8 Level of Disaster Resilience and Migration …
151
8.4 Discussion and Conclusion
This chapter develops a Japanese version of the Resilience Capacity Index (RCI),
which was the most promising sub-national level resilience index according to the
UNDP’s systematic review of resilience index maturity at municipality level. The
chapter then investigated the role of disaster resilience, measured by the Resilience
Capacity Index, in the migration behaviours of Japanese and non-Japanese residents.
The results of the empirical analysis found that (1) Even in the areas unaffected by
earthquakes, Japanese people are more likely to move-out from municipalities with
low resilience, while they are less likely to move-out from municipalities with high
resilience. (2) In the areas severely affected by earthquakes, municipalities with
low resilience suffered additional out-migration, while no additional out-migration
was observed in municipalities with middle or high resilience. (3) The analysis
of in-migration shows that having high resilience does not always benefit municipalities. People are less (more) likely to move-in to the municipalities with high
(low) resilience due to the high (low) within-community connectivity that excludes
newcomers. This is the negative side of community connectivity. Municipalities with
high resilience (community connectivity) tend to form a closed set of networks within
the community unconnected to larger society, making these municipalities isolated
from the outside world. (4) Foreigners do not respond to the level of resilience in
both earthquake-affected and non-affected municipalities. They behave as if there is
a separate community for non-Japanese people and do not seem to care about the
level of resilience among the Japanese community.
There are several limitations in this study. First, the Resilience Capacity Index is
the highest ranked sub-national level resilience index in terms of maturity according
to the UNDP’s systematic review in 2014. However, its relevance has not yet been
empirically verified. This chapter finds that municipalities with low resilience lose
additional residents, but municipalities with high resilience do not necessarily prevent
out-migration in areas affected by earthquakes. One interpretation of this is that the
RCI successfully identifies municipalities with no resilience against earthquakes, but
fails to identify municipalities highly resilient to earthquakes. There is a possibility
of underestimating the effect of having high resilience. Unfortunately, I cannot guarantee the relevance of the RCI. Future work should examine the relevance of the RCI
as a measurement of the level of resilience.
The second limitation is the robustness of the Resilience Capacity Index. In many
of the RCI’s 12 indicators, there are more than two candidate variables to potentially
measure each of the RCI’s indicators, and I need to choose one from these. The choice
of variable in each of the RCI’s 12 indicators certainly affects the value of RCI. For
income equality, when Gini coefficient is calculated, I assume that the average income
of the households with an annual income of more than 15 million yen is 20 million
yen. I checked the robustness of this assumption by calculating alternative Gini
coefficients by assuming that the average income of the household in this category
is 17.5 million or 22.5 million yen. For without disability, I also chose the number
of disability-related institutions per 1,000 population instead of the proportion of
151
8.4 Discussion and Conclusion
This chapter develops a Japanese version of the Resilience Capacity Index (RCI),
which was the most promising sub-national level resilience index according to the
UNDP’s systematic review of resilience index maturity at municipality level. The
chapter then investigated the role of disaster resilience, measured by the Resilience
Capacity Index, in the migration behaviours of Japanese and non-Japanese residents.
The results of the empirical analysis found that (1) Even in the areas unaffected by
earthquakes, Japanese people are more likely to move-out from municipalities with
low resilience, while they are less likely to move-out from municipalities with high
resilience. (2) In the areas severely affected by earthquakes, municipalities with
low resilience suffered additional out-migration, while no additional out-migration
was observed in municipalities with middle or high resilience. (3) The analysis
of in-migration shows that having high resilience does not always benefit municipalities. People are less (more) likely to move-in to the municipalities with high
(low) resilience due to the high (low) within-community connectivity that excludes
newcomers. This is the negative side of community connectivity. Municipalities with
high resilience (community connectivity) tend to form a closed set of networks within
the community unconnected to larger society, making these municipalities isolated
from the outside world. (4) Foreigners do not respond to the level of resilience in
both earthquake-affected and non-affected municipalities. They behave as if there is
a separate community for non-Japanese people and do not seem to care about the
level of resilience among the Japanese community.
There are several limitations in this study. First, the Resilience Capacity Index is
the highest ranked sub-national level resilience index in terms of maturity according
to the UNDP’s systematic review in 2014. However, its relevance has not yet been
empirically verified. This chapter finds that municipalities with low resilience lose
additional residents, but municipalities with high resilience do not necessarily prevent
out-migration in areas affected by earthquakes. One interpretation of this is that the
RCI successfully identifies municipalities with no resilience against earthquakes, but
fails to identify municipalities highly resilient to earthquakes. There is a possibility
of underestimating the effect of having high resilience. Unfortunately, I cannot guarantee the relevance of the RCI. Future work should examine the relevance of the RCI
as a measurement of the level of resilience.
The second limitation is the robustness of the Resilience Capacity Index. In many
of the RCI’s 12 indicators, there are more than two candidate variables to potentially
measure each of the RCI’s indicators, and I need to choose one from these. The choice
of variable in each of the RCI’s 12 indicators certainly affects the value of RCI. For
income equality, when Gini coefficient is calculated, I assume that the average income
of the households with an annual income of more than 15 million yen is 20 million
yen. I checked the robustness of this assumption by calculating alternative Gini
coefficients by assuming that the average income of the household in this category
is 17.5 million or 22.5 million yen. For without disability, I also chose the number
of disability-related institutions per 1,000 population instead of the proportion of