomy and reproductive preferences in Eritrea. J. Biosoc. Sci. 2009; 41 :161–181. [ PubMed ] [ Google Scholar ]
• World Bank . World Development Report 2012: Gender Equality and Development. World Bank; Washington, DC: 2012. https://openknowledge.worldbank.org/handle/10986/4391 . [ Google Scholar ]
• Yabiku ST, Agadjanian V, Sevoyan A. Husbands’ labour migration and wives’ autonomy, Mozambique 2000-2006. Popul. Stud. 2010; 64 :293–306. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Zafar MI. Husband-wife roles as a correlate of contraceptive and fertility behaviour. Pak. Dev. Rev. 1996; 35 :145–170. [ PubMed ] [ Google Scholar ]

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• Published: 21 May 2024

Effect of the contextual (community) level social trust on women’s empowerment: an instrumental variable analysis of 26 nations

• Alena Auchynnikava 1 ,
• Nazim Habibov   ORCID: orcid.org/0000-0003-3862-4348 1 ,
• Yunhong Lyu 2 &
• Lida Fan 3  

Humanities and Social Sciences Communications volume  11 , Article number:  648 ( 2024 ) Cite this article

Metrics details

• Social policy

The purpose of this paper is to examine the effect of contextual (community) level social trust on women’s empowerment. The specific knowledge gap explored in this study is that the previous studies theorized that community trust has a positive impact on women’s empowerment. Thus, an increase in trust in the community will empower women. However, such an assumption has been never empirically tested and confirmed. Against this backdrop, the present paper develops a theoretical argument on why the increase in community trust should lead to a higher level of women empowerment. Then, a cross-country survey was used as a data source to test the effect of community trust on women’s empowerment. A traditional single-stage OLS and instrumental variable regressions are estimated to test the effect of community trust on women’s empowerment and quantify the magnitude of such impact. The key finding of this paper is that community trust indeed significantly strengthens the empowerment of women by increasing women’s ownership of assets and improving the decision-making authority of women in the family. Importantly, our findings are robust for the separate rural and urban samples, as well as the samples of younger and older women. Equally, our findings are robust for an alternative set of instruments. The main implication of these findings is that policymakers, social administrators, and government authorities who are working on promoting gender equality should give priority to promoting community-based interventions that nurture and maintain women’s trust.

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Introduction.

Women’s empowerment is a strong precursor to economic development and poverty reduction across nations and over time (Doepke and Tertilt, 2019 ; UN, 2016 ; Wei et al., 2021 ). Thus, women’s decision-making power within families is associated with higher work productivity (Diiro et al., 2018 ), the rise in the share of the family budget spent on food and pro-children’s expenditures (Bobonis, 2009 ; Doss, 2013 ), increases in calorie availability and dietary diversity for families (Sraboni et al., 2014 ), and improvement in child nutrition, anthropometric, and health outcomes (Duflo, 2003 ; Malapit et al., 2015 ). It is also associated with a higher level of labor force participation (Majlesi, 2016 ) and a higher propensity for the use of prenatal, natal, and post-natal healthcare services (Auchynnikava and Habibov, 2021 ). Similarly, possession of assets such as land, bank accounts, and dwellings by women leads to a higher proportion of the family budget being spent on education (Quisumbing and Maluccio, 2003 ) and nutrition (Doss, 2013 ). The ownership of assets by women also increases the likelihood of prenatal healthcare utilization (Beegle et al., 2001 ) and reduces the probability of intimate partner violence (Pereira et al., 2017 ).

Examining the origins of women’s empowerment has become one of the important research objectives in women’s studies, economics, political science, and sociology (Doepke and Tertilt, 2019 ). Empowerment can arise through several different pathways, of which one is social capital (Machio et al. 2022 ). Social capital can be defined as trust within a network of individuals, their participation in local organizations, and reciprocity norms that facilitate cooperation for mutual benefit (Bourdieu, 1985 ; Putnam, 2000 ). A handful of studies have examined the association of social capital with the empowerment of women. Investigating a macro-finance program in Cameroon, Mayoux ( 2001 ) found that the social capital that was generated by the program considerably strengthened women’s empowerment. Social networks can support the dissemination of knowledge, which women can then use to their advantage (Hanmer and Klugman, 2016 ). If such networks teach members how to be assertive, joining networks can boost a woman’s ability to make decisions at home. Participation in self-help groups was found to be positively correlated with empowerment in Ethiopia (Alemu et al., 2018 ), Kenya (Po and Hickey, 2020 ), and India (Nayak and Panigrahi, 2020 ). The most recent study on Kenya by Machio et al. ( 2022 ) reported that active participation in local groups and maintaining a network of people to rely on lead to higher levels of women’s empowerment.

Against this backdrop, the current study contributes to the extant literature from both theoretical and methodological perspectives. From a theoretical perspective, one of our contributions is that we focus on contextualized community-level social trust, whereas previous studies have concentrated on individual-level social trust only. Another theoretical contribution is that the literature on women’s empowerment has focused exclusively on the network component of social capital, while the current study examines social trust.

From the research perspective, our contribution is that, as far as we know, it is the first study to use the instrumental variable regression method (IV) to quantify the effect of social trust on women’s empowerment. The majority of earlier research has cross-sectional designs, which renders the results susceptible to the problems of reverse causality, unobserved factors, and measurement error.

Finally, in our focus on the region of the post-communist countries, we are guided by theoretical, practical, and research considerations. From the policy standpoint, the focus on the post-communist countries can be explained by the fact that women’s empowerment has been considerably weakened in post-communist countries since the commencement of transitional from communist command-administrative socio-economic system to a more open market-oriented one, while the literature on the determinants of women empowerment in these countries is limited (Auchynnikava and Habibov, 2021 ; Barrett et al., 2012 ; Habibov et al., 2017 ). From the practical perspective, by focusing on the post-communist countries, we can utilize a unique large multinational survey in a diverse set of countries. In comparison, previous studies have concentrated on a single country as a case study, such as Ethiopia (Alemu et al., 2018 ), Kenya (Po and Hickey, 2020 ), and India (Nayak et al. 2020 ) reducing the generalizability of their findings. It is especially important since interpretations of social capital and women’s empowerment measures vary significantly across cultures, traditions, and societies, thus also affecting the universality of the previous findings (van Hoorn ( 2015 ); Hanmer and Klugman, 2016 ). Lastly, from the research standpoint, using such a unique data set on post-communist countries allows us to analyze information on the link between various dimensions of women’s empowerment and social trust, while previous studies almost exclusively focused only on social networks. Hence, the current study enriches the research literature on the link between women’s empowerment and different dimensions of social capital, especially those at the community level.

With this information in mind, let us move to the Theoretical Foundation section below.

Theoretical foundation

The outcome of interest: women’s empowerment.

Women’s empowerment refers to their liberation from discriminatory practices and gender-based prejudices in the economic, cultural, social, and political spheres (Adhikari et al. 2023 ). It encompasses giving women the autonomy to follow the paths they want to take in life and ensure the freedom to openly express their ideas, develop their self-esteem, and bargain for what they want by granting them greater autonomy and responsibility to make decisions that affect their own lives and providing them with pertinent resources, assets, and skills (Sharma, 2020 ). As outlined above, uncovering and evaluating the roots of women’s empowerment has emerged as one of the key research goals in economics, development studies, women’s studies, social policy, and sociology (Doepke and Tertilt, 2019 ).

Women’s asset ownership and women’s autonomy in decision-making

In the spirit of Kishor ( 2000 ), this study uses women’s assets and women’s autonomy in decision-making as the main indicators of women’s empowerment. Exploring the usefulness of various possible indicators of women’s empowerment, Kishor critiqued studies that merely link women’s empowerment with the achievement of demographic goals, like higher employment and education rates for failing to assess whether these goals have resulted in a rise in women’s control over their own live and environment (p. 124). For Kishor, such demographic goals are means of achieving the outcome of empowerment but not the ultimate outcomes of empowerment. Instead, Kishor advanced the notion of empowerment as an outcome. Thus, Kishor suggests that effective indicators of women’s empowerment should incorporate: (1) indicators that reveal evidence of achieving empowerment, for example, the extent of control women over household decisions, and (2) indicators that reveal of sources empowerment, for example, ownership of assets.

