1. bookVolume 9 (2020): Issue 1 (March 2020)
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Employment protection legislation, labor courts, and effective firing costs

Published Online: 30 Mar 2020
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Journal Details
License
Format
Journal
First Published
30 Apr 2019
Publication timeframe
1 time per year
Languages
English

In many countries, labor courts play a central role in the determination of firing costs by monitoring and supervising the procedures for dismissals, and, eventually, deciding severance payments mandated by the employment protection legislation (EPL). To get some insights about the impact of labor courts on effective firing costs, we explore a new database that contains information on labor courts’ intervention in firings before and after the implementation of significant EPL reforms modifying severance payments and procedures for dismissals. Our results suggest that labor court rulings on economic dismissals did not fully translate the reduction of firing costs mandated by the new EPL to effective firing costs.

Keywords

JEL Classification

Introduction

Labor market institutions are considered key determinants of the functioning of the labor market and, hence, of economic performance (Blanchard and Wolfers, 2000, Botero et al., 2005, Turrini et al., 2014, OECD, 2019). A less studied issue is, however, how enforcement of regulation by the judicial system affects labor market outcomes.

In the case of employment protection legislation (EPL), labor courts play a central role. EPL mandates procedural rules for the resolution of firings. These rules create some room for strategic behavior by employers and fired employees, which is even more pronounced when, as happens in many countries, there is the possibility of settlement before labor courts intervene. Hence, the intervention of labor courts determines effective firing costs, both for cases settled out-of-the courts and those ruled by judges (see Daughety and Reinganum, 2012). In sum, effective firing costs depend both on severance payments established by EPL and costs associated with litigation.

Judges are neither neutral nor unbiased agents, but rather they seem to decide on labor conflicts with some “social motivation” (Bornstein and Miller, 2009; Posner, 2010; Feld and Voigt, 2003; Muñoz Aranguren, 2011; Danziger et al., 2011), which widens the scope for strategic behavior by employers and dismissed employees. For instance, in Italy, there is some association between local labor market conditions, such as the unemployment rate, and labor courts’ decisions (Macis, 2001, Ichino et al., 2003); in Germany, even after controlling for the fact that court activity varies systematically with the political leaning of the government that appoints judges, there is a significant positive relation between court activity and unemployment (Berger and Neugart, 2011); in the UK, unemployment and firms’ bankruptcy rates seem also to be statistically associated with the probability of judges deciding in favor of dismissed employees (Marinescu, 2011); and in Spain, labor courts’ rulings in dismissal conflicts are similar across neighboring provinces suggesting that judges are subject to some “peer effects” (Martín-Román et al., 2015).

With the goal of reducing firing costs in Spain, two EPL reforms in 2010 and 2012 changed procedural rules for economic dismissals (mainly by widening the definition of “fair economic dismissals”) and reduced severance payments for unfair dismissals.

Labour Reform Law of 2010, Royal-Decree-Law of 2011, and Labour Reform Law 2012.

The aim of this paper was to gauge to what extent changes in firing procedures mandated by these EPL reforms translated into changes in the effective costs of economic dismissals.

More broadly, the paper provides some empirical evidence to the view that the effects of EPL reforms aimed at reducing firing costs may depend not only on mandated severance payments but also on labor courts’ rulings on firing conflicts and expectations of the parties on these rulings. We do so by performing comparisons of the likelihood of settlements and labor courts’ rulings before and after the EPL reforms. Both differences are estimated conditioning on a set of covariates, mostly related to local labor market conditions, which control for the incidence and the selection of dismissal cases brought to labor courts’ resolutions. We find that (i) settlements increased after the reforms (in particular, after 2012) and (ii) despite the widening in the definition of fair economic dismissals, the probability of a labor court ruling a firing as fair did not significantly increase. Therefore, the main effects of the Spanish EPL reforms on effective firing costs took place through the reduction of severance payments, not as a consequence of the changes in procedural rules for economic dismissals.

First, we describe the particular features of Spanish EPL and its reforms in 2010 and 2012, and advance some propositions regarding the implications of the EPL reforms for settlements and labor court decisions (Section 2). Empirical analysis of these implications is given in Section 3. In the Appendix, we lay off a theoretical model of the determinants of effective firing costs that illustrates the main mechanisms we have in mind to rationalize propositions and to interpret empirical results. Finally, Section 4 concludes.

EPL: severance payments and procedural rules
Institutional framework

In Spain, terminations of regular employment contracts have to be justified either by the lack of performance of the employee (disciplinary layoffs) or by economic, technological, or organizational reasons (economic dismissals). Before 2010, economic dismissals were considered to be justified only in very restrictive cases and exclusively as a measure of last resource. A fair economic dismissal required the existence of negative economic conditions, but the law did not clarify what “negative conditions” meant, so the ambiguity of the definition gave judges a great deal of discretion. In 2010, there was a substantial extension of the conditions under which economic dismissals were justified, such as the incidence of current or anticipated losses, and a persistent decline in revenues that could jeopardize either firm’s economic viability or employment. The labor market reform of 2012 made further progress on the clarification of what negative economic causes meant referring to situations in which “for three consecutive quarters the level of revenues or sales of the company was lower than in the same quarters of the previous year”.

On the other hand, disciplinary layoffs are considered to be fair only in the cases of misconduct or lack of adaptation of the employee to the job tasks. Spanish EPL reforms in 2010 and 2012 did not substantially change the definition of fair disciplinary layoffs.

Fired employees may appeal to a labor court. In contrast with other countries, Spanish judges are not entitled to establish severance payments according to the characteristics of each individual case but only to declare the dismissal fair, unfair, or null. An out-of-court settlement stage prior to the file of the claim at the labor court is compulsory.

Employees dismissed under fair economic reasons are entitled to a severance pay of 20 days’ wages per year of seniority, with a maximum of 12 months’ wages. Employees laid off for fair disciplinary reasons do not receive severance pay. EPL reforms in 2010 and 2012 did not change the amount of severance pay for fair dismissals. If either the economic dismissal or the disciplinary layoff is ruled out unfair, firms either had to pay 45 days’ wages per year of seniority with a maximum of 42 months’ wages or had to reinstate the worker. After 2012, severance pay for all unfair dismissals/layoffs was reduced to 33 days’ wages per year of seniority with a maximum of 24 months’ wages.

Some employees (i.e., pregnant employees, employees enjoying reduced working time in order to take care of a child, trade union officials, employees who have filed a claim against the company, among others) are further protected against unfair dismissals/layoffs, so that firing them could be declared as null/void, and the employees are entitled to reinstatement and interim wages (those corresponding to the period between the dates of dismissal and reinstatement). Moreover firings may be ruled as null if there is discrimination (a violation of the fundamental rights of the employee) or breach of union rights. Hence, the termination of employment contracts under these circumstances implies specific negotiations, which can result in the payment of very high compensations.

In order to avoid legal proceedings, it is common to reach agreements of severance compensations between 50 and 60 days of salary per year of service, which are much higher than the ones stated by EPL.

Nevertheless, there are few cases of this nature brought to labor courts (see Palomo Balda, 2013).

Before 2012, the employer was entitled to dismiss an employee recognizing unilaterally its “unfairness” (termination without cause). Thus, termination was effective on the same date the dismissal was initiated and after the payment of the full severance for unfair dismissal. Hence, labor authorities (either judicial or administrative) did not intervene (this was usually called “express dismissal”, despido exprés in Spanish).

Nevertheless, the dismissed employee could still challenge the employer’s decision before labor courts by claiming that the dismissal was null/void.

The cost advantages of the so-called express dismissal for the employer were twofold. First, it avoided the red tape costs of legal proceedings. Second, it eliminated the payment of interim wages (salarios de tramitación) when the labor court ruled the dismissal unfair. After 2012, the so-called express dismissal was eliminated. Thus, the labor court intervention could no longer be avoided (in case of no out-of-court settlement), and interim wages for unfair dismissals and layoffs were reintroduced.

