Silviase/jgov_v1.4_full_ann huggingface dataset:
$ t+1 $ , possible risk-coping strategies to a household is to reduce consumption, to dissave, to receive transfer income, or to borrow additional amounts. Formally, the roles of four different coping strategies are represented by the following partial derivatives based on equation (2):

$$ \frac{\partial\lambda_{it}}{\partial C_{it}}>0,\frac{\partial\lambda_{it}}{\partial A_{it}}<0,\frac{\partial\lambda_{it}}{\partial y_{it}}<0,\frac{\partial\lambda_{it}}{\partial z_{it}}<0. $$

In the empirical analyses, we investigate the responses of these coping strategies against various negative shocks caused by the earthquake. Since the adoptions of coping strategies are observed as discrete variables, we estimate the following binary dependent variable models separately for different coping strategies. Assuming an i.i.d. unobserved stochastic element, $ \varepsilon $ , we have the following reduced-form linear coping function for j-th risk coping strategy:

$$ P_{j i}{}^{*}=S_{i}\theta+H_{i}\beta+\varepsilon_{j i}. $$

Note that S represents a matrix of household-specific shock variables generated by the earthquake and that H is a matrix of household characteristics. We do not directly observe the intensity of risk-coping strategy, $ P^{*} $ . Hence, our dependent variable is whether a household adopted a particular coping device against the earthquake, which can be represented by a discrete variable, p:

$$ \begin{aligned}&p_{ji}=1if P_{ji}*>0\\&p_{ji}=0otherwise.\\ \end{aligned} $$

Note that $ \operatorname{Prob}(P^{*}>0)=\operatorname{Prob}(\varepsilon>-S\theta-H\beta) $ and $ \operatorname{Prob}(P^{*}\leq0)=\operatorname{Prob}(\varepsilon\leq-S\theta-H\beta) $ . We will estimate the model of equation (5) by using probit model, i.e., under an assumption of normality of the error term.

### 3. The Data Set and Empirical Results

The data set we employ in this paper is the survey data on consumer life after the earthquake, collected by Hyogo Prefecture (“Shinsai-go no Kurashi no Henka kara Mita Shouhi Kouzou ni tsuite no chousa Houkokusho (Research Report on Changes in Lifestyles and Consumption Behavior Following Disasters)” released on March 25 $ ^{th} $ , 1997 by Hyogo-ken Seikatsu Bunka-bu Seikatsu Souzou-ka Shouhi Seikatsu Taisaku-shitsu (Hyogo Prefecture,
Department of Livelihood and Culture, Livelihood Creation Section, Office for Livelihood Policy).

The survey was conducted in October 1996 in the six districts seriously hit by the earthquake. The survey was completed by 1,589 women who were selected, based on a stratified random sampling scheme, from all women above age of 30 in Higashinada-ku, Kita-ku and Suma-ku of Kobe city, Akashi city, and Nishinomiya city.

The definitions and summary statistics of the variables are given in Tables 1. The first key variable is a binary variable which takes one if a household reported that it faced unexpected increase in expenditure to cope with the earthquake and zero otherwise. According to the response, more than 80% of household reported that they were obliged to manage the unexpected increase in their expenditures. With respect to the rest of the variables, Table 1 reports the summary statistics for those people whose expenditures are disrupted by the earthquake.

Throughout the estimation of different risk-coping models, we employ binary dependent variables of four coping strategies, i.e., reduction in the cost of living, dissaving, borrowing, and receiving public and private transfers $ ^{7} $ .

We then have three sets of independent variables. The first block of variables is composed of the possible causes of the increase in expenditure. The surveys asked the respondents in detail about damages caused by the earthquake, such as damages to their house, household assets, health of the family members, and their connection to public utilities. It is notable that 42 percent and 78 percent of the respondents suffered from major damages to their house and household assets, respectively. Moreover, more than half the people experienced a disconnection of public utilities for more than one month. These figures reveal the seriousness of the economic loss caused by the earthquake.

The second block is composed of household characteristics. First, the ownership rate of housing is around 72 percent before the earthquake, where around 40 percent of those who own a house still held outstanding housing loans. The average age of the respondent is 51 years old; the majority are high school graduates or lower. There were 0.5 percent of the respondents who did not answer their education level properly. We suspect that their education level is minimal and the results reflect a stigma attached to the low level of education. Most of the respondents live with their children, and the joint-family co-residence rate is around 20 percent. On the other hand, only about 4 percent of the surveyed respondents were single. Household income was surveyed by
category. The median annual household income is somewhere between 6 million and 8 million yen.

Finally, to control for unobserved heterogeneity generated by the difference in the effects of the earthquake, we include the district-specific dummy variables. Since, among other things, the effects of the earthquake are determined by the proximity to the focus of it, we believe that inclusion of the district dummies are a reasonable choice.

