Surviving the Big One:Recovery after the 2008 Wenchuan Earthquake

Shuaizhang Feng and Patrick Nolen

SHUFE and Essex

October 11, 2010

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Introduction

Number of Natural Disasters has been increasing since 1960(CRED-Belgium)

Rural households in developing countries are especially vulnerablenegative shocks from extreme natural disasters.

Kahn (2006) and Stromberg (2007) show that, all else equal, thepoorer a country struck by a natural disaster, the more people die.Stromberg (2007), using cross-country data, argues that ‘better’institutions in developed countries can explain some of the differencesin death rates.Burgess, Deschenes, Donaldson, Greenstone (2010) show extreme heatleads to more death in rural areas of India.

Some work on vulnerability has examined what types of householdsare vulnerable to negative shocks.

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This Paper

Little or no micro-econometric work on causes of why somehouseholds recover quicker or suffer less ‘damage’ due to extremenegative shocks.

We will examine:

1 What household characteristics are associated with quicker recovery?2 What mechanisms do these characteristics suggest are allowing more

resilience?

In particular we will focus on the role of:

Off-farm labourLand holdingsPolitics and/or close connections to leaders.Government relief

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Background

May 12, 2008 an 8.0 magnitude earthquake centered in Wenchuanstruck.

Sky-scrappers in Shanghai, more than 1, 000 miles away shook.45 million people directly effected.70, 000 people died and 18, 000 still considered missing.

Mianzhu county was one of the hardest hit areas.

Of 500, 000 residents: 10, 000 died and 1, 898 are still missing.Government estimates direct economic loss of RMB130 billion ($19.4billion).

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Feng and Nolen (SHUFE and Essex) Sichuan Earthquake October 11, 2010 5 / 20

Data

Pre-Earthquake:

Detailed household income and expenditure survey for 800 families inrural Sichuan collected in August 2007.

Households from two towns: X and S.Town X is 10km north of Mianzhu, and Town S is 20km south ⇒Town X is 30km closer to the epicenter.Randomly sampled 9 sub-villages (from 3 villages) in Town X.Randomly sampled 6 sub-villages (from 3 villages) in Town S.

Post-Earthquake:

Detailed household income and expenditure survey with questionsregarding the earthquake and government support for over 850households collected in August 2009.

Same sub-villages were surveyed.700 of the same households from 2007 were sampled.

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Epicenter

Feng and Nolen (SHUFE and Essex) Sichuan Earthquake October 11, 2010 7 / 20

Pre-Earthquake Summary Statistics: 2007

Variable Town X Town S DifferenceAge 40.00 40.13 0.128Female 0.49 0.49 -0.001Urban HuKo 0.10 0.12 0.017Party Member 0.03 0.03 0.001Work Off-Farm 0.30 0.29 -0.006Height (cm) 154.00 152.09 -1.911**Weight (.5kilo) 56.20 62.75 6.549***Ciggarettes per day 3.80 3.52 -0.278Size of HH 3.17 3.26 0.094Land (mu) 3.50 2.92 -0.581***Monthly HH income (RMB) 1055.00 1289.26 234.259**Monthly HH off-farm income (RMB) 564.00 705.57 141.570**Monthly HH expenditure (RMB) 1038.00 1107.90 69.902

Town S slightly richer and has shorter, ‘fatter’ people, who do notwork on the land as much.

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Feng and Nolen (SHUFE and Essex) Sichuan Earthquake October 11, 2010 9 / 20

Effects of Earthquake

Variables Town X Town S DifferenceInjured 0.04 0.01 -0.034***Go to Hospital 0.03 0.01 -0.021***No treatment 0.02 0.00 -0.018***Cost of Inj (RMB) 197.20 2.34 -194.857**Out of pocket cost (RMB) 16.39 2.28 -14.113*Yeild Lost (RMB) 771.05 508.51 -262.544***Farm Inc Lost (RMB) 701 00 483 06 -217 940***Farm Inc Lost (RMB) 701.00 483.06 -217.940***Livestock Inc Lost (RMB) 738.50 388.56 -349.943***Lost workdays 0.23 0.18 -0.048***Workdays lost 25.95 16.85 -9.104***Lost off-farm income 0.23 0.18 -0.052***House Damaged 0.99 0.98 -0.009***Rebuilt House 0.96 0.91 -0.050***Gov Aid Receive (RMB) 21100.00 19679.42 -1,420.576**Gov Aid Expected (RMB) 4066.26 3709.72 -356.543**Cost of Rebuild (RMB) 76150.64 75178.46 -972.181

Town S suffered less than Town X from the earthquake.

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Feng and Nolen (SHUFE and Essex) Sichuan Earthquake October 11, 2010 11 / 20

Identification

To identify the effect of xi we will use a diff-in-diff strategy

We will estimate the following:

∆yi = ∆α + C1 · Iv=1 + β1∆xi + β2xi2007

+ β3 · Iv=1 · x2007 + B2007X2007 + ∆ε i

Such that:

x the channel we are examining; X is a matrix of controls; i representsperson or hh.Time trend concerns.

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Variables of Interest

Off-Farm Work: access to more information and connections withpeople who may not have suffered as much.

Party Membership: Being in the communist party could mean more‘favourable’ access to resources or aid, though, it could be a proxy forability.

Urban HuKo: With an urban HuKo an individual has more ‘outside’options.

Land: A Household with more land may recover quicker because ithas access to a productive asset.

Dependent Variables:

Weight for height (BMI).Household Income.