If the court ruling is notified exceeding 90 days since the lawsuit has been filed, the employer may claim from the Spanish Government the reimbursement of interim wages corresponding to the excess of that period (sentence of the Supreme Court of Spain of October 22, 2009).

Figure 1 sketches these firing regulations. Since the legal procedures for disciplinary layoffs were simpler and severance pay in case of unfair dismissal was the same than under economic dismissals, employers most frequently initiate firings alleging disciplinary causes. During 1984–2010, about 70% of dismissal cases resolved by labor judges’ rulings were declared unfair, with only a few of them being declared null.

Figure 1

Layoff procedure in the Spanish labor jurisdiction.

Source: Authors’ own elaboration.

Notes:

a. Out-of-court settlements are resolved in Spain by the “MAC” units (“Mediation, Arbitration and Conciliation Units”). The majority of out-of-court settlements resolved with an agreement between the employer and the employee end up with the effective firing of the employee. Settlements ended without an agreement are the main group of dismissal conflicts which arrive to the labor courts. Following the data of the Ministry of Employment and Social Security, there was a total of 220,095 out-of-court settlements in 2014, of which 101,426 ended with agreement between the employer and the employee.

b. In 2014, the number of dismissals resolved at the labor court was 118,225. This amount is calculated by adding the number of pre-trial settlements with agreement, the dismissals finally ruled by a labor court, and the number of cases withdrawn (including tacit withdrawals and voluntary dismissal of action by the parties).

c. The number of pre-trial layoff settlements in 2014 was 48,508.

d. In 2014, the number of dismissals resolved at the trial level in the labor courts was 42,992, of which a 78% were dismissals ruled as “unfair” (in favor of the employee).

e. In 2014, 26,725 dismissals were withdrawn (thus, they were not resolved by a judge in a trial) as a result of formal failures, tacit withdrawals, and voluntary dismissal of action by the parties.

It is also important to bear in mind that there are two alternative ways to terminate an employment contract besides individual firings. Since 1984, Spanish policy-makers, facing strong opposition to change EPL under regular employment contracts, introduced employment flexibility at the margin by creating a wide array of “atypical” contracts.

See Bentolila et al. (2012). There is an extensive literature documenting the negative effects of dualism in the Spanish labor market (among others, García-Serrano, 1998; Bentolila and Dolado, 1994; Bentolila et al., 2008; and Wölfl and Mora-Sanguinetti, 2012). For a recent survey, see Bentolila et al. (2019).

Regulation of these types of contracts changed several times and in fundamental ways, but segmentation between permanent and temporary employees, which began in the late 1980s, has prevailed since then. While regular employees are entitled the right to go to court to appealing the cause of the dismissal and may get higher severance payments in the case of unfair dismissals, temporary employees did not have the right to appeal the termination of their contracts. Hence, employers use fixed-term contract and other kinds of temporary contracts (nowadays amounting to more than 25% of employment) to buffer against negative shocks leading to downsizing of their labor force (Costain et al., 2010). Additionally, economic dismissals may be implemented collectively, and it is obliged to do so when they affect to more than 10% of the firm’s labor force in a given quarter. Firing costs under collective dismissals are typically higher than for individual dismissals/layoffs.

Some hypotheses on the effects of EPL reforms on litigation

Given the Spanish institutional framework, employers take three decisions when considering firings: (i) when to initiate a firing, (ii) whether to justify the firing as an economic dismissal or as a disciplinary layoff (notice that the employer could initiate a firing as a disciplinary layoff even if the true cause is economic and vice versa; we will refer to these cases as disguised dismissals), and (iii) under what circumstances to reach a settlement before the labor court ruling. Similarly, the dismissed employee also has to decide whether to reach a settlement or to litigate.

After the firing is initiated by the employer, the dismissed employee has to decide to appeal or not to a labor court. Since the cost of doing so is almost nil and the expected gains strictly positive, this decision is trivial.

Finally, judges rule those cases that are not settled following the EPL mandate. For employer and employee decisions, expectations about the sign of labor court rulings (fair or unfair) play a crucial role. For the employer, these expectations determine when a settlement is less costly, the relative cost of initiating the firing as a economic dismissal versus as a disciplinary layoff, and, hence, effective firing costs, which, themselves, determine when to initiate a firing. Similarly, the expectations of the fired employee on the labor court ruling determine his or her acceptance of a settlement.

There is a large literature on settlements and litigation, developed after the seminal work by Priest and Klein (1984) who argued that, because of selection effects, the percentage of litigated cases won by plaintiffs will not vary with legal standards. Thus, EPL reforms would not have any effect on the proportion of labor court ruling in dismissals/ layoff conflicts. However, a more formal analysis rejects the so-called “No Inference Hypothesis”: Klerman and Lee (2014) concluded that “even taking selection effects into account, one may be able to make valid inferences from the percentage of plaintiff trial victories, because selection effects are partial”. They also proved that, under plausible conditions, a change in the law ought to increase labor court rulings in favor of the party that wins more from it. Hence, changes in legal standards affect both the incentives to litigate and the expectations of the agents of outcomes of litigation, but not the extent to eliminate any effect on labor court rulings.

In the Appendix, we formally lay out a simple model of firing conflicts, similar to Klerman et al. (2018) but with some modifications to adapt it to the Spanish institutional context. From simple analysis of the comparative statics of the model, we conjecture the following effects of the Spanish labor market reforms on settlements and labor court rulings.

Proposition 1Reducing severance payments and red tape costs for fair economic dismissals leads to more firings initiated as economic dismissals and to less firings disguised as disciplinary layoffs, and diminishes effective firing costs of truthful dismissals. Assuming that judges’ behavior and employers’ and workers’ expectations on the probability of ruling economic dismissals as fair are unchanged, the incidence of settlements does not change and the proportion of labor court rulings declaring firings as fair increases.

Proposition 2Reducing severance payments and red tape for unfair dismissals leads to more firings disguised as disciplinary layoffs, and diminishes effective firing costs of truthful and untruthful dismissals. Assuming that judges’ behavior and employers’ and workers’ expectations on the probability of fair rulings are unchanged, the incidence of settlements does not change, and the proportion of labor court rulings declaring firings as fair decreases.

Proposition 3Widening the fair causes of economic dismissals yields more firings being initiated as economic dismissals, and to less disguised dismissals as disciplinary layoffs, decreases the incidence of settlements and effective firing costs for truthful economic dismissals, and increases the likelihood of a fair ruling. Settlements are less likely insofar as employers update upward their expectations on the probability of fair rulings, while the update in workers’ expectations is likely to be smaller because of asymmetric information about firm’s profits.

Proposition 4Lower firm profitability leads to more economic dismissals be initiated as such, and to less firings disguised as disciplinary layoffs, and lower effective firing costs. Settlements are less likely insofar as employers update upward their expectations on the probability of fair rulings, and worker’s update in their workers’ expectation is likely to be smaller because of asymmetric information about firm’s profits.

Proposition 5Worsening of local labor market conditions leads to less economic dismissals be initiated as such and to more disguised dismissals as disciplinary layoffs and raises effective firing costs. It also leads to less disciplinary layoffs, since workers shirk less when alternative employment opportunities decline. Settlements are unchanged insofar as updates of probabilities of a fair ruling are the same for employers and for workers.

In what follows, we turn to the data available to provide either confirmation or rejection of propositions above.

EPL reforms, settlements, and labor court rulings
Data

There are 345 labor courts operating in Spain. Geographical distribution is uneven and largely reflects population and firm density. Thus, there are 44 courts in the province of Barcelona, 43 in the province of Madrid, and only one or two in other 11 provinces.

There are 50 provinces corresponding to the Nomenclature of territorial units for statistics (NUTS3) level of disaggregation by Eurostat.

Each labor court is served by a single judge, and there are 348 court clerks.

