# J Supplementary tables and figures

<table><caption>Table J.1 – Event study: employment growth rate depending on the judge bias (with controls)</caption><thead><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr><tr><th></th><th>t-3</th><th>t-2</th><th>t</th><th>t+1</th><th>t+2</th><th>t+3</th></tr></thead><tbody><tr><td colspan="7"><strong>All firms</strong></td></tr><tr><td>bias<sub>ij</sub></td><td>0.002<br>(0.005)</td><td>-0.004<br>(0.003)</td><td>-0.001<br>(0.004)</td><td>-0.022***<br>(0.006)</td><td>-0.026***<br>(0.008)</td><td>-0.030**<br>(0.009)</td></tr><tr><td>N</td><td>7329</td><td>7329</td><td>7329</td><td>7329</td><td>7329</td><td>7329</td></tr><tr><td>R<sup>2</sup></td><td>0.042</td><td>0.042</td><td>0.038</td><td>0.063</td><td>0.079</td><td>0.089</td></tr><tr><td colspan="7"><strong>15 and more employees</strong></td></tr><tr><td>bias<sub>ij</sub></td><td>0.001<br>(0.007)</td><td>-0.008**<br>(0.003)</td><td>-0.007<br>(0.005)</td><td>-0.019**<br>(0.007)</td><td>-0.015*<br>(0.008)</td><td>-0.014<br>(0.010)</td></tr><tr><td>N</td><td>3638</td><td>3638</td><td>3638</td><td>3638</td><td>3638</td><td>3638</td></tr><tr><td>R<sup>2</sup></td><td>0.076</td><td>0.066</td><td>0.062</td><td>0.087</td><td>0.115</td><td>0.116</td></tr><tr><td colspan="7"><strong>1-14 employees</strong></td></tr><tr><td>bias<sub>ij</sub></td><td>0.000<br>(0.007)</td><td>-0.003<br>(0.005)</td><td>0.002<br>(0.007)</td><td>-0.024**<br>(0.009)</td><td>-0.036**<br>(0.013)</td><td>-0.043**<br>(0.015)</td></tr><tr><td>N</td><td>3677</td><td>3677</td><td>3677</td><td>3677</td><td>3677</td><td>3677</td></tr><tr><td>R<sup>2</sup></td><td>0.072</td><td>0.065</td><td>0.072</td><td>0.089</td><td>0.094</td><td>0.104</td></tr><tr><td colspan="7"><strong>All firms with low ROA</strong></td></tr><tr><td>bias<sub>ij</sub></td><td>0.004<br>(0.009)</td><td>-0.005<br>(0.005)</td><td>-0.005<br>(0.005)</td><td>-0.028**<br>(0.011)</td><td>-0.041**<br>(0.014)</td><td>-0.039**<br>(0.014)</td></tr><tr><td>N</td><td>3673</td><td>3673</td><td>3673</td><td>3673</td><td>3673</td><td>3673</td></tr><tr><td>R<sup>2</sup></td><td>0.068</td><td>0.068</td><td>0.063</td><td>0.082</td><td>0.095</td><td>0.107</td></tr><tr><td colspan="7"><strong>15 employees and more &amp; low ROA</strong></td></tr><tr><td>bias<sub>ij</sub></td><td>-0.005<br>(0.011)</td><td>-0.009<br>(0.006)</td><td>-0.015*<br>(0.008)</td><td>-0.023*<br>(0.012)</td><td>-0.018<br>(0.014)</td><td>-0.017<br>(0.014)</td></tr><tr><td>N</td><td>1815</td><td>1815</td><td>1815</td><td>1815</td><td>1815</td><td>1815</td></tr><tr><td>R<sup>2</sup></td><td>0.126</td><td>0.107</td><td>0.124</td><td>0.138</td><td>0.170</td><td>0.161</td></tr><tr><td colspan="7"><strong>1-14 employees &amp; low ROA</strong></td></tr><tr><td>bias<sub>ij</sub></td><td>0.003<br>(0.012)</td><td>-0.004<br>(0.007)</td><td>0.003<br>(0.009)</td><td>-0.029*<br>(0.018)</td><td>-0.061**<br>(0.026)</td><td>-0.059**<br>(0.027)</td></tr><tr><td>N</td><td>1849</td><td>1849</td><td>1849</td><td>1849</td><td>1849</td><td>1849</td></tr><tr><td>R<sup>2</sup></td><td>0.112</td><td>0.129</td><td>0.107</td><td>0.123</td><td>0.122</td><td>0.139</td></tr><tr><td colspan="7"><strong>All firms with high ROA</strong></td></tr><tr><td>bias<sub>ij</sub></td><td>0.001<br>(0.007)</td><td>-0.004<br>(0.004)</td><td>0.002<br>(0.005)</td><td>-0.016**<br>(0.007)</td><td>-0.011<br>(0.011)</td><td>-0.018<br>(0.013)</td></tr><tr><td>N</td><td>3638</td><td>3638</td><td>3638</td><td>3638</td><td>3638</td><td>3638</td></tr><tr><td>R<sup>2</sup></td><td>0.070</td><td>0.065</td><td>0.058</td><td>0.061</td><td>0.070</td><td>0.075</td></tr></tbody></table>
<table><caption>Table J.1 – Continued from previous page</caption><thead><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr><tr><th></th><th>t-3</th><th>t-2</th><th>t</th><th>t+1</th><th>t+2</th><th>t+3</th></tr></thead><tbody><tr><td colspan="7"><strong>15 employees and more &amp; high ROA</strong></td></tr><tr><td>bias<sub>ij</sub></td><td>0.005<br>(0.010)</td><td>-0.008<br>(0.007)</td><td>0.002<br>(0.005)</td><td>-0.013*<br>(0.007)</td><td>-0.006<br>(0.009)</td><td>-0.007<br>(0.012)</td></tr><tr><td>N</td><td>1808</td><td>1808</td><td>1808</td><td>1808</td><td>1808</td><td>1808</td></tr><tr><td>R<sup>2</sup></td><td>0.118</td><td>0.122</td><td>0.128</td><td>0.092</td><td>0.103</td><td>0.120</td></tr><tr><td colspan="7"><strong>1-14 employees &amp; high ROA</strong></td></tr><tr><td>bias<sub>ij</sub></td><td>-0.003<br>(0.011)</td><td>0.001<br>(0.007)</td><td>0.002<br>(0.009)</td><td>-0.017<br>(0.012)</td><td>-0.012<br>(0.019)</td><td>-0.023<br>(0.021)</td></tr><tr><td>N</td><td>1813</td><td>1813</td><td>1813</td><td>1813</td><td>1813</td><td>1813</td></tr><tr><td>R<sup>2</sup></td><td>0.124</td><td>0.101</td><td>0.102</td><td>0.122</td><td>0.116</td><td>0.122</td></tr></tbody></table>

