Poverty and Inclusion in the West Bank and Gaza

Tara Vishwanath and Roy Van der Weide

Oslo accord created a fragmented territory, with no Palestinian control over “Area C”

Overlaid by a regime of internal and external closures

Limited control over economic policies and trade

Dependence on international aid and Israel

-30

-20

-10

0

10

20

30

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

West Bank Gaza

30

50

70

90

110

130

150

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Agriculture Construction Private services Public services Manufacturing

Changes in the Sectoral Shares in GDP (Index; 1994=100)

GDP growth in the West Bank and Gaza (Annual percentage change)

0.0

10.0

20.0

30.0

40.0

50.0

60.0

2004 2005 2006 2007 2009

Total West Bank Gaza

0.00

0.05

0.10

0.15

0.20

0.25

Gaza West Bank

0%

10%

20%

30%

40%

50%

60%

West Bank Unemployment

West Bank Youth Unemployment

Gaza Unemployment

Gaza Youth Unemployment

Social Assistance as a share of total household consumption expenditures: West Bank and Gaza, 2004-2009

Unemployment: West Bank and Gaza, 2004-2009

Pakistan

Nigeria

Yemen

India

Egypt

Ghana

Sudan

Cameroon

Iraq

Turkey

Jordan

West Bank and Gaza

Life expectancy at birth (years)

Literacy rate, adult (% of people ages 15 and above)

JordanWest Bank and

Gaza

Turkey

Iraq

Ghana

Egypt

Cameroon

Sudan

Nigeria

Pakistan

India

Yemen

Stunting (%) Wasting (%)

Widespread perception of despair especially in Gaza: media reports of poverty, distress

How does this reconcile with consumption poverty estimates? Or does it reflect multiple deprivations?

Do subjective perceptions of poverty reflect this fundamental lack of improvement in economic conditions in Gaza?

Anecdotal evidence on the impact of checkpoints on growth and trade, very little systematic microeconomic evidence

Unique geo-referenced data set

Spatial disparities within the West Bank

First stage of evidence in how checkpoints adversely affect prices and unemployment

The Geography of Poverty: New Tools with Applications to the West BankRoy van der Weide (DECPI)The World Bank

April 21, 2011, Washington DC

OutlineSpatial analysis: Empirical questions and toolsHow we use the tools in the WBG Poverty Assessment:

The Spatial Dimensions of Poverty in the West Bank: Geography or Checkpoints?

On the agenda – Tool developmentOn the agenda – New applications

New dataNew countries

Putting poverty on the mapAre there well-defined pockets of poverty?

Where are the lagging and leading areas?Do poverty, low and (lack of) high waged economic activity, unemployment, (poor) access to markets, show a coherent geographical pattern?

Do areas with the highest poverty rates also hold the largest number of poor?

Is population growth tied to economic growth, and vice versa?

How well does the existing road network do in connecting people (and economies)?

Internal barriers vs. price differentialsHow large is the effect of distortions brought on by internal barriers on the economy?

What % increase in transaction costs?What % change in unemployment and wages in affected areas?

Methodology – Spatial kernel regression

Spatial smoothing: Estimating routes

Poverty and number of poor

Sectors of employment

Work in Israel and unemployment

Access to markets and checkpoints

Methodology – Spatial price differentials versus internal barriers

Regressing absolute spatial price differentials on the nr. of internal barriers between locations

Controlling for distanceA way of measuring the size of the distortions brought on by internal barriersSpatial price differentials serve as a proxy for transaction costs

In the absence of arbitrage, price differences are bounded by transaction costsKeep nearest neighbours as these are more likely to involve in trade

Prices and checkpointsLoc-nearest-loc Rice Vegetables Potato & onion Fruits Tea & sugar

Distance 0.012 0.010 0.018 0.005 0.006

1 checkpoint 0.032* 0.010 0.018 0.055** 0.017

2 or more cp. -0.005 0.040 0.090** 0.099** 0.083**

Constant 0.042 0.116** 0.056 0.094** 0.061**

Adj. R-squared 0.036 0.008 0.080 0.051 0.085

Obs. 95 325 173 203 176

On the agenda – ToolsSpatial kernel regression versus the poverty mapping approach put forward by Elbers et al. (2003)

Under what conditions do they provide very similar or different estimates?

Develop spatial kernel regression into a user friendly tool

Implement it in easy to use software

On the agenda – ApplicationsThe West Bank

Updating database of closure obstacles: Are mobility restrictions easing over time?Do internal barriers also impact on international trade?

Lao PDRSpatial analysis of rice price inflation

The PhilippinesIslands as internal barriers