Unemployment Impact of Product and Labor Market Regulation: Evidence from European Countries

In the theoretical literature, product market deregulation is usually defined as a reduction in barriers to entry or an increase in competition. Ebell and Haefke (2003) studied the dynamic relationship between product market entry regulation and equilibrium unemployment and wages. They assume matching frictions, monopolistic competition in the goods market, multi-worker firms, individual wage bargaining, and barriers to entry. They find a positive impact of product market deregulation on labor market outcomes: a reduction in entry barriers in the model brings down unemployment and pushes up wages.

Blanchard and Giavazzi (2003) distinguish between short-run and long-run effects. In their model, a reduction in entry costs has no effect in the short run since the number of firms is assumed to be fixed. The positive effect of deregulation comes only in the long run when new firms enter the market, implying a higher elasticity of demand and a lower markup. This in turn leads to lower unemployment and higher wages. Cacciatore et al. (2012) study the macroeconomic effects of a reduction in barriers to entry using a dynamic stochastic general equilibrium model. They assume endogenous producer entry, equilibrium unemployment, and costly job creation and destruction. In line with Blanchard and Giavazzi (2003), their results show a long-term effect but no short-term effect.

The story is different if an increase in product market competition is considered. In the Blanchard and Giavazzi model, firms are then facing more elastic demand associated with a lower markup in the short run. This, in turn, leads to both an increase in real wages and a fall in unemployment. In the long run, profits come back to their initial level, as do unemployment and wages. Using a general equilibrium model, Gersbach and Schniewind (2001) evaluate the final effect of promoting product market competition, without any distinction between short-run and long-run impact. They find a decline in the aggregate unemployment rate (although the unemployment rate can rise in some sectors). Amable and Gatti (2001) consider an increase in product market competition in a model of monopolistic competition with an endogenous determination of worker flows in and out of unemployment. Product market reform boosts the hiring rate as well as the separation rate, which can lead to a negative effect on unemployment depending on wage rigidities in the labor market.

The empirical findings are in line with the theory and point to a decrease in unemployment (Amable et al. 2011, Bassanini and Duval 2006a, De Serres et al. 2012, Griffith et al. 2007) and an increase in employment (Berger and Danninger 2007, Boeri et al. 2000, Fiori et al. 2007, Nicoletti et al. 2001, Nicoletti and Scarpetta 2005) if the product market is deregulated. Gal and Hijzen (2016) and Bordon et al. (2016) evaluate the impact over time and find a positive and increasing effect in the long run. The methodologies and results are summarized in Table 1.

Depending on the type of product market deregulation implemented by governments, the expected impact on labor market outcomes can differ. Papers distinguish between state controls (e.g., public ownership), barriers to entrepreneurship (e.g., administrative burdens, regulatory opacity, and barriers to entry), and barriers to trade [e.g., barriers to Foreign Direct Investment (FDI)]. Regarding government interventions, results are contrasted. Although some papers find a negative but not statistically significant impact of state control on employment (Boeri et al. 2000, Berger and Danninger 2007), Fiori et al. (2007) find a statistically significant positive relationship. Nicoletti and Scarpetta (2005) analyze the nonagricultural business employment rate (excluding public employment) and find a negative and statistically significant effect of public ownership. This implies that employment shifts, at least partially, from business to public sector as a result of an increase in public ownership. Regarding barriers to entrepreneurship and barriers to trade, the evaluated impact is always negative: more regulation would mean less employment (Fiori et al. 2007, Berger and Danninger 2007) even if the effect is sometimes not statistically significant (Boeri et al. 2000).

Labor market factors, that is, union density, employment protection, replacement rate, and active labor market policies, are also at the core of unemployment researches. In this paper, we are particularly interested in EPL which aims to protect workers against abusive dismissals and provides (financial) compensation for the income loss associated with dismissals. Flexibility of employment protection is considered to be essential for rapid adjustments in the workforce to changing economic conditions and to reallocate labor toward more productive activities.

