Wellbeing at work and the Great Recession: The effect of others’ unemployment

1 Wellbeing at work and the Great Recession: The effect of others’ unemployment Cristina Borra 1 and Francisco Gómez-García 1* 1 University of Seville *Corresponding author: C/ Ramón y Cajal, 1, Facultad de Ciencias Económicas y Empresariales, Departamento de Economía e Historia Económica (Universidad de Sevilla) 41018 Sevilla e-mail: [email protected] Abstract Economists have long been interested in the possibility that individuals’ wellbeing depends on their relative position. The recent recession has generated a tremendous increase in unemployment rates in Spain. In this paper we use a very rich repeated cross-section dataset on workers’ job conditions, together with regional unemployment information, to investigate whether peers’ unemployment affects individuals’ job satisfaction. We try to distinguish both the negative effect that others’ unemployment might inflict on individual on-the-job wellbeing via increased job insecurity and the positive effect, sometimes called social norm of unemployment, whereby individuals’ wellbeing increases when they feel relatively better than their peers. We find that peers’ unemployment shows both a negative and a positive effect in Spain. In fact, once perceived job insecurity is controlled for, a clear positive effect emerges, larger and more precisely estimated for men and private-sector workers. This result is robust to using different unemployment rate measures and, interestingly, to controlling for workforce selection. Our findings constitute a microeconometric foundation of the countercyclical pattern of productivity in Spain. Keywords: Job satisfaction, unemployment rate, relative position, job insequrity, Spain, Great Recession 2 1. Introduction This paper looks at the effect of peers’ unemployment on individuals’ job satisfaction. We therefore focus on the following question: Does others’ unemployment affect employees’ job satisfaction? Following the work of Locke (1969), Hammermesh (1977), Freeman (1978), and Borjas (1979), economists became increasingly interested in issues related to subjective evaluations of the utility derived from work as measured by stated job satisfaction since it is related to gains in productivity at an organizacional and an individual level (Mangione and Quinn 1975, Oswald 1997, Halkos and Bousinakis 2010, Bökerman and Ilmakunnas 2010, Phelps and Zoega 2013) 1 . The literature provides evidence for a strong relationship between wellbeing at work and specific socioeconomic characteristics, namely, gender, age, education, wages, working hours, trade unions status and establishment size (Theodossiou and Vasileiou 2007, García-Serrano 2011, Borra and Gómez 2012). A related literature analyzes the effect of unemployment on subjective life satisfaction. Unemployment is widely considered to have a strong negative impact on individual wellbeing and losing a job is associated with a significant drop in not only income, but also social status, self-esteem, and other non-pecuniary effects (Clark and Oswald 1994, Winkelmann y Winkelmann 1998, Clark 2003, Blanchflower and Oswald 2004). Recently, evidence has gathered showing also a clear negative effect of general unemployment on subjective wellbeing among the employed in United Kingdom and Germany (Clark et al. 2010, Luechinger et al. 2010, Schwarz 2012). The most obvious channel for this effect is via the individual’s perception of job insecurity: others’ unemployment increases one’s own risk of becoming unemployed 2 . On the other hand, individual welfare may be subject to social influences. Previous literature both from economists (Duesenberry 1949; Easterlin, 1974; Solnik and Hemenway 2005; Luttmer, 2005) and psychologists (Kahneman et al. 1999; Inglehart and Klingemann 2000) highlights that individuals’ welfare depends heavily on their achievement in comparison to others’ outcomes. In this context, a higher level of unemployment may bring some well-being benefits by reducing expectations of success: the employed feel better off when their relative standing increases (Eggers et al. 2006). In this paper we try to isolate both the negative insecurity effect and the positive comparison effect of unemployment rates on subjective wellbeing at work in Spain during 2006-2010. We use individual level data from the Spanish Working Conditions Survey (Encuesta de Calidad de Vida en el Trabajo 1 For a survey see Pugno and Depredi (2009). 