This circumstance is relatively exceptional in an international context, since it is only found in three other OECD countries, Portugal, Turkey and Chile (see OECD, 2013).

Statistical information about EPL enforcement is extremely scarce.

International surveys (CEPEJ, 2018; the OECD Civil Justice Project; Palumbo et al., 2013; or the World Bank Doing Business) provide some information, mostly of qualitative nature, about labor court intervention on firings conflicts.

With information on labor court activity provided by the Spanish General Council of the Judiciary (Consejo General del Poder Judicial, henceforth CGPJ), we constructed a new database that allows to identify some of the determinants of labor court rulings. Our database is composed of 154,962 observations over the period 2004Q1–2015Q2.

The unit of observation is the labor court. Data include labor court’s rulings on firing conflicts, i.e., if it was resolved in favor of the plaintiff (the employee) or the defendant (the employer) and refers to individual dismissals ruled by the first instance of the labor jurisdiction.

Dismissed workers can only claim against the employer at a first-instance labor court located in the province where he or she is employed. If there are several labor courts in the province, workers cannot choose among them since conflicts are assigned according to predetermined rules. The rulings of first-instance labor courts may be appealed, but appeals are infrequent. Thus, by restricting our analysis to the first-instance labor court rulings, we are not excluding a significant number of cases that could be overturned at higher instances.

Unfortunately, we cannot observe whether litigation was over an economic dismissal or a disciplinary layoff. Information on employer/employee’s characteristics is not available. As for labor courts’ characteristics, we observe the type of judge ruling on the dismissal conflict, that is, whether he or she is assigned to a particular court or appointed as a temporary replacement, reserve or substitute of the former. Additionally, we also compute a measure of congestion at labor courts.

Following García-Posada and Mora-Sanguinetti (2015), the congestion rate at each province and quarter is defined as the ratio between the sum of pending cases (measured at the beginning of the quarter) plus new cases in a specific quarter and the cases solved in the same quarter. In Spain, this ratio is frequently above one.

As for settlements, they take place at two stages. First, there is an out-of-court settlement stage that is compulsory at the so-called mediation, arbitration and conciliation units before the file of the claim in the labor court. Second, settlements may also occur at the labor courts before the judge’s ruling. For each labor court, we observe a settlement ratio computed as the proportion of settlements within all the firing cases brought at labor courts.

Since local labor conditions affect the number of firing conflicts and labor court rulings (see the Appendix), we also collect information on the provincial unemployment rate (in deviations with respect to the sample mean), the sectoral composition of activity in the province (relative employment weights of agriculture, industry, construction and services sectors), and the temporary employment rate (proportion of employees with fixed-term contracts out of the total number of employees), the presence of big firms, the incidence of collective dismissals (Expediente de Regulación de Empleo (EREs) in the Spanish legal terminology), and firm profitability. The presence of big firms in the province (per year) is calculated as the proportion of companies with more than 200 workers over the total number of companies according to the information collected by the Central Business Register (DIRCE) of the National Statistics Institute.

This variable may proxy for the potential effect of trade unions at supporting workers’ claims and settlements of labor courts.

As for the incidence of collective dismissals, we use the number of collective dismissal files and the number of workers affected, from data registered at the Ministry of Employment and Social Security. Firm profitability is measured by the lowest decile in the distribution of the return on assets (ROA) at each province using as a source the Bank of Spain Central Balance Sheet database. Conceivably, firms with lower profitability are most likely to initiate economic dismissals.

Table 1 provides the data definitions and sources. Table 2 displays the descriptive statistics before 2010, 2010–2012, and after 2012.

At the aggregate level, the proportion of economic dismissals over all firings increased up to 2013 to decline afterward (see Figure 2).

The proportion of firings declared as fair by labor courts is on average 25.9% for the whole sample and decrease from 27.3% before 2010 to 25.8% in 2010–2012 and 22.7% after 2012, with noticeable differences across provinces (see Figure 3 and Table 3). Also interestingly, this proportion is negatively correlated with the local unemployment rate (see column 3 in Table 5). We interpret this correlation as an indication that the local unemployment rate affects directly labor court decisions (see Appendix).

Definitions of variables and sources of data

VariableDefinitionScale/UnitPeriodSource
Court rulingsPercentage of labor court judgments ruling that the dismissal was fair or justified%By court, 2004–2015CGPJ
D1 (Reform 2010)Period of enforcement of the 2010 labor market reformDummy2004–2015Self elaboration
D2 (Reform 2012)Period of enforcement of the 2012 labor market reformDummy2004–2015Self elaboration
Unemployment ratePercentage of total workforce which is unemployed and is looking for a paid job (in differences from the average)%By province, 2004–2014Spanish National Statistics Institute (INE)
ProfitabilityReturn on assets (ROA) for the 10% of firms with a lower ROA%By province, 2004–2013Banco de España
Temporary employment ratePercentage of total workforce which has a fixed-term contract%By province, 2004–2014Spanish National Statistics Institute (INE)
Log of the number of workers under collective dismissalsLogarithm of the number of workers affected by collective dismissalsLogarithmBy province, 2004–2014Ministry of Employment and Social Security
Proportion of companies with more than 200 employeesProportion of companies with more than 200 employees over the total number of companies%By province, 2004–2014Spanish National Statistics Institute (INE)
Employment share of servicesPercentage of total workforce working on services sector%By province, 2004–2014Spanish National Statistics Institute (INE)
Employment share of industryPercentage of total workforce working on services sector%By province, 2004–2014Spanish National Statistics Institute (INE)
Employment share of constructionPercentage of total workforce working on services sector%By province, 2004–2014Spanish National Statistics Institute (INE)
Proportion of dismissal lawsuits analyzed (+) byPercentage of labor court judgments ruling that the dismissal was fair or justified%By court, 2004–2015CGPJ
professional judges over totalby professional judges over all the dismissal lawsuits analyzed by all judges
Proportion of days with temporaryProportion of days per 365-days a year with positionsFractionBy court, 2004–2014CGPJ
positions at the labor courts per year Judicial congestion rate (dismissals lawsuits)at the labor courts held by interim judges Ratio between the sum of pending cases in a labor court plus new cases and the cases resolved in the same quarterFractionBy court, 2004–2014CGPJ
Judicial congestion rate (pre-trial settlements)Ratio between the sum of pending settlements in a labor court plus new settlements and the settlements resolved in the same quarter%By court, 2010–2015CGPJ
Out-of-court settlements ratioRatio of the number of out-of- court settlements divided by the sum of those settlements and the total number of dismissal lawsuits%By court, 2004–2015CGPJ

Source: Authors’ own elaboration.

Descriptive statistics

VariableBefore 20102010–2012After 2012
ObsMeanStd. Dev.MinMaxObsMeanStd. Dev.MinMaxObsMeanStd. Dev.MinMax
Court rulings7,4440.27300.1362014,0250.25820.118000.81823,3900.22680.114401
Unemployment rate (in differences)8,328–0.05170.0496–0.13640.13974,1640.05700.0638–0.08590.23722,4290.0910.0658–0.02710.2711
Profitability8,3280.03980.090300.81004,1640.00760.033800.37631,3880.14112527013.5382
Temporary employment rate8,3280.30890.08110.16280.59494,1640.24800.06190.13150.48632,4290.23870.06110.13250.5088
Log of the number of workers under collective dismissals6,9407.92811.71892.833211.75124,1649.20741.25555.46411.20393,4708.92391.37143.989010.9548
Proportion of companies with more than 200 employees8,5780.00170.000900.00404,1640.00150.00080.00030.00322,7760.00160.00080.00020.0032
Employment share of services8,3280.66850.07340.4380.8444,1640.74000.07190.5360.88902,4290.76060.07050.5840.888
Employment share of industry8,3280.16260.06350.0440.3694,1640.14040.05530.0320.34202,4290.13670.05570.0310.279
Employment share of construction8,3280.12060.02760.0580.2394,1640.07730.01770.0410.16702,4290.05890.01170.0330.109
Proportion of dismissal lawsuits analyzed (+) by professional judges over total8,3280.90230.1767014,1640.80360.2736013,4700.84740.250901
Proportion of days with temporary positions at the labor courts per year8,2320.00830.040800.54,1160.01300.051600.25562,7440.00560.034200.2556
Judicial congestion rate (dismissals lawsuits)8,3282.04860.48771134,1642.60380.81731.04448.19580
Judicial congestion rate (pre-trial settlements)8,32815015154,1646.641412.779002853,4706.47275.01710.54445.5116
Out-of-court settlements ratio8,3280.54220.182200.93104,1640.44440.167200.86621,3880.67190.14200.9021

Source: Authors' own elaboration.