Similarly, Kabeer ( 1999 , p.366) distinguished between resource and agency. Resources are the characteristics that facilitate women’s empowerment. They include assets and access to resources. In comparison, the agency referred to autonomy and control over key decisions. Therefore, regardless of the exact terminology used, there seems to be agreement in the literature that empowerment is a multifaceted construct encompassing the resources women need and the power to make choices.

Predictor of interest: contextualized community-level social trust

The current study focuses on contextualized community-level social trust as the predictor of women’s empowerment. In comparison, previous studies have concentrated on individual-level social trust only as they followed the tradition of conceptualizing social capital as the resources embedded within an individual’s durable social network, and therefore the analysis was conducted at the individual level (Bourdieu, 1985 ; Lin, 1999 ; Arezzo and Giudici, 2017 ). However, the novelty of the concept of social capital lies in its collective, contextualized, area-level leverage (Kim et al., 2011 ; De Clercq et al. 2012 ; Habibov and Cheung, 2018 ). This line of conceptualization originates from the work of Putnam ( 2000 ), who demonstrated that social capital plays a role in the public good at both the community and area levels. For Putnam, social capital is an ecological characteristic and a collective resource that could be properly assessed at contextualized levels such as regions, areas, communities, or neighborhoods (Berkman and Kawachi, 2000 ). Mutual trust, strong social connections, and high rates of engagement in community affairs in selected regions of Italy were found to be the driving forces that created positive spillovers with potential benefits for all the citizens of the regions (Putnam et al., 1993 ). As such, this study follows Putnam’s tradition in conceptualizing social capital as a contextualized community resource, and it also fills the gap in the existing literature by testing its relationship with women’s empowerment.

At the same time, it should be highlighted that the current study examines social trust, while the previous literature on women’s empowerment has focused exclusively on the network component of social capital. Following Coleman’s ( 1988 ) tradition, social trust is considered to be a key cognitive dimension of social capital, which bolsters mutually reciprocal relationships within a network (Adjaye-Gbewonyo et al., 2018 ). The traditional survey question about social trust, articulated as “generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people”, has been used in the literature to capture the variation in social trust (Zhang, 2020 ).

At the individual level, social trust can be thought of either as particularized or generalized trust (Newton and Zmerli, 2011 ). Particularized trust is trust towards individuals we know, for instance, family members, relatives, co-workers, and neighbors. In contrast, generalized trust is trust towards unknown strangers. Particular and generalized types of trust at the individual level correspond with notions of bonding and bridging social capital (Giordano et al., 2012 ). Particularized trust is a type of bonding social capital that denotes trust between people who are similar in some aspects, for instance, place of residence or place of job. Conversely, generalized trust is a type of bridging social capital that links people from different places of residence and jobs. However, when averaged at the community level, social trust incorporates features of both types of trust (Zhang, 2020 ). Community-level social trust brings together particularized (i.e., bonding) and generalized (i.e., bridging) trust since it encompasses trust in unknown persons but among those individuals who reside in the same community (Glanville and Story, 2018 ; Wollebaek et al., 2012 ).

Link between contextualized community-level social trust and women’s empowerment

Evidence suggests that social trust at the community level may create an environment that facilitates women’s empowerment. It lowers the cost of social and commercial transactions by reducing the need for formal agreements, legal and regulatory frameworks, and costly enforcement (Sturgis et al., 2015 ). In this way, it helps increase employment and private entrepreneurship by enabling people to engage in secure and predictable ways (Bjørnskov, 2008 ; Kwon et al., 2013 ). As a result, a higher level of community-level trust is found to increase the probability of finding new employment, increasing hours of work at current jobs, and starting a new business (Habibov and Afandi, 2017 ). A higher level of trust is also a prerequisite for a more effective bureaucracy, a more just judicial system, and a higher level of reliability of market transactions that provide stronger protection for assets and property rights (Collier, 2002 ; Maluccio et al., 2000 ; Habibov et al., 2019 ).

Instruments

This is the first study to employ IV regression to evaluate the effect of social trust on women’s empowerment. The majority of earlier research has cross-sectional correlation designs, which renders the results susceptible to the problems of reverse causality, unobserved factors, and measurement error. Indeed, it is conceivable that causality runs in the opposite direction, specifically, from women’s empowerment towards higher trust. For instance, women with higher levels of trust may be more likely to be engaged in entrepreneurship, which would increase their level of empowerment. It is similarly conceivable that there could be unobservable factors, for example, personality traits or a previous history of relationships, that simultaneously affect trust and empowerment. Finally, both trust and empowerment are attitudinal subjective variables that are prone to a high degree of measurement error (Edlund, 2006 ). If issues related to reverse causality, unobserved factors, and measurement error are not taken explicitly into account, the result of regression model estimations will be inefficient and biased (Cameron and Trivedi, 2022 ). Estimation of IV requires instruments which are variables that are correlated with the predictor, but not the outcome. Two instruments, namely, population density and willingness to take the risk, are used in our main analysis, while the additional pair of instruments that are used for robustness analysis includes: latitude and caloric sustainability index.

Population density

The first instrument that is used in the main analysis is population. Population density is used as an instrument for social trust since it is a common determinant of social trust and is widely used in the existing literature (Beaumont et al., 2021 ). Higher population densities could theoretically cause public mistrust since “dense” social situations encourage individuals to withdraw inward in order to protect their privacy (Collier, 1998 ). This theoretical postulate was tested and confirmed in a number of population-based empirical studies across the world (Brueckner and Largey, 2008 ; Kim et al., 2011 ; Taylor et al., 2007 ). This postulate was also confirmed by experimental studies that demonstrated that reduced population density has been linked to acts of helpfulness (a notion closely connected to reciprocity and social trust) displayed by locals to strangers (Levine et al., 1994 ).

Willingness to take the risk

The second instrument that is used in the main analysis, is the degree of willingness to take the risk (Papadimitri et al., 2021 ). The theoretical reasoning behind this instrument is the Hofstede model (Hofstede, 2001 ), which postulates the significant differences between individualistic and collectivistic societies in relation to risk-taking. In collectivistic societies, people tend to value the collective over the individual and emphasize group accomplishments that require collective actions and hence higher levels of social trust (Gaganis et al., 2019 ). In contrast, in individualistic societies with lower needs for collaboration, cooperation, cohesion, and social trust, people tend to be more self-centered, independent, and primarily concerned with themselves and their close family members (Gaganis et al., 2019 ). In turn, individualism tends to promote overconfidence, underestimation of risks, and a higher likelihood of being engaged in risk-taking (Chui et al., 2010 ; Breuer et al., 2014 ; Ferris et al., 2013 ; Van den Steen, 2004 ). Conversely, people in collectivistic societies exhibit higher degrees of uncertainty avoidance and take fewer risks (Hofstede et al., 2010 ).

Latitude is an instrument that is used in the robustness analysis. Latitude is the absolute latitudinal distance from the community to the equator. Geographic latitude has been employed as an instrument of social trust in a number of previous studies since individuals residing in high-latitude areas are more likely to trust each other to help each other survive harsh weather (Folland, 2007 ; Lee and Law, 2017 ), while historically, trade relationships were more developed in lower latitude coastal areas where individuals developed more open-minded trusting attitudes towards strangers (Xiong et al., 2017 ; Papadimitri et al., 2021 ).

Caloric sustainability index

The Caloric Sustainability Index is another instrument for the robustness analysis. It is an indicator of the agricultural potential gauged which is defined the caloric yield that has been available for cultivation in the period after 1500 (Galor and Özak, 2016 ). The theoretical reasoning behind using this instrument is that low suitability for agriculture is associated with higher degrees of cooperation and the collective actions that are required for planning and harvesting (Ashkanasy et al., 2004 ; Gaganis et al., 2019 , Meggers, 1954 ). Thus, lower levels of land productivity in the past have been found to be a direct precursor to higher levels of current trust (Litina, 2016 ).