2 High unemployment may also induce other general negative externalities such as a higher crime rate, expectations of higher taxes to finance increased welfare spending, and increased income inequality (Luechinger et al. 2010) 3 (ECVT)), a yearly survey carried out by the Spanish Ministry of Labour and Social Affairs containing information on individual job satisfaction, demographic and human capital characteristics of employees, employers’ features, and pecuniary and non-pecuniary job characteristics, together with regional unemployment rates computed from the Spanish Labour Force Survey (Encuesta de Población Activa, EPA) for the same years. Our identification strategy uses time and cross-section variations in the data to estimate the effect of regional unemployment rates on job satisfaction. In order to distinguish insecurity and comparison effects we compare models including and excluding perceived job insecurity measures as additional controls. Understanding unemployment and individual wellbeing in Spain during the recent recession is especially relevant. Spain has witnessed a surge in unemployment from slightly over 8% in 2006 to more than 20% in 2010, the highest in the European Union with the only exception of Greece. The increase has not been homogeneous, though, with some regions experiencing moderate increases (from 7 to 14 % in the Basque Country) and others suffering from huge rises (from 12 to 28% in Andalusia). In addition, the recession is also having a large and damaging impact on the national debt (with risk premiums hitting historical records), on the banking sector (with some banks needing bailouts), and on the overall ability of the state to deal with these economic and political problems. We find that, for those currently working, peers’ unemployment shows both a negative insecurity effect and a positive comparison effect in Spain. In fact, once perceived job insecurity is controlled for, higher peers’ unemployment rates are associated with higher job satisfaction. With the exception of Eggers et al. (2006), no previous work has obtained similar results. Using information from the British Household Panel Survey, Clark (2003) finds a clear negative effect of surrounding unemployment on life satisfaction of the employed. A similar result is reported by Powdthavee (2007) for South Africa. In Germany, with data from the German Socio-Economic Panel, Clark et al (2010) reveal a clear negative effect of others’ unemployment on the general wellbeing of the employed, slightly lower for those with higher perceived insecurity, which are considered to be subject to the social norm of unemployment. Luechinger et al. (2010), with the same dataset, also show a negative effect of regional unemployment on the employed, but only significant for those who belong to the private sector. The only study obtaining a positive effect of higher unemployment rates on the wellbeing of the employed analyzes the tumultuous environment of post-Soviet Russia during the 1990s (Eggers et al. 2006). We also investigate whether this positive effect is due to sample selection instead of individuals’ relative standing. In an environment of very high unemployment, remaining workers may increasingly be selected from those who have greater motivation or better attitudes towards work, and higher job satisfaction may be just the consequence of a different workforce composition arising after the crisis. 4 Using propensity score matching techniques to correct for sample selection, we rule out that our results are driven by selection effects in a significant way. As far as we know, no previous study has examined the effect of peers’ unemployment on subjective wellbeing at work in the context of the Great Recession using a survey of employees. For instance, the literature of the macroeconomics of happiness (Di Tella et al. 2001, 2003, Wolfers 2003) examines the effects of business cycle volatility on subjective well-being, but so far the recent recession has not been examined. We also add to existing literature by examining a Southern European country such as Spain. So far previous studies have focused primarily on Germany (Clark et al 2010, Luetchinger et al. 2010, Schwarz 2012), the United Kingdom (Clark 2003), South Africa (Powdthavee 2007) and Rusia (Eggers et al. 2006). Compared to these studies we control for unobserved heterogeneity by including personality and psychological attitudes in the spirit of Ferrer-i-Carbonell and Frijters 2004 and Origo and Pagani 2009 and we focus on subjective wellbeing at work controlling for a vast array of working conditions that may have hardened during the recession. Moreover, we contribute to this literature by addressing the issue of sample selection through propensity score matching methods as in Kawaguchi et al. (2012) and Borra et al. (2013). Finally, our result constitutes a microeconometric foundation of the countercyclical pattern of productivity in Spain found by Mora-Sanguinetti and Fuentes (2012), and Maroto-Sanchez and Cuadrado-Roura (2013) among others. The positive effect of unemployment on workers’ wellbeing found in this paper implies that productivity increases during recessions, that is, countercyclically . This paper is organized as follows. The next section presents the theoretical framework. Section 3 describes the dataset and the estimation procedure. Section 4 presents the results and their heterogeneity with respect to different variables. Section 5 explores sample selection issues and, finally, Section 6 concludes. 