Is India Shinning?

Presented by: Nilanjan Banik

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.

Presentation Scheme

Related Literature

Disagreement and Agreement

Motivation

Why is this Study?

Empirical Model

Data and Variables

Results

Policy Implications

Conclusion

Literature

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.

Debate on Beta and Sigma Convergence

Literature (Cont.)

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).

Impact of reforms on income inequality

Agreement

Evidence of Sigma Convergence after reforms.

Mixed evidence about Beta Convergence.

Pockets of deprivation in progressive states.

Neighborhood effect is important.

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).

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.

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?

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.

Data (Cont.)

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.

Development Indicators

Median Adjusted Density and Distribution of log-

income in 1999/2000, 2001/02, and 2004/05

Evidence of Twin Peaks

0

.2

.4

.6

Den

sity

4 6 8 10 log(Rs)

Per capita Tr&Hotel-1999

Per capita Tr&Hotel-2005

Median adjusted

Kernel Density Plots of Log Per capita Trade&Hotel

0

.1

.2

.3

.4

.5

Den

sity

2 4 6 8 log(Rs)

Per capita Communication-1999

Per capita Communication-2005

Median adjusted

Kernel Density Plots of Log Per capita Communication

0

.2

.4

.6

Den

sity

7 8 9 10 11 log(Rs)

Per capita Srv-1999

Per capita Srv-2005

Median adjusted

Kernel Density Plots of Log Per capita Service

0

.1

.2

.3

.4

Den

sity

2 4 6 8 10 log(Rs)

Per capita Banking&Insurance-1999

Per capita Banking&Insurance-2005

Median adjusted

Kernel Density Plots of Log Per capita Banking&Insurance

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

23.22 (0.00)

16.08 (0.00)

22.11 (0.00) T-test of Mean Difference: Log Income

Z-Value of sign test of median: Income 6.87 (0.00)

6.78 (0.00)

4.98 (0.00)

4.99 (0.00) Z-Value of sign test of median: Log Income

a P-values are in the parenthesis

Tests of Distributional Difference of median

adjusted Log Income

Test Statistics

1999/00 and 2004/05

(without Gujarat and Delhi)

2001/02 and 2004/05

Kolmogorov-Smirnov (KS)

one sided test statistics

0.042 (0.38)a 0.036 (0.48)

a P-values are in the parenthesis

All India Moran Indices for income and growth

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 1999/00-

2004/05' 0.38 13.88

'Per-capita Annualized Income Growth 2000/01-

2004/05' 0.26 10.05

, 1

:( ' )*

n

ij i j

i j

w y y y y

I y Wtrace W W y

Moran Index (I):

Growth-Development Nexus

1

1,0~ 2

2

1

2222

2222

1111

1111

Nu

u

uW

WXXY

uW

WXXY

Equation 1 Equation 2

Dependent Variable Log income 2004/05 Log income 2001/02

Cross Equation Correlation 0.919

R-bar Square 0.6791 0.6850

No. observations, No. Variables 485, 19 485, 19

Variable Coefficient t-stat 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

Electricity connection 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

W*Gini coefficient 0.108 1.20 0.1064 1.30

W*Murder 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

ρ 1 , ρ2 0.096* 10.48 0.094* 10.10

* Indicates the coefficient is significant at a 2.5 per cent level, and ** indicates the coefficient is significant at a 1 per cent level.

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%.

Policy Analysis

Factories Electrification

Closed

drainage

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

Case of Bangalore Urban

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.

Policy Analysis

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.