Note: This table reports the estimates displayed in Figure 5. This table displays the coefficients $\alpha_{1k}$ of equation (4) in year $k$, $k \in [-3, 3]$ relative to the judgment year $t$ where the dependent variable is the symmetric employment growth rates relative to the year preceding the judgment year $t$ and the explanatory variable is the leave-one-out judge bias, $bias_{ij}$, controlling for social chamber fixed effects interacted with calendar year fixed effects, an indicator variable for economic dismissals, the age of the firm, the return on assets, the leverage and the capex the year preceding the judgment. Standard errors are clustered at the judge level. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.

<table><caption>Table J.2 – Judge bias and firm performance 3 years after the judgment, with quadratic terms</caption><thead><tr><th></th><th colspan="4">Firm type</th></tr><tr><th></th><th>All firms</th><th>&lt; 15 employees</th><th>All and low ROA</th><th>&lt; 15 employees and low ROA</th></tr></thead><tbody><tr><td>bias<sub>ij</sub></td><td>-0.031***<br>(0.009)</td><td>-0.043**<br>(0.015)</td><td>-0.039**<br>(0.015)</td><td>-0.059**<br>(0.024)</td></tr><tr><td>bias<sup>2</sup><sub>ij</sub></td><td>0.012*<br>(0.007)</td><td>-0.000<br>(0.011)</td><td>-0.001<br>(0.011)</td><td>-0.030<br>(0.018)</td></tr><tr><td>N</td><td>7329</td><td>3677</td><td>3673</td><td>1849</td></tr><tr><td>R<sup>2</sup></td><td>0.090</td><td>0.104</td><td>0.107</td><td>0.140</td></tr></tbody></table>