2. Theoretical framework The theoretical model that supports our empirical strategy is based on the hypothesis that a job is more than the salary and number of hours of work-against reductionist vision-neoclassical approach; other job characteristics are relevant to define the job post such as, the possibility of reconciling work and family or on-the-job training. In this paper we add an additional hypothesis: does others’ unemployment, as measured by regional unemployment rates, affect wellbeing at work? (Akerlof 1980 and Clark 2003). As supported by previous literatura, unemployment reduces individual welfare of those who are personally affected by it. 3 . However, high unemployment rates may also have nonngegligible effects on people who are not personally affected by unemployment. For instance, 3 Our simple includes only those in employment. See references above. 5 based on survey data from population samples from European Union member countries between 1975 and 1992, Di Tella et al. (2003) show than aggregate unemployment decreases average reported life satisfaction even if personal unemployment is kept constant. The most obvious effect of general unemployment on those employed is through job insecurity: bad news for others increase my own unemployment risks, producing a clear negative effect on wellbeing. In addition, overall unemployment may also generate negative or positive externalities: a) negative , due to empathy with the unemployed workers - see Clark (2003 ), Clark et al. (2010), Luechinger et al. (2010 ), Schwarz (2012) and Hudson and Barrett ( 2013 ); and b ) positive, coming from relative achievement in comparison to others’ outcomes. This positive comparison effect, profusively evidenced with respect to income (Hamermesh (1977), Clark and Oswald (1996), Solnik and Hemenway 2005; Luttmer, 2005), is most unusual with respect to unemployment in the empirical literature (Eggers et al. 2006). To distinguish between these externalities (positive and / or negative ) and changes in the economic risks that arise when having a job becomes less common, we include perceived job insecurity as a specific argument of the utility function. In light of the above, we present a model in which the individual's utility depends on perceived job insecurity and the regional unemployment: )1(),,( iri ZURJIU where U(⋅) represents utility derived from work , JI i is individual i’s perceived job insecurity i, U R is region r unemployment rate and Z i is a vector of control variables such as gender, education, and job characteristics –including the wage ratethat may affect the individual’s utility. In the following we assume there is a relationship between current utility (U) and subjective wellbeing at work (WAW i ), defined as: )2(),,( iirii ZURJIUWAW ε += Where the error term captures individual heterogeneity, mainly due to attitudes and personality traits, and measurement error. As stated by Kahneman y Krueger (2006), subjective wellbeing at work can be inferred from individuals’ satisfaction scores. 3. Data, variables, and empirical strategy We use two sources of data in our analysis: (1) individual level data from the Spanish Working Conditions Survey (Encuesta de Calidad de Vida en el Trabajo (ECVT)) spanning from 2006 through 2010, and (2) data on regional unemployment rates computed from the Spanish Labour Force Survey (Encuesta de Población Activa, EPA) for the same years. 6 The ECVT provides the most representative and frequent data on job satisfaction for the Spanish workforce. We use 40,000 individual records with information on demographic and human capital characteristics of employees, employers’ features, and pecuniary and non-pecuniary job characteristics. We choose the 2006-2010 period in order to analyze the potential effect of unemployment during the Great Recession and because important methodological changes took place in 2006, rendering previous surveys not directly comparable to the ones we use. The measure of overall job satisfaction is derived from the following question: “Indicate your level of satisfaction in your current job” It is measured on an ordinal 11-point Likert scale from “very badly” (0) to “excellently” (10). As a first approximation to our research question, Table 1 summarizes the dependent variable by survey year. Apparently the recession has not significantly altered the job satisfaction of those employed. Table 1. Dependent variable Satisfaction 2006 2007 2008 2009 2010 2006-2010 0 1.17 0.35 0.22 1.05 0.50 0.65 1 0.38 0.28 0.19 0.50 0.48 0.37 2 1.03 0.66 0.43 0.97 1.17 0.85 3 1.54 1.68 1.43 1.63 1.44 1.54 4 2.75 3.09 2.73 2.16 2.21 2.58 5 10.27 10.95 9.39 8.38 8.50 9.48 6 10.69 12.74 12.85 10.97 11.15 11.69 7 19.30 22.26 23.20 22.02 20.81 21.54 8 26.00 27.32 29.59 28.16 29.27 28.10 9 12.30 12.19 11.71 11.35 12.90 12.09 10 14.56 8.49 8.27 12.81 11.58 11.10 Total 100.00 100.00 100.00 100.00 100.00 100.00 Average 7.33 7.19 7.27 7.33 7.37 7.30 Regional unemployment