Welfare Impacts of Urbanization and Growth in South Asia: Perspective from

New Economic Geography

Muhammad Zeshan, Dr. Vaqar Ahmed and Muhammad Sohaib24-02-2013

Center for Jawaharlal Nehru StudiesJamia Millia Islamia (Central University)

Outline

• Introduction• Urbanization, Poverty and Inequality in South Asia• The New Economic Geography • Gains from Trade• Inclusive Urbanization• Econometric Model• Findings • Recommendations

Introduction

• Urban areas are now hubs of production activities • Urban Population of South Asia will increase to

around 1188 million by 2050 (World Urbanization Prospects 2011)

• Urban inclusion is helped in these ingredients o Open markets o Provision of public goods and serviceso Strengthening mechanism of Voice and accountability

Projection of Urban

Afghanistan Bangladesh Bhutan India Maldives Nepal Pakistan Sri Lanka0

100000

200000

300000

400000

500000

600000

700000

800000

900000

1000000

Year 2010 Year 2050

Growth Rate of Urbanization

Source: World Development Indicators

19811982

19831984

19851986

19871988

19891990

19911992

19931994

19951996

19971998

19992000

20012002

20032004

20052006

20072008

20092010

20112012

0

0.2

0.4

0.6

0.8

1

1.2

1.4

South Asia European Union High income: OECDLatin America & Caribbean (all income levels) North America OECD membersWorld

GDP Growth Rate

Source: World Development Indicator

19811982

19831984

19851986

19871988

19891990

19911992

19931994

19951996

19971998

19992000

20012002

20032004

20052006

20072008

20092010

20112012

-6

-4

-2

0

2

4

6

8

10

12

South Asia European Union High income: OECDLatin America & Caribbean (all income levels) North America OECD membersWorld

Urbanization, Poverty and Inequality in South Asia

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

0

20

40

60

80

100

Bangladesh

Urbanization Poverty Inequality

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

0102030405060708090

India

Urbanization Poverty Inequality

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

0102030405060708090

100

Pakistan

Urbanization Poverty Inequality

Source: World Development Indicators

Urbanization, Poverty and Inequality in South Asia

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

0

10

20

30

40

50

60

70

80

90

100

Nepal

Urbanization Poverty Inequality

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

0

10

20

30

40

50

60

Sri Lanka

Urbanization Poverty Inequality

Urbanization, Poverty and Inequality in South Asia

Source: World Development IndicatorDuring 2000, poverty in Pakistan reduced more than India

Overtime inequality in these countries reducing Poverty and Inequality reduced as urbanization increased overtime

Countries Bangladesh India Nepal Pakistan Sri Lanka

Time Urbanization (measured by Urban Population/Total Pupulation)

1980s 18.7 24.9 8.1 30.0 17.6

1990s 21.9 26.7 11.2 32.0 16.4

2000s 26.4 29.8 15.6 34.9 15.2

Poverty (measured by USD 2 a day)

1980s 89.4 83.5 92.6 88.8 50.8

1990s 87.8 80.7 87.9 81.0 46.3

2000s 79.6 73.6 68.2 63.7 31.4

Inequality (measured by Coefficient of Variation, population weighted)

1980s 29.4 82.9 12.2 29.3 11.6

1990s 29.3 81.8 12.4 29.5 10.6

2000s 28.4 73.7 12.1 28.3 8.4

New Economic Geography

• The externalities emerging from demand and supply spillovers also increase market interaction and reduces the transportation cost

• The new economic geography discusses economic activity based on location, increasing returns, monopolistic competition, and transaction costs

Gains from Trade

• A key role of Trade is contribution to Economic Growth

• Trade induced urban migration has important implications for poverty and income distribution

• Trade activities in urban areas provide new opportunities to the migrant labor and also equalize the wage rate across different regions.

Is Urbanization Inclusive?

• New Opportunities for the Poor rural workers• Impact of urbanization on poverty reduction • The clustering of urban population in a few places can

promote economies of scale which may reduce poverty (World Bank, 2009)

• The urban migration includes a significant share of the rural poor, which reduces the overall poverty and inequality (Ravallion et al., 2007).

Theoretical Framework

We formalize the framework as follows: rit = f(g it, y it, s it, u it), (1)pit = f(g it, y it, s it, u it), (2)i = 1, …, N (South Asian Countries)t = 1, …, T (Time)

r:Measur of inequalityp: Poverty rateg: Growth rate of GDPy: GDP per capitas: Trade integrationu: Urbanization

Econometric Model

Seemingly Unrelated Regression equations (SURE) framework to estimate the impact of urbanization, regional trade and economic growth on poverty and inequality ; (i = 1, 2, …, 8)

Results- Impact on Poverty

Seemingly unrelated regression

Dependent Variable: Poverty rate (USD 2 per day)

Bangladesh India Nepal Pakistan Sri Lanka

Urbanization

-1.198***

-1.642***

-1.783***

-4.715***

4.441***

Regional Trade

-0.043

0.899

-0.123***

-1.41***

-0.509***

GDP per capita -0.003-0.002

***-0.014

***0.018***

-0.002***

GDP growth rate -0.065 -0.007 -0.014 -0.104 0.004

Constant114.7***

124.0***

117.5***

232.1***

-19.0***

R-sq 0.86 0.97 0.97 0.93 0.99

P-value 0.00 0.00 0.00 0.00 0.00

***, ** and * indicate 1%, 5%, and 10% level of significance respectively.

Results-Impact on Inequality

Variables Afghanistan Bangladesh Bhutan India Nepal Maldives Pakistan Sri Lanka

Urbanization

-0.0003

0.0008 ***

-0.0001 ***

-0.003***

0.0005***

0.0001***

0.004***

0.003***

Regional Trade

0.0004***

-0.0002 ***

-0.000002***

-0.004**

0.000005

-0.000003*** -0.0004 ***

0.00003**

GDP per capita-0.0001

***-0.00006

***-0.000001

***-0.0001

*** -0.00002 ***-0.000002

*** -0.00005 *** -0.00001 ***

GDP growth rate0.0003

***0.00001

**-0.000007

* -0.00002 0.000004 -0.000001 -0.000008 0.000004

Constant0.123*** 0.296 ***

0.023***

0.965***

0.122***

0.01***

0.004***

0.064***

R-sq 0.87 0.99 0.98 0.99 0.97 0.99 0.99 0.99

P-value 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Fix Effects Model

Dependent Variable: Poverty

Variables South Asia

Urbanization -1.264***

Regional Trade -0.189***

GDP per capita -0.01***

GDP growth rate -0.068

Constant 111.9

F-stat 254

***, ** and * indicate 1%, 5% and 10% level of significance.

Dependent Variable: Inequality

Variables South Asia

Urbanization -0.0001

Regional Trade 0.00002

GDP per capita -0.000008***

GDP growth rate -0.0002**

Constant 0.225***

F-stat 3112

Fixed Effects Model

***, ** and * indicate 1%, 5% and 10% level of significance.

• Impact of trade liberalization on poverty is smaller, it is essential to revisit the trade policies across South Asia.

• Attention should be paid towards strengthening mechanism of community voices and gender empowerment.

• There is need to revisit tariff and non-tariff barriers in South Asia

• It is important to have in place commerce and environmental friendly urban zoning and building regulations.

Recommendations

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