they are on average 33.6 years old, have an average monthly income of $3,087 and monthly credit card expenditures of $1,106.

As one might expect, the summary statistics shown in column (1) of Table 2 indicate that clients of the partner bank are not representative of the entire Malaysian population. On the one hand, the age and gender composition of our sample is not substantially different from the country average: data from the Malaysian Department of Statistics for 2020 indicate that 51.4% of the Malaysian population is male (compared to 62% in our sample of bank customers) with a mean age of 31.4 years (compared to 33.6 years in our sample). On the other hand, we find substantial income differences. According to data from the Salaries and Wages Survey Report,<sup>10</sup> the average Malaysian household earned $1,767 (compared to $3,087 in our sample).

However, Table 2 also shows that there is no indication of selection into treatment. Customers who participated in our experiment are similar to non-respondents. Columns (2) and (3) compare the characteristics of the 2,872 clients who answered our survey (reported in column (2)) to the sample of 3,126 clients who were invited to the survey but did not respond (column (3)). Comparing columns (2) to (3) indicates that although there are some statistically significant differences in average characteristics, none of these differences are meaningful in magnitude. For example, the average age is 33.28 years among survey respondents as compared to 33.88 among non-respondents. The average monthly income is $3,129 among survey respondents as compared to $3,050 among non-respondents. The average credit card expenditures are $1,135 among survey respondents and $1,080 among non-respondents. The one possible exception is gender, where we find that men are more represented among survey respondents (67%) than among non-respondents (57%).

Table 3 provides additional descriptive statistics, based on survey and administrative data, and presents a test of randomization balance. Column (1) is based on the sample of all 2,872 survey respondents. The summary statistics show that the respondents in this sample are highly educated (87% have a college degree), around half (54%) are married, and around 10% are selfemployed. In columns (2) through (4) of Table 3, we compare the baseline characteristics and expenditures of the three treatment groups. Column (5) reports p-values for the null hypothesis that these characteristics are equal across all three treatment groups. The results indicate that, consistent with successful random assignment, pre-treatment observables are balanced across treatment groups. As expected, all differences across treatment groups are economically small. The difference is statistically significant (p-value=0.09) for only one of the 11 characteristics reported in the table: the number of dependents. This result is within expectations, given that 1 out of every 10 differences are expected to be statistically significant at the 10% level simply by chance. We nonetheless follow standard practice and include the number of dependents as a control variable in all regressions.

> 10. Source: Malaysian Department of Statistics, 2017.

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