Data, variables, and measurement

Although designing a survey to specifically capture community social trust and women’s empowerment would be ideal, it is very costly to create such surveys, especially to cover multiple countries. As such, surveys that test social trust and women’s empowerment are presently limited to very few selected countries (Hanmer and Klugman, 2016 ). To increase the generalizability and universality of findings, researchers have to turn to publicly available surveys that are currently in existence and that cover a large number of countries. The Life-in-Transition Survey (henceforth LITS) is one of the best currently available surveys for this purpose (Habibov et al., 2017a ). The LITS is a cross-sectional and multidisciplinary survey that contains records on the demographic, social, and economic characteristics of respondents and their beliefs and attitudes (EBRD, 2016 ). The third wave of the LITS first introduced questions about women’s status. It is for this reason that this current study is based on the third wave, which was conducted in 2016. In total, our sample consists of 23,292 women who reside in 26 post-communist countries in Eastern and Central Europe and Eurasia, including the former Soviet Union and Mongolia. The LITS uses a consistent survey design methodology, sampling design, and research questions that render direct comparability of data across countries (Habibov et al., 2017b ). In each country under investigation, about 1500 individuals were interviewed by trained interviewers. The number of women participating in the survey in each country can be found in Table 1 .

Guided by previous studies that used publicly available surveys (Aktakke et al., 2019 ; Barrett et al., 2012 ; Habibov et al., 2017a ; Davis and Williamson, 2019 ), we constructed two indices that capture women’s empowerment: (1) the Index of Women’s Asset Ownership and (2) the Index of Women’s Autonomy in Household Decision-Making. The Index of Women’s Asset Ownership is based on LITS questions that ask women about their ownership of three types of assets, namely, (a) land, (b) bank account, and (c) dwelling. The answers to these three questions are binomial (1= Yes, if women report ownership of a particular asset; 0 = No, if no ownership). The answers to these three questions are added up to create the summative Index of Women’s Asset Ownership. The index varies from 0 if a woman does not possess any assets to 3 if she possesses all three types of assets. Thus, a higher value of this index indicates a higher degree of asset ownership.

The Index of Women’s Autonomy in Household Decision-Making is based on three questions about the degree of a woman’s independence in taking decisions on: (a) controlling daily expenditures and paying bills; (b) saving, investing, and borrowing; and (c) making significant purchases for the home. The answers to these three questions are binomial. The responses are coded as 1 if the decisions are taken by the woman herself, equally with the partner, or equally with someone else in the family. In contrast, responses are coded as 0 if decisions are taken by a partner, by someone else in the family, or by someone else outside the family. The binomial responses are added up into the summative Index of Women’s Autonomy in Household Decision-Making. The index varies from 0 to 3. A higher value of the index reflects a higher level of autonomy for a woman.

The main predictor of interest is community social trust. Social trust was derived from the following question in the LITS: “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people? Please tell me on a scale from 0 to 10, where 0 means you can’t be too careful and 10 means that most people can be trusted”. Following the literature, individual responses averaged across communities will gauge the level of community social trust (Kim et al., 2011 ; Campos-Matos et al., 2015 ; Habibov and Cheung, 2018 ).

The first Instrument, population density, is measured as persons/km2 and is taken from the International Database of the US Census Bureau ( 2016 ). The second instrument, the degree of willingness to take the risk, is measured by using a question in the LITS that asks respondents to rate their willingness to take risks on a scale from 1 to 10, where 1 means that a respondent is not willing to take risks at all, and 10 means that the respondent is very willing to take risks. The responses are averaged at the country level to arrive at a country-level indicator of risk-taking.

We control for a comprehensive set of covariates that have been shown in earlier studies to have an effect on the level of women’s empowerment (Abbas et al., 2021 ; Abu-Lughod, 2009 ; Cinar and Kose, 2018 ). These covariates at the individual level encompass socio-economic characteristics such as age, marital status, education, and employment. At the family level, these covariates capture family compositional characteristics, namely, the share of young children (aged 0–7), older children (aged 8–17), adults (older than 16 and younger than 65), and elderly (aged 65 or older). Other family covariates capture socio-economic factors such as family income and expenditures, as well as place of residence in terms of rural vs. urban residence. All individual and family-level covariates are from the LITS. At the country level, cross-country variation is gauged by the Human Development Index, which has been compiled by the United Nations ( 2016 ) to incorporate life expectancy, educational attainment, and gross national income per capita, as well as a percentage of annual GDP growth by the World Bank ( 2016 ).

All variables used in the analysis (including outcomes, predictor, covariates and instruments), their definitions, and descriptive statistics can be found in Table 2 .

Method: instrumental variables

The simplest statistical technique to estimate the effect of community trust on women’s empowerment is to compute a conventional OLS model with one of the women’s empowerment indices serves as the dependent variable of interest while community level trust serves as the independent variable of interest. However, as mentioned in the opening section, such a basic method provides inconsistent and biased results due to endogeneity in the form of reverse causality, omitted variables, and measurement error. To tackle endogeneity, we estimate an instrumental variable (IV) regression model that consists of two stages, where each stage is an OLS regression (Cameron and Trivedi, 2022 ). In the first stage of OLS regression, the predictor, community trust, is regressed on a set of covariates and an instrument. In the second stage of OLS regression, the outcome variable, one of the indices of women’s empowerment, is regressed on the estimated value of community trust from the first stage and the set of covariates. The mathematical model used in this study can be summarized as follows:

\({{IV}}_{i}\) represents the excluded exogenous regressors. It is the instrument variable. \({Y}_{i}\) is the dependent variable for the ith observation and \({Z}_{i}\) is the predictor (represents the endogenous regressors) that is trust at community level. \({{\rm{X}}}_{{\rm{i}}}\) ’s is the set of covariates.

All estimations are conducted with Stata software package version 15.

Analytical plan

Estimation of IV regression can provide consistent and unbiased results if the selected instrument meets two conditions: the instrument is theoretically justified and empirically associated with the predictor (relevance condition), and the instrument is not directly correlated with the outcome (exclusion condition). As discussed and justified in the Theoretical Foundation section of the paper, two instruments, namely, (a) population density and (b) willingness to take the risk meet these conditions from the theoretical point of view. Furthermore, these conditions are empirically tested and reported in section 4.4 below.

Each of the instruments is used for separate analyses. Thus, all IV models that are estimated with population density as an instrument are denoted as Set A. In comparison, all IV models estimated with risk-taking as an instrument are denoted as Set B. Since we have two outcome variables of interest, estimations with Set A and Set B are conducted and reported separately for each outcome. In addition, in the sensitivity analysis, we extend our main model to test the robustness of the results for separate rural/urban and age samples, as well as the inclusion of individual-level trust and an additional set of instrumental variables.

OLS results

The results of single-stage OLS estimates are reported in the first two models of Table 3 . Model 1 reports OLS results for the Women’s Asset Ownership Index. Results suggest that a one-unit increase in community-level social trust is associated with an increase in women’s asset ownership by a factor of 0.103. Model 2 reports OLS results for the Women’s Autonomy in Household Decision-Making Index. Results suggest that there is no statistically significant association between social trust and women’s autonomy in decision-making. It should be recalled that classic OLS does not take into account the problems of reverse causality, omitted variables, and measurement error. Therefore, the results of OLS models should be considered descriptive and serve as a benchmark for further analysis with IV models.

Main results with IV

The results of IV estimations are reported in the last four columns of Table 3 . Models 3 and 4 show the results of IV estimations for Set A (where the instrument is population density). Both models indicate that higher levels of trust lead to a higher degree of women’s empowerment, although the effect of social trust is relatively stronger in magnitude for asset ownership as compared to household decision-making. Thus, Model 3 suggests that for a unit increase in social trust, women’s asset ownership increases by a factor of 1.215. In comparison, Model 4 suggests that for a unit increase in social trust, women’s autonomy in household decision-making improved by a factor of 0.270.