Note: This table displays the coefficients of equation (4) associated with the explanatory variables $bias_{ij}$ and $bias_{ij}^2$, three years after the judgment where the dependent variable is the symmetric employment growth rates relative to the year preceding the judgment, controlling for social chamber fixed effects interacted with calendar year fixed effects, an indicator variable for economic dismissals, the age of the firm, the return on assets, the leverage and the capex the year preceding the judgment. Standard errors, displayed in parentheses, are clustered at the judge level. *, **, and *** denote statistical significance at 10, 5 and 1%. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.
<table><caption>Table J.3 – Event study: employment growth rate depending on the judge bias (with control variables) and controlling for the judge bias as defined according to the dismissal qualification</caption><thead><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr><tr><th></th><th>t-3</th><th>t-2</th><th>t</th><th>t+1</th><th>t+2</th><th>t+3</th></tr></thead><tbody><tr><td>Judge bias wrt total amount</td><td>0.005<br>(0.006)</td><td>-0.004<br>(0.004)</td><td>0.002<br>(0.005)</td><td>-0.021**<br>(0.007)</td><td>-0.026**<br>(0.010)</td><td>-0.028**<br>(0.011)</td></tr><tr><td>Judge bias wrt total amount</td><td>-0.005<br>(0.007)</td><td>-0.000<br>(0.004)</td><td>-0.006<br>(0.005)</td><td>-0.002<br>(0.007)</td><td>-0.001<br>(0.009)</td><td>-0.004<br>(0.010)</td></tr><tr><td>N</td><td>7329</td><td>7329</td><td>7329</td><td>7329</td><td>7329</td><td>7329</td></tr></tbody></table>

Note: This table displays the coefficients $\alpha_{ik}$ of equation (4) in year $k$, $k \in [3, 3]$ relative to the judgment year $t$ where the dependent variable is the symmetric employment growth rates relative to the year preceding the judgment year $t$ and the explanatory variable is the leave-one-out judge bias, $bias_{ij}$, controlling for social chamber fixed effects interacted with calendar year fixed effects, an indicator variable for economic dismissals, the age of the firm, the return on assets, the leverage and the capex the year preceding the judgment. Contrary to equation (4), we also control for a second measure of judge bias, defined according to the dismissal qualification. Standard errors are clustered at the judge level. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.

<table><caption>Table J.4 – Event study: employment growth rate depending on the amount of compensation in the previous year payroll and the dismissal qualification, instrumented by two measures of judge bias</caption><thead><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr><tr><th></th><th>t-3</th><th>t-2</th><th>t</th><th>t+1</th><th>t+2</th><th>t+3</th></tr></thead><tbody><tr><td>Total compensation in % payroll</td><td>0.007<br>(0.011)</td><td>-0.008<br>(0.005)</td><td>-0.003<br>(0.009)</td><td>-0.036**<br>(0.018)</td><td>-0.046**<br>(0.021)</td><td>-0.034**<br>(0.017)</td></tr><tr><td>Dismissal deemed unfair</td><td>-0.572<br>(0.382)</td><td>0.040<br>(0.248)</td><td>-0.165<br>(0.382)</td><td>0.353<br>(0.656)</td><td>0.349<br>(0.849)</td><td>-0.415<br>(0.706)</td></tr><tr><td>N</td><td>5180</td><td>5180</td><td>5180</td><td>5180</td><td>5180</td><td>5180</td></tr></tbody></table>

Note: This table displays the coefficient $\beta_{1k}$ of equation (5) in year $k, k \in [-3, 3]$ relative to the judgment year $t$ where the dependent variable is the symmetric employment growth rates relative to the year preceding the judgment year $t$ and the explanatory variables are the total amount of compensation in the previous year payroll and the dismissal qualification. Those two explanatory variables are instrumented by the leave-one-out judge bias, $bias_{ij}$, and a measure of judge bias defined according to the dismissal qualification. We control for social chamber fixed effects interacted with calendar year fixed effects, an indicator variable for economic dismissals, the age of the firm, the return on assets, the leverage and the capex the year preceding the judgment. Standard errors are clustered at the judge level. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.
<figure><img src="image_19.png" /><figcaption>Figure J.1 – Histogram of compensation amounts in monthly wage</figcaption></figure>

Note: This graph is an histogram of compensation amounts in monthly wages, conditional on this amount being positive. Only amounts lower than 50 months of salary are displayed. Source: Appeal court rulings database.

