a comprehensive framework for assessing and...

2018/01/26 2018/01/26 © Shingo Nagamatsu

A Comprehensive Framework for Assessing and Responding to Disaster-Related Migration.

Prof. Adam Rose (Universtiy of Southern California) Dr. Jonathan Eyer (University of Southern California) Prof. Shingo Nagamatsu (Kansai University)

Sponsored by the Japan Foundation (July 2017 to Oct.2018) and Kansai University (Apr. 2017 to Mar. 2019)


Disaster Related Migration: An Overview

Job opportunity Relatives & family Proximity Amenity Social vulnerability Social capital Supports Disaster risk

Event type Magnitude

No-disaster area Time Age Sex Race Married Children Income Education Job Housing tenure Housing damage Sense of place etc.

Migrants

Job opportunity Damages Social vulnerability Social capital Supports Future risk

Public policies

Pre-migration

Out-migration

Return-migration

(Potential) Disaster area


‘Building Back Better’ Tohoku: A Contradicting Evidence

Shingo Nagamatsu, Ph.D. Faculty of Societal Safety Sciences, Kansai University

from Chapter 3 (pp.37-54) in Santiago-Fandiño, V., Sato, S., Maki, N., Iuchi, K. (Eds.) The 2011 Japan Earthquake and Tsunami: Reconstruction and Restoration, Springer, 2017.


Existing research on population recovery • Social capital enhance the demographic recovery (Aldrich 2012) • Provision of the ‘club goods’ by the community encourages

population recovery (Chamlee-Wright and Storr 2009) • New Orleans during recovery from Hurricane Katrina show that

the population that migrated out of the city was more vulnerable than those who migrated into the city (Fussell 2015, Fussell, Sastry, and Vanlandingham 2010, Groen and Polivka 2010).

• Vigdor (2008) explained why the population of New Orleans did not recover with a simple partial equilibrium analysis of the housing market.

• No study identified the paradoxical effect of reconstruction works on recovery.


Land Readjustment (Artificial Raising)

Relocation

Residential area Commercial area Park and fishery port

The height of the previous tsunami (L2)

The height of past frequent tsunami (L1)

Tsunami Levee

An Example of Recovery project (Onagawa city)

Total: 229 districts, 8840 households in 26 cities, 4.8 times of the past programs.

Total: 50 districts. 10 times in area of 1995 Kobe earhquake


Price hike induced by reconstruction demand

70

80

90

100

110

120

130

140

150

Year 2005 = 100 Price Index of Construction Materials

（Sendai）

総合

建築

土木

東日本大震災の影響


Sendai Framework for Action (2015) Priority 1. Understanding disaster risk Disaster risk management should be based on an understanding of disaster risk in all its dimensions of vulnerability, capacity, exposure of persons and assets, hazard characteristics and the environment. Such knowledge can be used for risk assessment, prevention, mitigation, preparedness and response. Priority 2. Strengthening disaster risk governance to manage disaster risk Disaster risk governance at the national, regional and global levels is very important for prevention, mitigation, preparedness, response, recovery, and rehabilitation. It fosters collaboration and partnership. Priority 3. Investing in disaster risk reduction for resilience Public and private investment in disaster risk prevention and reduction through structural and non-structural measures are essential to enhance the economic, social, health and cultural resilience of persons, communities, countries and their assets, as well as the environment. Priority 4. Enhancing disaster preparedness for effective response and to “Build Back Better” in recovery, rehabilitation and reconstruction The growth of disaster risk means there is a need to strengthen disaster preparedness for response, take action in anticipation of events, and ensure capacities are in place for effective response and recovery at all levels. The recovery, rehabilitation and reconstruction phase is a critical opportunity to build back better, including through integrating disaster risk reduction into development measures.


Research Question • Did this costly recovery projects promoted recovery?

• Population decrease has accelerated in tsunami affected municipalities compared to pre-disaster trend (Matanle 2013). Why?

