Abstract
Women who want to work often face many more hurdles than men. This is true in Tajikistan, where there is a large gender gap in labour force participation (LFP). We highlight the effects of two factors – international migration and education – on the LFP decision and its gender gap. Using probit and decomposition analysis, our investigation shows that education and migration have a significant association with the gender gap in LFP in Tajikistan. International emigration from Tajikistan, in which approximately 93.5 per cent of the participants are men, reduces LFP by men domestically; increased female education, especially at the university and vocational level, increases female participation. Both women acquiring greater access to education and men increasing their migration abroad contribute to reducing the gender gap.
Abstract
Les femmes qui veulent travailler font souvent face à plus de barrières que les hommes. C’est le cas au Tajikistan où il existe un large fossé entre les sexes quant à la participation des hommes et des femmes sur le marché du travail. Nous mettons en avant le rôle de deux facteurs – l’émigration internationale et le niveau d’études – qui pèsent sur la décision de travailler et sur le fossé entre les sexes qui y est relié. A l’aide d’une analyse de décomposition par la méthode des probits, notre enquête montre que les niveaux d’études et l’émigration sont tous deux associés de manière significative au fossé entre les sexes dans la participation à la main d’oeuvre au Tajikistan. L’émigration hors du Tajikistan, qui touche les hommes à 93,5 per cent, réduit la participation des hommes sur le marché du travail domestique; une hausse du nombre de femmes qui font des études, en particulier au niveau universitaire ou en filière professionnelle, augmente la quantité de femmes qui entrent sur le marché du travail et participent à la main d’oeuvre. Un meilleur accès aux études pour les femmes ainsi qu’une augmentation de l’émigration contribuent tous deux à la réduction du fossé entre les sexes sur le marché du travail.
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Notes
Formally, participation includes the employed and unemployed. However, most studies on labour supply do not count the unemployed in the definition of participation even though they still use the term ‘participation’. We follow this convention.
If migration is dominated by women, the demonstration effect will be larger for women relative to men.
For women, having migrant relatives after controlling for remittances is likely to increase labour market participation because a working member is absent and the demonstration effect will be negligible considering the low probability of female migration.
A major problem with our bivariate probit is the very small sample of women who migrated, which creates difficulty in estimating the bivariate probit model when rural and urban samples are studied separately.
For computing asymptotic standard errors of the characteristics and coefficients effects, see Yun (2005a). Robustness issues, known as the index or parameterization problem and the identification problem, have been dealt with in the detailed decompositions. A decomposition equation with a different parameterization
was computed; the results are not substantially different. Another interpretation issue is that the coefficients effect in the detailed decomposition is not invariant to the choice of omitted groups when dummy variables are used (Oaxaca and Ransom, 1999). The solution suggested by Yun (2005b, 2008) is used here: as alternative reference groups yield different estimates of the coefficients effects for each individual variable, it is natural to obtain estimates of the coefficients effects for every possible omission and take the average of the coefficients effects estimates as the ‘true’ contributions of individual variables to differentials. This can be accomplished with a single estimation by transforming the probit estimates into a normalized equation and using the normalized equation for the decomposition.The predicted gender gap of LFP is 39.7 per cent (=77.2–37.5 per cent) for the whole sample, 38.7 per cent (=77.4−38.7 per cent) for the rural sample and 42.7 per cent (=76.5–33.8 per cent) for the urban sample, respectively. The observed gender gaps of LFP are 39.7, 38.7 and 42.6 per cent for the whole sample, rural sample and urban sample, respectively.
was computed; the results are not substantially different. Another interpretation issue is that the coefficients effect in the detailed decomposition is not invariant to the choice of omitted groups when dummy variables are used (References
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Ira Gang thanks the Rutgers Research Council for partial support.
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Abdulloev, I., Gang, I. & Yun, MS. Migration, Education and the Gender Gap in Labour Force Participation. Eur J Dev Res 26, 509–526 (2014). https://doi.org/10.1057/ejdr.2014.27
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DOI: https://doi.org/10.1057/ejdr.2014.27