The results of IV estimations for Set B (where the instrument is risk-taking) are presented in Models 5 and 6. Again, both models indicate a significant positive effect of social trust on women’s empowerment, with the effect of social trust being a little bit stronger in magnitude for asset ownership as compared with household decision-making. For a unit increase in trust, asset ownership improves by a factor of 0.555 in Model 5, while household decision-making improves by a factor of 0.540.

The comparison across OLS and IV models in Table 3 reveals that OLS results are lower than IV results regardless of what instrument is employed. Such results signal that single-stage OLS models considerably underestimate the true effect of social trust on women’s empowerment since they do not take into account the problems of reverse causality, omitted variables, and measurement error.

Robustness testing and main model extensions

Several checks are performed to examine the robustness of our main results. First, the results are tested for separate urban and rural samples. The objective is to find out if the positive effect of trust on women’s empowerment could be observed in both samples, given that more patriarchal attitudes could be expected in rural areas than urban ones. Second, the results are tested for separate samples of younger and older women. The objective is to find out if the positive impact of trust on women’s empowerment varies considerably with age since trust may vary with socialization and experience. Fourth, the results are tested for the inclusion of social trust at the individual level, which can be correlated with the community-level social trust model. Finally, the results are tested for an alternative set of two instruments.

The results of IV estimations for separate urban and rural samples are presented in Table 4 . The results of estimations using Set A in Models 7 to 10 signal a positive effect of trust on women’s empowerment. This holds true for both outcomes of interest. The results of estimations using Set B in Models 11 to 14 tell a similar story. Nevertheless, it should be highlighted that, in all estimations, the magnitude of the effect of social trust on women’s empowerment is higher for rural samples. In fairness, the difference in effect between rural and urban samples is not substantial.

The results of IV estimations for women younger than 45 and older than 45 are presented in Table 5 . The results of estimations using Set A in Models 15 to 18 indicate a positive effect of trust on empowerment for both groups of women, irrespective of the outcome variable of interest. The results of estimations using Set B in Models 19 to 22 are comparable. Interestingly, in the majority of models (Models 15 to 20), the magnitude of the trust effect is greater for the sample of older women. In contrast, in Models 21 and 22, the magnitude of the effect is greater for the sample of younger women.

The results are tested for the inclusion of social trust at the individual level in Table 6 . The results of estimations using Sets A and B in Models 23 to Model 26 confirm the positive effect of community-level social trust on empowerment after controlling for individual- level trust. Note the negative sign for the individual level of trust. Such a counterintuitive direction of the effect is likely to be the result of multicollinearity with community-level trust. The community level of trust is not affected by multicollinearity because it is controlled by instruments, while individual-level trust is not.

Finally, our main models are tested by including a different set of instruments, namely, (a) Latitude and (b) the Caloric Suitability Index. Latitude is measured as the absolute latitudinal distance from the community to the equator, which is available in the LITS. The Caloric Suitability Index is available from Galor and Özak ( 2016 ).

The results of IV estimation with an alternative pair of instruments are reported in Models 27 and 28 of Table 6 . Reported results confirm that social trust leads to significant improvements in indicators of women’s empowerment.

Testing the estimated IV models

To test the assumption that the instrument is correlated with the predictor, the first-stage robust F statistic is estimated and reported for all models at the end of the respective tables (Cameron and Trivedi, 2022 ). The significant F statistic that is higher than 10 indicates that all estimated regression model instruments are strongly correlated with the predictor.

To test for a weak instrument, the formal test proposed by Stock and Yogo ( 2005 ) is used. The minimum eigenvalue statistics and Stock and Yogo’s critical values are estimated and reported for all models at the end of the respective tables. In all models, the minimum eigenvalue statistics are considerably lower than Stock and Yogo’s critical values indicating that our instruments are not weak (Stock et al., 2002 ; Stock and Yogo, 2002 ).

To test endogeneity, Durbin and Wu-Hausman tests for endogeneity are estimated for all models and reported at the end of the respective tables (Cameron and Trivedi, 2022 ). The significant value of the tests signals the presence of endogeneity. Such results suggest that IV should preferred over the single-stage models, such as OLS, since estimation of OLS in this case will produce biased results.

To test whether instruments are not correlated with the outcome other than via the predictor, Sargan and Basman overidentification tests are estimated for the models with two instruments (Models 27–28). Non-significant results of these tests confirm that taken together these instruments are not correlated with outcome (Baum, 2006 ). Although Sargan and Basman tests are for the models with two instruments and hence are not available for the models with a single instrument, Pearson’s correlation between each instrument and each outcome in all models with a single instrument is not higher than r = 0.1 (Cameron and Trivedi, 2022 ). Such correlation is considered negligible in the literature (Schober et al., 2018 ).

It should be noted that all instruments are measured at a larger geographical area than the predictor of interest, inasmuch as our instruments are at the country level, while the predictor is at the community level. The reason is that the severity of endogeneity is likely to decrease with an increase in the geographic size of the instrument (Dustmann and Preston, 2001 ; Awaworyi Churchill et al., 2019 ).

Discussion and implications

Given the paucity of studies on the effect of contextualized community-level social capital, and especially social trust, on the empowerment of women, we examined such an effect on a large and diverse sample of 26 post-communist countries. Reviewing results from the existing literature enables us to theorize that higher levels of community social trust will translate into higher levels of women’s empowerment. In the spirit of the previous studies, women’s empowerment is conceptualized as women’s ownership of assets and their decision-making authority in the family. To empirically test this theoretical assumption, we estimated single-stage OLS and IV regression models.

In line with our theoretical reasoning, the results of this paper suggest that community trust strengthens women’s empowerment. The results indicate that an increase in community-level trust leads to an increase in women’s ownership of assets and in women’s decision-making authority in the family. The assumption of a positive impact of community trust on women’s empowerment could be theoretically based on the findings of previous studies. However, there is a concern that this assumption has never been tested and confirmed. Hence, the main theoretical contribution of this paper is that it empirically proves this theoretical assumption. Importantly, our findings are robust for the separate samples of rural and urban, and younger and older women. Equally, our findings are robust for an alternative set of instruments.

Furthermore, our findings are also robust for controlling for individual-level trust and a comprehensive set of covariates at the individual, family, and country levels. The effect of community-level trust remains positive and significant even when we include individual trust and other covariates in the equations. This finding highlights the fact that community trust has an independent effect on women’s empowerment. As the first study to cover so many diverse countries with different cultures, traditions, and levels of socio-economic development, the generalizability of the findings has increased.

In addition, this study provides clarification on the causal link between community social trust and women’s empowerment. The estimation of IV models strengthens our conviction about the strong positive effect of community trust on women’s empowerment. At the same time, our findings help to quantify the effect of community social trust by highlighting the large differences in the estimated effect of community social trust between OLS and IV. They suggest that OLS (and other classic single-stage models) are likely to produce inefficient and biased results because of the problems of reverse causality, omitted variables, and measurement error. Consequently, caution should be exercised when evaluating the results of single-stage models.

From an organizational standpoint, the findings of this study suggest that community interventions aimed at developing and maintaining women’s groups will not only offer emotional and social support for women but will enable women to get access to assets and increase their decision-making authority. The example of such successful interventions can be found in developing countries and well-documented in the literature (Alemu et al., 2018 ; Po and Hickey, 2020 ). Thus, the organizations that are involved in community development should adapt these interventions to the specific conditions of the post-communist countries.

From the government standpoint, policymakers, social administrators, and government authorities who are working on promoting gender equality should give priority to promoting community-based interventions that nurture and maintain women’s trust. Adopting relevant legislation and regulation, formalizing women’s organizations, for instance, women self-help groups, women conversation groups, and other women informal groups, as well as channeling financial resources towards such organizations are identified in the literature as effective ways to facilitate the development of trust (Machio et al. 2022 ; Thapa Karki and Xheneti, 2018 ). For women who seek empowerment and men who want to help empower women, the findings of this study suggest that they should consider joining women’s groups in the community as the pathway to improve their empowerment (Nayak and Panigrahi, 2020 ).

