Nilanjan growth and development

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Nilanjan growth and development

  1. 1. Is India Shinning? Presented by: Nilanjan Banik
  2. 2. Background  Debate in policy circles about increase in income inequality, and a fall in poverty ratio.  “Talk of inclusive growth, rich getting richer, faster: Report,” 01 February 2011, Economic Times.
  3. 3. Presentation Scheme          Related Literature Disagreement and Agreement Motivation Why is this Study? Empirical Model Data and Variables Results Policy Implications Conclusion
  4. 4. Literature Debate on Beta and Sigma Convergence  Conflicting evidence in the literature whether regional inequality has increased, or decreased over time.  Cashin and Sahay (1996), Aiyer (2001), and Purfield (2006), find evidence in favor of convergence.  Rao et al. (1999), Bajpai and Sachs (1996), and Kurian (2000) find evidence in favor of divergence.
  5. 5. Literature (Cont.) Impact of reforms on income inequality  About, Ahluwalia (2002) finds it has fallen.  Bhattacharya and Sakthivel (2004), find it has increased.  All these studies mostly have used state level data, and use growth accounting framework as suggested in Barro and Sala-i-Martin (1992).
  6. 6. Agreement  Evidence of Sigma Convergence after reforms.  Mixed evidence about Beta Convergence.  Pockets of deprivation in progressive states.  Neighborhood effect is important.
  7. 7. Motivation  Twin Peaks Hypothesis: Quah’s (1996) and Jones (1997).  Variation in steady-state income level at a sub-state (district) level.  OLS estimate are conditional average, and fail to capture potential observational interaction across region.  Failure to capture such neighborhood effect can result in major model misspecification (Anselin, 1988).
  8. 8. Why this Paper?  We use district-level data and examine inter-regional income inequality.  We look at the factors that affect district-level income distribution.  We quantify the neighborhood effect using spatial econometric techniques.
  9. 9. Empirical Model  Is there any significant change in median adjusted per-capita income density?  Factors responsible for district-level income growth.  Quantifying the own effect, direct and indirect neighborhood effect?
  10. 10. Data  District income data (per-capita) covering 536 districts (out of 627 districts) in India.  Time period covered: 1999/2000, 2001/02, and 2004/2005.
  11. 11. Data (Cont.) Development Indicators       No. of factories per one lakh popn. No. of hospitals and dispensaries per one lakh popn. Percentage of household with electricity connection, availing banking services, drinking tap water, and with close drainage system. School enrollment as a percentage of total population. Gini Coefficient. Number of Murder committed in 2001.
  12. 12. Median Adjusted Density and Distribution of logincome in 1999/2000, 2001/02, and 2004/05
  13. 13. Evidence of Twin Peaks Kernel Density Plots of Log Per capita Trade&Hotel Kernel Density Plots of Log Per capita Communication Median adjusted 0 0 .1 .2 Density Density .2 .3 .4 .4 .5 .6 Median adjusted 4 6 8 10 2 4 log(Rs) 6 8 log(Rs) Per capita Tr&Hotel-1999 Per capita Tr&Hotel-2005 Per capita Communication-1999 Per capita Communication-2005 Kernel Density Plots of Log Per capita Service Kernel Density Plots of Log Per capita Banking&Insurance Median adjusted 0 0 .1 .2 Density .2 Density .4 .3 .6 .4 Median adjusted 2 4 6 log(Rs) Per capita Banking&Insurance-1999 Per capita Banking&Insurance-2005 8 10 7 8 9 log(Rs) Per capita Srv-1999 Per capita Srv-2005 10 11
  14. 14. Tests for significance in mean Income 1999/00 and 2004/05 (without Gujarat and Delhi) 2001/02 and 2004/05 T-test of Mean Difference: Income 19.41 (0.00)a 16.08 (0.00) T-test of Mean Difference: Log Income 23.22 (0.00) 22.11 (0.00) Z-Value of sign test of median: Income 6.87 (0.00) 4.98 (0.00) 6.78 (0.00) 4.99 (0.00) Z-Value of sign test of median: Log Income a P-values are in the parenthesis
