Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Relationship between the absolute values of the coefficients: Are they statistically different for different types of workers?
| Gender | Age | Education | ||||||
|---|---|---|---|---|---|---|---|---|
| Female | Male | 15-24(Y) | 25-49 (M) | 50-74 (0) | Low | Middle | High | |
| EPL | F=M | M=F | Y>M* and Y>0** | M<Y* and M=O | 0<Y** and 0=M | L=M and L=H | M=L and M=H | H=L and H=M |
| Individual dismissals | F=M | M=F | Y>M*** and Y>0*** | M<Y*** and M=O | 0<Y*** and 0=M | L=M and L=H | M=LandM>H** | H=LandH<M** |
| Collective dismissals | F=M | M=F | Y=M and Y=O | M=YandM=O | 0=Y and O=M | L=M and L=H | M=LandM>H** | H=LandH<M** |
| Temporary employment | F=M | M=F | Y=M and Y=O | M=YandM=O | 0=Y and O=M | L>M* and L>H** | M<L*andM=H | H<L**andH=M |
| PMR | F=M | M=F | Y=M and Y=O | M=YandM=O | O=Y and O=M | L=M and L>H*** | M=LandM>H* | H<L***andH<M* |
| State controls | F<M* | M>F* | Y=MandY>0* | M=YandM=O | 0<Y* and 0=M | L=M and L=H | M=LandM>H** | H=LandH<M** |
| Barriers to entrepreneurship | F=M | M=F | Y=M and Y=O | M=YandM=O | O=Y and O=M | L>M*andL>H*** | M<L*andM>H*** | H<L***andH<M*** |
| Barriers to trade and investment | F=M | M=F | Y=MandY>0* | M=YandM=O | 0<Y*and0=M | L=M and L=H | M=LandM>H** | H=LandH<M** |
Impact of EPL and PMR on the unemployment rate
| (1) | (2) | (3) | (4) | (5) | (6) | |
|---|---|---|---|---|---|---|
| Employment protection | 0.97* | -1.37*** | -6.56*** | -6.36*** | -5.96** | -6.68** |
| (0.52) | (0.37) | (1.30) | (2.06) | (2.57) | (2.75) | |
| PMR | 3.38*** | 6.05*** | 3.45*** | 3.97*** | 3.29*** | 3.89*** |
| (0.93) | (0.57) | (0.93) | (1.19) | (1.01) | (1.18) | |
| Estimator | OLS | OLS | FE | IV-FE | IV-FE | IV-FE |
| Control variables | Yes | Yes | Yes | Yes | Yes | Yes |
| Country fixed effects | No | No | Yes | Yes | Yes | Yes |
| Year fixed effects | No | Yes | Yes | Yes | Yes | Yes |
| PMR endogeneity | No | No | No | Yes | No | Yes |
| EPL endogeneity | No | No | No | No | Yes | Yes |
| Adjusted R2 | 0.83 | 0.88 | 0.35 | 0.39 | 0.44 | 0.45 |
| Number of observations | 317 | 317 | 317 | 281 | 279 | 277 |
| Weak identification test | – | – | – | 327.17 | 137.34 | 69.02 |
| Overidentification test | – | – | – | 0.30 | 0.84 | 0.60 |
| Endogeneity test | – | – | – | 0.19 | 0.95 | 0.42 |
Robustness checks of the impact of EPL and PMR on the unemployment rate
| Baseline regression | Excluding PT, GR, ES, and IT | Baseline regression with interaction term | Excluding PT, GR, ES, and IT and adding interaction term | |
|---|---|---|---|---|
| Employment protection | -6.56*** | 4.21*** | -5.91*** | 4.18*** |
| (1.30) | (1.59) | (1.34) | (1.61) | |
| PMR | 3.45*** | 2.83*** | 3.53*** | 2.82*** |
| (0.93) | (0.78) | (0.93) | (0.78) | |
| EPL × PMR | 6.68** | -0.60 | ||
| (3.36) | (4.59) | |||
| Estimator | FE | FE | FE | FE |
| Country fixed effects | Yes | Yes | Yes | Yes |
| Year fixed effects | Yes | Yes | Yes | Yes |
| Adjusted R2 | 0.35 | 0.28 | 0.36 | 0.28 |
| Number of observations | 317 | 254 | 317 | 254 |
Summary of empirical findings on the impact of PMR and EPL reforms on (un)employment