## Estimation Results

First of all, we estimate a probit model of the determinants of the expenditure increase to investigate the sources of expenditure shocks. The estimated results are reported in Table 2. According to this table, it is clear that the major expenditure shocks are generated by damages to the house and household assets. Interestingly, the level of education is negatively related with the expenditure increase. This finding suggests that less-educated people are more vulnerable against the natural disasters.

Table 3 summarizes the estimation results of probit models of determinants of different coping strategies. These results can be summarized in the following four findings. First, the columns for expenditure reallocation and borrowing reveal that, facing major or minor damage to their housing, people primarily coped with it by borrowing, while expenditure reallocation was not effective coping means. The last column indicates that obtaining transfers acted to some extent as an effective coping device against housing damage.

Second, according to the first column for the expenditure reallocation, it seems that those who owned a house without outstanding housing loans before the earthquake could borrow money sufficiently and, therefore, they did not need to reallocate their expenditures. The borrowing column indicates that borrowing was possible especially for those who had their own house before the earthquake. This suggests the importance of collateral to getting a loan after the earthquake. Moreover, educated respondents could effectively adopt borrowing as a coping strategy, which is consistent with the previous findings of Horioka and Kohara (1999) and Sawada, Ii, and Nawata (2003) that educated people are less likely to face credit constraints.

The third finding is from the second column for dissaving. According to this column, major or minor shocks to households' assets are coped with by means of dissaving. Interestingly, age has a positive impact on the probability of adopting dissaving. This might be a reflection of the life-cycle effects. Under a finite horizon, the optimal amount of precautionary saving is a negative function of the length of the remaining life [Caballero (1990)]. The positive coefficient we observe on the age variable might capture this effect—older people are more willing to dissave to cope.
with the shock than younger people, who still have long lives ahead of them.

Finally, as mentioned already, receiving a transfer is an effective coping means against major housing damage. Moreover, those who had outstanding housing loans before the earthquake have higher probabilities to receive transfers from outside. Yet, co-residence decreased the probability of coping via transfer significantly, suggesting the importance of ex ante intra-family arrangements as a self-insurance device through, for example, migration to mitigate risk spatially.

### 4. Concluding Remarks

In this paper, we examined how people cope with unexpected resource losses caused by a sudden earthquake occurred in Kobe in 1995 by employing a unique household-level data shortly after the earthquake. We found that the coping means are specific to the nature of shocks caused by the earthquake. For example, borrowing was extensively used to recover the damages to housing, while dissavings were utilized to compensate for the loss to household assets.

Our analysis in this paper contains important policy implications in the preparation of well-designed social safety nets against future natural disasters. The economic losses caused by a huge earthquake such as the Great Hanshin-Awaji earthquake are too large for the government to support effectively. Hence, the government’s ex-post support should be one that facilitates the self-insurance of the victims of the disaster. Our empirical results suggest that provisions of the subsidized loan programs to the victims can be a good example. Such interventions are not likely to create the moral hazard problems that Horwich (2000) pointed out, since they are not direct resource transfers to the victims.
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Table 1 Descriptive Statistics of the Variables Used

Variable Description	Variable Name	Mean (Standard Deviation)
Expenditure shock
Dummy=1 if the household faces an increase in its expenditure because of earthquake	exp_inc	0.803
Coping Variables
Dummy=1 if expenditure reallocations were the most important coping means	copebyexp	0.250
Dummy=1 if dissaving was the most important coping means	copebysav	0.537
Dummy=1 if borrowing was the most important coping means	copebybor	0.096
Dummy=1 if receiving transfers was the most important coping means	copebytra	0.116
Shock Variables
Dummy=1 if there was major damage to the house	lhshock	0.426
Dummy=1 if there was minor damage to the house	shshock	0.431
Dummy=1 if there was major damage to household assets	lashock	0.094
Dummy=1 if there was minor damage to household assets	sashock	0.773
Dummy=1 if there were healing-related shocks to the family	hlshock	0.213
Dummy=1 if there was utility disconnection for more than one month.	utshock	0.536
Household Characteristics
Dummy=1 if had own house before the earthquake	ownh_b	0.718
Dummy=1 if had outstanding housing loans before the earthquake	hloan_b	0.319
Age of the respondent	age	51.190 (10.842)
Dummy=1 if the respondent did not report education level	(default category)	0.005
Dummy=1 if the highest education of the respondent is high school or lower	midhigh	0.615
Dummy=1 if the highest education of the respondent is higher than high school	higher	0.380
Dummy=1 if the respondent is single	single	0.042
Dummy=1 if the respondent lives with children	child	0.623
Dummy=1 if the respondent lives with parents or grandchildren	cores	0.198
Dummy=1 if the household's annual income is lower than 2 million yen (default).	(default category)	0.061
Dummy=1 if the household's annual income is between 2 million and 4 million yen.	_Income_2	0.211
Dummy=1 if the household's annual income is between 4 million and 6 million yen.	_Income_3	0.219
Dummy=1 if the household's annual income is between 6 million and 8 million yen.	_Income_4	0.185
Dummy=1 if the household's annual income is between 8 million and 10 million yen.	_Income_5	0.150
Dummy=1 if the household's annual income is between 10 million and 12 million yen.	_Income_6	0.083
Dummy=1 if the household's annual income is between 12 million and 14 million yen.	_Income_7	0.039
Dummy=1 if the household's annual income is higher than 14 million yen.	_Income_8	0.052
Regional Characteristics
Dummy=1 if Higashinada-ku (default)	(default category)	0.163
Dummy=1 if Kita-ku	_Iarea_2	0.136
Dummy=1 if Suma-ku	_Iarea_3	0.136
Dummy=1 if Akashi city	_Iarea_4	0.370
Dummy=1 if Nishinomiya city	_Iarea_5	0.181
Dummy=1 if other area	_Iarea_6	0.014