rates are provided from the EPA directly by the Spanish Statistical Office (Instituto Nacional de Estadística, 2013). Table A.1 in the Appendix shows unemployment rates by region and year as in our benchmark definition of peer’s unemployment. A major advantage of the dataset is that it contains an extremely rich set of background variables, which allows the implementation of econometric methods to a very high standard. In particular the survey offers personal and demographic characteristics, human capital features and other non-financial job characteristics -apart from job security. Table A.2 in the appendix shows definitions and descriptive statistics of all variables used in the analyses, by survey year. Our purpose is to explore how increasing unemployment rates after the recession may have impacted individuals wellbeing at work. With that aim in mind, we estimate the following equation in our benchmark analysis 7 irttririrt ZURWAW εϕφγβα +++++= 1 (3) where the dependent variable is the individual’s i from region r overall job satisfaction in year t. The variable URr is a measure of the regional unemployment rate. We also control for a variety of individual level personal and job characteristics included in the vector X known to be correlated to subjective wellbeing, such as age, gender, marital status, educational attainment, job tenure, wages, contract type, firm size, accident risk, … 4 We also include regional r φ and year t ϕ fixed-effects to account for a variety of macroeconomic factors possibly correlated to individuals’ welfare, such as differences in crime rates, the public provision of unemployment support, divorce rates,… Finally, standard errors are clustered at the regional level as suggested by Moulton (1990). Absent any controls for perceived job insecurity, β 1 captures the combined insecurity plus comparison effects. In order to distinguish both, we also estimate a model with an additional control for subjective job insecurity irttriirirt XJSURWAW εϕφγδβα ++++++= 2 (4) Where JS measures satisfaction with job stability in a 0-10 scale. In this second model the coefficient of the unemployment rate β2 estimates now just the comparison effect. In our model β1 in equation (3) measures the combined externality plus job insecurity effect. We expect this parameter to have a negative or nil value due to the a priori relative weight of job security on wellbeing at work. β2 in equation (4) measures just the externality effect of general unemployment on job satisfaction. We expect this parameter to be larger than β1 and even positive if the positive comparison effect turns larger than the negative empathic effect in Spain. Our dependent variable is intrinsically ordered in nature. However, usual estimators like ordered probit or logit may not be flexible enough for our purposes. Van Praag and Ferrer-i-Carbonell (2006) show that the latent variable underlying an ordinal variable can be approximated by adequately rescaling the variable. Therefore, we will use this approach termed Probit OLS and transform the variable into a pseudo-continuous one as explained by Corneliben (2009) and use a traditional linear regression estimator. 4. Results Table 2 presents our baseline estimates for our sample of employees. The first specification includes no additional controls. The second specification adds in a range of variables indicating demographic and human capital characteristics of the individual, while the third specification controls for job characteristics, including the individual’s monthly earnings. The fourth specification includes personality and psychological attitudes, which are very likely to capture time-invariant unobserved 4 We include these characteristics sequentially to assess how the estimated coefficient changes as we include some variables that could be potentially considered endogenous, as is the case with contract type or job tenure. 8 factors in the absence of panel data (Ferrer-i-Carbonell and Frijters 2004; Origo and Pagani 2009). The fifth specification adds up region and year fixed effects while the sixth specification also includes perceived job stability. Table 2. The effect of regional unemployment rates on subjective wellbeing at work (1) (2) (3) (4) (5) (6) Spec. 1 Spec. 2 Spec. 3 Spec. 4 Spec. 5 Spec. 6 Regional Unemployment Rate 0.009** 0.008*** 0.009*** 0.009*** 0.008 0.010** (0.003) (0.003) (0.002) (0.002) (0.005) (0.003) Perceived Job Stability 0.155*** (0.003) Demographic and Human Capital Vars. No Yes Yes Yes Yes Yes Job Characteristics No No Yes Yes Yes Yes Personality Traits No No No Yes Yes Yes Region fixed effects No No No No Yes Yes Year fixed effects No No No No Yes Yes Observations 32,290 32,209 32,290 32,290 32,290 32,290 R-squared 0.003 0.069 0.117 0.124 0.134 0.267 Notes: This table shows the regression of perceived job satisfaction on the variables of interest. The sample includes only individuals aged 16-74 who are employed in the private or public sector, and not