In theory, more stringent EPL is modeled through an increase in the cost of firing staff. A priori, labor demand is thus negatively affected: firms reduce their hiring rates and unemployment increases (Cahuc and Zylberberg, 1996, Bassanini and Duval 2006b). To compensate for higher dismissal costs, firms offer lower wages. However, severance pay can be seen as an additional income for workers. If workers are risk neutral, it does not matter if the income is coming from wages or severance pay. Wages adjust, and the unemployment rate is not affected (Burda 1992). On the other hand, as the hiring rate declines, the average time job seekers spend in unemployment before finding a new job increases and unemployment becomes more costly.

Workers are more willing to accept lower wages to maintain their jobs, and labor market equilibrium is restored (Blanchard 1999). As a result, employment protection lowers labor turnover (both hiring and layoffs) and extends the duration of unemployment. The net effect on the aggregate unemployment rate remains ambiguous.

Labor market deregulation through less stringent EPL can provide different results. In the short run, it leads to lower wages and thus higher profits for firms. It either has no effect on unemployment (Blanchard and Giavazzi 2003) or initially increases layoffs more than it creates jobs and thus increases unemployment (Cacciatore et al. 2016). In the long run, higher profits attract new firms which hire new workers and thus the unemployment rate drops.

Empirical estimates on the potential impact of EPL on (un)employment vary. Although some papers find a positive effect of EPL deregulation on employment (Bordon et al. 2016, Berger and Danninger 2007, Boeri et al. 2000, Fiori et al. 2007) and a fall in unemployment (De Serres et al. 2012), others find a statistically insignificant impact (Kugler and Pica 2008, Bassanini and Duval 2006a, Belot and Van Ours 2004, Amable et al. 2011, Nicoletti and Scarpetta 2005) or even a negative impact on employment (Malk 2013). Studying 20 OECD countries during the period 1960–1999, Baker et al. (2002) find that a large part of unemployment movements was mainly due to country-specific effects rather than institutional factors such as EPL. In sum, the empirics do not provide unambiguous results that could justify prescriptions for labor market deregulation. A detailed summary of the results and the estimation methods are provided in Table 1.

Employment protection reforms can be implemented either on regular or on temporary contracts and thus have different impacts on labor market outcomes. Bassanini and Duval (2006a) point out that a statistically insignificant aggregate impact of EPL on unemployment may mask two opposite effects. On the one hand, regulation on permanent contracts implies upward pressure on unemployment with a positive coefficient in the unemployment equation. On the other hand, stricter rules for temporary contracts can induce downward pressure on unemployment and a negative coefficient. However, both effects disappear when Spain is removed from the sample (Spain undertook the deepest reforms on permanent contracts over the period 1982–2003) and thus the empirical findings are not particularly robust. In a study of 21 OECD countries over the period 1985–2007, De Serres et al. (2012) also found a positive but not statistically significant impact of permanent contract regulation on unemployment and a statistically insignificant negative effect of the share of temporary contracts on unemployment. By contrast, when analyzing the change in employment, Berger and Danninger (2007) estimated a negative and statistically significant effect of regulation for all types of EPL but with a larger impact for permanent contracts and protection against collective dismissals than for temporary contracts.

The difference between the levels of regulation for both types of contracts can also be crucial in determining the potential variation of unemployment. A stricter protection for permanent contracts compared to temporary contracts could raise the share of temporary contracts. However, this conclusion also depends on the initial level of regulation. If employment protection is initially strict for both types of contracts, a weakening in rules for temporary contracts would raise the share of temporary contracts (Boeri et al. 2000). The reform of temporary contracts in Spain in 1984 is a good illustration since the use of fixed-term contracts dramatically increased from 10% at the beginning of the 1980s to 35% in the 1990s.

Women, young workers, old workers, and the low-educated people are considered as vulnerable groups in terms of employment. A large share of those types of workers is either inactive or unemployed (Figure 1). The unemployment literature has widely studied the reasons behind their weaker attachment to the labor market.

