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The Labor Force Survey, a large-scale government statistics, and the causal forest algorithm are used to estimate the group average treatment effect of the COVID-19 on the employment status for each month from January to June 2020. We find that (1) because of the seasonality in employment status at monthly level, whether we use January 2020 as the base month for comparison, as done in most of the studies or whether we use the same month last year as the base comparison group makes a large difference; (2) whether we include those who are absent from work among the employed or not makes a large difference in the measure of the impact of COVID-19 and its changes; (3) if we use the employment measure which does not include those who are absent from work among the employed, 25–30% among the employed are adversely affected and that 10% of the employed experienced more than 10% decline in employment probability in April, 2020; (4) those who are the most affected by the COVID-19 are those who are unemployed or work part-time in the hotel and restaurant industry and service occupations; (5) in addition, younger and female respondents are more affected than are older and male respondents; and (6) we observe no clear differences in the impacts of COVID-19 with respect to living location, education status, and firm size among the most affected.

AbstractSurvey experiments have shown mixed results about the effect of information provision on attitudes toward controversial policies. We argue that one reason is varied receptiveness to different modes of information. Prior research suggests that people selectively ignore factual, statistical information that contradicts prior beliefs but are more attentive to narrative information that describes individual experiences. We test this in the context of Japanese attitudes toward poverty relief programs, which are less popular than other welfare expenditures. Using a conjoint survey, we show that there is a "narrative premium": Respondents who are shown a narrative story about the plight of a single mother are more likely to support higher expenditures on poverty relief than those who are shown statistical information about the share of single parents living in poverty. This premium is particularly effective in strengthening the convictions of those who are already aware of levels of societal poverty.