Main descriptive statistics by province

Court rulingsUnemployment rate

Unemployment rate (national value) shows the average rate of unemployment for the full period. Provincial values represent differences from that national average.

ProfitabilityTemporary employment rateLog number workers under collective dismissalsProportion of companies with more than 200 employeesOut-of-court settlements ratio
National (full period)0.26030.16300.03980.28058.56920.00160.5258
Provincial deviations from the mean
ALMERIA–0.04990.0651–0.03980.1884–2.2744–0.0003–0.1314
CADIZ0.01380.1045–0.03980.0734–0.8296–0.00080.0163
CORDOBA0.04640.07970.01120.1339–1.8571–0.0008–0.0626
GRANADA0.00080.0719–0.02180.1137–1.7881–0.0008–0.0729
HUELVA–0.02560.07080.00820.1877–2.4510–0.0005–0.0397
JAEN0.03780.07340.15240.0942–1.2823–0.0010–0.0181
MALAGA–0.00250.0671–0.03980.0617–0.7456–0.0008–0.1051
SEVILLA0.00590.0594–0.01050.0997–0.5248–0.00020.0468
HUESCA0.0138–0.0616–0.0013–0.0300–1.9673–0.0010–0.4078
TERUEL0.0904–0.05920.0579–0.0414–1.7696–0.0008–0.4256
ZARAGOZA–0.0450–0.0350–0.0340–0.03550.62550.0001–0.3313
ASTURIAS0.0599–0.0184–0.0168–0.01850.5581–0.0004–0.1168
ILLES BALEARS–0.0159–0.0128–0.0398–0.0033–1.1640–0.0004–0.2505
LAS PALMAS–0.04790.0682–0.03490.0565–0.86500.00000.0090
SANTA CRUZ DE TENERIFE–0.07400.0469–0.02680.0523–1.0567–0.00030.0172
CANTABRIA0.0009–0.0396–0.0171–0.03210.0364–0.0004–0.1808
AVILA–0.11090.00360.1450–0.0120–2.4403–0.00120.0710
BURGOS0.0685–0.0400–0.0141–0.0599–0.4829–0.00010.0105
LEON–0.0226–0.01670.0074–0.0229–0.6166–0.0010–0.1287
PALENCIA0.1060–0.03070.0070–0.0552–1.2430–0.0006–0.1260
SALAMANCA0.0079–0.01320.0365–0.0260–1.9131–0.0009–0.1264
SEGOVIA0.0425–0.0445–0.0300–0.0474–2.6397–0.0009–0.0417
SORIA0.0364–0.0647–0.0183–0.0622–2.4441–0.00060.0631
VALLADOLID0.0287–0.02930.0131–0.02960.1799–0.0002–0.0310
ZAMORA–0.0164–0.00670.3171–0.0001–2.7065–0.0013–0.1014
ALBACETE–0.01050.02390.06350.0158–1.3802–0.0009–0.1099
CIUDAD REAL0.01800.02871.41230.0313–2.0382–0.0011–0.0253
CUENCA0.0355–0.01040.2768–0.0016–2.7461–0.00120.0532
GUADALAJARA–0.0221–0.02470.0173–0.0453–2.3618–0.0004–0.0141
TOLEDO–0.07840.01950.13940.0290–1.4898–0.0010–0.0018
BARCELONA–0.0314–0.0210–0.0398–0.08222.01480.00060.2197
GIRONA0.0312–0.0114–0.0398–0.0461–0.6995–0.00060.0870
LLEIDA0.0426–0.0583–0.0378–0.0818–1.6490–0.00080.1113
TARRAGONA0.0388–0.0122–0.0398–0.0108–0.8174–0.00040.0428
ALICANTE–0.09150.0230–0.03790.0601–0.0219–0.0010–0.0450
CASTELLON0.03610.0104–0.03790.0072–0.04950.00060.0519
VALENCIA–0.03220.0102–0.00210.01430.99550.0000–0.0730
BADAJOZ0.03510.06390.02580.1115–1.5900–0.0009–0.0961
CACERES0.05510.03500.02440.0670–2.0785–0.00110.1215
A CORUÑA–0.0189–0.02850.0163–0.0031–0.1954–0.00020.0172
LUGO0.0170–0.05490.0226–0.0118–1.9468–0.0011–0.0427
OURENSE–0.0377–0.0228–0.0017–0.0188–1.9869–0.0008–0.0868
PONTEVEDRA0.0148–0.0013–0.00150.02350.1738–0.00050.0079
MADRID0.0421–0.0391–0.0398–0.06631.48110.00180.0787
MURCIA0.00150.0148–0.01450.0802–0.6336–0.0001–0.0656
NAVARRA0.0138–0.06080.0626–0.03280.60250.00100.0541
ARABA/ALAVA0.0759–0.0559–0.0044–0.0537–0.03100.00060.0205
GIPUZKOA0.0417–0.07560.1014–0.04050.38290.00000.0660
BIZKAIA0.0111–0.0425–0.0398–0.02650.64340.0007–0.0242
LA RIOJA–0.0189–0.0416–0.0177–0.0561–1.0135–0.00090.0848

Source: Authors' own elaboration.

Determinants of settlements

Robust standard errors (clustered by provinces) in parenthesis.

123456

In column (6), Madrid and Barcelona are excluded.

2010 reform–0.107

p < 0.01

(0.0188)
0.0118 (0.0128)0.0148 (0.0209)0.0211 (0.0127)–0.139

p < 0.01

(0.0372)
–0.129

p < 0.01

(0.0447)
2012 reform0.208

p < 0.01

(0.0163)
0.118

p < 0.01

(0.0172)
0.261

p < 0.01

(0.0172)
0.124

p < 0.01

(0.0183)
0.244

p < 0.01

(0.0588)
0.201

p < 0.01

(0.0463)
Unemployment rate–1.274

p < 0.01

(0.132)
–0.467

p < 0.01

(0.166)
–0.849

p < 0.01

(0.156)
–0.696

p < 0.01

(0.156)
2010 reform

p < 0.1.

Unemployment rate
0.840

p < 0.01

(0.168)
0.777

p < 0.01

(0.183)
2012 reform

p < 0.1.

Unemployment rate
–0.532

p < 0.05

(0.222)
–0.375

p < 0.1.

(0.196)
Profitability0.0106 (0.0157)0.439

p < 0.01

(0.0956)
0.466

p < 0.01

(0.0893)
0.475

p < 0.01

(0.0886)
2010 reform

p < 0.1.

Profitability
–0.107 (0.132)–0.135 (0.153)
2012 reform

p < 0.1.

Profitability
–0.699

p < 0.01

(0.197)
–0.625

p < 0.01

(0.155)
Province fixed effectsYESYESYESYESYESYES
Other controls

Other controls include: temporary employment rate, sectoral distribution of employment, logarithm of the number of workers affected by collective dismissals, proportion of companies with more than 200 employees, proportion of dismissal lawsuits analyzed by professional judges, days of temporary positions at the labor courts per year, and judicial congestion rate.

NOYESNOYESYESYES
Observations13,88010,97613,88010,97610,9768,192
R-squared0.2010.5210.3400.5430.5730.535
# labor courts347343347343343256

Determinants of labor court rulings declaring dismissals/layoffs as fair

Robust standard errors (clustered by province) in parenthesis.