Figure 1

Unemployment among young people appears to be one of the most highly sensitive variables in the labor market. It is directly linked to gross domestic product (GDP) growth: the youth unemployment rate falls during booms and rises during recessions. In addition, young workers are frequently mismatched in their employment (Shimer 2001). The employment process thus implies considerable searching and job changing before settling into a more or less permanent contract. In 2016, on average across European countries, 45% of the 15–24-year-old salaried workers had a temporary contract compared to 14% of the category aged 25–49 years. Job match improves with age, and older workers are often protected against job loss by seniority rights because they have built-up skills through experience. Despite job protection and the lower average unemployment rate, the possibilities of finding a new job decline with age. The net effect is that the long-term unemployment rate is higher for older workers. In 2016, 60% of the unemployed workers over 50 years had been disconnected from the labor market for more than 12 months in Europe. This rate was 28% for the age group of 15–24 years and 47% for the age group of 25–49 years.

In spite of the rise in their participation rate, from 52% in 1998 to 59% in 2016, there are still less women in the labor market than men, with a gap in the activity rate of 11 percentage points in 2016. As emphasized by Jaumotte (2004), education, the functioning of labor markets, and cultural attitudes (access to childcare, parental leave, integration) remain important determinants of female participation. Analyzing 18 OECD countries over the period 1980–2007, Thévenon (2013) finds that childcare services, maternity leave, and tax policies remain the most important drivers of increased female participation in the labor market.

Whatever the age or gender considered, unemployment is concentrated among those with the lowest level of education. Moreover, a large part of the increase in unemployment in Europe is due to a rise in joblessness among the low-skilled workers. The reason is a fall in demand for low-skilled workers. Competition from countries with low labor costs and technological progress are two factors often cited to explain labor demand shrinkage. However, as emphasized by Dolado et al. (2000), raising the educational attainment of the labor force does not always solve the unemployment problem unless other labor market rigidities are reduced.

Among the wide range of literature on product and labor market regulations, only very few articles have considered their impact on the unemployment rate for different categories of individuals. Gal and Theising (2015) point out that low-educated people, the young, and the elderly tend to be more affected by structural reforms. They study EPL in particular and find an heterogeneous impact on various segments of the population. In their analysis, stricter regulation reduces employment for women and low-educated workers and pushes up employment for highly educated individuals. Bassanini and Duval (2006b) also find contrasting results depending on the type of workers, with a decrease in employment for young workers but an increase for older workers. As emphasized in the OECD (2004)Employment Outlook, by reducing turnover, employment protection reduces the job prospects for those with relatively weak attachment to the labor market, such as young workers and women. Those opposing effects may explain the difficulty in finding a robust impact of EPL on aggregate unemployment since the impact depends on the composition of the working-age population in terms of skills and demographic characteristics. PMR seems to affect women more than men. Studying the impact of PMR on the employment rate for 20 OECD countries over the period 1982–2003, Bassanini and Duval (2006b) estimate a statistically significant negative effect for women but no statistically significant impact for men. De Serres et al. (2012) provide similar results by studying the unemployment rate: a stricter regulation implies a higher unemployment rate for women but not for men. Those two articles also find that the impact depends on the age of workers: PMR affects older workers positively, through an increase in their employment rate (Bassanini and Duval 2006b), but affects young people negatively, through an increase in the unemployment rate (De Serres et al. 2012).

The baseline regression using year and country fixed effects provides a positive coefficient for PMR equal to 3.45 (Table 2, column 3). Any deregulation in the product market thus implies a reduction in the unemployment rate. More precisely, a drop in the PMR index by 1 standard deviation (0.45) is associated with a predicted drop of 1.5 percentage points of the unemployment rate. The magnitude of the effect seems particularly high. Nevertheless, descriptive statistics

See Table S2.

