Measuring empowerment: Choices, values and norms

Maiorano, Diego; Shrimankar, Dishil; Thapar‐Björkert, Suruchi; Blomkvist, Hans

doi:10.1016/j.worlddev.2020.105220

Cited by 33 publications

(25 citation statements)

References 22 publications

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“…SWPER was adapted into a 14-question version designed to be applicable in all low-and middle-income countries (Ewerling et al, 2020). Another recent contribution is by Maiorano et al (2021), who introduce a choices-values-norms framework for measuring agency. Specifically on India, Kishor and Gupta (2004) adapt WEAI for nutrition, while Richardson et al (2019) develop an index of National Family Health Survey questions using confirmatory factor analysis.…”

Section: Measurement Of Women's Agencymentioning

confidence: 99%

Using Machine Learning and Qualitative Interviews to Design a Five-Question Women's Agency Index

Jayachandran¹,

Biradavolu²,

Cooper

2021

SSRN Journal

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Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The IZA Institute of Labor Economics is an independent economic research institute that conducts research in labor economics and offers evidence-based policy advice on labor market issues. Supported by the Deutsche Post Foundation, IZA runs the world's largest network of economists, whose research aims to provide answers to the global labor market challenges of our time. Our key objective is to build bridges between academic research, policymakers and society. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.

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Section: Measurement Of Women's Agencymentioning

confidence: 99%

Using Machine Learning and Qualitative Interviews to Design a Five-Question Women's Agency Index

Jayachandran¹,

Biradavolu²,

Cooper

2021

SSRN Journal

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Section: Measurement Of Women's Agencymentioning

confidence: 99%

Using machine learning and qualitative interviews to design a ﬁve-question women's agency index

Jayachandran¹,

Biradavolu²,

Cooper

2021

SSRN Journal

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We propose a new method to design a short survey measure of a complex concept such as women's agency. The approach combines mixed-methods data collection and machine learning. We select the best survey questions based on how strongly correlated they are with a "gold standard" measure of the concept derived from qualitative interviews. In our application, we measure agency for 209 women in Haryana, India, first, through a semi-structured interview and, second, through a large set of close-ended questions. We use qualitative coding methods to score each woman's agency based on the interview, which we treat as her true agency. To identify the close-ended questions most predictive of the "truth," we apply statistical algorithms that build on LASSO and random forest but constrain how many variables are selected for the model (five in our case). The resulting five-question index is as strongly correlated with the coded qualitative interview as is an index that uses all of the candidate questions. This approach of selecting survey questions based on their statistical correspondence to coded qualitative interviews could be used to design short survey modules for many other latent constructs.

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“…Women's empowerment and gender equality are paramount in achieving the United Nations Sustainable Development Goals (Maiorano et al 2021;UNDP 2020;Nationen 2014). Empowerment and equality for women are leading to faster economic growth, reduction in social inequalities, and scaledown of environmental degradation around the world (Bayeh 2016;Duflo 2012;Stevens 2010).…”

Section: Introductionmentioning

confidence: 99%

“…Some studies suggest that the role of social norms is key to understanding the process of intrahousehold decision-making (see e.g. Agarwal 1997;Jayachandran 2020;Laszlo 2020;Lundberg and Pollak 1996;Mabsout and Staveren 2010;Maiorano et al 2021). Ignoring gender norms can undermine women's empowerment interventions when too much focus is given to increasing women's asset ownership (Anderson et al 2021).…”

Section: Introductionmentioning

confidence: 99%

“…However, it is not always possible to collect both quantitative and qualitative information. A recent study by Maiorano et al (2021) developed a measure of empowerment that included measures of decision-making and the reasoning behind the decision process. The Maiorano et al (2021) decision-making questions are similar to the ones included in the WEIA, with the same options for the respondents (myself, spouse, joint), but they do not include questions on decisions regarding agricultural activities.…”

Section: Introductionmentioning

confidence: 99%

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Social norms and perceptions drive women’s participation in agricultural decisions in West Java, Indonesia

2021

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Increasing women’s participation in intrahousehold decision-making has been linked with increased agricultural productivity and economic development. Existing studies focus on identifying the decision-maker and exploring factors affecting women’s participation, yet the context in which households make decisions is generally ignored. This paper narrows this gap by investigating perceptions of women's participation and the roles of social norms in agricultural decision-making. It specifically applies a fine-scale quantitative responses tool and constructs a women’s participation index (WPI) to measure men’s and women’s perceptions regarding women’s participation in decisions about 21 agricultural activities. The study further examines the correlation between social norms in these perceptions as measured by the WPI for 439 couples in West Java, Indonesia. We find that first, men and women have different perceptions about women's decision-making in agricultural activities, but the same perceptions of the types of activities in which women have the most and the least participation. Second, joint decisions come in various combinations but overall, the women’s role is smaller. Third, social norms influence spouses' perceptions of decision-making participation, which explains most of the variation of the WPI. These results suggest that rigorous consideration of social norms is required to understand intrahousehold decision-making.

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Measuring empowerment: Choices, values and norms

Cited by 33 publications

References 22 publications

Using Machine Learning and Qualitative Interviews to Design a Five-Question Women's Agency Index

Using Machine Learning and Qualitative Interviews to Design a Five-Question Women's Agency Index

Using machine learning and qualitative interviews to design a ﬁve-question women's agency index

Social norms and perceptions drive women’s participation in agricultural decisions in West Java, Indonesia

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