Underlying mechanisms: Impact of the PAJE reform on labor supply
| . | A: Switching From Part-time to Full-time . | |||
|---|---|---|---|---|
| . | Women . | Men . | ||
| . | (1) . | (2) . | (3) . | (4) . |
| Half Benefits | .005 | .004 | ||
| (.016) | (.009) | |||
| Zero Benefits | .006 | –.001 | ||
| (.008) | (.004) | |||
| Number of Observations | 1,273 | 2,022 | 1,295 | 2,154 |
| R2 | .003 | .002 | .002 | .003 |
| . | B: Having Multiple Jobs . | |||
| . | Women . | Men . | ||
| . | (1) . | (2) . | (3) . | (4) . |
| Half Benefits | .002 | .010 | ||
| (.020) | (.015) | |||
| Zero Benefits | –.002 | .000 | ||
| (.010) | (.009) | |||
| Number of Observations | 1,409 | 2,198 | 1,407 | 2,283 |
| R2 | .007 | .011 | .001 | .000 |
| . | C: Labor Market Participation . | |||
| . | Women . | Men . | ||
| . | (1) . | (2) . | (3) . | (4) . |
| Half Benefits | .011 | –.028 | ||
| (.041) | (.038) | |||
| Zero Benefits | .013 | –.005 | ||
| (.023) | (.017) | |||
| Number of Observations | 2,402 | 3,567 | 2,072 | 3,275 |
| R2 | .005 | .007 | .006 | .001 |
| . | D: Overtime (>35 hours/week) . | |||
| . | Women . | Men . | ||
| . | (1) . | (2) . | (3) . | (4) . |
| Half Benefits | .136* | .119** | ||
| (.056) | (.036) | |||
| Zero Benefits | .125** | .118** | ||
| (.035) | (.029) | |||
| Number of Observations | 1,405 | 2,194 | 1,399 | 2,275 |
| R2 | .010 | .040 | .010 | .035 |
| Year Fixed Effects | Yes | Yes | Yes | Yes |
| . | A: Switching From Part-time to Full-time . | |||
|---|---|---|---|---|
| . | Women . | Men . | ||
| . | (1) . | (2) . | (3) . | (4) . |
| Half Benefits | .005 | .004 | ||
| (.016) | (.009) | |||
| Zero Benefits | .006 | –.001 | ||
| (.008) | (.004) | |||
| Number of Observations | 1,273 | 2,022 | 1,295 | 2,154 |
| R2 | .003 | .002 | .002 | .003 |
| . | B: Having Multiple Jobs . | |||
| . | Women . | Men . | ||
| . | (1) . | (2) . | (3) . | (4) . |
| Half Benefits | .002 | .010 | ||
| (.020) | (.015) | |||
| Zero Benefits | –.002 | .000 | ||
| (.010) | (.009) | |||
| Number of Observations | 1,409 | 2,198 | 1,407 | 2,283 |
| R2 | .007 | .011 | .001 | .000 |
| . | C: Labor Market Participation . | |||
| . | Women . | Men . | ||
| . | (1) . | (2) . | (3) . | (4) . |
| Half Benefits | .011 | –.028 | ||
| (.041) | (.038) | |||
| Zero Benefits | .013 | –.005 | ||
| (.023) | (.017) | |||
| Number of Observations | 2,402 | 3,567 | 2,072 | 3,275 |
| R2 | .005 | .007 | .006 | .001 |
| . | D: Overtime (>35 hours/week) . | |||
| . | Women . | Men . | ||
| . | (1) . | (2) . | (3) . | (4) . |
| Half Benefits | .136* | .119** | ||
| (.056) | (.036) | |||
| Zero Benefits | .125** | .118** | ||
| (.035) | (.029) | |||
| Number of Observations | 1,405 | 2,194 | 1,399 | 2,275 |
| R2 | .010 | .040 | .010 | .035 |
| Year Fixed Effects | Yes | Yes | Yes | Yes |
Notes: Robust standard errors are shown in parentheses. Each cell presents a regression discontinuity (RD) estimator using individual-level data. Results are reported using a first-order polynomial control function. In panel A, the dependent variable is a dummy variable indicator equal to 1 for individuals who switch from part-time employment to full-time employment (between April of the year before and April of the year considered). In panel B, the dependent variable is a dummy variable indicator equal to 1 for individuals who reported having multiple jobs. In panel C, the dependent variable is a dummy variable indicator for labor market participation. In panel D, the dependent variable is a dummy variable indicator equal to 1 for individuals working more than 35 hours per week, which corresponds to the legal number of working hours. “Half benefits” is a dummy variable indicator equal to 1 for households that receive half the amount of PAJE benefits and equal to 0 for households that receive the full PAJE benefits. “Zero benefits” is a dummy variable indicator equal to 1 for households that receive zero PAJE benefits and equal to 0 for households that are eligible for full or half the PAJE benefits. Regressions also include a linear control function, the interaction term between the control function and the RD estimator, and a year fixed effect.
*p < .05; **p < .01