By contrast, deregulation of the labor market measured by a reduction in the EPL index by 1 standard deviation (0.46) was associated with a predicted increase in the unemployment rate by 3.1 percentage points. When we consider the average level of deregulation (a decrease of 0.06 of the EPL index), the predicted unemployment rate should increase by 0.4 percentage point. Between 2008 and 2013, the EPL index fell on average by 0.13 point which is associated with a predicted increase in the unemployment rate by 0.9 percentage point. Deregulation in the labor market took place in the very last period of our sample, so that the estimated impact could be a short-run effect of deregulation. This result is in line with the findings of Cacciatore et al. (2016) and Bordon et al. (2016) who show that deregulating the labor market could be detrimental to unemployment in the short run while a positive impact (i.e., a reduction in the unemployment rate) occurs only in the long run. This result could have an incidence on the decision of policymakers to implement or not a labor market reform. Usually, as they have a defined mandate of few years, they will be less inclined to implement labor market reforms. This statement could explain why we do not observe a clear trend in deregulation for the labor market.

To test this hypothesis, we excluded from the sample countries which implemented the largest labor market reforms at the end of the period, namely Portugal, Greece, Spain, and Italy (Table 3). Although the coefficient of PMR remains the same, even if slightly lower, the effect of employment protection on the unemployment rate is reversed, that is, deregulating the labor market is now beneficial to reduce the unemployment rate. As this specification should better capture the long-run effect of labor market deregulation, results confirm the hypothesis of a negative short-run effect but a positive long-run effect.

Another potential explanation of the negative relationship between EPL and the unemployment rate is interaction between labor market and PMR. Most countries deregulated their product markets, which led to a low PMR index, ranging from 0.91 (the Netherlands) to 1.74 (Greece) in 2013. According to Amable et al. (2011), with low levels of PMR, employment protection yields a positive and statistically significant effect on employment (and thus potentially a reduction in the unemployment rate). Other papers (Fiori et al. 2007, Nicoletti and Scarpetta 2005, Griffith et al. 2007) show similar results. Reducing PMR is more beneficial in terms of employment when the labor market is highly regulated. Adding an interaction term in our baseline regression confirms results provided by Amable et al. (2011): deregulating the labor market is detrimental to unemployment only when PMR level is already low. However, as long as we exclude Portugal, Greece, Spain, and Italy from the regression, there is no longer statistically significant impact for the interaction term, while the individual effects of EPL and PMR remain. The estimated interaction between both types of deregulation could then also be a short-run effect rather than a long-run effect.

The positive and statistically significant coefficient of PMR can hide opposite effects. As shown in Table 4, the regressions taking the three types of PMR into account support this statement. Government interventions through public ownership and involvement in business operations do not appear to be detrimental to the unemployment rate. A decrease in state control by the average level of reform observed during the period (-0.32) is associated with a predicted rise in the unemployment rate by 0.6 percentage point. This effect seems to come from price controls and command and controls rather than public ownership. Although the literature on this topic is contradicting, some papers also find state controls to be beneficial to employment (Fiori et al. 2007) or statistically insignificant (Boeri et al. 2000, Berger and Danninger 2007).

The other two components of PMR have a positive coefficient. A reduction in barriers to entrepreneurship (average level of reform of -0.36 over the period) is associated with a statistically significant reduction in the predicted unemployment rate by 1.4 percentage point. Simplifying regulatory procedures and reducing administrative burdens on startups have a larger effect than reducing the protection of incumbents (e.g., by removing legal barriers, antitrust exemptions, and other barriers to entry). Barriers to trade and investment also have a positive but smaller coefficient. A drop by 0.18 (the average level of reform over the period) is associated with a decline in the predicted unemployment rate by 0.3 percentage point.

The EPL can be divided by types of contract (regular or temporary). For regular contracts, employment protection can refer to individual or collective dismissal costs. We estimate the specified unemployment equation for the three types of EPL. Results are presented in Table 5. Although the aggregate EPL index has a negative coefficient, the subdivision shows that this is only reflected in individual dismissal costs and regulation on temporary contracts. The largest effect occurs for individual dismissals. Less stringent protection (a fall in the index by on average 0.08) is associated with an increase in the predicted unemployment rate by 0.7 percentage point.

To a lesser extent, a lower rate of regulation in the use of temporary contracts (-0.07 on average) would also raise the unemployment rate by 0.1 percentage point. Regulation of temporary contracts includes rules for fixed-term contracts (valid cases for the use of fixed-term contracts, maximum number of successive fixed-term contracts, and maximum cumulated duration of successive fixed-term contracts) as well as rules for temporary work agency employment (types of work for which temporary work agency employment is legal, restrictions on the number of renewals, maximum cumulated duration, and equal treatment of regular and agency workers at the user firm).

