Economic development and equity: Evidence from Nepal

Background: Questions on economic development, development projects, and equality are studied in Humla, Nepal among the ethnic Nyinba minority. Many studies find that devel-opment programs reduce inequality (e.g. Duflo 2001; Sylwester 2002; Abdullah, Doucouliagos, and Manning 2013) although not all (e.g. Fields 1980, Ram 1989, Karim 2015). Similarly, women's participation in economic decision making varies cross-culturally and is positively associated with education (e.g. Sultana 2011, Sinha 2012). A country's level of economic de-velopment is also associated with performance in standardized tests (e.g. For example, the gender gap in Mental Rotation Test (MRT) is the bigger the richer the country (Lippa, Collaer, and Peters 2010). However, the MRT has not been given to truly economically little developed communities. Contribution: Changes in Nyinba culture are evaluated since the start of major flows of foreign aid. The MRT is given to an economically less developed community than in previous studies. Research questions: Have development projects reduced economic inequity? Have the genders become more equal in economic decision making? When economic development approaches minimum, does the gender gap in the MRT disappear? Methods: Asset survey, interviews, redrawn Vandenberg and Kuse Mental Rotation Test, linear regression Data: All the households of a village replied the asset survey. Interviews were conducted in five villages. 134 students did the mental rotation test (average age for boys is 15.08 years and for girls 15.54 years). Main findings: There has been some movement of households across economic strata, but a new elite of e.g. NGO employees has been created. Many felt that women are now more included in economic decision making than 10-15 years ago, and some attributed this to edu-cation. Almost everyone interviewed felt the genders are now equal, while in the past status of males was higher. The Mental Rotation Test showed no statistically significant (p=0.592) gender difference in mean scores (boys 1.96 and girls 1.82). Effect size is small (Cohen's d 0.15), which compares to medium to very large differences in rich countries and modest to medium sized differences in poor countries. When those who scored below guess-level are excluded (as in Vashro and Cashdan 2015) the averages are 2.36 (out of 6) for boys and 2.33 for girls in the pooled sample (N boys = 45, N girls =60)