Based on the insights from this study, much more research is warranted on this interesting topic. Future studies should extend the investigation of social trust to the nexus of women’s empowerment along several complementary avenues. First, they should include a wider range of indicators that could better gauge different dimensions of women’s empowerment and social trust beyond those used in the current study. For instance, increasing the range of relevant women’s assets could be a very useful way to confirm and extend our findings. Second, in comparison with the secondary analysis of the existing survey, the development of specific purpose surveys could lead to the acquisition of richer information about trust and empowerment. Ideally, such a survey would allow for country-by-country comparisons, which this study was not able to employ due to the small country samples that were available to it. Comparing the effect of trust on the empowerment of women in countries with different levels of socio-economic development, especially those with different levels of women’s empowerment, could complement the findings of the current study. Third, despite the fact that there are no theoretical or empirical grounds on which to believe that the instruments may have had a direct impact on the outcome, such a probability cannot be fully dismissed. Finally, qualitative studies could provide excellent information about which of the dimensions of empowerment and trust are the most important. Likewise, qualitative studies can provide important information about the mechanisms through which trust translates to empowerment. Overall, the implications and caveats of the current study should be kept in mind to help shape future investigations Footnote 1 .

Data availability

The data sets used or analyzed during the current study are provided as supplementary files.

While Machio et al. ( 2022 ) employed IV method as well, their study does not consider social trust and does not take into consideration contextualized community-level indicators.

Abbas S, Isaac N, Zia M, Zakar R, Fischer F (2021) Determinants of women’s empowerment in Pakistan: evidence from Demographic and Health Surveys, 2012–13 and 2017–18. BMC Public Health 21(1):1–14. https://doi.org/10.1186/s12889-021-11376-6

Article   Google Scholar  

Abu-Lughod L (2009) Dialects of women’s empowerment: the international circuitry of the Arab human development report 2005. Int J Middle East Stud 41(1):83–103

Adhikari D, Gazi KH, Giri BC, Azizzadeh F, Mondal SP (2023) Empowerment of women in India as different perspectives based on the AHP-TOPSIS inspired multi-criterion decision making method. Results Control Optim 12:100271. https://doi.org/10.1016/j.rico.2023.100271

Adjaye-Gbewonyo K, Kawachi I, Subramanian SV, Avendano M (2018) High social trust associated with increased depressive symptoms in a longitudinal South African sample. Soc Sci Med 197:127–135. https://doi.org/10.1016/j.socscimed.2017.12.003

Article   PubMed   Google Scholar  

Aktakke N, Aran MA, Munoz Boudet AM (2019) Gender Relations in Europe and Central Asia: Results from the Life in Transition Survey III. SSRN Electronic J https://doi.org/10.2139/ssrn.3426165

Alemu SH, Van Kempen L, Ruben R (2018) Women empowerment through self-help groups: the bittersweet fruits of collective apple cultivation in highland Ethiopia. J Hum Dev Capabil 19(3):308–330. https://doi.org/10.1080/19452829.2018.1454407

Arezzo MF, Giudici C (2017) The effect of social capital on health among European Older adults: an instrumental variable approach. Soc Indic Res 134(1):153–166. https://doi.org/10.1007/s11205-016-1411-5

Ashkanasy NM, Gupta V, Mayfield MS, Trevor-Roberts E (2004) Future orientation. in Culture, leadership and organizations: The globe study of 62 societies (pp. 282–342). London: SAGE Publications Inc

Auchynnikava A, Habibov N (2021) Women’s decision-making autonomy and utilization of antenatal, natal and post-natal healthcare services: Insights from Tajikistan’s national surveys. Int J Health Plann Manag 36(1):158–172

Awaworyi Churchill S, Farrell L, Smyth R (2019) Neighbourhood ethnic diversity and mental health in Australia. Health Econ 28(9):1075–1087. https://doi.org/10.1002/hec.3928

Barrett BJ, Habibov N, Chernyak E (2012) Factors affecting prevalence and extent of intimate partner violence in Ukraine. Violence Women 18(10):1147–1176. https://doi.org/10.1177/1077801212464387

Baum CF (2006) An introduction to modern econometrics using stata. Stata Press, College Station, Tx

Google Scholar  

Beaumont J-F, Bocci S, Fonberg J, Schellenberg G (2021) Measuring social capital at the neighborhood level: experimental estimates of sense of belonging to the local community measured at the census tract level. Analytical Studies: References and Methods: Statistics Canada. https://publications.gc.ca/collections/collection_2021/statcan/11-633-x/11-633-x2021007-eng.pdf

Beegle K, Frankenberg E, Thomas D (2001) Bargaining power within couples and use of prenatal and delivery care in Indonesia. Stud Fam Plan 32(2):130–146. https://doi.org/10.1111/j.1728-4465.2001.00130.x

Article   CAS   Google Scholar  

Berkman LF, Kawachi I (2000) Social Cohesion, Social Capital, and Health. In Soc Epidemiol. Oxford University Press, New York

Bjørnskov C (2008) Social capital and happiness in the United States. Appl Res Qual Life 3(1):43–62. https://doi.org/10.1007/s11482-008-9046-6

Bobonis GustavoJ (2009) Is the allocation of resources within the household efficient? New evidence from a randomized experiment. J Polit Econ 117(3):453–503. https://doi.org/10.1086/600076

Bourdieu P (1985) The forms of capital. Greenwood, New York

Breuer W, Riesener M, Salzmann AJ (2014) Risk aversionvs.individualism: what drives risk taking in household finance? Eur Rev Financ 20(5):446–462. https://doi.org/10.1080/1351847x.2012.714792

Brueckner JK, Largey AG (2008) Social interaction and urban sprawl. J Urban Econ 64(1):18–34. https://doi.org/10.1016/j.jue.2007.08.002

Cameron AC, Trivedi PK (2022) Microeconometrics using Stata. Stata Press, College Station, Texas

Campos-Matos I, Subramanian SV, Kawachi I (2015) The “dark side” of social capital: trust and self-rated health in European countries. Eur J Public Health 26(1):90–95. https://doi.org/10.1093/eurpub/ckv089

Chui ACW, Titman S, Wei KCJ (2010) Individualism and Momentum around the World. J Financ 65(1):361–392. https://doi.org/10.1111/j.1540-6261.2009.01532.x

Cinar K, Kose T (2018) The determinants of women’s empowerment in Turkey: a multilevel analysis. South Eur Soc Polit 23(3):365–386. https://doi.org/10.1080/13608746.2018.1511077

Collier P (1998) The political economy of ethnicity. CSAE Work Pap Ser 1998-08, Centre for the Study of African Economies, University of Oxford

Collier P (2002) Social capital and poverty: a microeconomic perspective. In The role of social capital in development: An empirical assessment (pp. 19–41). Cambridge University Press Cambridge, UK

Coleman JS (1988) Social Capital in the Creation of Human Capital. Am J Socio 94:S95–S120. https://doi.org/10.1086/228943

Davis LS, Williamson CR (2019) Does individualism promote gender equality? World Dev 123:104627. https://doi.org/10.1016/j.worlddev.2019.104627

De Clercq B, Vyncke V, Hublet A, Elgar FJ, Ravens-Sieberer U, Currie C, Maes L (2012) Social capital and social inequality in adolescents’ health in 601 Flemish communities: a multilevel analysis. Soc Sci Med 74(2):202–210. https://doi.org/10.1016/j.socscimed.2011.10.025

Diiro GM, Seymour G, Kassie M, Muricho G, Muriithi BW (2018) Women’s empowerment in agriculture and agricultural productivity: Evidence from rural maize farmer households in western Kenya. PLOS ONE 13(5):e0197995. https://doi.org/10.1371/journal.pone.0197995