123456

In column (6), Madrid and Barcelona are excluded.

2010 reform 2012 reform–0.0012 (0.00598) –0.0339

p < 0.01

(0.00526)
0.0376

p < 0.01

(0.00807) –0.0065 (0.00605)
0.0426

p < 0.01

(0.00479) –0.0088 (0.00590)
0.0385

p < 0.01

(0.0080) 0.00003 (0.0065)
0.0120 (0.0197) 0.00126 (0.0214)0.0288 (0.0187) 0.00138 (0.0278)
Unemployment rate–0.467

p < 0.01

(0.0800)
–0.304

p < 0.05

(0.128)
–0.386

p < 0.01

(0.133)
–0.312

p < 0.05

(0.134)
2010 reform

p < 0.1. Clustered by province.

Unemployment rate
0.137 (0.0836)0.0680 (0.0776)
2012 reform

p < 0.1. Clustered by province.

Unemployment rate Profitability
–0.0036

p < 0.01

(0.0009)
–0.0530 (0.0570)–0.0102 (0.0892) –0.0181 (0.0550)–0.0161 (0.104) –0.0181 (0.0550)
2010 reform

p < 0.1. Clustered by province.

Profitability
–0.177

p < 0.05

(0.0817)
–0.234

p < 0.01

(0.0813)
2012 reform

p < 0.1. Clustered by province.

Profitability
–0.0317 (0.150)–0.0250 (0.151)
Province fixed effectsYESYESYESYESYESYES
Other controls

Other controls include: temporary employment rate, sectoral distribution of employment, logarithm of the number of workers affected by collective dismissals, proportion of companies with more than 200 employees, proportion of dismissal lawsuits analyzed by professional judges, days of temporary positions at the labor courts per year, and judicial congestion rate.

NOYESNOYESYESYES
Observations14.18110.20212.82510.20210.2027.586
R-squared0.0170.0550.0360.0580.0600.056
# labor courts343339343339339255

Figure 2

Proportion of economic dismissals over all dismissals.

Source: Spanish Ministry of Employment.

Figure 3

Percentage of labor court judgments ruling that the dismissal is fair.

Source: Authors’ own elaboration based on data provided by the CGPJ.

Empirical approach

Variation across time and labor courts with controls by labor court and provincial characteristics allows us to make inferences on the effects of EPL reforms on labor court rulings and on the incidence of settlements.

As discussed above, labor market reforms of 2010 and 2012 affected red tape costs and procedures of economic dismissals and disciplinary layoffs differently. Hence, the incidence of economic dismissals and disciplinary layoffs and the selection of both conflicts into settlements and litigation are likely to have changed as a result of the reforms. Given that we do not observe economic dismissals and disciplinary layoffs separately, we perform an event study (comparisons before and after) with a set of controls that proxy the incidence and composition (economic dismissals versus disciplinary layoffs) of firings. Thus, we regress the ratio of labor court rulings stating that the dismissal/layoff is fair and the proportion of settlements on time dummies that capture the entry into force of the EPL reforms and a group of relevant controls that vary by time (at the quarterly frequency), by labor court, and by province (also including fixed effects by province). All models are estimated both fitting a linear specification and odds-ratios (Bishop et al., 1975; Williamson et al., 1995).

We only report OLS results though, since estimated probabilities are not significantly different.

Errors in all models are clustered at the provincial level, and standard errors are robust to heteroskedasticity and autocorrelation.

Among the covariates, we specifically focus on the local (provincial) unemployment rate and the local (provincial) profitability of firms (the two variables that may directly influence judges’ decisions on economic dismissals according to our model), and interact both with the time dummies indicating the timing of the reforms. These interactions should capture by how much judges’ discretion on rulings changes with the EPL reforms.

Thus, we estimate

Yist=αs+k=1KδkXkist+β1D1+β2D2+β3Ust+β4Πst++β5(D1Ust)+β6(D1Πst)+β7(D2Ust)+β8(D2Πst)+εist$$\begin{align}& {{Y}_{ist}}={{\alpha }_{s}}+\sum\limits_{k=1}^{K}{{{\delta }_{k}}}{{X}_{kist}}+{{\beta }_{1}}{{D}_{1}}+{{\beta }_{2}}{{D}_{2}}+{{\beta }_{3}}{{U}_{st}}+{{\beta }_{4}}{{\Pi }_{st}}+ \\ & \,\,\,\,\,\,\,\,\,\,\,\,+{{\beta }_{5}}\left( {{D}_{1}}^{\star }{{U}_{st}} \right)+{{\beta }_{6}}\left( {{D}_{1}}^{\star }{{\Pi }_{st}} \right)+{{\beta }_{7}}\left( {{D}_{2}}^{\star }{{U}_{st}} \right)+{{\beta }_{8}}\left( {{D}_{2}}^{\star }{{\Pi }_{st}} \right)+{{\varepsilon }_{ist}} \\ \end{align}$$

where Yist is, alternatively, the settlement ratio and the proportion of labor court rulings declaring the dismissal/conflict fair at labor court i province s, and time t; Xkist is the set of controls that includes the proportion of employees with temporary contracts, the sectoral distribution of employment (agriculture, manufacturing, construction, and services), the proportion of establishments with more than 200 employees, the number of employees affected by collective dismissals (in logs), the proportion of dismissal conflicts ruled by professional judges, days covered by temporary judges at the labor court per year, and the judicial congestion rate at labor court i, province s, and time t; and Ust and Πst are, respectively, the unemployment rate and the lowest decile of the distribution of firm profit rates

ROA according to the Bank of Spain database.

at province s and time t. D1 and D2 are time dummies that take value one after the second quarter of 2010 and the first quarter of 2012, respectively, the dates at which reforms came into effect. Regressions also include fixed province effects, αs. Controlling by characteristics of labor courts (status of the judge, interim days at the labor court) should take care of changes that might have affected the rulings other than the EPL reforms.

Results

The main results are displayed in Tables 4 (settlements) and 5 (likelihood of a labor court ruling declaring the dismissal/layoff as fair).

While the 2010 reform led to some significant decrease in the likelihood of settlements, the 2012 reform had the opposite effect. Overall, the proportion of settlements is about 7% to 10% points higher after 2012 (columns 5 and 6). Settlements are less likely the higher the local unemployment rate and the lower firm profitability are. Interestingly, the association between the incidence of settlements and local unemployment became positive after the 2010 reform and negative again after the 2012 reform. Under our interpretation of the coefficients of these variables as the divergence between employer and employees expectations on labor court rulings, these results suggest that the reforms reduced this divergence both overall and, particularly, when local labor market conditions and firm profitability were worse.

It is also noteworthy that the judicial congestion rate increased the likelihood of settlements (not shown in Table 4).

Another conclusion from the estimated changes in the likelihood of settlements is that dismissal conflicts being solved by labor court trials after the reforms are those in which employers’ expectations on the probability of a fair ruling increased by more and above dismissed workers’ expectations. We cannot see why this should happen in the case of disciplinary layoffs (whose regulation was unchanged). Thus, by joining this to the observation that the overall proportion of firings initiated as economic dismissals was higher after the reform, we conclude that, if anything, the proportion of economic dismissals out of all firing conflicts solved by labor courts ought to have increased. An increase in the weight of economic dismissals being solved by trial in the labor courts and the broadening of the definition of fair causes of economic dismissals should weight positively in the likelihood of firings being ruled as fair by the labor courts.

However, Table 5 shows that the proportion of dismissals/layoffs being ruled as fair increased immediately after the 2010 reform but was not very much changed with the 2012 reform. In fact, under the most complete specifications (columns 5 and 6), neither of the two reforms seem to have a significant effect on the rulings. An increase in the unemployment rate of 10% points is associated with a decrease in the proportion of fair rulings of approximately 3% to 5% points. As for firm profitability, there is no statistically significant association with judges’ rulings, once that other covariates controlling for incidence and composition of firings are included Nevertheless, after the 2010 reform, it seems that judges’ decisions took more into account the economic situation of the firm, so that lower profitability led to a higher probability of a fair ruling (effect that is not observed after the 2012 reform, somehow surprisingly).