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BMI: Weight Over Height Squared

VARIABLES [1] [2] [3] [4]Off-farm 2007 (=1) -0.000 -0.001

[0.001] [0.001]Off-farm 2007 * Town S -0.000 -0.000

[0.002] [0.002]Urban HuKo 2007 0.005*** 0.006***

[0.002] [0.002]Urban HuKo 2007 * Town S -0.006** -0.007***

[0.002] [0.002]Constant 0.003** 0.003** 0.003** 0.003**

[0.001] [0.001] [0.001] [0.001]

Fixed Effects SV Vil SV VilControls: Marriage, Gender YES YES YES YESControls: Age, Education, Year YES YES YES YES

Observations 2,455 2,455 2,450 2,450Standard errors in brackets*** p<0.01, ** p<0.05, * p<0.1

Dependent Variable is Weight / Height^Sq

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Variables of Interest

Only HuKo status has an effect on weight for height.

Mean BMI 0.0039 and standard deviation is 0.015 so having an urbanHuKo status in an area hit harder by a natural disaster is equivalent toan increase of 0.33 standard deviations.

An urban HuKo allows individuals to reside in an urban areas andaccess urban resources.

To examine how an urban HuKo status is effecting weight for heightwe can examine movement after the earthquake.

We examine if people with urban HuKo status were more likely toleave the county and/or stay away longer.

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Urban HuKo Mechanism

VARIABLES

Off-farm 2007 (=1) 0.084*** 0.084*** 6.552*** 6.689***[0.025] [0.025] [2.004] [2.001]

Off-farm 2007 * Town S 0.048 0.049 2.940 3.016[0.033] [0.033] [2.664] [2.663]

Urban HuKo 2007 -0.094** -0.073** -5.655* -4.025[0.039] [0.035] [3.150] [2.833]

Urban HuKo 2007 * Town S 0.087 0.045 0.984 -2.441[0.053] [0.049] [4.345] [4.020]

Fixed Effects SV Vil SV Vil SV Vil SV VilControls: Marriage, Gender YES YES YES YES YES YES YES YESControls: Age, Education, Year YES YES YES YES YES YES YES YES

Constant 0.122*** 0.122*** 0.176*** 0.179*** 11.776*** 12.006*** 16.053*** 16.501***[0.027] [0.026] [0.025] [0.025] [2.152] [2.149] [2.029] [2.026]

Observations 2,026 2,026 2,021 2,021 2,026 2,026 2,021 2,021R-squared 0.082 0.078 0.070 0.064 0.065 0.056 0.054 0.045Standard errors in brackets*** p<0.01, ** p<0.05, * p<0.1

Dependent Varibales(=1) when the person left the county after

the Earthquake hit.Number of days person/family spent out

of county after earthquake

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Urban HuKo Mechanism

VARIABLES Go Hosp Get TreatMoney From

GovCost of

Rebuilding

Urban HuKo 2007 -0.008 -0.002 8,147.563*** 446.772[0.013] [0.012] [1,729.645] [7,138.363]

Urban HuKo 2007 * Town S 0.006 0.001 -9,481.423*** 12,695.337[0.019] [0.018] [2,454.602] [10,130.309]

Fixed Effects Vil Vil Vil VilControls: Marriage, Gender YES YES YES YESControls: Age, Education, Year YES YES YES YES

Constant 0.022** 0.020** 22,080.267*** 71,451.535***[0.010] [0.009] [1,237.346] [5,106.613]

Observations 2,021 2,021 2,021 2,021R-squared 0.013 0.014 0.034 0.035Standard errors in brackets*** p<0.01, ** p<0.05, * p<0.1

Dependent Variable

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Variables of Interest

Look at Household Income

Having a member of the communist party is significant but does notseem to be due to selection on ability.

Households that recover better after the earthquake are ones thatreceived more aid (urban HuKo), have a party member in them, andhave more land.

Aid and access to land are drivers of household recovery.

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Household Income

VARIABLES [1] [2] [3] [4] [7] [8]

Off-farm 2007 (=1) 0.725*** 0.763***[0.130] [0.130]

Off-farm 2007 * Town S -0.174 -0.201[0.173] [0.171]

Communist 2007 0.348** 0.373***[0.138] [0.139]

Communist 2007 * Town S -0.572** -0.563**[0.252] [0.249]

Land Size in 2007 0.201*** 0.212***[0.037] [0.036]

Land Size in 2007 * Town S -0.144** -0.159***[0.061] [0.060]

Fixed Effects SV Vil SV Vil SV VilControls: Year, gender, HHsize Yes Yes Yes Yes Yes YesControls: Age, Education Yes Yes Yes Yes Yes Yes

Constant 7.587*** 7.528*** 7.909*** 7.858*** 7.604*** 7.553***[0.187] [0.189] [0.186] [0.188] [0.195] [0.195]

Observations 1,599 1,599 1,599 1,599 1,502 1,502R-squared 0.233 0.223 0.212 0.199 0.231 0.219Robust standard errors in brac*** p<0.01, ** p<0.05, * p<0.1

Dependent Variable is Log of Household Income

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Household Income

VARIABLES Original OriginalMore

EducationMax

Education

Communist 2007 0.348** 0.373*** 0.336** 0.374**[0.138] [0.139] [0.139] [0.155]

Communist 2007 * Town S -0.572** -0.563** -0.575** -0.715**[0.252] [0.249] [0.249] [0.277]

Fixed Effects SV Vil Vil VilControls: Year, gender, HHsize Yes Yes Yes YesControls: Age, Education Yes Yes Yes Yes

Constant 7.909*** 7.858*** 7.999*** 7.672***[0.186] [0.188] [0.186] [0.239]

Observations 1,599 1,599 1,599 1,157R-squared 0.212 0.199 0.225 0.222Robust standard errors in bracket*** p<0.01, ** p<0.05, * p<0.1

Dependent Variable is Log HH Income

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