Deregulation in EPL for collective redundancies, on the contrary, appears to reduce unemployment. However, decrease in the rigidity of rules for collective redundancies (such as specific requirements, delays, and costs to employers) has been very limited over the period, meaning that the average level of reform (-0.03) is predicted to have induced only a slightly reduction in the unemployment rate by 0.05 percentage point.

Since aggregate results were different when excluding some countries, we also tested the estimation of subcomponents of EPL without Portugal, Greece, Spain, and Italy. Interestingly, coefficients of individual dismissals and temporary employment become not statistically significant, such that different level of regulation has no incidence on the unemployment rate. The only remaining effect is coming from collective dismissals which keep a positive and highly statistically significant coefficient. In other words, even after controlling for countries which implemented the largest labor market reforms during the period, reducing protection against collective dismissals still remains beneficial to decrease the unemployment rate.

See Table S3

Based on the unemployment rates for different categories of workers, we estimated the impact of PMR and EPL using fixed-effects regression.

Endogeneity tests also show no evidence of reverse causality for different types of workers. As a result, only the fixed-effect estimation is presented in this section.

The results, presented in Table 6, show the effects in similar directions across types of workers. All estimated regressions provide a negative coefficient for EPL, meaning that deregulation raises the unemployment rate and a positive coefficient for PMR which implies that deregulation reduces the unemployment rate. The magnitude of the coefficients differs. Analysis by gender shows a larger effect of structural reforms on women: a reduction by 1 standard deviation of PMR reduces the female unemployment rate by 1.7 percentage points against only 1.5 percentage points for men. In the case of employment protection reforms, a decrease by 1 standard deviation raises the unemployment rate by 3.3 percentage points for women and 2.8 percentage points for men. Nevertheless, for both structural reforms, coefficients for men and women are not statistically different for men and women.

Subdivision of workers by age indicates that the impact of deregulation in EPL on the unemployment rate is larger for young workers. Reduction in the strictness of employment protection increases the unemployment rate by 6 percentage points for 15–24-year-old workers, against 3.2 percentage points for 25–49-year-old workers, and 2.8 percentage points for workers older than 50 years. Although young workers are the most affected, coefficients between the two other age categories are not significantly different. Moreover, no statistical differences are observed in terms of product market deregulation.

The three levels of education are equally impacted by reforms in EPL (the coefficients are not statistically different). Deregulation by 1 standard deviation pushes up the unemployment rate by 2.7 percentage points on average. The effect of product market reforms does not differ between low- and middle-educated individuals either, but is significantly lower for highly educated workers. Although deregulation in product market reduces the unemployment rate by 2.2 for low-educated workers and by 1.6 percentage points for middle-educated people, the unemployment rate falls by only 0.6 percentage points for highly educated workers.

Results on subcomponents of regulation for different types of workers provide similar results as the aggregate effect (Table 7). Moreover, coefficients for all workers and for all subcomponents remain of the same sign than the baseline regression with the total unemployment rate. In terms of gender, the magnitude of the effect is equivalent for all types of regulation except for state control for which the effect is greater among men than among women. However, the difference is significant only at 90%. The decomposition by age shows that results on the aggregate EPL index hold only for individual dismissals and not for collective dismissals and temporary employment. For those two types of regulation, results are not statistically different for the three age categories. In terms of PMR, younger workers are slightly more impacted than older workers for state controls and barriers to trade and investment. Finally, the analysis by level of education shows that results for the aggregate index hide some opposing effects. For individual and collective dismissals, middle-educated workers are significantly more impacted than highly educated workers. On the other hand, regulation on temporary contracts has a higher effect on low-educated workers. Regarding PMR, we see that highly educated workers are significantly less affected by all types of regulation. Although, on the aggregate index, low- and middle-educated workers are equally impacted, the effect of barriers to entrepreneurship seems to slightly affect more low-educated workers than middle-educated workers.