• Reconstruction paradox: the reconstruction works by the recovery programs applied by the government impeded the recovery process of a municipality because of

1. Length of time to complete relocation 2. Amount of money to be covered by the affected residents.


Damage or Recovery? (2012)


Damage or Recovery? (2015) Scale of recovery program better explains the population recovery than the housing damage.


Determinant of the Scale of Recovery Program

Scale of the recovery program is better explained by fatality rate than damages.


The model 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑖𝑖,𝑡𝑡

= 𝛼𝛼0 + 𝛼𝛼1𝑆𝑆𝑆𝑆𝑀𝑀𝑆𝑆𝑆𝑆𝑖𝑖,𝑡𝑡 + 𝛼𝛼2𝐷𝐷𝑀𝑀𝐷𝐷𝑀𝑀𝑀𝑀𝑆𝑆𝑖𝑖,𝑡𝑡 + 𝛼𝛼3𝐷𝐷𝑀𝑀𝐷𝐷𝑀𝑀𝑀𝑀𝑆𝑆𝑖𝑖,𝑡𝑡𝐷𝐷𝑢𝑢𝐷𝐷𝐷𝐷𝑢𝑢𝑢𝑢𝑢𝑢 + 𝛽𝛽𝑋𝑋𝑖𝑖,𝑡𝑡+ 𝛾𝛾𝑇𝑇𝑀𝑀𝑆𝑆𝑀𝑀𝑇𝑇𝑖𝑖 + 𝑢𝑢𝑖𝑖𝑡𝑡

Migration : population movement, net, in and out from the municipal area. Scale : the scale of the recovery program each municipal government applied. Damage : the physical damages on each municipality. Dummy2011 : dummy variable that take 1 in the year of 2011, which may absorb the shock in the year of disaster. X : control variables other than damage. Trend : trend of migration before the disaster. u : error term. Subscript i and t : municipalities and year respectively. (i=1,..,28, t=2009,…,2015) α,β, and γ : parameters.


Data description Net Migration: Population increasing ratio to previous

year. Scale: A ratio of the number of housing units being

developed by the recovery project by government over total household in 2010.

Damaged ratio: A ratio of the number of totally or half collapsed housing over total number of household in 2010.

Inundated ratio: inundated household by Tsunami / total number of household in 2010

Dummy_2011: A dummy variables that takes 1 in 2011. Income per capita: a taxable income per capita Average number of parsons per a household: total

number of population / number of households Percentage of population over 65 (%): a ratio of people

over 65 to number of population Distance: the least distance from either Morioka, Sendai,

Koriyama, and Iwaki city. Net migration trend: Average of Net Migration of each

municipalities from 2009 to 2010.

Mean Median Max. Min. Std. Dev. N

Net Migration (%) -0.90 -0.54 1.98 -10.67 1.77 196

In-migration (%) 3.93 2.78 89.84 0.39 6.54 196

Out-migration (%) 4.93 3.50 109.52 2.10 7.93 196

Scale of recovery programs (%) 5.82 0.25 44.13 0.00 10.13 196

Damaged housing ratio (%) 23.45 18.84 82.43 0.00 23.85 196

Inundated housing ratio (%) 32.07 27.14 116.16 0.00 31.49 196

Dummy2012 0.14 0.00 1.00 0.00 0.35 196

Average Income per taxpayer (Million Yen) 2.58 2.53 3.37 2.08 0.26 196

Average number of persons per household 2.60 2.60 3.26 2.00 0.27 196

Newly consructed housing ratio (%) 2.48 1.63 12.76 0.00 2.32 196

Persentage of population over 65 (%) 28.39 29.26 39.80 17.51 5.14 196

Distance from a hub city (km) 50.57 61.65 93.70 0.00 29.55 196

Net migration trend -0.42 -0.45 1.70 -1.29 0.50 196

In-migration trend 5.80 3.38 46.10 2.04 8.19 196

Out-migration trend 6.60 3.54 56.11 2.36 9.91 196


Result 1: Net migration by all samples Dependent VariablesDamage variablePeriodNumer of cross sectionsNumber of observations

