Effects of the Great East Japan Earthquake on Subjective Well-Being

Tuesday, July 15, 2014: 10:30 AM
Room: Booth 48
Oral Presentation
Akiko KAMESAKA , Aoyama Gakuin University, Japan
Takuya ISHINO , Kanazawa Seiryo University, Japan
Toshiya MURAI , Kyoto University, Japan
Masao OGAKI , Keio University, Japan
We study changes in Japanese people’s subjective well-being (happiness) and feelings of altruim before and after the Great East Japan Earthquake of March 2011. We use a panel data set compiled by a group of researchers mainly from Keio University. Although the questionnaire is large, we focus on a question about people’s altruism. We are interested in altruism because, according to a Japanese Statistics Bureau report on expenditure by Japanese households, charitable donations increased by over 850 percent in March 2011 compared to one year earlier.

Using this large panel survey consisting of responses from over 4000 households all over Japan, we found that many Japanese people reported more feelings of altruism following the earthquake, even in the most affected areas; this is consistent with the rise in charitable giving. We also found that a large number of people reported an increase in happiness after the earthquake, in fact, as the number who reported a drop in happiness. An interpretation of this finding is suggested by a recent experiment by Dunn et al., who find that spending money on others promotes happiness; according to this story, many Japanese people became more altruistic after the earthquake, inducing them to make charitable donations, which in turn made them happier.

We are interested in seeing how changes in altruism affect changes in happiness. However, both variables are subjective, so their measurement errors are likely to be correlated. Therefore, we use a two-step procedure, first identifying the effect of altruism on an objective variable, charitable giving, and then measuring the effect of charitable giving on happiness. In each step of the analysis, we run a two-stage logit regression, which controls for reverse causality. This analysis, which deals effectively with the aforementioned problem of correlated measurement errors, yields results that are consistent with our story.