| Studies | Data | Dependent variable | Definition: PMR and EPL | Methodology | Endogeneity tests | Results |
|---|---|---|---|---|---|---|
| Boerietal. (2000) | 19 OECD countries, 1982-1995 | Nonagricultural employment rate | EPL: OECD indicator for permanent and temporary workers PMR: OECD economy-wide index | Step 1: reduced-form model for EPL; step 2: country-specific effect; | – | Countries with restrictive PMR tend to have lower employment rates in the nonagricultural business sector. EPL has a negative impact on employment rate (90% significance) |
| Nicoletti et al (2001) | 20 OECD countries, 1982-1998 | Employment rate | PMR: OECD sectoral index | Reduced-form models estimated with fixed and random effects | – | Anticompetitive PMR has significant negative effects on nonagricultural employment rate. In some countries, the product market regulatory environment may account for up to 3 PP of deviations of the employment rate from the OECD average |
| Baker et al (2002) | 20 OECO countries, 1960-1999 | Unemployment rate | EPL: OECD indicator | Feasible generalized least squares | Do not consider EPL as endogenous. Control for the endogeneity of ALMPs by instrumenting it using countries' average ALMP value over the period 1985-1999 | No argument in favor of labor market deregulation since nearly all the change in structural unemployment rates was accounted for by country-specific effects not by institutional factors |
| Belot and Van Ours (2004) | 17 OECD countries, 1960-1999 | Unemployment rate | EPL: index based on three subindexes (protection of open-ended contracts, fixed-term contracts, and temporary work agencies), own computation, scale of 0-1 | FE regressions taking interactions between labor market institutions into account | – | No clear causal relationship between employment protection and unemployment rate. Estimating the regression with fixed effect made the coefficient of employment protection statistically insignificant |
| Nicoletti and Scarpetta (2005) | 20 OECD countries, 1980-2002 | Nonagricultural employment rate | EPL: OECD indicator for permanent and temporary workers PMR: OECD sectoral index | Fixed effect: regression | – | Significant employment gains can be obtained by deregulating product markets in overly regulated countries. EPL has a negative impact on employment rate but this impact is not significant in all specifications, particularly when they control for outliers and add country fixed effects |
| Bassanini and Duval (2006a) | 20 OECD countries, 1982-2003 | Unemployment rate | EPL: OECD indicator for permanent and temporary workers PMR: OECD sectoral index | Feasible GSL with fixed and random effects | IV estimation using lagged institutional variables (2-year lag) PMR and EPL coefficients become statistically insignificant | PMR raise aggregates unemployment. EPL effect on unemployment is statistically insignificant |
| Berger and Danninger (2007) | 27OECD countries, 1980-2004 | Employment growth rate | EPL: OECD indicator for permanent and temporary workers PMR: OECD economy-wide index | Time series panel techniques with fixed and random effects, IV and GMM | GMM based on Arellano and Bond (1991) with a four-lag structure | Lower levels of product and labor market regulator foster employment growth |
