2016
DOI: 10.1016/j.jebo.2016.07.015
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Gender composition and group dynamics: Evidence from a laboratory experiment with microfinance clients

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Cited by 21 publications
(11 citation statements)
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References 39 publications
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“…There remain important unanswered questions about the extent to which differences among women undermine their collective action potential. This might seem surprising in light of recent evidence that women demonstrate strong problemsolving abilities and achieve high levels of cooperation in all-women groups (Berge, Juniwaty, and Sekei 2016;Fearon and Humphreys 2017;Greig and Bohnet 2009). Such evidence is consistent with claims that womenacross a wide variety of cultures and contextsdisplay strong norms of communal and pro-social behavior (Eagly and Wood 1991;Hyde 2014).…”
supporting
confidence: 53%
“…There remain important unanswered questions about the extent to which differences among women undermine their collective action potential. This might seem surprising in light of recent evidence that women demonstrate strong problemsolving abilities and achieve high levels of cooperation in all-women groups (Berge, Juniwaty, and Sekei 2016;Fearon and Humphreys 2017;Greig and Bohnet 2009). Such evidence is consistent with claims that womenacross a wide variety of cultures and contextsdisplay strong norms of communal and pro-social behavior (Eagly and Wood 1991;Hyde 2014).…”
supporting
confidence: 53%
“…Hjort (2014) finds that ethnic diversity leads to lower productivity in a flower factory. Functional diversity has been shown to hold the greatest promise of a positive effect; however Berge, Juniwaty andSekei (2017), Lyons (2017) and de Oliveira and Nisbett (2017) call into question the general applicability of such a finding. Taken as a whole, a diverse group faces a seemingly insurmountable hurdle in increasing production.…”
Section: Resultsmentioning
confidence: 99%
“…The GCC region ( Alqahtani et al., 2017 ), Middle Eastern and Asian countries ( Rosman et al., 2014 ) ( Rosman et al., 2014 ), Sri Lanka ( Wijesiri et al., 2015 ), and Indonesia ( Farida et al., 2018 ) most often use Data Envelopment Analysis (DEA) as a tool to measure this factor. Other methods besides DEA include Development Economic Analysis ( Hudon and Périlleux, 2014 ; Nashihin and Harahap, 2014 ), Stochastic Frontier Analysis (SFA) ( Nurboja and Košak, 2017 ), OLS and Tobit ( Bitar et al., 2017 ), and profit models ( Berge et al., 2016 ).…”
Section: Literature Reviewmentioning
confidence: 99%