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Journal of Quantitative Economics

Erschienen in:

13.04.2016 | Original Article

Gender Bias in Education in West Bengal

verfasst von: Amita Majumder, Chayanika Mitra

Erschienen in: Journal of Quantitative Economics | Ausgabe 1/2017

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Abstract

This paper attempts to capture gender bias at two different levels of education, namely, below class-10 and above class-10 using NSSO 64th round education expenditure data on West Bengal. The analysis for the below class-10 level involves an intra household framework and Heckman’s two step model. Further, for this section the analysis is split up into classes 1–8 and classes 9–10 in view of the Right to Education act (2005). For above class-10 level, gender bias has been captured through a multinomial logit model for selection of subjects across households.

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We are grateful to a referee for pointing this out to us.

The Brown et al. (1980) approach has been applied in many studies of wage differentials for various classifications of the population, namely, by gender in Dolton and Kidd (1994), Kidd and Shannon (1994, 1996) and Meng and Miller (1995), by race in Gabriel and Schmitz (1989), Moll (1992), by immigration status in Liu et al. (2004) and by Indian social group in Madheswaran and Attewell (2007).

Zero expenditure on education may be a result of the decision at the first stage and a corner solution at the second stage where households end up incurring zero expenditure. The Double Hurdle model distinguishes between households who decide not to spend in the first stage and those who decide to spend, but end up spending zero amounts. Since no information regarding this can be retrieved from the available data, we use Heckman’s model.

See Section 14.4.1 in Cameron and Trivedi (2005).

The inverse Mill’s ratio takes account of the possible selection bias, arising out of a censored dependent variable, which causes a concentration of observations at zero values. Ignoring this leads to biased OLS estimates.

This type of decomposition technique has been used in Meng and Miller (1995).

The specification of multinomial logit model is guided by the literature (e.g., Schmidt and Strauss 1975; Miller 1987; Meng and Miller 1995). A similar analysis has been performed by Liu et al. (2004) in studying the earnings differentials between the immigrants and the natives of Hong Kong.

Here education level of the household head is the years of schooling of the head.

It is often found that students, after their class-10 board exam get some financial help from state government via accessibility to certain facilities.

The number of observations on girls studying Science and Commerce in the rural sector is too small to run meaningful regression.

Given that we are addressing the issue of gender discrimination in terms of cost incurred by a household on education, we look at the issue from the perspective of female participation, given that the males are already concentrated in streams that involve higher cost.

The data did not permit examination of discrimination in the rural sector in our framework at the above class-10 level.

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Titel: Gender Bias in Education in West Bengal
verfasst von: Amita Majumder
Chayanika Mitra
Publikationsdatum: 13.04.2016
Verlag: Springer India
Erschienen in: Journal of Quantitative Economics / Ausgabe 1/2017
Print ISSN: 0971-1554
Elektronische ISSN: 2364-1045
DOI: https://doi.org/10.1007/s40953-016-0038-3

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