To better gage the impact of the EPL reforms on labor court rulings, in Figure 4, we plot the observed probability of a dismissal/layoff being ruled as fair by the labor court and the change in that probability due to EPL reforms and their effects through interactions with the local unemployment and firm profitability (using estimates from column 5 in Table 5). While this marginal effect increased immediately after the 2010 reform (but only by about 2.5% points), after the 2012 reform, it decreased by 3% points (although this negative effect was vanishing gradually up to 2015). With these results we conclude that effective firing costs were not significantly reduced by the widening of the scope for economic dismissals associated with the Spanish EPL reforms of 2010 and 2012.

Concluding remarks

Labor courts’ intervention on dismissal cases is key for the determination of effective firing costs. Since judges often behave as socially motivated agents and have some discretion in the application of EPL, the parties (employers and dismissed employees) act strategically taking into account the procedural rules for the initiation and resolution of dismissal conflicts. As a result, there are several channels by which EPL affects effective firing costs and the consequences of EPL reforms may be different than intended.

We analyze two significant EPL reforms in 2010 and 2012 than changed both severance payments and procedural rules in Spain to make economic dismissals less costly. Even though the proportion of economic dismissals over all firings increased, the average probability that a dismissal was declared fair by a labor court did not increase significantly, despite the widening of the fair causes of economic dismissals. By controlling for local labor market conditions, diminishing firm profitability, and reduction of severance payments for unfair dismissals, we identify the effects of EPL reforms on labor courts’ ruling on firing conflicts. We conclude that the reduction of effective firing costs in Spain after 2010 took place mainly because of the lower severance payments for unfair dismissals and less so due to the extension of the fair causes of economic dismissals.

This conclusion has three implications for the policy debate on the need of introducing further labor market reforms. One is that the reduction in effective firing costs has been lower than the one intended by the legislated EPL reforms. Second, and similarly, the changes in the indicators about the stringency of EPL for regular contracts usually discussed in the debate (for instance the OECD indicators) overestimate the impact of the EPL reforms, since they are based on changes in legal costs and neglect the costs from enforcement (i.e., labor courts’ intervention). Finally, the reduction of effective firing costs for economic dismissals under the regular employment contract has not been as large as envisioned by the policy-makers. Given that the difference between these firing costs and termination costs of temporary contracts, which determines the proportion of employees with fixed-term contracts, is still very large, the high incidence of temporary employment observed in Spain would not be very much reduced by these reforms.

Figure 4

Marginal effect of reforms, unemployment, and profitability on labor court rulings declaring dismissals/layoffs as fair.

Note: Proportion of fair rulings by labor courts (observed values) is measured in left axis and marginal effect (from estimates in column 5 in Table 5) on the right axis.

Figure 1

Layoff procedure in the Spanish labor jurisdiction.Source: Authors’ own elaboration.Notes:a. Out-of-court settlements are resolved in Spain by the “MAC” units (“Mediation, Arbitration and Conciliation Units”). The majority of out-of-court settlements resolved with an agreement between the employer and the employee end up with the effective firing of the employee. Settlements ended without an agreement are the main group of dismissal conflicts which arrive to the labor courts. Following the data of the Ministry of Employment and Social Security, there was a total of 220,095 out-of-court settlements in 2014, of which 101,426 ended with agreement between the employer and the employee.b. In 2014, the number of dismissals resolved at the labor court was 118,225. This amount is calculated by adding the number of pre-trial settlements with agreement, the dismissals finally ruled by a labor court, and the number of cases withdrawn (including tacit withdrawals and voluntary dismissal of action by the parties).c. The number of pre-trial layoff settlements in 2014 was 48,508.d. In 2014, the number of dismissals resolved at the trial level in the labor courts was 42,992, of which a 78% were dismissals ruled as “unfair” (in favor of the employee).e. In 2014, 26,725 dismissals were withdrawn (thus, they were not resolved by a judge in a trial) as a result of formal failures, tacit withdrawals, and voluntary dismissal of action by the parties.
Layoff procedure in the Spanish labor jurisdiction.Source: Authors’ own elaboration.Notes:a. Out-of-court settlements are resolved in Spain by the “MAC” units (“Mediation, Arbitration and Conciliation Units”). The majority of out-of-court settlements resolved with an agreement between the employer and the employee end up with the effective firing of the employee. Settlements ended without an agreement are the main group of dismissal conflicts which arrive to the labor courts. Following the data of the Ministry of Employment and Social Security, there was a total of 220,095 out-of-court settlements in 2014, of which 101,426 ended with agreement between the employer and the employee.b. In 2014, the number of dismissals resolved at the labor court was 118,225. This amount is calculated by adding the number of pre-trial settlements with agreement, the dismissals finally ruled by a labor court, and the number of cases withdrawn (including tacit withdrawals and voluntary dismissal of action by the parties).c. The number of pre-trial layoff settlements in 2014 was 48,508.d. In 2014, the number of dismissals resolved at the trial level in the labor courts was 42,992, of which a 78% were dismissals ruled as “unfair” (in favor of the employee).e. In 2014, 26,725 dismissals were withdrawn (thus, they were not resolved by a judge in a trial) as a result of formal failures, tacit withdrawals, and voluntary dismissal of action by the parties.

Figure 2

Proportion of economic dismissals over all dismissals.Source: Spanish Ministry of Employment.
Proportion of economic dismissals over all dismissals.Source: Spanish Ministry of Employment.

Figure 3

Percentage of labor court judgments ruling that the dismissal is fair.Source: Authors’ own elaboration based on data provided by the CGPJ.
Percentage of labor court judgments ruling that the dismissal is fair.Source: Authors’ own elaboration based on data provided by the CGPJ.

Figure 4

Marginal effect of reforms, unemployment, and profitability on labor court rulings declaring dismissals/layoffs as fair.
Marginal effect of reforms, unemployment, and profitability on labor court rulings declaring dismissals/layoffs as fair.

Figure A1

Proportion of magistrates belonging to professional associations.
Proportion of magistrates belonging to professional associations.

Dismissals: initiation, settlements and effective firing costs

Truthful dismissalsDisguised
EconomicDisciplinaryAs economic
Initiated1+βr(π,μ)δr>$1+{{\beta }^{r}}\left( \pi ,\mu \right){{\delta }^{r}}>$Always1+βr(π,μ)δr$1+{{\beta }^{r}}\left( \pi ,\mu \right){{\delta }^{r}}\le $
>τrrd(cucf)Xer(π,μ)$>\frac{{{\tau }^{r}}-{{r}^{d}}}{\left( {{c}^{u}}-{{c}^{f}} \right)X_{e}^{r}\left( \pi ,\mu \right)}$τrτd(cucf)Xer(π,μ)$\le \frac{{{\tau }^{r}}-{{\tau }^{d}}}{\left( {{c}^{u}}-{{c}^{f}} \right)X_{e}^{r}\left( \pi ,\mu \right)}$
SettlementXer(μ)<Xwr(μ)$X_{e}^{r}\left( \mu \right)<X_{w}^{r}\left( \mu \right)$Xed(μ)<Xwd(μ)$X_{e}^{d}\left( \mu \right)<X_{w}^{d}\left( \mu \right)$Always
Effective firing costscu+τd${{c}^{u}}+{{\tau }^{d}}$
If settledXwr(μ)cf+[1Xwr(μ)]cu+τr$X_{w}^{r}\left( \mu \right){{c}^{f}}+\left[ 1-X_{w}^{r}\left( \mu \right) \right]{{c}^{u}}+{{\tau }^{r}}$[1Xwd(μ)]cu+τd$\left[ 1-X_{w}^{d}\left( \mu \right) \right]{{c}^{u}}+{{\tau }^{d}}$
At labor courtXer(π,μ)cf+[1Xer(π,μ)]cu+τr$X_{e}^{r}\left( \pi ,\mu \right){{c}^{f}}+\left[ 1-X_{e}^{r}\left( \pi ,\mu \right) \right]{{c}^{u}}+{{\tau }^{r}}$[1Xed(μ)]cu+τd$\left[ 1-X_{e}^{d}\left( \mu \right) \right]{{c}^{u}}+{{\tau }^{d}}$

Main descriptive statistics by province

Court rulingsUnemployment rate

Unemployment rate (national value) shows the average rate of unemployment for the full period. Provincial values represent differences from that national average.