Article   CAS   PubMed   PubMed Central   Google Scholar  

Doepke M, Tertilt M (2019) Does female empowerment promote economic development? J Econ Growth 24(4):309–343. https://doi.org/10.1007/s10887-019-09172-4

Doss C (2013) Intrahousehold Bargaining and Resource Allocation in Developing Countries. World Bank Res Obs 28(1):52–78. https://doi.org/10.1093/wbro/lkt001

Duflo E (2003) Grandmothers and Granddaughters: Old-Age Pensions and Intrahousehold Allocation in South Africa. World Bank Econ Rev 17(>1):1–25. https://doi.org/10.1093/wber/lhg013

Article   MathSciNet   Google Scholar  

Dustmann C, Preston I (2001) Attitudes to ethnic minorities, ethnic context and location decisions. Eco J 111(470):353–373. https://doi.org/10.1111/1468-0297.00611

EBRD. (2016). Life in transition survey III. London: European Bank for Reconstruction and Development and World Bank. https://www.ebrd.com/what-we-do/economic-research-and-data/data/lits.html

Edlund J (2006) Trust in the Capability of the Welfare State and General Welfare State Support: Sweden 1997–2002. Acta Sociol 49(4):395–417. https://doi.org/10.1177/0001699306071681

Ferris SP, Jayaraman N, Sabherwal S (2013) CEO Overconfidence and International Merger and Acquisition Activity. J Financ Quant Anal 48(1):137–164. https://doi.org/10.1017/s0022109013000069

Folland S (2007) Does “community social capital” contribute to population health? Soc Sci Med 64(11):2342–2354. https://doi.org/10.1016/j.socscimed.2007.03.003

Article   MathSciNet   PubMed   Google Scholar  

Gaganis C, Hasan I, Papadimitri P, Tasiou M (2019) National culture and risk-taking: Evidence from the insurance industry. J Bus Res 97:104–116. https://doi.org/10.1016/j.jbusres.2018.12.037

Galor O, Özak Ö (2016) The Agricultural Origins of Time Preference. Am Econ Rev Insights 106(10):3064–3103. https://doi.org/10.1257/aer.20150020

Giordano GN, Björk J, Lindström M (2012) Social capital and self-rated health–a study of temporal (causal) relationships. Soc Sci Med 75(2):340–348

Glanville JL, Story WT (2018) Social capital and self-rated health: clarifying the role of trust. Soc Sci Res 71:98–108. https://doi.org/10.1016/j.ssresearch.2018.01.002

Habibov N, Afandi E (2017) Community-level social capital and household strategies for coping with global crisis in transitional Countries. Soc Indic Res 130(2):687–710. https://doi.org/10.1007/s11205-015-1197-x

Habibov N, Cheung A (2018) The contextual-level effects of social trust on health in transitional countries: Instrumental variable analysis of 26 countries. Int J Health Plann Manag 33(1):225–234. https://doi.org/10.1002/hpm.2427

Habibov N, Cheung A, Auchynnikava A (2017b) Does trust increase willingness to pay higher taxes to help the needy? Int Soc Secur Rev 70(3):3–30. https://doi.org/10.1111/issr.12141

Habibov N, Barrett BJ, Chernyak E (2017a) Understanding Women’s empowerment and its determinants in post-communist Countries: results of Azerbaijan National Survey. Women’s Stud Int Forum 62:125–135

Habibov N, Auchynnikava A, Luo R (2019) Does community level trust improve self-rated welfare? Soc Indic Res 146(3):669–697. https://doi.org/10.1007/s11205-019-02139-3

Hanmer L, Klugman J (2016) Exploring Women’s agency and empowerment in developing countries: where do we stand? Fem Econ 22(1):237–263. https://doi.org/10.1080/13545701.2015.1091087

Hofstede G (2001) Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations. Sage, Thousand Oaks, CA

Hofstede G, Hofstede GJ, Minkov M (2010) Cultures and Organizations: Software of the Mind: Intercultural Cooperation and Its Importance for Survival (3rd ed.). Maidenhead: McGraw-Hill

International Database of US Census Bureau. (2016). Retrieved from www.census.gov website: https://www.census.gov/data-tools/demo/idb

Kabeer N (1999) Resources, agency, achievements: reflections on the measurement of Women’s empowerment. Dev Change 30(3):435–464. https://doi.org/10.1111/1467-7660.00125

Kim D, Baum CF, Ganz ML, Subramanian SV, Kawachi I (2011) The contextual effects of social capital on health: a cross-national instrumental variable analysis. Soc Sci Med 73(12):1689–1697. https://doi.org/10.1016/j.socscimed.2011.09.019

Article   PubMed   PubMed Central   Google Scholar  

Kishor S (2000) Empowerment of Women in Egypt and Links to the Survival and Health of Their Infants. In Women’s Empowerment and Demographic Processes: Moving Beyond Cairo. Oxford University Press, New York/Oxford

Kwon K, Heflin C, Ruef M (2013) Community social capital and entrepreneurship. Am Socio Rev 78(6):980–1008

Lee WC, Law SH (2017) Roles of formal institutions and social capital in innovation activities: a cross-country analysis. Glob Eco Rev 46(3):203–231. https://doi.org/10.1080/1226508x.2017.1292859

Levine RV, Martinez TS, Brase G, Sorenson K (1994) Helping in 36 U.S. cities. J Pers Soc Psychol 67(1):69–82. https://doi.org/10.1037/0022-3514.67.1.69

Lin N (1999) Building a network theory of social capital. Connections 22(1):28–51

Litina A (2016) Natural land productivity, cooperation and comparative development. J Econ Growth 21(4):351–408. https://doi.org/10.1007/s10887-016-9134-7

Machio PM, Kimani DN, Kariuki PC, Ng’ang’a AM, Alice Muthoni, MM (2022) Social Capital and Women’s Empowerment. Forum Soc Econ, 1–19

Majlesi K (2016) Labor market opportunities and women’s decision making power within households. J Dev Econ 119:34–47. https://doi.org/10.1016/j.jdeveco.2015.10.002

Malapit HJL, Kadiyala S, Quisumbing AR, Cunningham K, Tyagi P (2015) Women’s empowerment mitigates the negative effects of low production diversity on maternal and child nutrition in Nepal. J Dev Stud 51(8):1097–1123. https://doi.org/10.1080/00220388.2015.1018904

Maluccio J, Haddad L, May J (2000) Social capital and household welfare in South Africa, 1993–98. J Dev Stud 36(6):54–81. https://doi.org/10.1080/00220380008422654

Mayoux L (2001) Tackling the downside: social capital, women’s empowerment and micro-finance in Cameroon. Dev Change 32(3):435–464

Meggers BJ (1954) Environmental limitation on the development of culture. Am Anthropol 56(5):801–824. https://doi.org/10.1525/aa.1954.56.5.02a00060

Nayak AK, Panigrahi PK (2020) Participation in self-help groups and empowerment of women: a structural model analysis. J Dev Areas, 54(1). https://doi.org/10.1353/jda.2020.0001

Newton K, Zmerli S (2011) Three forms of trust and their association. Eur Polit Sci Rev 3(02):169–200. https://doi.org/10.1017/s1755773910000330

Papadimitri P, Pasiouras F, Tasiou T (2021) Do national differences in social capital and corporate ethical behaviour perceptions influence the use of collateral? Cross-country evidence. J Bus Ethics 172(4):765–784

Pereira A, Peterman A, Yount K (2017) Exploring Women’s empowerment through asset ownership and experience of intimate partner violence. Am J Public Health 107(5):747–755

Po JYT, Hickey GM (2020) Cross-scale relationships between social capital and women’s participation in decision-making on the farm: a multilevel study in semi-arid Kenya. J Rural Stud 78:333–349. https://doi.org/10.1016/j.jrurstud.2020.04.024

Putnam RD (2000) Bowling alone: the Collapse and Revival of American Community. Simon Schuster, New York: New York, USA

Putnam RD, Leonardi R, Raffaella N (1993) Making democracy work : civic traditions in modern Italy. Princeton Univ. Press, Princeton, Nj