self-employed. Regressions include a constant term together with the control variables in Table A.2 in a sequential way. Observations are weighted using the individual weights in the ECVT. Standard errors in parentheses adjusted for clustering on the regional level. * significant at 10% ** significant at 5%; *** significant at 1%. Source: ECVT and EPA 2006-2010. When comparing the estimated effect in specification (5) –equation (3)- to that in specification (6) – equation (4) it becomes apparent that, after controlling for all demographic variables, job characteristics, personality traits, and regional and time variation, the general combined effects of unemployment are virtually inexistent. However, when obtaining the net effect, controlling for perceived job stability, a clear positive effect emerges. Therefore in Spain the general externalities of unemployment on the employed are mainly positive and related to the comparison effect. In a recent study Oesch and Lipps (2011) report for Germany and Switzerland, that unemployment hurts alike in regions with high and low unemployment. Luechinger et al. (2010) on the contrary report for a cross section of countries (including German SOEP data), that unemployment has negative effects even on workers in employment, but more so for workers in the private than in the public sector. This is the result found in most studies on this subject –see Clark (2003), Powdthavee (2007), Clark et al. (2010), Schwarz (2012) y Hudson y Barrett (2013). The only exception relates to the study of the effect of unemployment on life satisfaction of workers in Rusia during the 1990’s. Perceived job stability is measured indirectly by means of the individual’s satisfaction with job stability. An even more direct measured is offered in the 2010 survey where respondents are asked about the probability of keeping one’s job in a 1 though 4 likert scale. Given the qualitative and quantitative importance of perceived job stability in our analysis, as a robustness check, we estimated 9 the model on the 2010 sample including perceived probability of keeping one’s job instead of satisfaction with job stability as a control. The results, shown in Table 3, are virtually identical to those offered in the sixth specification of Table 2. Table 3. The effect of regional unemployment rates on subjective wellbeing at work (1) (2) Spec. 5 Spec. 6 Regional Unemployment Rate 0.013*** 0.015*** (0.002) (0.001) Probability of Keeping One’s Job 0.122*** (0.011) Demographic and Human Capital Vars. Yes Yes Job Characteristics Yes Yes Personality Traits Yes Yes Region fixed effects Yes Yes Year fixed effects No No Observations 6497 6497 R-squared 0.162 0.175 Notes: This table shows the regression of perceived job satisfaction on the variables of interest. The sample includes only individuals aged 16-74 who are employed in the private or public sector, and not self-employed. Regressions include a constant term together with the control variables in Table A.2. Observations are weighted using the individual weights in the ECVT. Standard errors in parentheses adjusted for clustering on the regional level. * significant at 10% ** significant at 5%; *** significant at 1%. Source: ECVT and EPA 2010. We also test the reliability of the baseline results to changes in different elements of the model. We consider different stratifications of the sample to investigate heterogeneity in the results; and we adopt different definitions of our regional unemployment variable. The heterogeneity analysis is presented in Table 4. In all the columns we offer the complete (equation 3) and the net (equation 4) effects of regional unemployment on subjective wellbeing at work. We first include self employed individuals in the sample. We then stratify by gender the sample of employees. Finally we divide the sample into public and private sector employees. The results are generally robust to changes in the population of interest. Apparently, when considering the self-employed, male workers, and those employed in the private sector, the comparison effect is as large as to outweight the countervailing effect of increased job insecurity. Contrary to previous findings on the subject (see Luechinger et al. 2010), we find a clear positive effect of regional unemployment on private sector employees’ wellbeing at work, even without controlling for perceived job stability. Controlling for subjective job insecurity only increases the magnitude of the effect. We do not find any significant effects for public sector employees. 