| Fiori et al (2007) | 20 OECO countries, 1980-2002 | Nonagricul- tural employ- ment rate | EPL: OECD indicator for permanent and tempo- rary workers PMR: OECD sectoral index | Feasible GLS | Control function approach of Rivers and Vuong (1988) finds that there is no endog- eneity and thus GLS results are consistent | Anticompetitive PMR has a negative impact on employment rate Tight labor market regulation tends to reduce employment |
| Griffith et al. (2007) | 14 OECO countries, 1986-2000 | Unemploy- ment rate | PMR: captures changes in the extent of competition using a measure of the average level of firm profitability+2 indicators based on an opinion sur- vey and 1 reported by the Fraser Institute | Fixed-effect regression | Two-stage estimation approach: first, the impact of PMR and LMR on profitability, and then, the impact of profitability on the unemployment rate | Increased competition reduces unemployment |
| Kugler and Pica (2008) | Italian Social Security employer- employee panel data, 1986-1995 | Accession or separation between worker and firm | EPL: dummy variable which takes the value of 1 after 1990 (after the reform) and a dummy variable which takes the value of 1 if the worker is employed in a small firm | Difference-in-difference approach by comparing worker and job flows in small and large firms before and after the reform | Use the 1990 reform on workers and job flows (increasing dismissal costs for small firms) as a natural experiment | The increase in dismissal costs decreased accession and separation rates for workers in small relative to large firms. Negligible impact on net employment |
| Amable et al. (2011) | 18 OECD countries, 1930-2004 | Jobless, inactivity and unemploy- ment | EPL: model the evolution of the OECD index using EPL index from the FRDB Social Reforms: Data- base as well as country dummies and time trends as regressors PMR: OECD index (economy wide and sectoral) | Limited dependent variable model with country dum- mies + fixed-effect vector decomposition | IV estimation using lagged institutional variables | Regressions on joblessness show a negative impact of PMR and a positive impact of EPL on employment. Regression using sectoral PMR index shows not statistically significant impact on joblessness |
| De Serres et al. (2012) | 21 OECD countries, 1985-2007 | Unemploy- ment rate | EPL: OECD indicator on regular contracts + share of workers with fixed- term contracts PMR: OECD sectoral index | Dynamic unemployment equation taking the per- sistence of unemployment into account estimated using FE LSDV estimator + NLS estimator | Difference GMM: The impact of EPL on regular contracts remains positive and significant. However, the impact of PMR becomes negative and insignificant | Easing of EPL on regular contracts reduces the persistence of unemployment (statistically significant only in half of the specifications including the one based on diff-GMM) |
