Table 4: Employment Effects of the Tax Cut by Subgroups

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
||All frms|Employment<br>Low TFP|High TFP|All frms|Elasticity<br>Low TFP|High TFP|
|**Panel A: By wage**|||||||
|Jobs paying at most 1.5_×_minimum wage|0.0039<sup>_∗∗∗_</sup>|0.0032<sup>_∗∗∗_</sup>|0.0007<sup>_∗∗∗_</sup>|-0.43|-0.48|-0.31|
||[0.0005]|[0.0004]|[0.0002]|[0.06]|[0.06]|[0.09]|
||_{_35%_}_|_{_27%_}_|_{_8%_}_||||
||_⟨_0.1239_⟩_|_⟨_0.0922_⟩_|_⟨_0.0316_⟩_||||
|Jobs paying above 1.5_×_minimum wage|0.0016<sup>_∗∗∗_</sup>|0.0020<sup>_∗∗∗_</sup>|-0.0004|-0.17|-0.55|0.07|
||[0.0005]|[0.0003]|[0.0005]|[0.05]|[0.08]|[0.09]|
||_{_65%_}_|_{_24%_}_|_{_40%_}_||||
||_⟨_0.2221_⟩_|_⟨_0.0748_⟩_|_⟨_0.1473_⟩_||||
|**Panel B: By occupation**|||||||
|Low-paid occupations|0.0028<sup>_∗∗∗_</sup>|0.0030<sup>_∗∗∗_</sup>|-0.0001|-0.29|-0.55|0.03|
||[0.0004]|[0.0003]|[0.0002]|[0.04]|[0.05]|[0.05]|
||_{_51%_}_|_{_28%_}_|_{_24%_}_||||
||_⟨_0.1716_⟩_|_⟨_0.0956_⟩_|_⟨_0.0761_⟩_||||
|High-paid occupations|0.0024<sup>_∗∗∗_</sup>|0.0023<sup>_∗∗∗_</sup>|0.0001|-0.25|-0.47|-0.02|
||[0.0006]|[0.0003]|[0.0005]|[0.06]|[0.06]|[0.11]|
||_{_49%_}_|_{_19%_}_|_{_30%_}_||||
||_⟨_0.1743_⟩_|_⟨_0.0716_⟩_|_⟨_0.1028_⟩_||||
|**Panel C: By education**|||||||
|Primary and lower-secondary education jobs|0.0038<sup>_∗∗∗_</sup>|0.0037<sup>_∗∗∗_</sup>|-0.0001|-0.29|-0.54|0.02|
||[0.0005]|[0.0004]|[0.0003]|[0.04]|[0.06]|[0.05]|
||_{_70%_}_|_{_37%_}_|_{_33%_}_||||
||_⟨_0.2354_⟩_|_⟨_0.1140_⟩_|_⟨_0.1214_⟩_||||
|Upper-secondary education jobs|-0.0000|0.0004<sup>_∗∗_</sup>|-0.0004|0.00|-0.22|0.34|
||[0.0003]|[0.0002]|[0.0003]|[0.10]|[0.11]|[0.26]|
||_{_16%_}_|_{_8%_}_|_{_8%_}_||||
||_⟨_0.0547_⟩_|_⟨_0.0256_⟩_|_⟨_0.0291_⟩_||||
|Tertiary education jobs|0.0013<sup>_∗∗∗_</sup>|0.0011<sup>_∗∗∗_</sup>|0.0001|-0.54|-0.69|-0.15|
||[0.0003]|[0.0002]|[0.0003]|[0.12]|[0.13]|[0.44]|
||_{_14%_}_|_{_7%_}_|_{_7%_}_||||
||_⟨_0.0528_⟩_|_⟨_0.0258_⟩_|_⟨_0.0270_⟩_||||
|_∗p <_0_._1, _∗∗p <_0_._05, _∗∗∗p <_0_._01|||||||

_Note_ : Table shows difference-in-differences estimates of the impact of the payroll tax cut on private sector employment based on estimating equation (9) separately for various subgroups. Panel A considers employment in jobs paying above vs. below 150% of the minimum wage. Panel B considers employment in occupations with above- vs. below-median average wages in 2012. Panel C considers employment in occupations requiring different levels of education, defined as the modal level of education in the Labor Force Survey in 2012. In each case we estimate the regression equation (9) using employment in a given subgroup (job or occupation) and firm type (all firms in column 1, below-median TFP firms in column 2, and above-median TFP firms in column 3) as the outcome variable. In curly brackets we report the subgroup share within each panel. In angle brackets we report the mean of the outcome variable in May 2012 – the probability of being employed in a given subgroup and firm type. Columns (1)-(3) report the difference-in-differences estimate that compares the change in employment among the 55 to 57 age group that was affected by the payroll tax cut with the change in employment among the 52 to 54 age group that was not affected by the tax cut. In Columns (4)-(6) we calculate the employment elasticity with respect to the wage for all firms (column 4) and separately for below-median (column 5) and above-median (column 6) TFP firms. We obtain percent change in employment by dividing the estimated change in employment with the mean outcome variable reported in angle brackets. Then we divide the percent change in employment with the percent change in labor cost (estimates are not reported, but available on request). Standard errors are reported in brackets, clustered at the age _×_ period level. ( _N_ = 9 _,_ 003 _,_ 984 individual-months)