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Ashwini DeshpandeDelhi School of Economics,
University of Delhi.
Greater market orientation, liberalization, globalization would reduce disparities.
Labour market discrimination expected to decline.
Foreign agents less likely to discriminate. Creation of new jobs new
opportunities, avenues of mobility out of traditional stigmatizing occupations for Dalits (ex-untouchable castes).
Wage gaps expected to decline.
Skills needed to take advantage of new opportunities (e.g. knowledge of English, computing skills)
Legacy of exclusion: disparities in educational attainment; differential quality
Deshpande and Newman (2007): Urban formal sector labour markets: lip-service to merit, with deep awareness of social cleavages. Stereotypical beliefs about merit.
External agents – foreign employers – would not want to rock the boat too strongly in areas of employment (might want tax rules or property rules to change).
Tension between the need to respect/follow local traditions and the desire to change status-quo.
MNCs have predominantly Indian staff, especially in the HR departments.
International evidence: discrimination and strong market orientation can co-exist.
Hypothesis: promotes competition, cheaper and easily accessible material goods for Dalits: breaks the exclusivity of the “Upper Caste Consumer Club”
Improved labour market outcomes for Dalits.
Implicit argument: over time, new labour market requirements will improve educational outcomes
Emancipatory effects on groups traditionally excluded from decent jobs in the formal sector
FDI data for 14627 non-technical approvals (1995-July 2010) from Ministry of Commerce, GOI
Technical: agreements for technology transfer
Non-technical: financial: approvals for investment in equity
SEZs not included FDI from “automatic route” (not
included): not possible to identify location precisely
Advantage of this data: location of the project at the sub-state level.
National Sample Survey: population: total and by broad caste groups, daily wages, education levels, broad occupational categories (regular wage-salaried, self-employed etc), %urban.
Three rounds of NSS data: 1999-2000 (55th round); 2004-05 (61st round);2009-10 (66th round)
Determinants of FDI: some infrastructure data (e.g. bank deposits) from other sources; road length as a proxy for connectivity etc.
Matching outcomes from the three NSS rounds to cumulative approvals in the preceding 4 years
Approvals calculated as “approval rate”= number of approvals per 100,000 population.
Approvals (total) spread over 31 states, but concentrated in a small number of states.State Freq. Percent
Maharashtra 3,774 25.8
Delhi 2,311 15.8
Karnataka 2,078 14.21
Tamil Nadu 1,945 13.3
AP 1,000 6.84
Gujarat 692 4.73
HP 526 3.6
West Bengal 475 3.25
UP 466 3.19
Kerala 250 1.71
Goa 206 1.41
Rajasthan 182 1.24
Sectoral composition: close to 60% in tertiary sector: skill intensive; English knowledge essential.
New employment? Mergers and acquisitions (M&A) versus
Greenfield: former has no net employment creation (Brownfield: M&A that resembles Greenfield)
Other lit: M&A as the preferred form of FDI: negligible new employment creation.
averages 1995-98 1999-2003 2003-2008
Approvalrate 3.35 9.47 5.68
Rel wages 0.66 0.55 0.57
Dependent variable: log of relative wage
I II III IVlog approval -0.08 -0.16 -0.16 -0.13
(0.004)*** (0.006)***
(0.006)*** (0.01)***
log reledu -0.06 -0.06
(0.005)** (0.005)**
time dummy period2neg significant
neg significant neg significant*
time dummy period 3
neg significant
neg significant neg significant***
approvalt2 neg significant**approvalt3 not significant
district fixed effects yes yes yes yes
N 12773 12616 12608 12608R-squared 0.68 0.72 0.73 0.73
(Robust standard errors in parenthesis, clustered at the district level. All regressions include a constant term)
A similar exercise with gender wage gaps
Discussion of the results in terms of state-specific factors which might affect relative wages.
Linking these results to state-level differences in labour market discrimination.