| Malk (2013) | Micro- data from labor force survey for Es- tonia and Lithuania, 2007-2011 | Worker flows out from em- ployment and into employ- ment | EPL: dummy variable which takes the value of 1 after the reform and a dummy variable which takes the value of 1 if the worker is in Estonia | Difference-in-difference approach by comparing labor flows in Lithuania and Estonia before and after the reform | Analyze the Estonian reform in mid-2009 decreasing EPL (for all workers) and use Lithuania as a control | Labor flows out of and into employment increased in Estonia relative to Lithuania. Statistically significant only for flows out of employment |
| Bordon et al. (2016) | 30 OECD countries, 1980-2013 | Variation in the employ- ment rate (from 1 to 5 years) | EPL: OECD indicator on regular contracts PMR: OECD sectoral index | Define two reform variables (for PMR and EPL) which take the value of 1 when the index drop by more than 2 standard deviations of the change in the indicator overall observations; esti- mation using local projections techniques | AIPW method that esti- mates the treatment effects of reforms while controlling for potential selection bias | Structural reforms have a lagged but positive impact on employment Both labor and product market reforms increase employment rates by about a little over 1% pain: over 5 years |
| Gal and Hijzen (2016) | 10 regulat- ed indus- tries in 18 advanced economies, 1998-2013 | Employment based on the firm-level da- tabase Orbis | PMR OECD sectoral index | Impulse response function using the local projection method | Instrumental variables | Product market reforms have positive effects on employment and their effects increase overtime |
Impact of different types of PMR on the unemployment rate
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Employment protection | 1.39* | -0.60 | -6.16*** | -5.85*** | -6.30* | -7.67* | 0.15 | -1.98*** | -6.21*** | -6.12*** | -7.20*** | -8.32* | ||
| (0.54) | (0.67) | (1.23) | (1.92) | (2.36) | (2.52) | (0.50) | (0.27) | (1.24) | (1.89) | (2.37) | (2.52) | |||
| PMR | ||||||||||||||
| 1) State control | -0.14 | 0.67 | -1.74* | -2.87* | -1.48** | -2.35* | ||||||||
| a) Public ownership | 0.25 | -0.31 | -0.14 | -0.64 | 0.12 | -0.30 | ||||||||
| (0.25) | (0.30) | (0.39) | (0.43) | (0.38) | (0.48) | |||||||||
| b) Price controls and C&C | 0.34 | 0.88** | -2.20*** | -2.78*** | -2.06*** | -2.58*** | ||||||||
| (0.62) | (0.45) | (0.46) | (0.67) | (0.54) | (0.68) | |||||||||
| 2) Barriers to entrepreneurship | 3.15*** | 4.64*** | 3.91*** | 4.68*** | 3.16*** | 3.97*** | ||||||||
| (0.40) | (0.45) | (0.72) | (1.04) | (0.83) | (0.98) | |||||||||
| a) Regulatory and admin opacity | 1 18*** | 1 14*** | 1 43*** | 1 64*** | 1 15*** | 1 33*** | ||||||||
| (0.15) | (0.15) | (0.29) | (0.46) | (0.32) | (0.43) | |||||||||
| b) Administrative burdens on startups | 2.92*** | 3.26*** | 2.24*** | 2.80*** | 1.72*** | 2.31*** | ||||||||
| (0.34) | (0.31) | (0.56) | (0.66) | (0.62) | (0.67) | |||||||||
| c) Barriers to competition | -2.80*** | -0.58* | 0.48 | 0.75 | 0.71 | 0.92 | ||||||||
| (0.51) | (0.31) | (0.57) | (0.65) | (0.50) | (0.65) | |||||||||
| 3) Barriers to trade and investment | -0.46 | 0.80 | 1.53* | 2.33* | 1.75* | 2.52* | ||||||||
