2022
DOI: 10.5547/01956574.43.2.ased
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Electrification and Socio-Economic Empowerment of Women in India

Abstract: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz ge… Show more

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Cited by 9 publications
(4 citation statements)
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“…It is important to note that the effect of exposure on instrumental empowerment is greater than the effect on intrinsic empowerment in a statistical sense at usual levels of significance. In addition, we also use principal component analysis for measuring empowerment, as has been used in other studies (Sedai et al, 2022), to ensure our estimates are robust (Columns 4–6). Furthermore, we use another measure created by standardizing the summation of all individual indicators responding in the affirmative with a “Yes” (Columns 7–9).…”
Section: Resultsmentioning
confidence: 99%
“…It is important to note that the effect of exposure on instrumental empowerment is greater than the effect on intrinsic empowerment in a statistical sense at usual levels of significance. In addition, we also use principal component analysis for measuring empowerment, as has been used in other studies (Sedai et al, 2022), to ensure our estimates are robust (Columns 4–6). Furthermore, we use another measure created by standardizing the summation of all individual indicators responding in the affirmative with a “Yes” (Columns 7–9).…”
Section: Resultsmentioning
confidence: 99%
“…Therefore, women benefiting from PRONER could have different observable and unobservable characteristics than those who did not benefit from it, potentially biasing the estimation results. In order to correct this bias, some authors generally use instrumental variables methods (Dinkelman, 2011), fixed-effect models (Sedai et al, 2020), matching methods (Samad and Zhang, 2019;Rathi and Vermaak, 2018; and the inverse probability weighted regression adjustment method (Chhay and Yamazaki, 2021). However, it remains a challenge to select a good tool.…”
Section: Jadee 141mentioning
confidence: 99%
“…In a social context of gender disparity, access to electricity can be a powerful lever for improving women's well-being through (1) new employment opportunities in the labour market (Samad and Zhang, 2019;Rud, 2012;Dinkelman, 2011), (2) increased agricultural productivity (Chakravorty et al, 2016), (3) improved family finances (Thomas et al, 2020;Rao, 2013), (4) reduced fertility (Fujii and Shonchoy, 2020;Grimm et al, 2015), ( 5) greater involvement in decision-making (Sedai et al, 2020;Samad and Zhang, 2019), (6) improved education (Samad and Zhang, 2019;Lipscomb et al, 2013) and ( 7) less time spent on fuel collection (Gould and Urpelainen, 2018;Khandker et al, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…It is the first survey of its kind to be conducted by NSSO to collect 12 Given the outcome variable that is time spent in food preparation (which is very household specific) and endogenous variable (LPG use), it is reasonable to rule out spillover impacts where the village level average LPG use a↵ects the household time spent in cooking directly after a large set of household and village characteristics are controlled for. Spillover (or general equilibrium) impacts are discussed in the case of economic outcome variables (such as income) and endogenous variable (electricity supply) in Sedai et al (2020Sedai et al ( , 2021Sedai et al ( , 2022.…”
Section: Datamentioning
confidence: 99%