Estimation method

constant 3.8585 (2.599) 0.3843 (1.088) 2.2940 (3.396) -0.2424 (1.401)Scale of recovery programs -0.0467 (0.017) *** -0.0486 (0.009) *** -0.0661 (0.018) *** -0.0516 (0.011) ***

Damage -0.0123 (0.008) -0.0014 (0.004) 0.0028 (0.007) 0.0013 (0.003)Damage*2011 dummy -0.0821 (0.011) *** -0.0756 (0.005) *** -0.0638 (0.008) *** -0.0528 (0.003) ***

Average income per a taxpayer -0.4383 (0.52) 0.0790 (0.261) -0.2360 (0.654) 0.2495 (0.297)Average number of persons per household -0.5205 (0.392) -0.1911 (0.15) -0.2004 (0.51) -0.1382 (0.172)Newly constructed house ratio 0.1548 (0.055) *** 0.1343 (0.03) *** 0.0957 (0.082) 0.1066 (0.033) ***

Percentage of population over 65 -0.0497 (0.032) -0.0124 (0.012) -0.0583 (0.037) -0.0115 (0.015)Distance from a hub city 0.0009 (0.004) 0.0024 (0.001) * 0.0086 (0.005) * 0.0030 (0.002)Trend 0.8107 (0.14) *** 0.8073 (0.097) *** 0.8723 (0.174) *** 0.7466 (0.119) ***

R squaredAjusted R squaredF statistics *** *** *** ***Breusch-Pagan *** ***

Note: Numbers in parenthesis are cross section weighted standard errors*, **, *** represents 10%, 5%, and 1% significance respectively.

2009 to 2015Damaged house rate Inundated house rateDamaged house rate Indundated house rate

2009 to 2015 2009 to 2015 2009 to 2015

1 2 3 4Net Migration Net Migration Net Migration Net Migration

28

0.6840.669

0.7750.764

196Cross Sectionweighted GLS

196 196 196

OLSCross Sectionweighted GLS

OLS

28 28 28

18.005 13.699

0.5670.546

0.7690.758

44.739 71.188 27.097 68.882

• Coefficients of damage variables are not significant.

• Coefficient of Scale of recovery are all negative and significant.

• Spurious correlation?


Dependent variablesDamage variablePeriodNumer of cross sectionsNumber of observationsconstant 3.5243 (2.677) 4.3027 (3.42) -0.9622 (1.95) -0.6077 (2.263)Scale of recovery programs -0.0393 (0.016) ** -0.0509 (0.016) *** -0.0351 (0.017) ** -0.0353 (0.019) *

Damage -0.0099 (0.007) -0.0008 (0.006) 0.0114 (0.007) 0.0034 (0.005)Damage*2011 dummy -0.0816 (0.008) *** -0.0614 (0.006) *** -0.0355 (0.009) *** -0.0231 (0.005) ***

Average income per a taxpayer -0.2515 (0.448) -0.2702 (0.595) 0.4279 (0.406) 0.3661 (0.451)Average number of persons per household -0.7380 (0.394) * -0.6033 (0.525) -0.1274 (0.277) -0.1886 (0.285)Newly constructed house ratio 0.1651 (0.04) *** 0.1700 (0.063) *** 0.0226 (0.051) 0.0663 (0.039) *

Percentage of population over 65 -0.0782 (0.046) * -0.1229 (0.063) * -0.0030 (0.017) -0.0032 (0.019)Distance from a hub city 0.0197 (0.007) *** 0.0214 (0.008) *** 0.0011 (0.002) 0.0000 (0.003)Trend 1.0250 (0.192) *** 0.8228 (0.232) *** 0.6174 (0.26) ** 0.5629 (0.295) *

R squaredAjusted R squaredF statistics *** *** *** ***

Estimation method: cross section weighted general least squareNote: Numbers in parenthesis are cross section weighted standard errors*, **, *** represents 10%, 5%, and 1% significance respectively.