Note) Numbers in parentheses are standard deviation.
Table 2

The Sources of Expenditure Shocks

Dependent variable: Dummy=1 if the household faces an increase in expenditure because of the earthquake

Explanatory Variables	Variable Name	dF/dx	(Standard Error)
Dummy=1 if there was major damage to the house	lhshock	0.238	(0.020)****
Dummy=1 if there was minor damage to the house	shshock	0.168	(0.021)***
Dummy=1 if there was major damage to household assets	lashock	0.098	(0.027)**
Dummy=1 if there was minor damage to household assets	sashock	0.136	(0.029)***
Dummy=1 if there were healing-related shocks to the family	hlshock	0.030	(0.027)
Dummy=1 if there was utility disconnection for more than one month.	utshock	0.007	(0.020)
Dummy=1 if had own house before the earthquake	ownh_b	0.034	(0.029)
Dummy=1 if had outstanding housing loans before the earthquake	hloan_b	0.032	(0.024)
Age of the respondent	age	-0.001	(0.001)
Dummy=1 if the highest education of the respondent is high school or lower	midhigh	-0.786	(0.048)***
Dummy=1 if the highest education of the respondent is higher than high school	higher	-0.985	(0.010)***
Dummy=1 if the respondent is single	single	-0.012	(0.051)
Dummy=1 if the respondent lives with children	child	0.012	(0.023)
Dummy=1 if the respondent lives with parents or grandchildren	cores	-0.019	(0.026)
Dummy=1 if the household's annual income is between 2 million and 4 million yen.	_Inco~2	0.002	(0.043)
Dummy=1 if the household's annual income is between 4 million and 6 million yen.	_Inco~3	0.020	(0.040)
Dummy=1 if the household's annual income is between 6 million and 8 million yen.	_Inco~4	-0.003	(0.047)
Dummy=1 if the household's annual income is between 8 million and 10 million yen.	_Inco~5	0.031	(0.041)
Dummy=1 if the household's annual income is between 10 million and 12 million yen.	_Inco~6	0.013	(0.048)
Dummy=1 if the household's annual income is between 12 million and 14 million yen.	_Inco~7	0.034	(0.053)
Dummy=1 if the household's annual income is higher than 14 million yen.	_Inco~8	0.095	(0.027)**
Dummy=1 if Kita-ku	_Iarea_2	-0.072	(0.048)
Dummy=1 if Suma-ku	_Iarea_3	-0.057	(0.049)
Dummy=1 if Akashi city	_Iarea_4	0.038	(0.034)
Dummy=1 if Nishinomiya city	_Iarea_5	-0.042	(0.043)
Dummy=1 if other area	_Iarea_6	-0.122	(0.141)

Sample size	1279

Note 1) In this table, “dF/dx” reports the change in the probability for a marginal change in continuous independent variable and for a discrete change of dummy independent variable from 0 to 1, evaluated at the mean independent variables.