16 the context of the Great Recession using a survey of employees. It should also be noted that such a positive impact is itself a novel finding, with the exception of Eggers et al. (2006). Our result constitutes a microeconometric foundation of the countercyclical pattern of productivity in Spain before and during the crisis. The positive effect of unemployment on workers’ wellbeing found in this paper implies that productivity varies countercyclically given that increased job satisfaction during recessions stimulates individual and organizational productivity. From a public policy standpoint, in order to maintain productivity during periods of expansion, when others’ unemployment decreases, an alternative to efficiency wages might well be efficiency job conditions, such as those related to corporate social responsibility. This sort of organizational innovations may well improve workers job effort at all wage levels. Finally a potential extension of this paper may rest in testing whether such a strong comparison effect has also been present in other developed countries during the Great Recession or whether it has just been specific of the countries most hard hit by the recession such as Greece, Portugal and Ireland. 17 References - Akerlof, G. (1980): “A Theory of Social Custom, of Which Unemployment May Be One Consequence”, Quarterly Journal of Economics, 94(4), pp. 749-775. - Askildsen, J.E., Bratberg,, E. and Nilsen, A. 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(2007): “Making the Risk of Job Loss a Way of Life: Does it Affect Job Satisfaction?”, Research in Economics, 61, pp. 71-83. - Van Praag, B.M.S. y Ferrer-i-Carbonell, A. (2006) "An Almost Integration-free Approach to Ordered Response Models," Tinbergen Institute Discussion Papers 06-047/3, Tinbergen Institute. - Winkelmann, L. y Winkelmann, R. (1998): “Why are the Unemployed so Unhappy? Evidence from Panel Data”, Economica, 65, pp. 1-15. - Wolfers, J. (2003): “Is Business Cycle Volatility Costly? Evidence from Surveys of Subjetive Well-being”, International Finance, 6(1), pp. 1-26. 20 Appendix Table A.1. Regional unemployment rates 2006 2007 2008 2009 2010 Andalucía 12.68 12.76 17.83 25.35 27.97 Aragón 5.54 5.24 7.15 12.82 14.77 Asturias, Principado de 9.31 8.48 8.45 13.42 15.97 Balears, Illes 6.46 6.98 10.18 18.02 20.37 Canarias 11.68 10.44 17.36 26.19 28.70 Cantabria 6.56 5.90 7.17 11.99 13.87 Castilla y León 8.11 7.18 9.51 13.78 15.78 Castilla - La Mancha 8.81 7.61 11.59 18.81 20.99 Cataluña 6.60 6.55 9.00 16.25 17.75 Comunitat Valenciana 8.37 8.76 12.13 21.24 23.30 Extremadura 13.43 13.06 15.20 20.55 23.04 Galicia 8.48 7.64 8.73 12.59 15.40 Madrid, Comunidad de 6.37 6.30 8.69 14.03 16.08 Murcia, Región de 7.85 7.56 12.63 20.73 23.35 Navarra, Comunidad Foral de 5.30 4.76 6.72 10.89 11.85 País Vasco 6.97 6.12 6.45 11.04 10.55 Rioja, La 6.18 5.66 7.79 12.75 14.27 21 Table A.2 Control variables 2006 2007 2008 2009 2010 2006-2010 Demographic and Human Capital Characteristics age 41.97 41.71 42.08 41.81 42.84 42.09 (11.0) (11.2) (10.9) (10.6) (10.6) (10.9) male 0.57 0.59 0.59 0.58 0.56 0.58 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) inmigrant 0.06 0.11 0.09 0.11 0.10 0.09 (0.2) (0.3) (0.3) (0.3) (0.3) (0.3) partner 0.67 0.66 0.67 0.68 0.69 0.67 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) nhijos 0.50 0.53 0.48 0.57 0.54 0.52 (0.8) (0.8) (0.8) (0.8) (0.8) (0.8) secundaria 0.19 0.20 0.21 0.23 0.21 0.21 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) fp_bachiller 0.32 0.32 0.33 0.33 0.38 0.34 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) universitario 0.25 0.23 0.26 0.25 0.26 0.25 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) adecuado 0.77 0.79 0.78 0.78 0.79 0.78 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) sobreeducado 0.19 0.15 0.18 0.18 0.17 0.17 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) nocorrespond 0.02 0.03 0.02 0.02 0.02 0.02 (0.1) (0.2) (0.1) (0.1) (0.1) (0.1) Job Characteristics tenure 10.97 10.50 10.84 10.69 11.43 10.89 (10.6) (10.8) (10.7) (10.5) (10.5) (10.6) ln_wage 7.03 7.03 7.09 7.06 7.05 7.05 (0.6) (0.6) (0.5) (0.6) (0.6) (0.6) autonomo 0.14 0.17 0.17 0.19 0.18 0.17 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) spublico 0.21 0.19 0.20 0.22 0.20 0.20 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) indefinido 0.63 0.61 0.65 0.63 0.62 0.63 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) tcompleto 0.87 0.87 0.88 0.86 0.86 0.87 (0.3) (0.3) (0.3) (0.3) (0.3) (0.3) subord 0.30 0.19 0.25 0.23 0.22 0.24 (0.5) (0.4) (0.4) (0.4) (0.4) (0.4) equipo 0.78 0.74 0.72 0.78 0.70 0.74 (0.4) (0.4) (0.4) (0.4) (0.5) (0.4) jcontinua 0.54 0.51 0.52 0.53 0.54 0.53 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) horas_trabajo 40.31 40.47 40.20 39.78 39.66 40.08 (11.0) (9.9) (9.2) (11.0) (10.4) (10.3) unusual 0.36 0.36 0.35 0.37 0.37 0.36 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) sindicato 0.20 0.17 0.19 0.18 0.18 0.18 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) riesgo 3.72 3.53 3.24 3.56 3.55 3.52 (3.2) (3.3) (3.2) (3.1) (3.2) (3.2) size1 0.09 0.11 0.13 0.12 0.11 0.11 (0.3) (0.3) (0.3) (0.3) (0.3) (0.3) size2 0.27 0.25 0.24 0.24 0.25 0.25 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) size3 0.18 0.20 0.20 0.18 0.18 0.19 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) size4 0.13 0.13 0.13 0.13 0.14 0.13 (0.3) (0.3) (0.3) (0.3) (0.3) (0.3) size5 0.34 0.31 0.30 0.33 0.31 0.32 