Consumption insurance against natural disasters: evidence from the Great Hanshin-Awaji (Kobe) earthquake
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<ul><li><p>This article was downloaded by: [University of Connecticut]On: 10 October 2014, At: 05:39Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK</p><p>Applied Economics LettersPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/rael20</p><p>Consumption insurance against natural disasters:evidence from the Great Hanshin-Awaji (Kobe)earthquakeYasuyuki Sawada a & Satoshi Shimizutani ba Faculty of Economics , University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033,Japanb Institute of Economic Research , Hitotsubashi University , 2-1 Naka, Kunitachi-shi, Tokyo186-8603, JapanPublished online: 18 Feb 2011.</p><p>To cite this article: Yasuyuki Sawada & Satoshi Shimizutani (2007) Consumption insurance against natural disasters:evidence from the Great Hanshin-Awaji (Kobe) earthquake, Applied Economics Letters, 14:4, 303-306, DOI:10.1080/13504850500447364</p><p>To link to this article: http://dx.doi.org/10.1080/13504850500447364</p><p>PLEASE SCROLL DOWN FOR ARTICLE</p><p>Taylor & Francis makes every effort to ensure the accuracy of all the information (the Content) containedin the publications on our platform. 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Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions</p><p>http://www.tandfonline.com/loi/rael20http://www.tandfonline.com/action/showCitFormats?doi=10.1080/13504850500447364http://dx.doi.org/10.1080/13504850500447364http://www.tandfonline.com/page/terms-and-conditionshttp://www.tandfonline.com/page/terms-and-conditions</p></li><li><p>Applied Economics Letters, 2007, 14, 303306</p><p>Consumption insurance against</p><p>natural disasters: evidence from the</p><p>Great Hanshin-Awaji (Kobe)</p><p>earthquake</p><p>Yasuyuki Sawadaa and Satoshi Shimizutanib,*</p><p>aFaculty of Economics, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku,</p><p>Tokyo 113-0033, JapanbInstitute of Economic Research, Hitotsubashi University, 2-1 Naka,</p><p>Kunitachi-shi, Tokyo 186-8603, Japan</p><p>We investigated whether people were insured against unexpected losses</p><p>caused by the Great Hanshin-Awaji (Kobe) earthquake in 1995 and found</p><p>that the full consumption insurance hypothesis was rejected overwhel-</p><p>mingly, suggesting the ineffectiveness of the formal/informal insurance</p><p>mechanisms against the earthquake.</p><p>I. Introduction</p><p>The Great Hanshin-Awaji (Kobe) earthquake, whichoccurred on 17 January 1995, induced one of thelargest economic damages recorded in history(Horwich, 2000; Sawada and Shimizutani, 2005). Asan unexpected exogenous event, an earthquakeprovides an unusual situation under which we cantest the full consumption insurance hypothesis byapplying the empirical strategy of Cochrane (1991)and Mace (1991) to our unique data on the earth-quake. Kohara et al. (2001,2002) rejected the fullconsumption insurance hypothesis against the earth-quake by employing region-specific slope dummiesfor the income change variables. However, thesevariables are not exogenous to a household, resultingin a possible estimation bias (Cochrane, 1991; Mace,1991). Our findings are less susceptible to econo-metric problems since we tested consumption reactionto direct shocks caused by the unexpected event,which cannot be affected by households. To the bestof our knowledge, our data is one of the few data sets</p><p>that allow us to test the hypothesis using directshocks caused by the earthquake. Section II estab-lishes the theoretical and econometric frameworks.Section III briefly describes the data and presents ourfindings.</p><p>II. The Framework</p><p>Under full risk sharing, we obtain the conditions bysolving a benevolent social planners problem tomaximize the weighted sum of peoples utilities(Cochrane, 1991; Mace, 1991):</p><p>u 0citu 0cit1</p><p> u0cjt</p><p>u 0cjt11</p><p>where u () is a concave instantaneous utility of ahousehold, c is the household consumption and i andj denote the i-th and j-th household, respectively.Suppose that the utility function takes the form</p><p>*Corresponding author. E-mail: email@example.com</p><p>Applied Economics Letters ISSN 13504851 print/ISSN 14664291 online 2007 Taylor & Francis 303http://www.tandf.co.uk/journalsDOI: 10.1080/13504850500447364</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Uni</p><p>vers</p><p>ity o</p><p>f C</p><p>onne</p><p>ctic</p><p>ut] </p><p>at 0</p><p>5:39</p><p> 10 </p><p>Oct</p><p>ober</p><p> 201</p><p>4 </p></li><li><p>of a constant absolute risk aversion function, i.e.