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Three Essays in Applied Labor Economics
von Annina Rebecca Eva Eymann LeistIn this thesis, I analyze topics in the area of labor economics and examine them for the case of Switzerland. Labor economics tries to understand Events in the labor market, and more specifically, evaluates the behavior of workers and employers. Workers supply their labor services to the employers, employers offer work places. The finding of a match is important. Furthermore, the resulting wages are of great interest.
Switzerland offers an interesting case for analyzing labor topics. It has many unique characteristics: the small open economy lies at the heart of Europe and is affected by labor market decisions from abroad. Evidence from labor studies in other countries cannot be directly used as comparison since the Swiss education system is very specific. The educational System in Switzerland is based on vocational education: two-thirds of Youngsters follow an apprenticeship directly after secondary education. Apprenticeships are offered by the employer, and students work two to three days at the work place. Moreover, they follow general and occupation-specific schooling one to two days a week. This provides a very early and tight connection to the labor market. Another important aspect of the Swiss system is its flexibility and the low importance of regulations.
A major challenge in applied labor economics is the nonrandom selection. Many treatments are only available to the more motivated and more able workers that have different personality traits, so mean comparison of outcomes would overestimate the effect of these treatments. This demands the choice of adequate microeconometric methods in order to eliminate, or at least reduce, the existing bias so that results are causally interpretable.
In chapter 2 of this thesis, my co-author J¨urg Schweri and I analyze skills mismatches. The motivation for this analysis stems from an often heard hypothesis about vocational education. Vocational education is assumed to be very specific and thus hindering labor market flexibility of its graduates. One way to examine this hypothesis is to focus on wage differentials between workers with vocational education and others with general education who experience a skills mismatch. Skills mismatch can be defined in various ways. We compare wages of matched and mismatched workers based on two definitions. The first definition views skill mismatch as a divergence between the formal education and the current occupation. The second definition views skill mismatch as a divergence between the set of qualifications a worker has and the qualifications needed at the current job. This second definition is also called subjective horizontal mismatch since it evaluates whether skills fit qualitatively or not, and does not analyze if there are too few or too many skills. Based on the Swiss Household Panel data, the analysis Shows that a substantial share of workers is formally mismatched, but that a much smaller share feels mismatched in regards to qualifications. Recognizing the existence of unobserved individual heterogeneity and applying fixed effects regression, wage penalties are insignificant. The sub-analysis of workers with apprenticeship training and workers with a tertiary education does not show that vocational education hinders mobility. However, there seems to be a gender gap story. Male workers, independently of their educational background, do not experience a wage penalty due to being mismatched. On the other hand, female workers with a vocational background experience a wage penalty if they are subjectively horizontally mismatched. Yet, the penalty is not statistically different compared to females with a general educational background. We conclude that vocational education, at least when analyzing skills mismatches, does not hinder mobility.
As a result of the previous chapter, constant updating of skills and qualifications is important. Chapter 3 examines the causal wage return to training. Training is defined as being supported by the employer, be it partially or fully funded, or taking place during work hours. Furthermore, training lasts at minimum 40 hours a year. The problem of positive selection arises again. Workers who participate in employer-financed training are a nonrandom group. To estimate the causal wage effect of training, two approaches are used. The first approach, which is proposed by Leuven and Oosterbeek (2008), uses in-depth data information. Available data in the Swiss Labor Force Survey helps to build a quasi-randomized control group. Only workers who wanted to participate in training but could not due to a random event are used as the adequate controls. If this event is random, it acts as random assignment to treatment. The second approach applies econometric methods to eliminate different sources of the bias. In the sample, approximately 20% of full-time employed male workers enjoy firm-financed training. The preferred approach to eliminate nonrandom selection in this setting is the enhancement of the quasi-randomization approach with econometric methods. It is shown that both approaches contain certain problems, so a combination is most fruitful. The wage effect of employer-financed training, corrected for selection bias, is rather small, but positive.
Chapter 4 aims to describe the dynamics in job satisfaction after a job or an occupation change. Workers change jobs in order to maximize their utility. In contrast to the previous chapters, the focus lies on non-monetary utility. Non-monetary job utility can be proxied with job satisfaction. Selfrated levels of job satisfaction are trustworthy and offer new insights in the dynamics of the labor market. Literature shows that low job satisfaction levels are good predictors of job search behavior or job mobility (e. g., Freeman, 1978; Clark, Georgellis, and Sanfey, 1998). Vice versa, high job satisfaction reduces quitting. How persistent is the impact of a job change on the level of job satisfaction? Is there an adaptation process? The Swiss Household Panel is perfectly designed to answer these questions. Workers are identified to be either movers or stayers. Propensity score matching allows identifying the impact of job changes on future job satisfaction levels. The impact is significant for up to three years, the size of the impact is quite large, but decreasing. It seems that individuals adapt to a new, but the adaptation process takes some time. Analyzing the impact of job change in more detail, I find that satisfaction with work conditions matters a lot. On the other hand, the impact on the log of annual wages is rather small and insignificant. Comparing men and women, it becomes evident that men react more to job changes than women. The impact for men is very long-lasting and large in size, be it on the job satisfaction level itself or especially on the satisfaction with work conditions. The analysis in this chapter shows that the inclusion of non-monetary factors is important and is able to describe the Adaptation process followed by a job change.
Summing up, this thesis draws on two panel data sets to analyze various topics of labor economics. In combination with microeconometric methods, I am able to examine labor market outcomes, be they wage or non-monetary utility. I find that training is important for updating individuals’ labor market perspectives. Furthermore, training itself increases wages. Individuals do not only evaluate monetary incentives, they are also driven by non-monetary factors. A thorough analysis of labor market events includes monetary and non-monetary outcomes and accounts for the nonrandom selection.