ProfitabilityTemporary employment rateLog number workers under collective dismissalsProportion of companies with more than 200 employeesOut-of-court settlements ratio
National (full period)0.26030.16300.03980.28058.56920.00160.5258
Provincial deviations from the mean
ALMERIA–0.04990.0651–0.03980.1884–2.2744–0.0003–0.1314
CADIZ0.01380.1045–0.03980.0734–0.8296–0.00080.0163
CORDOBA0.04640.07970.01120.1339–1.8571–0.0008–0.0626
GRANADA0.00080.0719–0.02180.1137–1.7881–0.0008–0.0729
HUELVA–0.02560.07080.00820.1877–2.4510–0.0005–0.0397
JAEN0.03780.07340.15240.0942–1.2823–0.0010–0.0181
MALAGA–0.00250.0671–0.03980.0617–0.7456–0.0008–0.1051
SEVILLA0.00590.0594–0.01050.0997–0.5248–0.00020.0468
HUESCA0.0138–0.0616–0.0013–0.0300–1.9673–0.0010–0.4078
TERUEL0.0904–0.05920.0579–0.0414–1.7696–0.0008–0.4256
ZARAGOZA–0.0450–0.0350–0.0340–0.03550.62550.0001–0.3313
ASTURIAS0.0599–0.0184–0.0168–0.01850.5581–0.0004–0.1168
ILLES BALEARS–0.0159–0.0128–0.0398–0.0033–1.1640–0.0004–0.2505
LAS PALMAS–0.04790.0682–0.03490.0565–0.86500.00000.0090
SANTA CRUZ DE TENERIFE–0.07400.0469–0.02680.0523–1.0567–0.00030.0172
CANTABRIA0.0009–0.0396–0.0171–0.03210.0364–0.0004–0.1808
AVILA–0.11090.00360.1450–0.0120–2.4403–0.00120.0710
BURGOS0.0685–0.0400–0.0141–0.0599–0.4829–0.00010.0105
LEON–0.0226–0.01670.0074–0.0229–0.6166–0.0010–0.1287
PALENCIA0.1060–0.03070.0070–0.0552–1.2430–0.0006–0.1260
SALAMANCA0.0079–0.01320.0365–0.0260–1.9131–0.0009–0.1264
SEGOVIA0.0425–0.0445–0.0300–0.0474–2.6397–0.0009–0.0417
SORIA0.0364–0.0647–0.0183–0.0622–2.4441–0.00060.0631
VALLADOLID0.0287–0.02930.0131–0.02960.1799–0.0002–0.0310
ZAMORA–0.0164–0.00670.3171–0.0001–2.7065–0.0013–0.1014
ALBACETE–0.01050.02390.06350.0158–1.3802–0.0009–0.1099
CIUDAD REAL0.01800.02871.41230.0313–2.0382–0.0011–0.0253
CUENCA0.0355–0.01040.2768–0.0016–2.7461–0.00120.0532
GUADALAJARA–0.0221–0.02470.0173–0.0453–2.3618–0.0004–0.0141
TOLEDO–0.07840.01950.13940.0290–1.4898–0.0010–0.0018
BARCELONA–0.0314–0.0210–0.0398–0.08222.01480.00060.2197
GIRONA0.0312–0.0114–0.0398–0.0461–0.6995–0.00060.0870
LLEIDA0.0426–0.0583–0.0378–0.0818–1.6490–0.00080.1113
TARRAGONA0.0388–0.0122–0.0398–0.0108–0.8174–0.00040.0428
ALICANTE–0.09150.0230–0.03790.0601–0.0219–0.0010–0.0450
CASTELLON0.03610.0104–0.03790.0072–0.04950.00060.0519
VALENCIA–0.03220.0102–0.00210.01430.99550.0000–0.0730
BADAJOZ0.03510.06390.02580.1115–1.5900–0.0009–0.0961
CACERES0.05510.03500.02440.0670–2.0785–0.00110.1215
A CORUÑA–0.0189–0.02850.0163–0.0031–0.1954–0.00020.0172
LUGO0.0170–0.05490.0226–0.0118–1.9468–0.0011–0.0427
OURENSE–0.0377–0.0228–0.0017–0.0188–1.9869–0.0008–0.0868
PONTEVEDRA0.0148–0.0013–0.00150.02350.1738–0.00050.0079
MADRID0.0421–0.0391–0.0398–0.06631.48110.00180.0787
MURCIA0.00150.0148–0.01450.0802–0.6336–0.0001–0.0656
NAVARRA0.0138–0.06080.0626–0.03280.60250.00100.0541
ARABA/ALAVA0.0759–0.0559–0.0044–0.0537–0.03100.00060.0205
GIPUZKOA0.0417–0.07560.1014–0.04050.38290.00000.0660
BIZKAIA0.0111–0.0425–0.0398–0.02650.64340.0007–0.0242
LA RIOJA–0.0189–0.0416–0.0177–0.0561–1.0135–0.00090.0848

Determinants of settlementsRobust standard errors (clustered by provinces) in parenthesis.

123456

In column (6), Madrid and Barcelona are excluded.

2010 reform–0.107

p < 0.01

(0.0188)
0.0118 (0.0128)0.0148 (0.0209)0.0211 (0.0127)–0.139

p < 0.01

(0.0372)
–0.129

p < 0.01

(0.0447)
2012 reform0.208

p < 0.01

(0.0163)
0.118

p < 0.01

(0.0172)
0.261

p < 0.01

(0.0172)
0.124

p < 0.01

(0.0183)
0.244

p < 0.01

(0.0588)
0.201

p < 0.01

(0.0463)
Unemployment rate–1.274

p < 0.01

(0.132)
–0.467

p < 0.01

(0.166)
–0.849

p < 0.01

(0.156)
–0.696

p < 0.01

(0.156)
2010 reform

p < 0.1.

Unemployment rate
0.840

p < 0.01

(0.168)
0.777

p < 0.01

(0.183)
2012 reform

p < 0.1.

Unemployment rate
–0.532

p < 0.05

(0.222)
–0.375

p < 0.1.

(0.196)
Profitability0.0106 (0.0157)0.439

p < 0.01

(0.0956)
0.466

p < 0.01

(0.0893)
0.475

p < 0.01

(0.0886)
2010 reform

p < 0.1.

Profitability
–0.107 (0.132)–0.135 (0.153)
2012 reform

p < 0.1.

Profitability
–0.699

p < 0.01

(0.197)
–0.625

p < 0.01

(0.155)
Province fixed effectsYESYESYESYESYESYES
Other controls

Other controls include: temporary employment rate, sectoral distribution of employment, logarithm of the number of workers affected by collective dismissals, proportion of companies with more than 200 employees, proportion of dismissal lawsuits analyzed by professional judges, days of temporary positions at the labor courts per year, and judicial congestion rate.

NOYESNOYESYESYES
Observations13,88010,97613,88010,97610,9768,192
R-squared0.2010.5210.3400.5430.5730.535
# labor courts347343347343343256

Determinants of labor court rulings declaring dismissals/layoffs as fairRobust standard errors (clustered by province) in parenthesis.

123456

In column (6), Madrid and Barcelona are excluded.