  15. 15. Tests of Distributional Difference of median adjusted Log Income Test Statistics Kolmogorov-Smirnov (KS) one sided test statistics a P-values are in the parenthesis 1999/00 and 2004/05 (without Gujarat and Delhi) 0.042 (0.38)a 2001/02 and 2004/05 0.036 (0.48)
  16. 16. All India Moran Indices for income and growth w  y n Moran Index (I): Iy : W ij i , j 1 i y  y j y  trace(W 'W ) *   y  Variable Moran Index (I) t-statistics 'Per-capita Income 1999/2000' 0.54 19.74 'Per-capita Income 2001/02' 0.53 20.33 'Per-capita Income 2004/05' 0.48 18.51 'Per-capita Annualized Income Growth 1999/002004/05' 0.38 13.88 'Per-capita Annualized Income Growth 2000/012004/05' 0.26 10.05
  17. 17. Growth-Development Nexus Y1  X1  WX 1  1 1  1W1  u1 Y2  X 2  WX 2   2  2   2W 2  u2   u1  2 1   ~ N  0,    u     2      1 
  18. 18. Equation 1 Log income 2004/05 Dependent Variable Equation 2 Log income 2001/02 Cross Equation Correlation 0.919 R-bar Square 0.6791 0.6850 No. observations, No. Variables 485, 485, Variable Coefficient 19 t-stat 19 Coefficient t-stat Constant 8.3647** 86.48 8.2919** 93.94 No. of factories total 0.0004* 2.38 0.0004* 2.44 Gini coefficient 0.6409* 2.31 0.6116* 2.42 Murder 0.0003 0.76 0.0003 0.98 0.003* 2.28 0.0031* 2.54 Closed drainage 0.0057** 2.95 0.0044* 2.52 School enrolment 0.009** 3.72 0.0085** 3.83 Hospitals and dispensaries 0.0034** 3.65 0.0031** 3.67 Banking services 0.0064** 2.92 0.0062** 3.12 Tap drinking water 0.0029** 2.81 0.0023* 2.41 W*No. of factories total 0.0002** 4.37 0.0002** 3.18 0.108 1.20 0.1064 1.30 0 -0.23 0 0.29 W*Electricity connection 0.0004 1.16 0.0008** 2.63 W*HH closed drainage 0.0003 0.40 -0.0002 -0.27 W*School enrolment -0.0002 -0.40 -0.0002 -0.38 W*Hospitals and dispensaries -0.0003 -0.80 -0.0003 -0.83 W*Banking services -0.002** -3.53 -0.0019** -3.56 W*Tap drinking water -0.0003 -1.32 -0.0004 -1.78 0.096* 10.48 0.094* 10.10 Electricity connection W*Gini coefficient W*Murder ρ 1 , ρ2 * Indicates the coefficient is significant at a 2.5 per cent level, and ** indicates the coefficient is significant at a 1 per cent level.
  19. 19. Regression Results  In terms of direct own effect all the development indicators, sans murder, affect income.  In terms of direct neighborhood effect, only factory, electricity and bank, affect income.  Evidence about cross income correlation.  Indirect neighborhood effect is 10%.
  20. 20. Policy Analysis Case of Bangalore Urban Factories Closed drainage Electrification School enrollment Banks Drinking water Bangalore Urban 0.18 0.30 0.41 0.25 0.17 0.27 Dharmapuri 0.03 0.06 0.09 -0.07 -0.02 0.01 Bangalore Rural 0.03 0.06 0.08 -0.07 -0.02 0.01 Chamarajanagar 0.01 0.01 0.02 -0.02 0.00 0.00 Kolar 0.01 0.01 0.02 -0.02 0.00 0.00 Salem 0.01 0.01 0.01 -0.01 0.00 0.00 Erode 0.00 0.01 0.01 -0.01 0.00 0.00 Tumkur 0.00 0.01 0.01 -0.01 0.00 0.00 Mandya 0.00 0.01 0.01 -0.01 0.00 0.00 Viluppuram 0.00 0.01 0.01 -0.01 0.00 0.00 Tiruvanamala 0.00 0.01 0.01 -0.01 0.00 0.00 Vellore 0.00 0.01 0.01 -0.01 0.00 0.00
  21. 21. Policy Analysis  A 1% increase in the number of factories increase income for Urban Bangalore by 0.18 per cent  Similarly, a 1% increase in electrification, closed drainage, school enrolment, banks, and drinking water, resulted in an increase in per capita income by 0.30 per cent, 0.41 per cent, 0.25 per cent, 0.17 per cent, and 0.27 per cent, respectively.
  22. 22. Conclusion  There is no evidence in support of emergence of clusters: clustering of the rich-income districts, and clustering of poor-income districts.  Private sector is taking initiative in moving to districts with lesser input costs.  Income growth is spatially correlated.  Human capital, physical, and social infrastructure, are significantly contributing to the Indian growth story.
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