Note 2) Huber-White consistent robust standard errors are employed. The symbols *, **, and *** indicate statistical significance at 10%, 5%, and 1% levels, respectively.
Explanatory Variables	Variable Name	Expenditure Reallocation	Dissaving	Borrowing	Receiving Transfers
dF/dx (Std. Err.)	dF/dx (Std. Err.)	dF/dx (Std. Err.)	dF/dx (Std. Err.)
Dummy=1 if there was major damage to the house	lhshock	-0.237 (0.054)***	0.007 (0.077)	0.214 (0.068)***	0.092 (0.047)**
Dummy=1 if there was minor damage to the house	shshock	-0.068 (0.051)	0.014 (0.071)	0.154 (0.061)***	-0.013 (0.040)
Dummy=1 if there was major damage to household assets	Lashock	-0.036 (0.089)	0.177 (0.096)*	-0.037 (0.027)	-0.048 (0.029)
Dummy=1 if there was minor damage to household assets	sashock	-0.025 (0.060)	0.124 (0.072)*	-0.040 (0.038)	-0.046 (0.049)
Dummy=1 if there were healing-related shocks to the family	hlshock	-0.012 (0.048)	0.017 (0.058)	-0.014 (0.023)	0.015 (0.031)
Dummy=1 if there was utility disconnection for more than one month.	utshock	0.017 (0.040)	0.104 (0.048)**	-0.062 (0.023)***	-0.024 (0.022)
Dummy=1 if had own house before the earthquake	ownh_b	-0.098 (0.057)*	0.064 (0.064)	0.050 (0.021)**	-0.040 (0.039)
Dummy=1 if had outstanding housing loans before the earthquake	hloan_b	0.086 (0.052)*	-0.103 (0.059)**	-0.020 (0.023)	0.052 (0.034)*
Age of the respondent	Age	-0.007 (0.002)***	0.009 (0.003)***	-0.001 (0.001)	-0.001 (0.001)
Dummy=1 if the highest education of the respondent is high school or lower	midhigh	-0.145 (0.321)	0.268 (0.344)	0.636 (0.112)***	-0.195 (0.134)*
Dummy=1 if the highest education of the respondent is higher than high school	higher	-0.158 (0.268)	0.244 (0.335)	0.923 (0.062)***	-0.123 (0.077)
Dummy=1 if the respondent is single	single	-0.049 (0.104)	0.070 (0.133)	-0.006 (0.062)	-0.016 (0.054)
Dummy=1 if the respondent lives with children	child	0.039 (0.044)	-0.117 (0.054)**	0.043 (0.022)*	0.006 (0.026)
Dummy=1 if the respondent lives with parents or grandchildren	cores	-0.020 (0.051)	0.017 (0.060)	0.051 (0.033)*	-0.051 (0.023)*
Dummy=1 if the household's annual income is between 2 million and 4 million yen.	_Inco~2	-0.114 (0.079)	0.193 (0.106)	-0.046 (0.030)	0.003 (0.058)
Dummy=1 if the household's annual income is between 4 million and 6 million yen.	_Inco~3	-0.105 (0.081)	0.202 (0.108) $ ^{*} $	-0.056 (0.028)	-0.009 (0.056)
Dummy=1 if the household's annual income is between 6 million and 8 million yen.	_Inco~4	-0.081 (0.087)	0.074 (0.124) $ ^{*} $	-0.052 (0.028)	0.081 (0.090)
Dummy=1 if the household's annual income is between 8 million and 10 million yen.	_Inco~5	-0.115 (0.078)	0.192 (0.112)	-0.039 (0.031)	-0.006 (0.061)
Dummy=1 if the household's annual income is between 10 million and 12 million yen.	_Inco~6	-0.162 (0.059) $ ^{*} $	0.223 (0.115) $ ^{*} $	-0.037 (0.032)	0.045 (0.091)
Dummy=1 if the household's annual income is between 12 million and 14 million yen.	_Inco~7	-0.139 (0.073)	0.298 (0.100) $ ^{**} $	-0.061 (0.016) $ ^{*} $	-0.017 (0.067)
Dummy=1 if the household's annual income is higher than 14 million yen.	_Inco~8	-0.173 (0.052) $ ^{**} $	0.197 (0.128)	-0.037 (0.033)	0.125 (0.137)
Dummy=1 if Kita-ku	_Iarea_2	0.191 (0.091) $ ^{**} $	-0.054 (0.091)	-0.008 (0.037)	-0.073 (0.022) $ ^{**} $
Dummy=1 if Suma-ku	_Iarea_3	0.036 (0.081)	0.063 (0.086)	-0.015 (0.033)	-0.043 (0.029)
Dummy=1 if Akashi city	_Iarea_4	0.015 (0.059)	0.044 (0.070)	-0.009 (0.027)	-0.022 (0.028)
Dummy=1 if Nishinomiya city	_Iarea_5	-0.007 (0.070)	0.107 (0.081)	0.012 (0.039)	-0.063 (0.023) $ ^{**} $
Dummy=1 if other area	_Iarea_6	-0.024 (0.201)	0.134 (0.183)	-0.020 (0.057)	-0.037 (0.050)

Sample size	513	513	513	513

Note 1) In this table, “dF/dx” reports the change in the probability for a marginal change in continuous independent variable and for a discrete change of dummy independent variable from 0 to 1, evaluated at the mean independent variables.

Note 2) Huber-White consistent robust standard errors are employed. The symbols *, **, and *** indicate statistical significance at 10%, 5%, and 1% levels, respectively.