Quisumbing AR, Maluccio JA (2003) Resources at marriage and intrahousehold allocation: evidence from Bangladesh, Ethiopia, Indonesia, and South Africa*. Oxf Bull Econ Stat 65(3):283–327. https://doi.org/10.1111/1468-0084.t01-1-00052

Schober P, Boer C, Schwarte LA (2018) Correlation coefficients: appropriate use and interpretation. Anesth Analg 126(5):1763–1768. https://doi.org/10.1213/ane.0000000000002864

Sharma M (2020) Empowerment of women in India-historical perspective. Elementary Educ Online 19(4):4309. https://doi.org/10.17051/ilkonline

Sraboni E, Malapit HJ, Quisumbing AR, Ahmed AU (2014) Women’s empowerment in agriculture: what role for food security in Bangladesh? World Dev 61:11–52. https://doi.org/10.1016/j.worlddev.2014.03.025

Stock JH, Yogo M, National Bureau Of Economic Research (2002) Testing for weak instruments in linear IV regression. National Bureau Of Economic Research, Cambridge, Mass. https://www.nber.org/system/files/working_papers/t0284/t0284.pdf

Stock JH, Wright JH, Yogo M (2002) A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments. J Bus Econ Stat 20(4):518–529. https://doi.org/10.1198/073500102288618658

Stock J, Yogo M Testing for Weak Instruments in Linear IV Regression. In: Andrews DWK Identification and Inference for Econometric Models. New York: Cambridge University Press; 2005. pp. 80-108

Sturgis P, Patulny R, Allum N, Buscha F (2015) Social connectedness and generalized trust: a longitudinal perspective. In Handbook of research methods and application in social capital. Edward Elgar, Northampton, MA

Taylor P, Funk C, Clark C (2007) Americans and social trust: Who, where and why. Pew Res Center: Soc Trends Rep 1–10

Thapa Karki S, Xheneti M (2018) Formalizing women entrepreneurs in Kathmandu, Nepal. Int J Socio Soc Policy 38(7-8):526–541. https://doi.org/10.1108/ijssp-12-2017-0166

United Nations (2016) Human development reports. Retrieved from https://hdr.undp.org/data-center

van Hoorn A (2015) Individualist–Collectivist Culture and Trust Radius. J Cross Cult Psychol 46(2):269–276. https://doi.org/10.1177/0022022114551053

Article   ADS   Google Scholar  

Van den Steen E (2004) Rational Overoptimism (and Other Biases). Am Eco Rev 94(4):1141–1151. https://doi.org/10.1257/0002828042002697

Wei W, Sarker T, Żukiewicz-Sobczak W, Roy R, Alam GMM, Rabbany MdG, Aziz N (2021) The Influence of Women’s Empowerment on Poverty Reduction in the Rural Areas of Bangladesh: Focus on Health, Education and Living Standard. Int J. Environ. Res Public Health 18(13):6909. https://doi.org/10.3390/ijerph18136909

Wollebaek D, Lundåsen SW, Trägårdh L (2012) Three forms of interpersonal trust: evidence from swedish municipalities. Scan Polit Stud.35(4):319–346. https://doi.org/10.1111/j.1467-9477.2012.00291.x

World Bank. (2016) World Development Indicators | DataBank. Retrieved from Worldbank website: https://databank.worldbank.org/source/world-development-indicators

Xiong A, Westlund H, Li H, Pu Y (2017) Social capital and total factor productivity: evidence from Chinese Provinces. China World Eco 25(4):22–43. https://doi.org/10.1111/cwe.12204

Yoga MJH (2005) Testing for weak instruments in linear IV regression. In Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg (pp. 80–108). New York: Cambridge University Press

Zhang RJ (2020) Social trust and satisfaction with life: a cross-lagged panel analysis based on representative samples from 18 societies. Soc Sci Med 251:112901. https://doi.org/10.1016/j.socscimed.2020.112901

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AA and NH initiated the present study. AA designed the theoretical foundation in conjunction with NH. NH, AA, and LF worked together on the study design. YL, NH, and AA analyzed data. YL, NH, and LF were responsible for results interpretation. NH, AA, and LF formulated the discussion and implications. All authors contributed to producing the draft of the paper. All authors read and approved the final manuscript.

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Correspondence to Nazim Habibov .

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Auchynnikava, A., Habibov, N., Lyu, Y. et al. Effect of the contextual (community) level social trust on women’s empowerment: an instrumental variable analysis of 26 nations. Humanit Soc Sci Commun 11 , 648 (2024). https://doi.org/10.1057/s41599-024-03123-0

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The Women of Greek Myths Are Finally Talking Back

Novels that take on the marginalized or vilified women in mythology are flooding bookstores and reigniting questions about who gets to tell these stories, and how.

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By Alexandra Alter

For centuries, the Greek Gorgon Medusa has been cast as a vicious monster, a beastly woman with writhing snakes for hair and a deadly gaze that turns living creatures to stone.

Several years ago, when Nataly Gruender was studying classics as an undergraduate at the University of Arizona, she started to wonder if there was more to Medusa’s story.

Scattered references in Greek and Roman works by Hesiod, Apollodorus and Ovid described her death at the hands of the hero Perseus, but also hinted at a fuller life. In Ovid’s telling, Medusa wasn’t born a monster, but was turned into one as punishment by the goddess Athena, after Medusa was raped by the sea-god Poseidon in Athena’s temple.

Drawing on the fragments she could find, and adding scenes to flesh out Medusa’s narrative, Gruender wrote her own version of the myth. “Often, you only really get to see her as a decapitated head in Perseus’ hand,” Gruender said. “I really wanted to give her a voice and tell the story from her perspective.”

She imagined a climactic moment in which Medusa confronts Athena and asks the goddess why she, the victim, was unjustly punished, and added a noncanonical love affair between Medusa and a female water nymph. “I’m queer, so I wanted to see that reflected in her,” Gruender said. “I was like, you know, she deserves one nice thing.”

Gruender’s debut novel, “Medusa,” which Grand Central will publish this August, is the latest fictional reworking of the Gorgon’s tale. The increasingly crowded sub-sub-genre includes novels like Natalie Haynes’s “Stone Blind, ” Hannah Lynn’s “ Athena’s Child ,” Lauren J.A. Bear’s “Medusa’s Sisters,” Katherine Marsh’s middle grade novel “Medusa,” Claire Heywood’s “The Shadow of Perseus” and Jessie Burton’s young adult novel “Medusa: The Girl Behind the Myth .”

And Medusa is just one of a legion of female mythological figures who are getting literary makeovers. Following in the wake of blockbusters like Madeline Miller’s “ Circe ,” which spotlighted the powerful witch from Homer’s “Odyssey” and sold more than 2.5 million copies, there’s been a flood of novels featuring women from Greek mythology who have often been overlooked, maligned or sidelined as pawns in male heroes’ journeys.

For the women writing these feminist revisions, and the millions of readers enthralled by the stories, placing women at the center of familiar, ancient myths feels like a necessary and overdue corrective.

For most of recorded history, Greek and Roman mythology has been dominated by men, from ancient bards and dramatists like Homer, Euripides and Aeschylus, to the translators and scholars who have interpreted those myths in the centuries since. Female characters have either been relegated to the fringes, or filtered through the male gaze, depicted as helpless victims, sexual objects and war prizes. If they had any agency at all, women in myth were often cast as supernatural monsters like Circe and Medusa, or murderous villains like Medea and Clytemnestra.

To Miller, it makes sense that women are excavating ancient stories and giving new life to female characters whose perspectives have been elided.

“Overwhelmingly, the voices we hear from the ancient world are male,” she said. “It’s not just that the women in these stories lead oppressed lives, it’s that we don’t get their vision of what their lives look like.”

At the same time, these ancient stories retain their potency, culturally and psychologically. As long as myths continue to resonate, writers will extract fresh meaning from them.