<figure><img src="image_20.png" /><figcaption>Figure J.2 – Relation between compensations for wrongful dismissals set by Appeal courts and by *prud'hommes*</figcaption></figure>

Note: This graph is a scatter plot of the compensations for wrongful dismissals set by Appeal courts and by *prud'hommes*. Compensations are expressed in monthly wage. Source: Appeal court rulings database.
<figure><img src="image_21.png" /><figcaption>Figure J.3 – Network of judges</figcaption></figure>

Note: Each dot represents a judge. Two dots are connected if the two judges shared the same social chamber at least once. The higher the network density, the higher the mobility of judges across social chambers. If judges were not mobile whatsoever, one would observe perfectly distinct judge clusters, each cluster representing one social chamber. Source: Appeal court rulings database.
<figure><img src="image_22.png" /><figcaption>Figure J.4 – Event study: employment growth rate depending on the judge bias conditional on firm survival</figcaption></figure>

Note: This figure displays the coefficients $\alpha_{1k}$ of equation (4) in year $k, k \in [-3, 3]$ relative to the judgment year $t$ where the dependent variable is the symmetric employment growth rates relative to the year preceding the judgment year $t$ for firms which survive at least until three years after the judgment, and the explanatory variable is the leave-one-out judge bias, $bias_{ij}$, controlling for social chamber fixed effects interacted with calendar year fixed effects, an indicator variable for economic dismissals, the age of the firm, the return on assets, the leverage and the capex the year preceding the judgment. The left panel reports the results for all firms, the middle panel for firms with 15 employees or more and the right panel for firms under 15 employees the year preceding the judgment. The top panel is for all firms independently of their return on assets the year preceding the judgment, the middle panel for firms with return on assets below the median and the bottom panel for firms with return on assets above the median. Standard errors are clustered at the judge level. Vertical bars represent 95% confidence intervals. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.
<figure><img src="image_23.png" /><figcaption>Figure J.5 – Event study: probability for a permanent worker to work for the same firm in the years after the judgment depending on the judge bias, for surviving firms</figcaption></figure>

Note: This figure displays the coefficients $\alpha_{1k}$ of equation (4) in year $k, k \in [-3, 3]$ relative to the judgment year $t$ where the dependent variable is an indicator variable equal to one for the survival of permanent workers employed in the firm the year before the judgment and 1, 2, 3 years after the judgment. The sample is restricted to firms surviving at least 3 years after the judgment. The explanatory variable is the leave-one-out judge bias, $bias_{ij}$, controlling for social chamber fixed effects interacted with calendar year fixed effects, an indicator variable for economic dismissals, the age of the firm, the return on assets, the leverage and the capex the year preceding the judgment. The left panel reports the results for all firms, the middle panel for firms with 15 employees or more and the right panel for firms under 15 employees the year preceding the judgment. The top panel is for all firms independently of their return on assets the year preceding the judgment, the middle panel for firms with return on assets below the median and the bottom panel for firms with return on assets above the median. Standard errors are clustered at the judge level. Vertical bars represent 95% confidence intervals. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.
<figure><img src="image_24.png" /><figcaption>Figure J.6 – Event study: permanent and temporary employment growth rates depending on the amount of compensation in the previous year payroll instrumented by judge bias</figcaption></figure>

Note: This figure displays the coefficients $\beta_{1k}$ of equation (5) in year $k, k \in [-3, 3]$ relative to the judgment year $t$ where the dependent variables are the symmetric growth rates of permanent and temporary employment relative to the year preceding the judgment year $t$ and the explanatory variable is the total amount of compensation in the previous year payroll instrumented by leave-one-out judge bias, $bias_{ij}$, controlling for social chamber fixed effects interacted with calendar year fixed effects, an indicator variable for economic dismissals, the age of the firm, the return on assets, the leverage and the capex the year preceding the judgment. The left panel reports the results for all firms and the right panel for firms under 15 employees the year preceding the judgment. The top panel is for all firms independently of their return on assets the year preceding the judgment, the middle panel for firms with return on assets below the median and the bottom panel for firms with return on assets above the median. Standard errors are clustered at the judge level. Vertical bars represent 95% confidence intervals. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.
<figure><img src="image_25.png" /><figcaption>Figure J.7 – Event study: growth of the hourly wage, conditional on remaining employed in the same firm, in the years after the judgment depending on the judge bias</figcaption></figure>