| (0.75) | (1.07) | (0.47) | (0.94) | (0.60) | (0.89) | |||||||||
| a) Barriers to FDI | -0.45 | -0.74 | 1.89* | 1.64 | 1.55 | 1.83 | ||||||||
| (0.90) | (0.87) | (1.10) | (1.36) | (1.00) | (1.36) | |||||||||
| b) Regulatory barriers | 0.40 | 1.12** | 0.29 | 0.84 | 0.44 | 0.85 | ||||||||
| (0.39) | (0.47) | (0.38) | (0.58) | (0.38) | (0.54) | |||||||||
| Estimator | OLS | OLS | FE | IV-FE | IV-FE | IV-FE | OLS | OLS | FE | IV-FE | IV-FE | IV-FE | ||
| Control variables | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | ||
| Country fixed effects | No | No | Yes | Yes | Yes | Yes | No | No | Yes | Yes | Yes | Yes | ||
| Year fixed effects | No | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | ||
| PMR endogeneity | No | No | No | Yes | No | Yes | No | No | No | Yes | No | Yes | ||
| EPL endogeneity | No | No | No | No | Yes | Yes | No | No | No | No | Yes | Yes | ||
| Adjusted R2 | 0.83 | 0.88 | 0.43 | 0.45 | 0.50 | 0.48 | 0.87 | 0.90 | 0.45 | 0.48 | 0.52 | 0.51 | ||
| Number of observations | 317 | 317 | 317 | 281 | 279 | 277 | 317 | 317 | 317 | 281 | 279 | 277 | ||
| Weak identification test | – | – | – | 63.52 | 141.91 | 33.44 | – | – | – | 20.19 | 137.33 | 14.46 | ||
| Overidentification test | – | – | – | 0.14 | 0.86 | 0.17 | – | – | – | 0.35 | 0.88 | 0.45 | ||
| Endogeneity test | – | – | – | 0.34 | 0.72 | 0.37 | – | – | – | 0.52 | 0.47 | 0.29 |
Descriptive statistics
| Number of observations | Mean | Standard deviation | Minimum | Maximum | Average variation over the period | |
|---|---|---|---|---|---|---|
| Unemployment rate | ||||||
| Total | 384 | 7.9 | 4.2 | 1.8 | 27.5 | |
| By gender | ||||||
| Female | 384 | 8.5 | 4.8 | 2.2 | 31.4 | |
| Male | 384 | 7.5 | 4.2 | 1.3 | 25.6 | |
| By age (years) | ||||||
| 15–24 | 384 | 17.9 | 9.6 | 4.3 | 58.3 | |
| 25–49 | 384 | 7.1 | 4.0 | 1.3 | 27.8 | |
| 50–74 | 373 | 5.5 | 3.2 | 0.8 | 20.3 | |
| By level of education | ||||||
| Low education | 379 | 13.7 | 8.8 | 2.5 | 53.3 | |
| Middle education | 376 | 7.9 | 4.7 | 1.4 | 31.2 | |
| High education | 369 | 4.4 | 2.6 | 1.2 | 20.4 | |
| EPL | ||||||
| Total | 344 | 2.6 | 0.5 | 1.6 | 4.1 | -0.06 |
| Individual dismissals | 344 | 2.4 | 0.7 | 1.0 | 4.6 | -0.08 |
| Collective dismissals | 344 | 3.2 | 0.7 | 1.6 | 5.1 | -0.03 |
| Temporary employment | 338 | 1.7 | 1.0 | 0.3 | 4.8 | -0.07 |
| PMR | ||||||
| Total | 354 | 1.8 | 0.4 | 0.9 | 3.2 | -0.29 |
| State control | 354 | 2.6 | 0.6 | 1.2 | 4.2 | -0.32 |
| Public ownership | 354 | 3.0 | 0.8 | 1.1 | 5.0 | -0.23 |
| Price controls and command and | 359 | 2.1 | 0.9 | 0.9 | 4.8 | -0.41 |
| control | ||||||
| Barriers to entrepreneurship | 354 | 2.2 | 0.5 | 1.1 | 3.4 | -0.36 |
| Regulatory and administrative opacity | 354 | 2.5 | 0.9 | 0.4 | 4.5 | -0.44 |
| Administrative burdens on startups | 359 | 2.4 | 0.7 | 1.1 | 4.1 | -0.29 |
| Barriers to competition | 354 | 1.6 | 0.6 | 0.6 | 3.0 | -0.36 |
| Barriers to trade and investments | 359 | 0.6 | 0.5 | 0.1 | 3.1 | -0.18 |
| Barriers to FDI, tariffs, and discriminatory | 359 | 0.3 | 0.3 | 0.0 | 1.6 | -0.09 |
| procedures | ||||||
| Regulatory barriers | 359 | 1.0 | 0.8 | 0.2 | 4.7 | -0.27 |
| Control variables | ||||||
