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Gender, L abour and Self-Employment in India

Gender, L abour and Self-Employment in India. Ashwini Deshpande Delhi School of Economics University of Delhi INDIA. RURAL LFPRs (1983-2010). URBAN LFPRs (1983-2010). Why are female LFPRs low?.

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Gender, L abour and Self-Employment in India

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  1. Gender, Labour and Self-Employment in India AshwiniDeshpande Delhi School of Economics University of Delhi INDIA.

  2. RURAL LFPRs (1983-2010)

  3. URBAN LFPRs (1983-2010)

  4. Why are female LFPRs low? • Demand-based explanations: Low prody agriculture + excess supply of lab. Women’s paid lab needed only when men’s lab exhausted. • Supply-side explanations: Socially ordained division of lab: women in reproductive activities within the household • Discrimination-based explanation: employers discriminate against female workers, both in terms of hiring and wages. • Measurement issues: lot of women’s work not counted as “productive” plus women often deny involvement in productive work.

  5. Employment Status and Sectoral Distribution • Share of women in regular wage/salaried employment lower than that of men (rural: 4% female WF in RWS (vs. 9) & urban: 39 vs. 42) (2009-10) • Correspondingly, share of women in casual workers & self-employment higher than men. • Rural: 79% women in agri; Urban: 53% women in tertiary

  6. Raw Daily Wage Gaps • 2009-2010: NSS 66th round emp. survey • Urban: RWS average daily wage: Rs. 364.95. Rural: Rs. 231.59 • Rural Male: Rs. 249.15; Rural Female: 155.87 => ratio of 0.63. Urban Male: 377.16; Urban female: 308.79 • Ratio of 0.82 * Casual labour: 0.67 (Rural) and 0.58 (Urban)

  7. Male-Female Wage Gaps • Blinder-Oaxaca Decomposition (Khanna 2012): Strong evidence of labour market discrimination

  8. Quantile Regressions • This plots the log of the gender wage gap at each of the 99 percentiles using NSS 2009-2010 wage data for those reporting regular wage/salaried employment (Khanna 2012). • The “Sticky Floor” effect is evident: wage gaps are much larger at the bottom of the distribution and decline almost monotonically till the top of the wage distribution. • The average gap (given by the OLS coefficient) is instructive, but misses out on this nuanced picture.

  9. QR Decompositions: if men were paid like women

  10. QR Decompositions: if women were paid like men

  11. Self-Employment

  12. Ownership and Management by women

  13. Industry divisions of women ents

  14. Caste and Religion • Women are not a homogenous category. • For example: overlap of caste and gender. • Earlier evidence: greater taboos on upper caste women, who were materially more prosperous – trade-off between prosperity and immurement. • LFPRs among SC-ST women higher than UC. • Now: trade-off vanishing. Dalit women worst off: triple burden of gender, caste and class.

  15. Legal and institutional barriers • With greater legal differentiation, fewer women work, own or run businesses (WBL, 2012) • South Asia (except SL) one of the 3 regions where explicit legal gender differentiation in accessing institutions and in using property is most common. • Moreover, benefits such as paternity leave absent.

  16. Accessing institutions • Lack of autonomy in interacting with government institutions • Access to judicial system • Getting a job: differences in work hours, restrictions by industry, poor anti-discriminatory laws, with even poorer implementation • Benefits (e.g. maternity leave): India: employer pays (rather than the government), raising the cost of hiring women.

  17. Gender discrimination lowers growth • India: gender disc in lab mkt => wage gaps and differential access to wage employment, sometimes exclusion of women. • Discrimination  inefficiencies and lower growth (Esteve-Volart, 2004). • Individuals belonging to a group which is discriminated against face higher interest rates in credit markets. • => lab mkt disc  credit market discrimination

  18. INDIA: 1961-1991 • EsteveVolart (2004): • An increase of 10% in the F/M ratio of managers would increase PC NDP by 2% • An increase of 10% in F/M ratio of total workers would increase PC NDP by 8%. • => Gender inequality in the access to working positions is a bigger break on growth than gender inequality in the access to managerial positions.

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