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Responding to Natural Hazards: The Effects of Disaster on Residential Location Decisions and Health Outcomes James Price Department of Economics University of New Mexico April 6 th , 2012 1 Introduction Analyses Overview Residential Sorting

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Responding to Natural Hazards:

The Effects of Disaster on Residential Location Decisions and Health Outcomes

James Price Department of Economics University of New Mexico April 6th, 2012

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Analyses Overview

1.

Residential Sorting and the Value of Hazard Risk Reduction

2.

County Migration Patterns and the Risk of Natural Hazards

3.

Determinants of Mental Health & Displacement Following Hurricanes Katrina and Rita

Introduction

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Residential Sorting

 Current Efforts:

 Improve Disaster Risk Management (DRM)

investments

 Attempts to quantify the benefits and costs of DRM

interventions

 Objective: Estimate WTP for reductions in

hazard risk within the United States

Residential Sorting

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Previous Literature

 Theoretical Framework

 Ehrlich and Becker (1972)  Berger et al. (1987)

 Hedonic Housing Analyses  Residential Sorting

 Timmins (2007)  Bayer et al. (2009)

Residential Sorting

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Theoretical Model

 Two-Stage Optimization Problem

  • 1. Determine the optimal allocation of income between

consumption goods

  • 2. Select the location that maximizes utility, taking into

account location-specific attributes

 Assumptions

 Knowledge of markets and amenities at each location  Labor and housing market equilibrium  Costly migration

Residential Sorting

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Theoretical Model (cont.)

Residential Sorting

E(Uij) = (1 )UND(Ci,Hi;X j,Mij) + UD(Ci,Hi;X j,Mij) Iij = C + jH

C = Composite Numeraire Good H = Housing Services X = Location -Specific Attributes M = Migration Cost = Probability of Hazard Occurance I = Household Income = The Price of Housing Services

 Expected Utility Function and Budget Constraint

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Theoretical Model (cont.)

 Indirect Expected Utility Function

E(Vij) = (1 )VND(Iij

ND, j ND;X j ND,Mij) + VD(Iij D, j D;X j D,Mij)

 Select Optimal Location

E(Vij) > E(Vik) j k, k =1,2,..., j

Residential Sorting

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Empirical Model

Residential Sorting

Uij = Ci

C Hi H e X j

X +M ij + j + ij

Iij = C + jH

Ci = C C + H

  • Iij Hi =

H C + H

  • Iij

j

 Utility Function and Budget Constraint  Demand Functions

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Empirical Model (cont.)

Residential Sorting

 Indirect Utility Function

ln Vij

( ) = + I ln Iij ( ) H ln j ( ) + X X j + Mij + j + ij

where = c ln c I

  • + H ln H

I

  • and I = C + H

MWTP

i = MUX

MUI = X I Iij  Marginal Willingness-to-Pay

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Empirical Model (cont.)

 Indirect Utility Function

ln Vij

( ) = + I ln Iij ( ) H ln j ( ) + X X j + Mij + j + ij

where = c ln c I

  • + H ln H

I

  • and I = C + H

ln Iij

( ) = ln Îij ( ) +ij

j =

j

*

Mij = MSMij

S + MDMij D + MRMij R

Residential Sorting

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Empirical Model (cont.)

 Indirect Utility Function

ln Vij

( ) = + I ln Îij ( ) H ln

j

*

( ) + X X j

+ MSMij

S + MDMij D + MRMij R + j + Iij + ij

Residential Sorting

 Indirect Utility Function

ln Vij

( ) = I ln Îij ( ) + MSMij

S + MDMij D + MRMij R + j + ij

where j = H ln

j

*

( ) + X X j + j

and ij = Iij + ij

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Empirical Model (cont.)

 Conditional Logit Model

Residential Sorting

P[ln(Vij) ln(Vik)] = e

I ln º ij

( )+ MSM ij

S + MDM ij D + MRM ij R + j

e

I ln º ij

( )+ MSM ij

S + MDM ij D + MRM ij R + j

k=1 j

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Empirical Model (cont.)

Residential Sorting

 Quality-of-Life Decomposition

j = H ln

j

*

( ) + X X j + j

j + H ln

j

*

( ) = + X X j + j

Hi = H C + H

  • Iij

j H = I jHi Iij

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Data

 2005-2009 American Community Survey

 Housing services regression  Wage regressions  Conditional logit

model

Residential Sorting

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Data (cont.)

Residential Sorting

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Data (cont.)

Residential Sorting

  • Expected Number of Disaster Events
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Data (cont.)

Residential Sorting

  • Expected Number of Disaster Events by MSA
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Results: Conditional Logit

Residential Sorting

* p<0.1 ** p<0.05 *** p<0.01 N=50,000

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Results: Quality-of-Life Index

Residential Sorting

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Results: Quality-of-Life Decomposition

Residential Sorting

* p<0.1 ** p<0.05 *** p<0.01 N=296

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Results: WTP Estimates

Residential Sorting

($275) HRISK (Events/1000 Years) ($213) NPLSITES (Sites) ($154) EMISSIONS (Lb/Per) $383 PRECIP (Inches) $759 TEMP (°F) MWTP (Median Income) Variable

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Conclusions

Residential Sorting

 Residential location decisions are partially

determined by high-consequence low- probability events

 Households are WTP $275 annually for a

marginal reduction in the number of expected hazard events per 1000 years.

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Net Migration

Net Migration

 The spatial equilibrium model suggests

household select their residential location so as to maximize utility--taking into account economic conditions and amenities

 Objectives:

 Quantify the relationship between county-

level migration rates and natural hazard risk

 Identify possible spatial heterogeneity in the

migration-risk relationship

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U.S. Migration (cont.)