Damaged house rate Inundated house rate Damaged house rate Inundated house rate

1 2 3 4Net Migration Net Migration Net Migration Net Migration

2009 to 2015 2009 to 2015 2009 to 2015 2009 to 201514 (fatality>1%) 14(fatality>1%) 14(fatality=<1%) 14(fatality=<1%)

98 98 98 98

0.845 0.773 0.492 0.6250.829 0.749 0.440 0.587

53.298 33.230 9.475 16.322

Results 2 : Net migration grouped by fatality level

• Coefficient of Scale of recovery are all negative and significant.

• But the significance are lower in low fatality group.


Results3 : In and Out migration by different fatality groups

Dependent VariablesDamage variablePeriodNumer of cross sectionsNumber of observationsConstant -3.6475 (1.891) * -2.4183 (1.613) -4.7357 (2.214) ** -3.1958 (2.713)Scale of recovery programs 0.0283 (0.027) 0.0370 (0.036) 0.0446 (0.029) 0.0707 (0.038) *

Damage -0.0227 (0.011) ** -0.0119 (0.008) -0.0423 (0.011) *** -0.0199 (0.008) **

Damage*2011 dummy 0.0184 (0.013) 0.0079 (0.008) 0.0492 (0.013) *** 0.0264 (0.009) ***


Estimation method: cross section weighted general least squareNote: Numbers in parenthesis are cross section weighted standard errors*, **, *** represents 10%, 5%, and 1% significance respectively.

0.647 0.635 0.533 0.47920.758 19.773 13.291 10.927

98 98 98 98

0.680 0.669 0.576 0.528

2009 to 2015 2009 to 2015 2009 to 2015 2009 to 201514 (fatality=<1%) 14 (fatality=<1%) 14 (fatality=<1%) 14 (fatality=<1%)

Damaged house rate Flooded house rate Damaged house rate Flooded house rate

5 6 7 8In Migration In Migration Out Migration Out Migration

Dependent VariablesDamage variablePeriodNumer of cross sectionsNumber of observationsConstant 5.1545 (4.066) 5.4528 (3.431) -3.5817 (5.106) -2.4330 (4.544)Scale of recovery programs 0.0119 (0.016) 0.0293 (0.019) 0.0504 (0.021) ** 0.0754 (0.024) ***

Damage -0.0223 (0.009) ** -0.0295 (0.009) *** -0.0035 (0.012) -0.0182 (0.012)Damage*2011 dummy 0.0072 (0.01) 0.0101 (0.01) 0.0850 (0.014) *** 0.0827 (0.013) ***


1 2 3 4In Migration In Migration Out Migration Out Migration

14 (fatality>1%) 14 (fatality>1%) 14 (fatality>1%)14 (fatality>1%)

Damaged house rate Flooded house rate Damaged house rate Flooded house rate2009 to 2015 2009 to 2015 2009 to 2015 2009 to 2015

98 98 98 98

0.480 0.330 0.533 0.4670.427 0.262 0.485 0.4139.032 4.819 11.161 8.569

Scale of reconstruction accelerates out-migration, but not in-migration.

High fatality group

Low fatality group

Scale of reconstruction does not show significant impact on both in- and out-migration.


Conclusion and Policy implication • To avoid reconstruction paradox, providing more subsidy to the

affected people is a simple idea, • However, the option raise the overall cost of the recovery program,

and is inevitably challenged in terms of efficiency and equality. • With regard of efficiency, future tsunami risk is avoidable to some degree by

alternative countermeasures (e.g. evacuation) • With regard of inter-regional justice, investment for disaster reduction should

not concentrate on only Tohoku area. • We could not shorten the time for reconstruction significantly

because the delays in reconstruction were mainly because of the lack of construction capacity.

• Alternative recovery programs that enable resettlement at the original location is recommended.

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