Table 4. Explaining Heterogeneity in Effect Sizes for Subsamples by Type of Financial Behavior and Target Group

||(1)<br>Borrow|(2)<br>Borrow<br>×<br>low inc.<br>clients|(3)<br>Save|(4)<br>Save<br>×<br>low inc.<br>clients|(5)<br>Budget|(6)<br>Budget<br>×<br>low inc.<br>clients|
|---|---|---|---|---|---|---|
|RCT|-0.136***<br>(0.022)|-0.100***<br>(0.026)|-0.002<br>(0.045)|-0.035<br>(0.058)|||
|TOT|<br>0.089**|<br>0.106**|<br>0.090|<br>0.074|||
||(0.033)|(0.039)|(0.054)|(0.079)|||
|Delay|-0.000<br>(0.000)|-0.000*<br>(0.000)|0.000<br>(0.000)|-0.000<br>(0.000)|-0.001<br>(0.002)|-0.019<br>(0.012)|
|1/SE|<br>0.000|<br>0.001**|<br>-0.000|<br>0.000|<br>-0.003*|<br>-0.007|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.002)|(0.005)|
|Intensity / week|<br>0.003**<br>(0.001)|<br>0.003**<br>(0.001)|<br>0.003*<br>(0.002)|<br>0.004**<br>(0.002)|<br>0.037<br>(0.031)|<br>0.595*<br>(0.308)|
|Duration|<br>-0.000<br>(0.000)|<br>-0.000<br>(0.000)|<br>-0.001<br>(0.001)|<br>0.000<br>(0.001)|<br>-0.000<br>(0.003)|<br>0.017<br>(0.014)|
|Low income clients|<br>-0.043**<br>(0.019)||<br>-0.050**<br>(0.022)||||
|Years of schooling|<br>-0.023***<br>(0.006)|-0.023***<br>(0.008)|<br>-0.018***<br>(0.007)|-0.011<br>(0.011)|-0.020*<br>(0.011)|0.017<br>(0.022)|
|Low/lower-mid. inc. econ.|-0.178***<br>(0.052)|-0.199***<br>(0.067)|-0.142***<br>(0.045)|-0.102<br>(0.066)|||
|Mandatory|-0.069**|-0.120***|-0.025|-0.010|||
||(0.032)|(0.039)|(0.031)|(0.049)|||
|Teachable moment|<br>0.100***<br>(0.025)|<br>0.087***<br>(0.026)|<br>0.084**<br>(0.036)|<br>0.114*<br>(0.065)|||
|Constant|<br>0.375***|<br>0.326**|<br>0.305***|<br>0.147|0.361**|-0.685|
||(0.087)|(0.114)|(0.091)|(0.165)|(0.134)|(0.524)|
|R<sup>2</sup>|0.473|0.394|0.194|0.147|0.206|0.359|
|n (Studies)|32|20|67|31|20|11|
|n(Effect sizes)|100|73|166|91|40|27|

Notes: Non-standardized coefficients from OLS regressions with clustered standard errors at the study-level in parentheses. We only include right hand side variables where differential information from at least two studies is available in the regressions. ***, ** and * denote significance at the one percent, five percent and ten percent level. Source: Authors’ analysis based on data sources discussed in the text.

Turning to the subsample of 20 studies on budgeting and record keeping behavior (column 5 of table 4), on which financial education yields the largest effects, we find that intensity is not significantly related to effect size. Additionally, all of the other signs and relative magnitudes of the coefficients remain similar to our benchmark estimation; however, with increased standard errors due to only 20 studies and 40 observations. Completing this exercise, we now examine determinants of treatment effects for the subsample of studies reporting on budgeting outcomes for low-income clients (column 6 of table 4). There are 11 studies in this subsample reporting 27 estimates. Again, qualitative results are similar and intensity now, again, is a marginally significant predictor of effect sizes on budgeting behavior.

Overall, we find that the positive effects from increased intensity appear to be driven by interventions focused on (retirement-) saving and borrowing behavior, whereas the timing and voluntary participation matter, especially for borrowing behavior. Thus, the financial behavior that is 21