</p><p>u(cit)(1/) exp(cit), we obtain1:</p><p>cit 1</p><p>N</p><p>XNj1</p><p>cjt</p><p> !2</p><p>where is a first-difference operator and N</p><p>represents the number of households in an insurance</p><p>network. Under full insurance, the idiosyncratic</p><p>household income changes should be absorbed by</p><p>all other members in the same insurance network, andthese shocks should not affect the changes in</p><p>consumption.Following Cochrane (1991) and Ravallion and</p><p>Chaudhuri (1997), our empirical specification to test</p><p>Equation 2 can be expressed as follows:</p><p>ci XKk1</p><p>kRak Si ui 3</p><p>where k is an identifier of regional insurance net-</p><p>works and Ra is a dummy variable, which is equal toone if the i-th household is located in the region k. We</p><p>utilize the area dummies for the variable Ra to control</p><p>the average change in consumption. The matrix, S,</p><p>comprises indicators of income and nonincome</p><p>shocks. The final is a well-behaved error term.The null hypothesis is that all the elements of a</p><p>vector, , in Equation 3 are jointly zero. Although we</p><p>cannot identify the direction of consumption changes</p><p>from our data, we can observe whether consumption</p><p>has changed and can also use this variable as a</p><p>dependent variable. Even in such cases, the rejection</p><p>of the null hypothesis should coincide with the</p><p>rejection of the necessary condition for the full</p><p>insurance model, while the failure to reject does not</p><p>necessarily support the full insurance model.We can construct a dummy variable, I c, which</p><p>takes the value of two for major changes, one for</p><p>minor changes, and zero otherwise. Accordingly, we</p><p>employ the ordered probit model to test Equation 3:</p><p>I ci 2 if ci is large Choice 1</p><p> 1 if ci is small Choice 2</p><p> 0 otherwise Choice 3:</p><p>III. Data and Empirical Results</p><p>We employed the micro-level data from Shinsai-go no</p><p>Kurashi no Henka kara Mita Shouhi Kouzou ni Tsuite</p><p>no Chousa Houkokusho (research report on changes in</p><p>lifestyles and consumption behaviour following the</p><p>disaster), a survey conducted in the Hyogo Prefecture</p><p>in October 1996 (Hyogo Prefecture, 1997). This survey</p><p>was completed by 1589 women aged above 30, who</p><p>Table 1. Basic statistics</p><p>Variables Mean</p><p>Consumption changes (before and after the earthquake)Dummy 1 for major changes in consumption behaviour 0.095Dummy 1 for minor changes in consumption behaviour 0.532</p><p>Income shocks caused by the earthquakeDummy 1 for positive income shock 0.063Dummy 1 for negative income shock 0.339</p><p>Nonincome shocks caused by the earthquakeDummy 1 for major damages to houses 0.129Dummy 1 for moderate damages to houses 0.175Dummy 1 for minor damages to houses 0.409Dummy 1 for major damages to household assets 0.079Dummy 1 for minor damages to household assets 0.707Dummy 1 for health-related shocks 0.177</p><p>Regional variablesDummy 1 for Higashinada-ku (default category) 0.125Dummy 1 for Kita-ku 0.170Dummy 1 for Suma-ku 0.145Dummy 1 for Akashi city 0.334Dummy 1 for Nishinomiya city 0.210Dummy 1 for other areas 0.016</p><p>1Our empirical framework will not change under the constant relative risk aversion (CRRA) utility.</p><p>304 Y. Sawada and S. Shimizutani</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Uni</p><p>vers</p><p>ity o</p><p>f C</p><p>onne</p><p>ctic</p><p>ut] </p><p>at 0</p><p>5:39</p><p> 10 </p><p>Oct</p><p>ober</p><p> 201</p><p>4 </p></li><li><p>were selected on the basis of a stratified randomsampling scheme in the six seriously affected areas.</p><p>Table 1 reports the summary statistics of thevariables. First, less than 10% of all respondentschanged their consumption substantially, and morethan half of them changed it slightly. Second, wehave two types of income shock variables adummy variable for a positive income shock causedby the earthquake (6.3% of all respondents) and adummy variable for a negative income shock(33.9%). Third, we obtain a set of nonincomeshock variables to record the details of the damages,including those to the house, the householdassets, and the health of the family members.2</p><p>Of the respondents, 71.3% and 78.6% incurreddamages to their houses and household assets,respectively.