Note: This figure displays the coefficients $\alpha_{1k}$ of equation (4) in year $k, k \in [-3, 3]$ relative to the judgment year $t$ where the wage growth, relative to the year before the judgment, of workers employed in the firm the year before the judgment and employed in the same firm in 1, 2, 3 years after the judgment. The explanatory variable is the leave-one-out judge bias, $bias_{ij}$, controlling for social chamber fixed effects interacted with calendar year fixed effects, an indicator variable for economic dismissals, the age of the firm, the return on assets, the leverage and the capex the year preceding the judgment. The left panel reports the results for all firms, the middle panel for firms with 15 employees or more and the right panel for firms under 15 employees the year preceding the judgment. The top panel is for all firms independently of their return on assets the year preceding the judgment, the middle panel for firms with return on assets below the median and the bottom panel for firms with return on assets above the median. Standard errors are clustered at the judge level. Vertical bars represent 95% confidence intervals. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.
<figure><img src="image_26.png" /><figcaption>Figure J.8 – Event study: employment growth rate depending on the judge bias conditional on firm fixed-effects</figcaption></figure>

Note: This figure displays the coefficients $\alpha_{1k}$ of equation (4) in year $k, k \in [-3, 3]$ relative to the judgment year $t$ where the dependent variable is the symmetric employment growth rates relative to the year preceding the judgment year $t$ minus the firm fixed effect estimated before year $t-1$ as explained in Section 6.1. The explanatory variable is the leave-one-out judge bias, $bias_{ij}$, controlling for social chamber fixed effects interacted with calendar year fixed effects, firm fixed-effects and an indicator variable for economic dismissals. The left panel reports the results for all firms, the middle panel for firms with 15 employees or more and the right panel for firms under 15 employees the year preceding the judgment. The top panel is for all firms independently of their return on assets the year preceding the judgment, the middle panel for firms with return on assets below the median and the bottom panel for firms with return on assets above the median. Standard errors are clustered at the judge level. Vertical bars represent 95% confidence intervals. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.
<figure><img src="image_27.png" /><figcaption>Figure J.9 – Augmented component-plus-residual plot</figcaption></figure>

Note: This figure is an augmented component-plus-residual plot of the reduced-form estimation of the correlation between the leave-one-out judge bias and the employment growth of firms with fewer than 15 employees and whose return on assets is below the median at 3-year horizon. The non-linear line is a lowess smooth of the plotted points. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.
<figure><img src="image_28.png" /><figcaption>Figure J.10 – Event study: employment growth rate depending on the judge bias, firms split by return on equity</figcaption></figure>

Note: This figure displays coefficients $\alpha_{1k}$ from equation (4) in year $k, k \in [-3, 3]$ relative to the judgment year $t$ where the dependent variable is the symmetric employment growth rates relative to year $t-1$, preceding the judgment year. The explanatory variable is the leave-one-out judge bias, $bias_{ij}$, controlling for social chamber fixed effects interacted with calendar year fixed effects, an indicator variable for economic dismissals, the age of the firm, the return on assets, the leverage and the capex the year preceding the judgment. The left panel reports the results for all firms, the middle panel for firms with 15 employees or more and the right panel for firms under 15 employees the year preceding the judgment. The top panel is for all firms independently of their return on assets the year preceding the judgment, the middle panel for firms with return on assets below the median and the bottom panel for firms with return on assets above the median. Standard errors are clustered at the judge level. Vertical bars represent 95% confidence intervals. Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.
<figure><img src="image_29.png" /><figcaption>Figure J.11 – Event study: employment growth rate depending on the judge bias conditional on the credit score of firms</figcaption></figure>

Note: This figure displays the coefficients $\alpha_{1k}$ from equation(4) in year $k, k \in [-3, 3]$ relative to the judgment year $t$, where the dependent variable is the symmetric employment growth rate relative to year $t-1$, preceding the judgment year. The explanatory variable is the leave-one-out judge bias, $bias_{ij}$, controlling for social chamber fixed effects interacted with calendar year fixed effects and an indicator variable for economic dismissals. The left panel reports the results for all firms, the middle panel for firms with 15 employees or more, and the right panel for firms under 15 employees the year preceding the judgment. The top panel is for all firms independently of their credit rating by the *Banque de France* the year preceding the judgment, the middle panel for firms with credit rating below the median and the bottom panel for firms with credit rating above the median. Standard errors are clustered at the judge level. Vertical bars represent 95% confidence intervals.
Source: DADS, FICUS-FARE, SIREN, Appeal court rulings database.