Employment and Earnings in Rural India: 2004-2012 Shantanu Khanna, Deepti Goel and René Morissette  NOPOOR POLICY SEMINAR, March 11, 2016

What do we Study? Document the change in rural earnings distribution between 2004/05 to 2011/12 Study EARNINGS and not wage rates Focus on change in inequality measures over this period

Motivation Studies on earnings in urban India (Kijima 2006; Azam 2012) and on consumption expenditure (Sen and Himanshu 2004; Cain et al 2010; Motiram and Vakulabharanam 2013; Subramanian and Jayaraj 2015) We don’t know of similar analysis for rural earnings Document changes at various percentiles: Other studies have found that inequality has risen because of changes in the top end Methodology gives factor contribution in explaining the change over time at the unconditional quantiles

Preview: Earnings in Rural India 2004/05 to 2011/12 Real Earnings increased at all percentiles Sharp fall in earnings inequality Gini: 0.461 to 0.395 Much of the drop is coming from changes in the top half of the earnings distribution Decline in inequality is explained by changes in returns to characteristics Had returns to characteristics remained fixed, inequality would have risen Education has an inequality increasing effect

Data Employment Unemployment Surveys of the National Sample Survey Organisation 2004/05 (61st round) and 2011/12 (68th round) Analysis sample: Wage earners, in the 15-64 age group, in 23 major states of rural India Wage earners make up a little less than 30% of adult population 44,500 in 2004/05 and 36,000 in 2011/12 Dropped 0.1 percent of observations at both ends

Methodology Fortin, N. M., T. Lemieux, and S. Firpo. 2011, Decomposition Methods in Economics, Chapter in the Handbook of Labor Economics Concept of Unconditional Quantile Regression Unconditional quantile regressions (UQR, Firpo et al., 2009) help us examine the marginal effects of covariates on the unconditional quantiles of an outcome variable. Recentered Influence Function Decomposition based on above Allows detailed decomposition of Structure and Compositions Effects at unconditional quantiles Closest in spirit to the Oaxaca-Blinder Method for decomposition at the mean

Kernel Density Estimates of Log of Real Weekly Earnings; Rightward shift; More Compressed; Median earnings increased from 265 to 458 rupees per week (from 2.5 times to 4 times the 2004/05 poverty line)

Absolute Earnings increase smaller at lower percentiles: Real Weekly Earnings (in rupees) at each percentile Absolute Earnings increase smaller at lower percentiles: 98, 193 and 307 at first, median and ninth deciles.

Change in LOG Real Weekly Earnings (in rupees) at each percentile Percentage increase: 89, 72 and 44 percent at 1st, 5th and 9th deciles. Shows inequality decreased over the seven year period. 25/10 ratio of raw earnings not much change, 90/75 ratio sharp drop.

Decomposition: Accounting Exercise Not a Causal Analysis Total Change in any distributional statistic broken into two parts Structure Effect: Due to changes in Returns to Characteristics Composition Effect: Due to changes in Distribution of Characteristics

Complete List of Characteristics we look at Age Male: 70% to 75% Married Muslim Caste Education: Illiterate- 47% to 36% Industry: Agriculture 61 to 49% & Manufacturing 21 to 33% Occupation State of Residence

Unconditional Quantile Regressions: Male, 2011/12

Unconditional Quantile Regressions: College & Beyond, 2011/12

Re-centered Influence Functions Aggregate Decomposition Results Based on characteristics 2004/05 and returns 2011/12; both have sig. positive contri in overall increase at each percentile except at top; structure eff dominant; Ineq decreased mainly coz returns to charac increased much more for lower percentiles than for higher. If returns unchanged, inequality would have increased.

Aggregate Decomposition of Total Change Structure Effect -0.393 -0.095 Decomposition of Changes in Inequality Measures from 2004/05 to 2011/12 90-10 50-10 90-50 Gini Value in 2004/05 1.855 0.881 0.974 0.461 Value in 2011/12 1.575 0.792 0.783 0.395 Total Change -0.280 -0.089 -0.191 -0.066 Aggregate Decomposition of Total Change Structure Effect -0.393 -0.095 -0.298 Composition Effect 0.113 0.006 0.107 0.029 Detailed Decomposition of the Composition Effect Education 0.098 0.009 0.090 0.024 Experience 0.027 0.001 0.008 Male -0.018 -0.013 -0.005 -0.006 Married 0.003 States 0.002 Muslim 0.000 Caste -0.002 -0.001

Rural Real Earnings, 2004/05 to 2011/12 Increase in real earnings at all percentiles suggests that economic growth has been accompanied by decline in poverty In rupee terms was higher at higher percentiles In percentage terms was higher at lower percentiles Sharp fall in earnings inequality in rural India Gini of 0.461 in 2004/05; and 0.395 in 2011/12 (rural) Gini of 0.505 in 2004/05; and 0.498 in 2011/12 (urban) At the aggregate level, decline in inequality explained by changes in returns to characteristics; if these returns had not changed, inequality would have risen on account of changes in the distribution of characteristics Education has a significant inequality increasing effect Gini : Brazil-53.9 (2009); Russia-39.7 (2009); India-33.9 (2009); China-42.1 (2010) and South Africa-63 (2008).

Concluding Remarks Rural and Urban inequality dynamics are different Our work shows that earnings inequality declined in recent times in rural, while it remained stagnant in urban To inform policy, the next step should be to try to unearth the mechanisms that explain this decline Our work shows that it is not the overall change in characteristics but the change in returns to these characteristics that is explaining the decline in inequality Education has an inequality increasing effect Feminization of workforce also has an inequality increasing effect Perhaps, measures such as MGNREGA could be contributing to the decline (conjecture)