</p><p>Table 2 reports the results. First, households withlarger negative income shocks are more likely tochange their consumption behaviour; however, this isnot the case with positive income shocks. Second,households with larger nonincome shocks tend tochange their consumption. In both cases, the joint testoverwhelmingly rejects the necessary condition of thefull consumption model.</p><p>We conclude that formal and informal mutualinsurance mechanisms are incomplete against shocks</p><p>caused by the earthquake. Particularly, a consider-able magnitude of the marginal effects in relation tomajor or moderate damages to houses or householdassets is observed. This finding suggests that the lackof insurance for real estates and physical assets isparticularly serious. These findings are consistentwith the fact that only 3% of the total populationin the Hyogo Prefecture, where Kobe is located,was covered by the earthquake insurance inJanuary 1995.</p><p>Acknowledgement</p><p>We would like to thank the Quality of Life PolicyBureau, Cabinet Office, and the Hyogo Prefecture forproviding us with the valuable data set. The viewsexpressed in this study are our own.</p><p>References</p><p>Cochrane, J. H. (1991) A simple test of consumptioninsurance, Journal of Political Economy, 99, 95776.</p><p>Horwich, G. (2000) Economic lessons from Kobe earth-quake, Economic Development and Cultural Change,48, 52142.</p><p>Table 2. Tests of complete insurance (marginal effects)</p><p>(I) (II)</p><p>Explanatory variablesChoice 2 toChoice 1</p><p>Choice 3 toChoice 2</p><p>Choice 2 toChoice 1</p><p>Choice 3 toChoice 2</p><p>Income shocksDummy 1 for positive income shock 0.009 (0.022) 0.011 (0.026)Dummy 1 for negative income shock 0.072*** (0.014) 0.080*** (0.012)</p><p>Nonincome shocksDummy 1 for major damages to houses 0.082*** (0.028) 0.074*** (0.014)Dummy 1 for moderate damagesto houses</p><p>0.065*** (0.021) 0.069*** (0.015)</p><p>Dummy 1 for minor damages to houses 0.014 (0.012) 0.022 (0.019)Dummy 1 for major damages tohousehold assets</p><p>0.143*** (0.047) 0.076*** (0.011)</p><p>Dummy 1 for minor damages tohousehold assets</p><p>0.045*** (0.011) 0.085*** (0.026)</p><p>Dummy 1 for health-related shocks 0.040*** (0.015) 0.050*** (0.027)Wald test statistics for a null hypothesis under</p><p>which the coefficients on shock variables arejointly zero [p-value]</p><p>36.69*** (0.00) 78.07*** (0.00)</p><p>Sample size 1332 1289</p><p>Notes: See section II for a description of the dependent variable. The numbers within parentheses refer to the SE. We alsoincluded the regional dummy variables (not reported). We report the marginal effects, i.e. the change in the probability for adiscrete change in each shock. The symbol *** indicates statistical significance at the 1% level.</p><p>2 Shortly after the earthquake, the local governments conducted metrical surveys and issued formal certificates for damages tohouses, and the available information on damages is objective and accurate.</p><p>Consumption insurance against natural disasters 305</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Uni</p><p>vers</p><p>ity o</p><p>f C</p><p>onne</p><p>ctic</p><p>ut] </p><p>at 0</p><p>5:39</p><p> 10 </p><p>Oct</p><p>ober</p><p> 201</p><p>4 </p></li><li><p>Hyogo Prefecture (1997) Shinsai-go no Kurashi no HenkaKara Mita Shouhi Kouzou ni Tsuite no ChousaHoukokusho (Research report on changes in lifestylesand consumption behaviour following the disaster),Hyogo Ken.</p><p>Kohara, M., Ohtake, F. and Saito, M. (2001) A test of thefull insurance hypothesis: the case of Japan, mimeo,Hitotsubashi University.</p><p>Kohara, M., Ohtake, F. and Saito, M. (2002) A test of thefull insurance hypothesis: the case of Japan, Journal ofthe Japanese and International Economies, 16, 33552.</p><p>Mace, B. J. (1991) Full insurance in the presence ofaggregate uncertainty, Journal of Political Economy,99, 92896.</p><p>Ravallion, M. and Chaudhuri, S. (1997) Risk andinsurance in village India: comment, Econometrica,65, 17184.</p><p>Sawada, Y. and Shimizutani, S. (2005) Are peopleinsured against natural disasters? Evidence fromthe Great Hashin-Awaji (Kobe) earthquake, CIRJEDiscussion Paper F-314, Faculty of Economics,University of Tokyo.</p><p>306 Y. Sawada and S. Shimizutani</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Uni</p><p>vers</p><p>ity o</p><p>f C</p><p>onne</p><p>ctic</p><p>ut] </p><p>at 0</p><p>5:39</p><p> 10 </p><p>Oct</p><p>ober</p><p> 201</p><p>4 </p></li></ul>
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