| Net replacement rate | 352 | 39.7 | 14.7 | 10.9 | 74.0 | |
| Union density | 375 | 35.1 | 22.2 | 6.5 | 99.1 | |
| GDP gap (%) | 382 | 0.0 | 1.8 | -10.6 | 9.3 | |
| Inflation | 376 | 2.8 | 2.3 | -1.7 | 16.3 | |
| Labor productivity growth | 384 | 1.4 | 2.4 | -6.4 | 11.4 |
Instrumental variable estimations using different lagged values
| Testing PMR endogeneity | Testing EPL endogeneity | Testing PMR and EPL endogeneity | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Lag 1 | Lag 2 | Lag 3 | Lag 4 | Lag 5 | Lag 1 | Lag 2 | Lag 3 | Lag 4 | Lag 5 | Lag 1 | Lag 2 | Lag 3 | Lag 4 | Lag 5 | |
| Employment protection | -6.74***- | 6.36***- | 6.35***- | 6.80***- | 7.53***- | 6.43***- | 5.96** | -6.55** | -7.26** | -8.24** | -7.13***- | 6.68** | -7.25** | -8.24** | -9.47** |
| (1.90) | (2.06) | (2.18) | (2.30) | (2.46) | (2.38) | (2.57) | (3.18) | (3.43) | (3.56) | (2.61) | (2.75) | (3.31) | (3.63) | (3.73) | |
| PMR | 414*** | 3 97*** | 4 25*** | 4 28*** | 4 25** | 3 14*** | 3 29*** | 3 50*** | 3 10*** | 2 68** | 4 25*** | 3 89*** | 4 24*** | 417*** | 444** |
| (1.12) | (1.19) | (1.33) | (1.48) | (1.73) | (0.97) | (1.01) | (1.06) | (1.15) | (1.26) | (1.17) | (1.18) | (1.33) | (1.48) | (1.80) | |
| Estimator | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE | IV-FE |
| Control variables | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| PMR endogeneity | Yes | Yes | Yes | Yes | Yes | No | No | No | No | No | Yes | Yes | Yes | Yes | Yes |
| EPL endogeneity | No | No | No | No | No | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Adjusted R2 | 0.39 | 0.39 | 0.39 | 0.40 | 0.41 | 0.41 | 0.44 | 0.44 | 0.45 | 0.46 | 0.41 | 0.45 | 0.44 | 0.46 | 0.47 |
| Number of observations | 299 | 281 | 263 | 242 | 221 | 298 | 279 | 260 | 238 | 216 | 297 | 277 | 257 | 234 | 211 |
| Weak identification test | 80.1 | 327.2 | 178.8 | 99.4 | 56.3 | 37.1 | 137.3 | 92.0 | 56.2 | 40.6 | 42.6 | 69.0 | 44.4 | 26.1 | 16.6 |
| Overidentification test | - | 0.30 | 0.24 | 0.16 | 0.16 | - | 0.84 | 0.18 | 0.31 | 0.50 | - | 0.60 | 0.27 | 0.37 | 0.54 |
| Endogeneity test | 0.20 | 0.19 | 0.17 | 0.22 | 0.34 | 0.99 | 0.95 | 0.31 | 0.45 | 0.66 | 0.33 | 0.42 | 0.81 | 0.96 | 0.94 |
Excluding PT, GR, ES, and IT as robustness check
| (1) | (2) | (1') | (2') | (1'') | (2'') | (1''') | (2''') | |
|---|---|---|---|---|---|---|---|---|
| Employment protection | -6.56*** (1.30) | 4.21*** (1.59) | -6.16*** (1.23) | 3.35** (1.49) | -6.21*** (1.24) | 2.76* (1.56) | ||
| 1) Individual dismissals | -8.52*** (1.22) | -0.70 (1.48) | ||||||
| 2) Collective dismissals | 1.62** (0.73) | 4.65*** (0.77) | ||||||
| 3) Temporary employment | -1.22*** (0.35) | -0.51 (0.55) | ||||||
| PMR | 3.45*** (0.93) | 2.83*** (0.78) | 3.02*** (0.92) | 2.82*** (0.78) | ||||
| 1) State control | -1.74*** (0.54) | -1.54*** (0.46) | ||||||
| a) Public ownership | -0.14(0.39) | -0.08(0.32) | ||||||
| b) Price controls and C&C | -2.20*** (0.46) | -1.63*** (0.44) | ||||||
| 2) Barriers to entrepreneurship | 3.91*** (0.72) | 3.21*** (0.64) | ||||||
| a) Regulatory and admin opacity | 1.43*** (0.29) | 1.29*** (0.24) | ||||||
| b) Administrative burdens on startups | 2.24*** (0.56) | 1.88*** (0.58) | ||||||