Along with Circe and Medusa, other female villains from Greek epics and tragedies are getting resurrected and redeemed in fiction. The murderous Queen Clytemnestra , who killed both her husband, the warrior Agamemnon, and his war concubine, the Trojan princess Cassandra, gets center stage in novels by Costanza Casati and Susan C. Wilson . Medea — one of the most reviled figures in myth, who takes vengeance on her deceitful husband, Jason, by murdering her own children — has inspired recent fictional retellings by Rosie Hewlett and Eilish Quin .

“There’s a huge appetite for these stories because they have a massively archetypal quality,” said Haynes, a classicist turned novelist who is working on her own novelization of Medea.

The trend shows no signs of slowing: This summer, publishers are releasing a fresh wave of feminist Greek mythological reboots.

Claire North’s “The Last Song of Penelope,” due out in June, reimagines the story of Odysseus’ homecoming after the Trojan War from the perspective of his clever wife, Penelope, as she schemes behind the scenes to keep her family safe from the carnage. Caro De Robertis’s new novel, “The Palace of Eros,” out in August, reinvents the myth of Eros, the god of desire, and Psyche, the beautiful mortal he falls in love with. In De Robertis’s version, Eros is a nonbinary deity who presents as female and can change genders, a plot twist that adds new layers to the original story’s themes of forbidden love and desire.

And in “Hera,” also out in August, the best-selling novelist Jennifer Saint recasts the goddess as a powerful, cunning deity in her own right, rather than just the petty, jealous wife of Zeus. In Saint’s version, Hera feels herself every bit Zeus’ equal, but she is forced to marry him after he tricks her by disguising himself as a small injured bird, then overpowering and raping her. From then on, she is bent on revenge against not only her unfaithful husband, but also the nymphs and goddesses he pursues.

“It was important to me to write a woman who is not likable, who is relentlessly ambitious and striving for power and control, and considers that to be her birthright as much as Zeus’,” said Saint, whose previous novels have reanimated female mythological figures like Ariadne, Elektra and Atalanta. “We see Hera through the worst misogynist stereotypes; so often she’s presented as spiteful and vindictive, as nagging Zeus and holding him back, and it’s so deeply unfair. Does Hera look different if we see her through a female lens?”

There’s a long literary tradition of revising and reimagining Greek myths. Romans like Virgil and Ovid adapted these stories. Ancient myths figure in the plays of Shakespeare, in poetry by Derek Walcott and Louise Glück, and in novels by Margaret Atwood, Ursula K. Le Guin, Ali Smith and Rick Riordan, whose Percy Jackson series has sold more than 100 million copies globally. The ancient Greeks and Romans themselves were prone to spinning new versions of their lore, which often morphed from storyteller to storyteller, leaving no fixed or final version.

Still, the recent rise of Greek mythological retellings with an overtly feminist lens stands out for the sheer volume of novels and the seemingly bottomless appetite for mythological fare among both readers and publishers.

Several factors are driving the genre’s explosion. Many of these novels have arrived in the wake of #MeToo, and may hold appeal because the narratives give voice and agency to female characters who are victims of sexual violence and assault.

Some writers are taking myths in which women are victimized, subjugated and objectified, and turning them into stories of romantic and sexual empowerment. The myth of Hades and Persephone — an unsettling story about how the god of the underworld abducted young Persephone, dragged her into the bowels of the earth and forced her to marry him — has been reimagined as a steamy love story in two best-selling series: the “Hades x Persephone Saga,” a spicy romantasy series by Scarlett St. Clair that has sold more than a million print copies, and Rachel Smythe’s graphic novel series “Lore Olympus,” a blockbuster that has more than 2.3 million copies in print.

Queer and gender-flipped versions of Greek myths are part of the new landscape too. Miller’s debut novel, “The Song of Achilles,” which came out more than a decade ago but more recently found a huge audience through TikTok, and went on to sell more than three million copies, centers on a romance between the warrior Achilles and his comrade-in-arms Patroclus. The young adult novelist and TikTok star Bea Fitzgerald’s forthcoming novel, “The End Crowns All,” due out in July from Penguin U.K., is a Sapphic young adult romance in which Helen and Cassandra come together and rewrite their fates to stop the fall of Troy.

Another addition to the canon, Elyse John’s new novel “Orphia and Eurydicius,” retells the story of the poet Orpheus’ journey to the underworld to rescue the woman he loves, Eurydice. In John’s version, Orphia is a female poet who travels to Hades’s realm to save her bisexual male lover, Eurydicius — a radical change that puts a woman in the hero’s role and scrambles gender stereotypes.

“By changing Orpheus into a woman, I could explore what it means to be a creator-heroine, a woman using storytelling to take on the gods,” John said.

Greek mythology has also seeped into other corners of pop culture, showing up in TV, comics, graphic novels and video games, making it feel more accessible and less like an elite, scholarly field.

For younger generations raised on superhero blockbusters and ever-expanding I.P.-derived cinematic universes with endless reboots and character spinoffs, novelizations of myths may hold a similar appeal: You’ve seen this character, but you’ve never gotten her side of the story.

New translations of classical texts by women are also helping to reshape the popular understanding of Western myths, and are in turn inspiring novelists.

In Stephanie McCarter’s 2022 translation of Ovid’s “Metamorphosis,” a Latin poem that recounts famous tales of transformation, love and violence, McCarter uses blunt language to describe the gods’ sexual pursuit of women, labeling assaults as rape, rather than resorting to the euphemisms often used in earlier translations, like “ravished” and “plundered.”

The classicist Emily Wilson ’s translations of Homer’s “ The Odyssey ” and “ The Iliad ” won acclaim, and stirred some controversy, for using plain language to describe the subjugation of women, and by avoiding sexist phrases used by male translators. Whereas some previous versions called the servant girls in Odysseus’ household who were seduced by Penelope’s suitors “sluts” or “whores” — words with sexist overtones that aren’t present in Homer’s original verses — Wilson calls them “slave women.”

Wilson said novelizations of Greek myths appeal to readers in part because they have the patina of high culture, but may feel less intimidating than translations of the originals.

“People are a little bit afraid of ancient literature,” said Wilson, who in addition to translating classics is also working on her own fictional version of Trojan War stories. “The ‘you go girl’ feminism thing — you may think she’s a victim but actually she’s a goddess — is a very relatable, inspiring thing to many young readers.”

Not everyone appreciates mythological makeovers. Some classical purists have taken to social media to criticize new translations and feminist revisions, arguing that these new works are distorting ancient stories by imposing a feminist agenda. A critique of the genre in The New Statesman by Finn McRedmond last year argued that feminist revisions tend to be one-note, and often misread the stories they attempt to unearth: “It is difficult to extract honest feminist parable from stories written in a world that wouldn’t recognize the concept,” she wrote.

Helen Morales, a professor of Hellenic studies at the University of California, Santa Barbara, said that while some recent feminist versions have preserved the moral complexity of these myths, others may go too far in seeking to placate modern readers with uplifting stories of female empowerment.

“Part of the appeal of myth is that it’s complex and unpredictable,” said Morales, author of “ Antigone Rising ,” which explores how Greek and Roman myths have been reclaimed and reinterpreted to speak to contemporary concerns. “If it’s rendered in a way that makes readers complacent, or reaffirms what we know or what we want to hear, I don’t think that’s good for myth, and it’s not good for feminism either.”

Others complain that the genre has become oversaturated — like any popular cultural trend, the explosion of mythological retellings has yielded works that vary widely in quality, and in their fidelity to the originals.

Still, for ardent fans of these stories, and the writers producing them, Greek myths seem to offer endless possibilities for reinterpretation.

“There’s no final word on anything, because language is always changing, so there’s no definitive myth,” said Miller, who is currently working on a new novel about Persephone and Demeter, her mother. “These were fluid texts right from the beginning.”

And for now, readers continue to crave new vantage points on female characters — and the archives are still full of mythological women worthy of their own epics, Miller said.

“They could all have their own novels,” she said.

Alexandra Alter writes about books, publishing and the literary world for The Times. More about Alexandra Alter

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