2010 reform 2012 reform–0.0012 (0.00598) –0.0339

p < 0.01

(0.00526)
0.0376

p < 0.01

(0.00807) –0.0065 (0.00605)
0.0426

p < 0.01

(0.00479) –0.0088 (0.00590)
0.0385

p < 0.01

(0.0080) 0.00003 (0.0065)
0.0120 (0.0197) 0.00126 (0.0214)0.0288 (0.0187) 0.00138 (0.0278)
Unemployment rate–0.467

p < 0.01

(0.0800)
–0.304

p < 0.05

(0.128)
–0.386

p < 0.01

(0.133)
–0.312

p < 0.05

(0.134)
2010 reform

p < 0.1. Clustered by province.

Unemployment rate
0.137 (0.0836)0.0680 (0.0776)
2012 reform

p < 0.1. Clustered by province.

Unemployment rate Profitability
–0.0036

p < 0.01

(0.0009)
–0.0530 (0.0570)–0.0102 (0.0892) –0.0181 (0.0550)–0.0161 (0.104) –0.0181 (0.0550)
2010 reform

p < 0.1. Clustered by province.

Profitability
–0.177

p < 0.05

(0.0817)
–0.234

p < 0.01

(0.0813)
2012 reform

p < 0.1. Clustered by province.

Profitability
–0.0317 (0.150)–0.0250 (0.151)
Province fixed effectsYESYESYESYESYESYES
Other controls

Other controls include: temporary employment rate, sectoral distribution of employment, logarithm of the number of workers affected by collective dismissals, proportion of companies with more than 200 employees, proportion of dismissal lawsuits analyzed by professional judges, days of temporary positions at the labor courts per year, and judicial congestion rate.

NOYESNOYESYESYES
Observations14.18110.20212.82510.20210.2027.586
R-squared0.0170.0550.0360.0580.0600.056
# labor courts343339343339339255

Severance payments in the theoretical model

FEPWEG
Economic Truthful dismissalsXer(π,μ)Cf+[1Xer(π,μ)]Cu+τr$X_{e}^{r}\left( \pi ,\mu \right){{C}^{f}}+\left[ 1-X_{e}^{r}\left( \pi ,\mu \right) \right]{{C}^{u}}+{{\tau }^{r}}$Xwr(μ)Cf+[1Xwr(μ)]Cu$X_{w}^{r}\left( \mu \right){{C}^{f}}+\left[ 1-X_{w}^{r}\left( \mu \right) \right]{{C}^{u}}$
Disguised as disciplinarycu+τd${{c}^{u}}+{{\tau }^{d}}$cu${{c}^{u}}$
Disciplinary layoffs
Truthful[1Xed(μ)]cu+τd$\left[ 1-X_{e}^{d}\left( \mu \right) \right]{{c}^{u}}+{{\tau }^{d}}$[1Xwd(μ)]cu$\left[ 1-X_{w}^{d}\left( \mu \right) \right]{{c}^{u}}$
Disguised as economiccu+τr${{c}^{u}}+{{\tau }^{r}}$cu${{c}^{u}}$

Effects of EPL reforms

EconomicdismissalsDisciplinarySettlementsFiring costsFair ruling
TruthfulDisguised
Severance payments/
court costs
Fair dismissals ↓unchangedunchanged
Unfair dismissals ↓unchangedunchanged
Cause of economic dismissalsunchanged
Downturns
Firm profitability ↓unchanged
Local labor market conditionsunchanged

Definitions of variables and sources of data

VariableDefinitionScale/UnitPeriodSource
Court rulingsPercentage of labor court judgments ruling that the dismissal was fair or justified%By court, 2004–2015CGPJ
D1 (Reform 2010)Period of enforcement of the 2010 labor market reformDummy2004–2015Self elaboration
D2 (Reform 2012)Period of enforcement of the 2012 labor market reformDummy2004–2015Self elaboration
Unemployment ratePercentage of total workforce which is unemployed and is looking for a paid job (in differences from the average)%By province, 2004–2014Spanish National Statistics Institute (INE)
ProfitabilityReturn on assets (ROA) for the 10% of firms with a lower ROA%By province, 2004–2013Banco de España
Temporary employment ratePercentage of total workforce which has a fixed-term contract%By province, 2004–2014Spanish National Statistics Institute (INE)
Log of the number of workers under collective dismissalsLogarithm of the number of workers affected by collective dismissalsLogarithmBy province, 2004–2014Ministry of Employment and Social Security
Proportion of companies with more than 200 employeesProportion of companies with more than 200 employees over the total number of companies%By province, 2004–2014Spanish National Statistics Institute (INE)
Employment share of servicesPercentage of total workforce working on services sector%By province, 2004–2014Spanish National Statistics Institute (INE)
Employment share of industryPercentage of total workforce working on services sector%By province, 2004–2014Spanish National Statistics Institute (INE)
Employment share of constructionPercentage of total workforce working on services sector%By province, 2004–2014Spanish National Statistics Institute (INE)
Proportion of dismissal lawsuits analyzed (+) byPercentage of labor court judgments ruling that the dismissal was fair or justified%By court, 2004–2015CGPJ
professional judges over totalby professional judges over all the dismissal lawsuits analyzed by all judges
Proportion of days with temporaryProportion of days per 365-days a year with positionsFractionBy court, 2004–2014CGPJ
positions at the labor courts per year Judicial congestion rate (dismissals lawsuits)at the labor courts held by interim judges Ratio between the sum of pending cases in a labor court plus new cases and the cases resolved in the same quarterFractionBy court, 2004–2014CGPJ
Judicial congestion rate (pre-trial settlements)Ratio between the sum of pending settlements in a labor court plus new settlements and the settlements resolved in the same quarter%By court, 2010–2015CGPJ
Out-of-court settlements ratioRatio of the number of out-of- court settlements divided by the sum of those settlements and the total number of dismissal lawsuits%By court, 2004–2015CGPJ

Descriptive statistics

VariableBefore 20102010–2012After 2012
ObsMeanStd. Dev.MinMaxObsMeanStd. Dev.MinMaxObsMeanStd. Dev.MinMax
Court rulings7,4440.27300.1362014,0250.25820.118000.81823,3900.22680.114401
Unemployment rate (in differences)8,328–0.05170.0496–0.13640.13974,1640.05700.0638–0.08590.23722,4290.0910.0658–0.02710.2711
Profitability8,3280.03980.090300.81004,1640.00760.033800.37631,3880.14112527013.5382
Temporary employment rate8,3280.30890.08110.16280.59494,1640.24800.06190.13150.48632,4290.23870.06110.13250.5088
Log of the number of workers under collective dismissals6,9407.92811.71892.833211.75124,1649.20741.25555.46411.20393,4708.92391.37143.989010.9548
Proportion of companies with more than 200 employees8,5780.00170.000900.00404,1640.00150.00080.00030.00322,7760.00160.00080.00020.0032
Employment share of services8,3280.66850.07340.4380.8444,1640.74000.07190.5360.88902,4290.76060.07050.5840.888
Employment share of industry8,3280.16260.06350.0440.3694,1640.14040.05530.0320.34202,4290.13670.05570.0310.279
Employment share of construction8,3280.12060.02760.0580.2394,1640.07730.01770.0410.16702,4290.05890.01170.0330.109
Proportion of dismissal lawsuits analyzed (+) by professional judges over total8,3280.90230.1767014,1640.80360.2736013,4700.84740.250901
Proportion of days with temporary positions at the labor courts per year8,2320.00830.040800.54,1160.01300.051600.25562,7440.00560.034200.2556
Judicial congestion rate (dismissals lawsuits)8,3282.04860.48771134,1642.60380.81731.04448.19580
Judicial congestion rate (pre-trial settlements)8,32815015154,1646.641412.779002853,4706.47275.01710.54445.5116
Out-of-court settlements ratio8,3280.54220.182200.93104,1640.44440.167200.86621,3880.67190.14200.9021

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