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) 22 Table A.2 Control variables (cont.) 2006 2007 2008 2009 2010 2006-2010 Additional controls ln_income 7.44 7.42 7.43 7.47 7.41 7.43 (0.6) (0.6) (0.6) (0.6) (0.6) (0.6) tamanno1 0.20 0.22 0.22 0.23 0.24 0.22 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) tamanno2 0.27 0.27 0.27 0.26 0.27 0.27 (0.4) (0.4) (0.4) (0.4) (0.4) (0.4) tamanno3 0.12 0.12 0.12 0.12 0.11 0.12 (0.3) (0.3) (0.3) (0.3) (0.3) (0.3) tamanno4 0.33 0.32 0.31 0.31 0.30 0.31 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) tamanno5 0.08 0.07 0.08 0.08 0.08 0.08 (0.3) (0.3) (0.3) (0.3) (0.3) (0.3) Personality and attitudinal variables pref_spriv 0.44 0.42 0.39 0.44 0.43 0.43 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) pref_empleado 0.65 0.66 0.70 0.70 0.72 0.69 (0.5) (0.5) (0.5) (0.5) (0.4) (0.5) pref_esapeq 0.46 0.41 0.41 0.43 0.40 0.42 (0.5) (0.5) (0.5) (0.5) (0.5) (0.5) satis_estab 7.34 7.30 7.30 7.21 7.22 7.27 (2.5) (2.5) (2.7) (2.7) (2.6) (2.6) satis_vida 7.58 7.54 7.55 7.36 7.44 7.49 (1.9) (2.0) (1.8) (1.8) (1.8) (1.9) Unemployment measures nat_unemp 8.51 8.26 11.34 18.01 20.06 13.29 (0.0) (0.0) (0.0) (0.0) (0.0) (4.9) reg_unemp 7.92 7.71 10.48 16.93 18.83 12.43 (2.2) (2.3) (3.4) (4.4) (4.8) (5.9) gender_unemp 7.92 7.63 10.40 16.91 18.80 12.39 (3.3) (3.1) (3.8) (4.5) (5.0) (6.1) age_gend_unemp 7.12 7.02 9.40 15.44 17.09 11.26 (4.2) (4.1) (5.2) (7.0) (7.3) (7.1) educ_gend_unem p 8.14 8.03 10.88 17.73 19.55 12.92 (4.0) (4.0) (5.3) (7.1) (7.6) (7.6) 23 Propensity Score Matching Mahalanobis on private life satisfaction and gender within PS calipers Mahalanobis on private life satisfaction, gender, and tenure within PS calipers 2010 2006 2007 2008 2009 2006 2007 2008 2009 2006 2007 2008 2009 Mean Mean t-test Mean t-test Mean t-test Mean t-test Mean t-test Mean t-test Mean t-test Mean t-test Mean t-test Mean t-test Mean t-test Mean t-test satis_vida 7.40 7.60 0.04 7.58 1.73* 7.56 0.85 7.40 -0.29 7.79 0.00 7.75 0.00 7.69 0.00 7.55 0.00 7.85 0.00 7.80 0.00 7.74 0.00 7.59 0.00 pref_spriv 0.40 0.41 -1.78* 0.40 -1.19 0.38 -0.84 0.41 1.18 0.41 -1.32 0.40 0.13 0.38 0.88 0.41 -0.73 0.41 -1.92* 0.40 0.99 0.39 0.88 0.41 0.27 pref_emple~o 0.80 0.73 2.63** 0.75 -0.31 0.78 0.29 0.79 -1.83 0.74 1.51 0.76 -1.44 0.78 -0.39 0.79 0.72 0.74 1.48 0.76 -0.99 0.78 -0.29 0.79 -0.52 pref_esapeq 0.36 0.42 -0.20 0.38 -2.17** 0.38 -0.68 0.38 2.62*** 0.42 1.11 0.38 -0.86 0.38 0.83 0.38 -0.11 0.41 -1.01 0.38 0.79 0.38 -0.37 0.38 -0.74 age 41.04 41.28 0.73 40.86 -1.88* 41.28 -0.21 41.14 0.45 41.40 0.88 40.99 0.72 41.30 -0.38 41.26 -0.33 41.48 -1.24 40.96 -0.34 41.27 1.01 41.33 -0.55 male 0.55 0.55 -1.86* 0.56 -0.51 0.57 -0.09 0.56 0.97 0.55 0.00 0.57 0.00 0.58 0.00 0.57 0.00 0.56 0.00 0.57 0.00 0.58 0.00 0.57 0.00 inmigrant 0.10 0.07 -1.43 0.11 0.40 0.10 -0.75 0.11 0.06 0.06 -1.71* 0.11 -0.81 0.09 -1.31 0.10 -1.31 0.06 -0.67 0.10 -1.14 0.09 -1.46 0.10 -0.77 partner 0.66 0.65 2.5** 0.64 0.99 0.65 0.15 0.67 1.25 0.66 0.22 0.65 0.25 0.66 -0.64 0.68 0.02 0.66 -0.99 0.65 0.68 0.66 0.71 0.68 0.51 nhijos 0.55 0.50 1.44 0.53 1.65* 0.47 0.78 0.57 1.63 0.51 -0.02 0.53 -0.02 0.48 0.69 0.57 0.78 0.51 0.18 0.53 0.95 0.48 1.04 0.57 1.43 secundaria 0.20 0.19 -1.52 0.20 1.47 0.21 2.09** 0.22 1.79* 0.20 1.56 0.20 -0.55 0.21 1.13 0.22 0.43 0.20 -0.63 0.20 -1.41 0.21 -0.25 0.21 0.79 fp_bachiller 0.33 0.33 1.18 0.33 0.17 0.33 -0.68 0.33 0.21 0.33 0.88 0.33 1.29 0.33 0.53 0.33 -0.57 0.34 0.97 0.34 1.58 0.34 0.13 0.34 0.14 universita~o 0.29 0.27 1.21 0.25 -1.09 0.28 -2.74 0.27 -1.91* 0.27 -2.72 0.26 -0.23 0.28 -1.61 0.28 0.12 0.27 -0.46 0.27 0.35 0.28 -0.68 0.28 0.63 adecuado 0.77 0.76 -1.32 0.78 -1.22 0.77 0.06 0.78 0.75 0.76 -0.47 0.78 0.00 0.77 -0.68 0.78 0.38 0.77 -0.93 0.78 -0.02 0.78 0.41 0.79 0.94 sobreeducado 0.19 0.20 1.34 0.17 0.53 0.19 0.64 0.19 -0.64 0.20 0.74 0.17 0.27 0.19 0.18 0.18 -0.10 0.19 1.37 0.17 -0.08 0.19 0.40 0.18 -0.54 nocorrespond 0.02 0.02 -0.25 0.03 2.69** 0.02 -0.51 0.02 -0.52 0.02 -1.18 0.03 -0.06 0.02 0.13 0.02 -0.78 0.02 -0.81 0.02 0.75 0.02 -2.60 0.02 -0.20 tenure 9.98 10.39 1.93* 9.70 -0.19 10.19 -0.22 10.10 0.74 10.54 1.19 9.89 0.73 10.29 0.71 10.26 0.44 10.57 -1.41 9.96 -0.17 10.32 0.36 10.29 -0.97 ln_wage 7.06 7.02 0.46 7.01 0.73 7.09 -1.82* 7.07 0.22 7.03 -1.63 7.03 -0.61 7.10 -0.75 7.08 -0.19 7.04 -1.43 7.04 -0.61 7.10 1.43 7.09 1.77 spublico 0.28 0.26 1.89* 0.24 -1.74* 0.24 -0.68 0.27 -1.06 0.26 -0.04 0.24 -1.23 0.24 -0.39 0.27 -0.27 0.26 -0.13 0.24 -1.13 0.25 -0.15 0.26 -0.04 indefinido 0.79 0.76 2.85*** 0.75 1.10 0.79 -0.17 0.78 -1.18 0.77 1.57 0.76 1.27 0.79 0.78 0.79 1.21 0.77 2.88*** 0.77 3.81 0.79 3.11*** 0.79 1.75* tcompleto 0.85 0.87 -1.08 0.87 -0.61 0.88 -0.55 0.86 0.59 0.87 0.03 0.87 0.73 0.88 -0.03 0.86 0.29 0.87 -0.52 0.87 0.42 0.88 0.82 0.87 0.85 subord 0.21 0.29 -0.40 0.17 -0.38 0.23 -2.52** 0.21 -0.13 0.28 -2.3** 0.18 -2.29** 0.24 -1.02 0.21 -0.09 0.28 -2.28** 0.18 -0.74 0.24 -1.56 0.22 0.83 equipo 0.86 0.84 0.27 0.82 0.77 0.82 0.18 0.85 -0.30 0.84 -0.59 0.83 0.02 0.82 -1.15 0.86 -0.08 