Net Migration

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Empirical Model: SAC

Net Migration

 Spatial Simultaneous Autoregressive

M = WM + EE + DD + AA + u u = Wu + e M = Net In - Migration Rate E = Economic Characteristics D = Demographic Characteristics A = Environmental Amenities W = Spatial Weight Matrix

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Empirical Model: SAC (cont.)

Net Migration

 Net Inmigration Rate

Net Inmigration Ratei = Net Domestic Migrationit

t= 2001 2009

  • 1

9

  • *

Populationit

t= 2001 2009

  • *100

 Spatial Weight Matrix

Wij = dij dij

i=1 n

  • where dij = 1 if counties i and j are neighbors

0 otherwise.

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Results: SAC

Net Migration

N=3107

* p<0.1 ** p<0.05 *** p<0.01

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Empirical Model: GWR

Net Migration

Mi = iEEi + iDDi + iAAi + i ~ i.i.d. N(0, 2)

 Geographically Weighted Regression

)

  • i = (

X

iWiXi)1

X

iWiY i

Wik = exp dik b2

  •  Estimate Parameter Values

 Weight Matrix

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Results: GWR (Environmental Variables)

Net Migration

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Results: GWR (Hazard Risk)

Net Migration

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Conclusions

Net Migration

 County migration patterns are negatively

correlated with hazard risk

 Hurricane and flood risk have a substantially

greater affect on migration than earthquake risk

 There is significant spatial heterogeneity in the

relationship between migration and hazard risk

 This migration-risk relationship is greatest along

the Gulf Coast

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Determinants of Mental Health and Displacement

Mental Health and Displacement

 Hurricanes Katrina and Rita devastated parts of

the Gulf Coast in 2005

 Mass displacement  $191 billion in property damage  Extreme physical and psychological stress

 Objectives:

 Evaluate the effects of post-disaster stress on long

term mental health status

 Identify determinants of displacement and

displacement duration

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Data

Mental Health and Displacement

 Panel Survey of Income Dynamics

 2005 and 2007  Supplemental questionnaire for residents of

hurricane-affected areas

 Federal Emergency Management Agency

 Geospatial data regarding hurricane damage

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Empirical Model: Mental Health

Mental Health and Displacement

MHi = f (Ei,Bi,SSi,PDVIi) PDVIi = f (Ei,Bi,SSi,DSi) MH = Mental Health Indicator E = Socioeconomic Characteristics B = Behavioral and Health Characteristics SS = Social Support Index PDVI = Post Disaster Vulnerability Index DS = Disaster Severity

 Simultaneous Equations Model

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Empirical Model: Mental Health

Mental Health and Displacement

 Post-Disaster Vulnerability Index

 Displacement Duration  Property Damage  Food Shortages  Water Shortages  Unsanitary Conditions  Loss of Electricity

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Data (cont.)

Mental Health and Displacement

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Results and Conclusions: Mental Health

Mental Health and Displacement

 Several socioeconomic variables are

correlated with adverse mental health

  • utcomes

 The SSI is negatively correlated with

adverse mental health outcomes

 The PDVI is positively correlated with

adverse mental health outcomes

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Empirical Model: Displacement

Mental Health and Displacement

x1 j = f (H j,DS j,E j

h,B j h,SS j)

x2 j = f (H j,DS j,E j

h,B j h,SS j)

H = Housing Damage DS = Disaster Severity E = Socioeconomic Characteristics B = Behavioral and Health Characteristics SS = Social Support Index

 Probit-Weibull Hurdel Model

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Displacement Duration

Mental Health and Displacement

  • Plot of Kaplan-Meier Estimator
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Results and Conclusions: Displacement

Mental Health and Displacement

 Housing damage is positively correlated with

both displacement and displacement duration

 Most socioeconomic variables are not

significantly correlated with displacement

 The SSI is positively correlated with

displacement and negatively correlated with displacement duration

 Remittances from family are negatively

correlated with displacement duration

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Questions?

Mental Health and Displacement

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Exposure to Natural Hazards

 Major hazard events since 2000

 3740 (Globally)  246 (United States)

 Exposure to natural hazards is rapidly increasing

 Population growth within hazard-prone areas  Climate Change

Introduction

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Theoretical Model (cont.)

Residential Sorting

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Empirical Model (cont.)

Residential Sorting

 Conditional Logit Model

P[ln(Vij) ln(Vik) j k] = e

Vij (I ij , j ;X j ,M ij )

e

Vik (I ij , j ;X j ,M ij ) k=1 j

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Empirical Model (cont.)

Residential Sorting

ln(UCij) = 0 + ln( j) + DD + ij UC = User Cost = MSAfixed - effects D = Dweling Characteristics

ln(Wij) = 0 + SSij + PP(RB,RD | SC) + PP(RB,RD | SC)2 + ij W = Hourly Wage Rate S = Socioeconomic Charateristics P(•) = Probability that Person Born in RB resides in RD  Price of Housing Services Estimates  Income Estimates

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Data (cont.)

 Data Sources for Location-Specific

Attributes

 City and County Database  Core of Common Data  County Business Patterns  National Climate Data Center  Environmental Protection Agency  Global Risk Data Platform

Residential Sorting

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Results: Housing Regression

Residential Sorting

N=1,599,627 R2=0.6047

* p<0.1 ** p<0.05 *** p<0.01

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Results: Wage Regression

Residential Sorting

N: Mean=5405 Max.=99324 Min.=547 R2: Mean=0.373 Max.=0.517 Min.=0.238

88.4% of coefficients are significant at p<0.1

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Results: WTP Estimates

Residential Sorting

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U.S. Migration

Net Migration

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Results: GWR (Emissions)

Net Migration