152
H. Matsuura
people with a disability certificate, which can have a lot of missing values due to
the institutional background. For health insurance coverage, I used the number of
physicians per 1,000 population instead of the proportion of people covered by health
insurance because I do not want to assign 100% to all municipalities. I checked the
robustness of my results against the different choices of variables as much as possible,
but I am unable to check all of the combinations.
There is also an issue of missing observations especially in voter participation
rates, income equality, regional affordability and homeownership variables. I calculate RCI unless each of the three dimensions of RCI has missing values in more
than two variables. As a result, the RCI in some municipalities is calculated from
fewer variables than the others. Among all, RCI in four municipalities in Fukushima
(Idate-mura, Kawauch-mura, Hirono-machi and Naraha-machi) was calculated from
only seven indicators, while RCI in 278 municipalities was calculated from eight
indicators.
Third is the measurement of post-disaster recovery. In this study, I primarily focus
on in- and out-migration because population recovery is an essential part of the postdisaster recovery. However, in- and out-migration are not the only measures for the
post-disaster recovery. Various economic, infrastructure and transportation metrics
can be also used to measure the degree of post-disaster recovery (Aldrich 2012). I
leave this for future studies.
Fourth, I limited the sample up to 2016, which was before 2016 Kumamoto
Earthquake affected the in- and out-migration statistics. I also did not use information
on the number of deaths caused by natural disasters other than earthquakes due to
the limitation of data available. Again, I leave this to future studies.
Despite these limitations, the results of this chapter provide two important policy
implications regarding the role of resilience in the post-disaster recovery process.
First, reducing the number of municipalities with low resilience is an effective
strategy to mitigate a post-disaster population decline. By doing so, I can avoid the
negative side of high within-community connectivity associated with high resilience.
Second, foreigners behave as if they have different communities from the local
communities in which I measure the level of resilience using the Resilience Capacity
Index. This is the issue of foreigner integration and community inclusion. Foreigners
with a lack of access to information and resources are disproportionately affected by
disasters. Fortunately, Goal 11 of the SDGs states the promotion of inclusive societies. The community inclusion of foreigners can substantially develop the resilience
of all members in the community in the face of disasters.
Appendix: Ranking of Municipalities Based
on the Resilience Capacity Index
H. Matsuura
people with a disability certificate, which can have a lot of missing values due to
the institutional background. For health insurance coverage, I used the number of
physicians per 1,000 population instead of the proportion of people covered by health
insurance because I do not want to assign 100% to all municipalities. I checked the
robustness of my results against the different choices of variables as much as possible,
but I am unable to check all of the combinations.
There is also an issue of missing observations especially in voter participation
rates, income equality, regional affordability and homeownership variables. I calculate RCI unless each of the three dimensions of RCI has missing values in more
than two variables. As a result, the RCI in some municipalities is calculated from
fewer variables than the others. Among all, RCI in four municipalities in Fukushima
(Idate-mura, Kawauch-mura, Hirono-machi and Naraha-machi) was calculated from
only seven indicators, while RCI in 278 municipalities was calculated from eight
indicators.
Third is the measurement of post-disaster recovery. In this study, I primarily focus
on in- and out-migration because population recovery is an essential part of the postdisaster recovery. However, in- and out-migration are not the only measures for the
post-disaster recovery. Various economic, infrastructure and transportation metrics
can be also used to measure the degree of post-disaster recovery (Aldrich 2012). I
leave this for future studies.
Fourth, I limited the sample up to 2016, which was before 2016 Kumamoto
Earthquake affected the in- and out-migration statistics. I also did not use information
on the number of deaths caused by natural disasters other than earthquakes due to
the limitation of data available. Again, I leave this to future studies.
Despite these limitations, the results of this chapter provide two important policy
implications regarding the role of resilience in the post-disaster recovery process.
First, reducing the number of municipalities with low resilience is an effective
strategy to mitigate a post-disaster population decline. By doing so, I can avoid the
negative side of high within-community connectivity associated with high resilience.
Second, foreigners behave as if they have different communities from the local
communities in which I measure the level of resilience using the Resilience Capacity
Index. This is the issue of foreigner integration and community inclusion. Foreigners
with a lack of access to information and resources are disproportionately affected by
disasters. Fortunately, Goal 11 of the SDGs states the promotion of inclusive societies. The community inclusion of foreigners can substantially develop the resilience
of all members in the community in the face of disasters.
Appendix: Ranking of Municipalities Based
on the Resilience Capacity Index