0.84 -0.37 0.83 0.28 0.82 0.21 0.86 0.92 jcontinua 0.58 0.59 -0.42 0.55 0.13 0.57 0.40 0.59 0.49 0.59 0.67 0.56 -0.79 0.57 -0.20 0.59 0.28 0.59 0.65 0.56 -0.17 0.58 -1.20 0.58 -0.27 horas_trab~o 38.60 39.12 -2.26** 39.32 0.49 39.17 -0.12 38.64 -0.17 39.00 -0.74 39.17 0.31 39.13 0.62 38.66 0.31 38.97 -0.55 39.17 -0.43 39.14 0.40 38.72 0.61 unusual 0.35 0.35 0.30 0.34 0.23 0.34 1.06 0.36 1.49 0.35 -0.53 0.34 -1.29 0.34 -0.81 0.36 1.16 0.35 -1.46 0.34 -1.64 0.34 -0.96 0.36 0.77 sindicato 0.22 0.22 0.31 0.19 0.78 0.22 0.76 0.21 -0.52 0.22 0.68 0.20 0.26 0.22 0.67 0.22 -0.04 0.23 0.26 0.20 0.98 0.22 1.11 0.22 1.02 riesgo 3.60 3.83 -0.46 3.62 -1.27 3.34 1.56 3.69 1.59 3.82 0.13 3.62 0.76 3.38 0.36 3.72 1.26 3.80 0.47 3.62 -0.35 3.37 1.25 3.72 0.49 size1 0.01 0.01 -1.01 0.01 -0.54 0.03 2.13 0.01 0.87 0.01 -0.98 0.01 0.00 0.02 1.10 0.01 -1.38 0.01 -1.55 0.01 -1.34 0.02 0.19 0.01 0.00 size2 0.20 0.23 -1.50 0.22 0.00 0.21 0.17 0.20 1.00 0.22 -0.52 0.22 0.47 0.21 -1.64 0.20 -0.44 0.22 -0.72 0.21 -0.46 0.21 -0.20 0.20 -2.43** size3 0.21 0.20 1.61 0.23 -0.51 0.23 0.81 0.21 0.22 0.20 -0.38 0.23 0.31 0.23 1.49 0.21 0.66 0.20 0.07 0.23 1.48 0.23 -0.41 0.21 0.72 size4 0.17 0.15 -0.15 0.16 0.39 0.16 -1.05 0.16 -1.26 0.15 3.24 0.16 0.71 0.16 1.19 0.17 -0.25 0.16 1.69 0.16 -0.26 0.16 0.97 0.17 1.16 size5 0.41 0.41 0.33 0.38 0.26 0.37 -0.75 0.41 -0.22 0.41 -1.34 0.38 -1.20 0.38 -1.12 0.41 0.30 0.41 -0.34 0.38 -0.41 0.38 -0.26 0.41 0.56 occupation1 0.00 0.00 -0.17 0.00 1.14 0.00 0.56 0.01 1.49 0.00 -0.82 0.00 2.04 0.00 0.85 0.00 1.94 0.00 2.13** 0.00 0.17 0.00 0.70 0.00 -1.05 occupation2 0.00 0.00 -0.53 0.00 0.82 0.00 -0.82 0.00 0.00 0.00 1.00 0.00 1.00 0.00 -0.63 0.00 -1.15 0.00 1.00 0.00 0.00 0.00 0.47 0.00 1.16 occupation3 0.03 0.02 0.14 0.03 1.78* 0.03 -1.30 0.03 -0.72 0.02 -0.81 0.03 0.11 0.03 0.22 0.03 -0.45 0.02 -0.82 0.03 0.33 0.03 -0.33 0.03 -0.28 occupation4 0.00 0.00 0.28 0.00 . 0.00 1.81* 0.00 1.34 0.00 0.90 0.00 . 0.00 -0.60 0.00 -0.71 0.00 0.28 0.00 . 0.00 0.45 0.00 0.45 occupation5 0.00 0.00 0.00 0.00 -2.24** 0.00 -1.53 0.00 1.73 0.00 1.41 0.00 0.00 0.00 -0.63 0.00 0.45 0.00 1.41 0.00 1.00 0.00 0.38 0.00 1.73* 24 occupation6 0.00 0.00 -0.14 0.00 0.23 0.00 1.14 0.00 0.00 0.00 -0.15 0.00 -0.63 0.00 -0.33 0.00 1.21 0.00 -0.91 0.00 0.00 0.00 0.82 0.00 0.22 occupation7 0.00 0.00 -1.41 0.00 0.00 0.00 1.9* 0.00 . 0.00 -0.82 0.00 -1.00 0.00 -1.63 0.00 . 0.00 -1.41 0.00 -1.73* 0.00 -1.28 0.00 . occupation8 0.00 0.00 . 0.00 1.00 0.00 0.58 0.00 -1.34 0.00 . 0.00 0.00 0.00 0.00 0.00 . 0.00 . 0.00 1.00 0.00 -0.45 0.00 . occupation9 0.00 0.00 1.67 0.00 0.00 0.00 0.48 0.00 . 0.00 1.67* 0.00 0.00 0.00 -1.09 0.00 . 0.00 -0.28 0.00 1.00 0.00 0.17 0.00 . occupation10 0.01 0.01 0.12 0.01 0.61 0.02 -0.07 0.01 -0.31 0.01 -0.12 0.02 0.15 0.02 0.58 0.01 0.57 0.01 0.24 0.02 -0.45 0.02 -0.21 0.01 0.51 occupation11 0.02 0.01 -0.60 0.01 0.38 0.01 -0.15 0.02 0.07 0.02 -2.21** 0.02 -1.02 0.01 -0.15 0.02 -0.78 0.02 -0.32 0.02 -1.69 0.01 0.63 0.02 -0.40 occupation12 0.03 0.04 0.83 0.03 -0.16 0.04 -1.41 0.03 0.35 0.04 -1.49 0.03 -0.32 0.04 -0.84 0.03 -0.50 0.05 -0.96 0.03 0.16 0.04 -0.66 0.04 0.36 occupation13 0.00 0.00 -0.25 0.01 0.99 0.00 -0.60 0.01 0.25 0.00 -0.14 0.01 1.14 0.00 -0.13 0.01 0.39 0.00 -0.15 0.01 0.37 0.00 -0.13 0.01 2.03 occupation14 0.01 0.02 2.47 0.01 -1.53 0.01 -1.19 0.01 -1.09 0.02 -0.88 0.01 0.11 0.01 0.61 0.01 -0.33 0.02 2.20 0.01 0.36 0.01 1.16 0.01 -0.96 occupation15 0.01 0.01 -0.11 0.01 -1.58 0.01 -2.43 0.01 -0.94 0.01 0.47 0.01 0.73 0.01 -0.45 0.01 1.7* 0.01 -0.36 0.01 1.84 0.01 -0.37 0.01 0.52 occupation16 0.01 0.01 -1.27 0.01 0.00 0.01 0.39 0.01 -1.26 0.01 -0.79 0.01 0.56 0.01 -0.31 0.01 0.27 0.01 -0.25 0.01 1.70 0.01 -0.47 0.01 0.86 occupation17 0.02 0.02 0.20 0.02 -1.91 0.02 -0.76 0.02 -0.33 0.02 -1.05 0.02 -0.21 0.02 -1.67 0.02 0.61 0.02 -0.76 0.02 0.59 0.02 -0.63 0.02 0.55 occupation18 0.03 0.03 0.00 0.03 0.59 0.03 -0.52 0.03 -0.21 0.04 -0.75 0.03 -0.88 0.03 0.35 0.03 -1.31 0.04 -0.97 0.03 -1.30 0.03 0.00 0.03 0.00 occupation19 0.01 0.02 2.19** 0.01 -2.29** 0.01 0.84 0.01 -0.89 0.02 -0.07 0.01 -0.09 0.01 -0.09 0.01 -0.10 0.01 -0.16 0.01 1.15 0.01 0.39 0.01 -0.60 occupation20 0.04 0.03 0.76 0.03 0.55 0.03 1.71* 0.03 -1.48 0.03 0.34 0.03 -0.11 0.03 -0.38 0.03 -0.42 0.03 -0.94 0.03 0.45 0.03 0.11 0.03 0.11 occupation21 0.01 0.01 0.88 0.01 -0.70 0.01 -0.26 0.01 1.34 0.01 -0.83 0.01 0.66 0.01 1.14 0.01 -0.10 0.01 1.66 0.01 0.78 0.01 0.76 0.01 -0.60 occupation22 0.01 0.00 -1.95* 0.00 -2.83*** 0.00 -0.21 0.00 0.46 0.00 -0.72 0.00 -0.69 0.00 1.21 0.00 -1.44 0.00 0.90 0.00 0.19 0.00 1.00 0.00 -1.37 occupation23 0.03 0.04 0.90 0.03 -0.22 0.03 -0.44 0.03 0.71 0.04 -0.14 0.03 1.14 0.03 0.17 0.03 0.52 0.04 0.15 0.03 1.77 0.03 0.98 0.03 2.09 occupation24 0.07 0.06 1.06 0.08 -0.20 0.07 -1.73* 0.07 -0.75 0.07 0.54 0.08 -0.31 0.07 -0.75 0.07 -0.25 0.07 0.23 0.08 0.66 0.07 0.53 0.07 -0.07 occupation25 0.01 0.01 1.54 0.01 -1.61 0.01 -0.24 0.01 0.09 0.01 1.39 0.01 -0.22 0.01 0.25 0.01 1.07 0.01 0.00 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