Switzerland offers an interesting case for analyzing labor topics. It has many unique characteristics: the small open economy lies at the heart of Europe and is affected by labor market decisions from abroad. Evidence from labor studies in other countries cannot be directly used as comparison since the Swiss education system is very specific. The educational System in Switzerland is based on vocational education: two-thirds of Youngsters follow an apprenticeship directly after secondary education. Apprenticeships are offered by the employer, and students work two to three days at the work place. Moreover, they follow general and occupation-specific schooling one to two days a week. This provides a very early and tight connection to the labor market. Another important aspect of the Swiss system is its flexibility and the low importance of regulations.
A major challenge in applied labor economics is the nonrandom selection. Many treatments are only available to the more motivated and more able workers that have different personality traits, so mean comparison of outcomes would overestimate the effect of these treatments. This demands the choice of adequate microeconometric methods in order to eliminate, or at least reduce, the existing bias so that results are causally interpretable.
In chapter 2 of this thesis, my co-author J¨urg Schweri and I analyze skills mismatches. The motivation for this analysis stems from an often heard hypothesis about vocational education. Vocational education is assumed to be very specific and thus hindering labor market flexibility of its graduates. One way to examine this hypothesis is to focus on wage differentials between workers with vocational education and others with general education who experience a skills mismatch. Skills mismatch can be defined in various ways. We compare wages of matched and mismatched workers based on two definitions. The first definition views skill mismatch as a divergence between the formal education and the current occupation. The second definition views skill mismatch as a divergence between the set of qualifications a worker has and the qualifications needed at the current job. This second definition is also called subjective horizontal mismatch since it evaluates whether skills fit qualitatively or not, and does not analyze if there are too few or too many skills. Based on the Swiss Household Panel data, the analysis Shows that a substantial share of workers is formally mismatched, but that a much smaller share feels mismatched in regards to qualifications. Recognizing the existence of unobserved individual heterogeneity and applying fixed effects regression, wage penalties are insignificant. The sub-analysis of workers with apprenticeship training and workers with a tertiary education does not show that vocational education hinders mobility. However, there seems to be a gender gap story. Male workers, independently of their educational background, do not experience a wage penalty due to being mismatched. On the other hand, female workers with a vocational background experience a wage penalty if they are subjectively horizontally mismatched. Yet, the penalty is not statistically different compared to females with a general educational background. We conclude that vocational education, at least when analyzing skills mismatches, does not hinder mobility.
As a result of the previous chapter, constant updating of skills and qualifications is important. Chapter 3 examines the causal wage return to training. Training is defined as being supported by the employer, be it partially or fully funded, or taking place during work hours. Furthermore, training lasts at minimum 40 hours a year. The problem of positive selection arises again. Workers who participate in employer-financed training are a nonrandom group. To estimate the causal wage effect of training, two approaches are used. The first approach, which is proposed by Leuven and Oosterbeek (2008), uses in-depth data information. Available data in the Swiss Labor Force Survey helps to build a quasi-randomized control group. Only workers who wanted to participate in training but could not due to a random event are used as the adequate controls. If this event is random, it acts as random assignment to treatment. The second approach applies econometric methods to eliminate different sources of the bias. In the sample, approximately 20% of full-time employed male workers enjoy firm-financed training. The preferred approach to eliminate nonrandom selection in this setting is the enhancement of the quasi-randomization approach with econometric methods. It is shown that both approaches contain certain problems, so a combination is most fruitful. The wage effect of employer-financed training, corrected for selection bias, is rather small, but positive.
Chapter 4 aims to describe the dynamics in job satisfaction after a job or an occupation change. Workers change jobs in order to maximize their utility. In contrast to the previous chapters, the focus lies on non-monetary utility. Non-monetary job utility can be proxied with job satisfaction. Selfrated levels of job satisfaction are trustworthy and offer new insights in the dynamics of the labor market. Literature shows that low job satisfaction levels are good predictors of job search behavior or job mobility (e. g., Freeman, 1978; Clark, Georgellis, and Sanfey, 1998). Vice versa, high job satisfaction reduces quitting. How persistent is the impact of a job change on the level of job satisfaction? Is there an adaptation process? The Swiss Household Panel is perfectly designed to answer these questions. Workers are identified to be either movers or stayers. Propensity score matching allows identifying the impact of job changes on future job satisfaction levels. The impact is significant for up to three years, the size of the impact is quite large, but decreasing. It seems that individuals adapt to a new, but the adaptation process takes some time. Analyzing the impact of job change in more detail, I find that satisfaction with work conditions matters a lot. On the other hand, the impact on the log of annual wages is rather small and insignificant. Comparing men and women, it becomes evident that men react more to job changes than women. The impact for men is very long-lasting and large in size, be it on the job satisfaction level itself or especially on the satisfaction with work conditions. The analysis in this chapter shows that the inclusion of non-monetary factors is important and is able to describe the Adaptation process followed by a job change.
Summing up, this thesis draws on two panel data sets to analyze various topics of labor economics. In combination with microeconometric methods, I am able to examine labor market outcomes, be they wage or non-monetary utility. I find that training is important for updating individuals’ labor market perspectives. Furthermore, training itself increases wages. Individuals do not only evaluate monetary incentives, they are also driven by non-monetary factors. A thorough analysis of labor market events includes monetary and non-monetary outcomes and accounts for the nonrandom selection.