| c) Barriers to competition | 0.48 (0.57) | -0.68 (0.56) | ||||||
| 3) Barriers to trade and investment | 1.53*** (0.47) | 1.34*** (0.39) | ||||||
| a) Barriers to FDI | 1.89* (1.10) | 0.82 (0.92) | ||||||
| b) Regulatory barriers | 0.29 (0.38) | 0.71** (0.34) | ||||||
| Estimator | FE | FE | FE | FE | FE | FE | FE | FE |
| Adjusted R2 | 0.35 | 0.28 | 0.41 | 0.33 | 0.43 | 0.38 | 0.45 | 0.42 |
| Number of observations | 317 | 254 | 312 | 249 | 317 | 254 | 317 | 254 |
Impact of PMR and EPL on unemployment rate for different types of workers using FE regressions
| Gender | Age | Education | ||||||
|---|---|---|---|---|---|---|---|---|
| Female | Male | 15-24(Y) | 25-49 (M) | 50-74 (0) | Low | Middle | High | |
| Employment protection | -7.02*** | -6.08*** | -12.80*** | -6.91*** | -6.09*** | -5.84*** | -6.33*** | -5.84*** |
| (1.29) | (1.37) | (2.74) | (1.24) | (0.99) | (1.81) | (1.41) | (0.73) | |
| PMR | 3.76*** | 3.26*** | 4.42** | 3.19*** | 2.54*** | 5.05*** | 3.50*** | 1.32*** |
| (0.92) | (0.98) | (1.96) | (0.89) | (0.71) | (1.29) | (1.00) | (0.52) | |
| Estimator | FE | FE | FE | FE | FE | FE | FE | FE |
| Control variables | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Country fixed effects | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Year fixed effects | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Adjusted R2 | 0.30 | 0.40 | 0.39 | 0.38 | 0.41 | 0.44 | 0.37 | 0.44 |
| Number of observations | 317 | 317 | 317 | 317 | 317 | 314 | 314 | 314 |
| |Coeff| EPL statistically different | F=M | M=F | Y>M* andY>0** | M<Y*and M=O | O<Y**and O=M | L=M and L=H | M=L and M=H | H=L and H=M |
| |Coeff| PMR statistically different | F=M | M=F | Y=M and Y=O | M=Y and M=O | O=Y and O=M | L=M and L>H*** | M=L and M>H* | H<L***and H<M* |
Impact of different types of EPL on the unemployment rate
| (1) | (2) | (3) | (4) | (5) | (6) | |
|---|---|---|---|---|---|---|
| Employment protection | ||||||
| 1) Individual dismissals | -0.00 | -1.14*** | -8.52*** | -8.30*** | -10.09*** | -10.27*** |
| (0.29) | (0.28) | (1.22) | (1.72) | (2.13) | (2.25) | |
| 2) Collective dismissals | 1.31*** | 0.20 | 1.62** | 1.77** | 3.10*** | 3.08*** |
| (0.28) | (0.14) | (0.73) | (0.87) | (1.03) | (1.03) | |
| 3) Temporary employment | 0.48*** | 0.47*** | -1.22*** | -1.49*** | -1.60*** | -1.54*** |
| (0.17) | (0.16) | (0.35) | (0.48) | (0.59) | (0.59) | |
| PMR | 2.50*** | 5.25*** | 3.02*** | 2.87*** | 2.22** | 2.73** |
| (0.82) | (0.63) | (0.92) | (1.11) | (1.04) | (1.18) | |
| Estimator | OLS | OLS | FE | IV-FE | IV-FE | IV-FE |
| Control variables | Yes | Yes | Yes | Yes | Yes | Yes |
| Country fixed effects | No | No | Yes | Yes | Yes | Yes |
| Year fixed effects | No | Yes | Yes | Yes | Yes | Yes |
| PMR endogeneity | No | No | No | Yes | No | Yes |
| EPL endogeneity | No | No | No | No | Yes | Yes |
| Adjusted R2 | 0.84 | 0.88 | 0.41 | 0.47 | 0.50 | 0.50 |
| Number of observations | 312 | 312 | 312 | 278 | 274 | 274 |
| Weak identification test | – | – | – | 282.12 | 25.66 | 24.57 |
| Overidentification test | – | – | – | 0.27 | 0.46 | 0.43 |
| Endogeneity test | – | – | – | 0.27 | 0.18 | 0.26 |