Return to Experience and Initial Wage Level: Do Low Wage Workers Catch Up?

Sørensen, Kasper; Vejlin, Rune

doi:10.1002/jae.2346

Cited by 11 publications

(11 citation statements)

References 21 publications

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“…Hence, focusing on the CCEP results, an additional year of work experience leads to an increase in hourly wages by 6.4%. This result is in line with the existing literature, where the effect of experience is typically found to be 3–6% (see, e.g., Sørensen & Vejlin, ; Lagakos, Moll, Porzio, Qian, & Schoellman, ). EXP2 is insignificant with estimated effects that are small (in absolute value) when compared to the previous literature (see, e.g., Belzil & Hansen, ; Heckman, Lochner, & Todd, ).…”

Section: Applicationsupporting

confidence: 92%

CCE in fixed‐T panels

Westerlund

Petrova

Norkutė

2019

J of Applied Econometrics

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Summary The presence of unobserved heterogeneity and its likely detrimental effect on inference has recently motivated the use of factor‐augmented panel regression models. The workhorse of this literature is based on first estimating the unknown factors using the cross‐section averages of the observables, and then applying ordinary least squares conditional on the first‐step factor estimates. This is the common correlated effects (CCE) approach, the existing asymptotic theory for which is based on the requirement that both the number of time series observations, T, and the number of cross‐section units, N, tend to infinity. The obvious implication of this theory for empirical work is that both N and T should be large, which means that CCE is impossible for the typical micro panel where only N is large. In the current paper, we put the existing CCE theory and its implications to a test. This is done by developing a new theory that enables T to be fixed. The results show that many of the previously derived large‐T results hold even if T is fixed. In particular, the pooled CCE estimator is still consistent and asymptotically normal, which means that CCE is more applicable than previously thought. In fact, not only do we allow T to be fixed, but the conditions placed on the time series properties of the factors and idiosyncratic errors are also much more general than those considered previously.

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Section: Applicationsupporting

confidence: 92%

CCE in fixed‐T panels

Westerlund

Petrova

Norkutė

2019

J of Applied Econometrics

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“…For instance, Gruetter and Lalive (2009) and Woodcock (2008), find that firm differences explain the bulk of the variation in industry average wages (75 and 72 per cent, respectively). Conversely, Sørensen and Vejlin (2013), find that worker differences explain roughly 74 per cent of the raw inter-industry wage differentials. Card et al (2013) report that both components, firm and individual effects, are important, although worker effects are slightly more important than firm effects (i.e.…”

Section: Main Results: the Contribution Of Firm Wage Policies To Wage Dispersionmentioning

confidence: 96%

Decomposing the structure of wages into firm and worker effects

Rebollo‐Sanz

2017

IJM

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Purpose The purpose of this paper is to show that for some key topics on labour economics such as the effect of seniority and job mobility in wages, it is important to explicitly consider firm fixed effects. The author also wants to test whether the importance of firm in explaining wage dispersion is higher or lower in Spain than in other European countries. Design/methodology/approach The author estimates an individual wage equation where firm and workers effects are considered and the estimation process control for censored wages. This exercise is performed for the Spanish economy over the course of a whole business cycle, i.e., 2000-2015. Findings The author demonstrates that Spanish firms contribute to explain around 27 per cent of the individual wage heterogeneity but more importantly around 74 per cent of inter-industry wage differentials. In both cases, this contribution is mainly related to large dispersion in firm’s wage policies. The process of positive sorting of workers across firms or industries does not play an important role. Interestingly, the importance of firm’s wage policies in explaining individual wage dispersion has increased over the current Big Recession. Practical implications The results confirm that firms set wages and, henceforth, are partially responsible for individual wage heterogeneity but more importantly for inter-industrial wage dispersion. Originality/value The exercise is performed under optimal conditions because the author uses a longitudinal matched employer-employee data set, observed wages are at a monthly frequency, and implements an estimation method suitable for censored models with two high-dimensional fixed effects. This is the first study that looks deeply into the role of firms in explaining wage heterogeneity at the individual and industry level in Spain and along the current Big Recession.

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“…However, if most of the variation in wage growth comes from firm effects then it will matter a lot for the worker which job he or she takes. Baker (1997), Gladden and Taber (2009), and Sørensen and Vejlin (2011) show differences in wage growth given initial wages. They particularly show that it matters for the worker which job he or she enters into as the wage structure is different for different initial jobs.…”

Section: Introductionmentioning

confidence: 95%

“…zero worker‐specific effects) then guiding workers into any job increasing overall physical experience the most would be optimal. With worker‐specific effects [Sørensen and Vejlin (2011) refer to worker effects as worker‐specific return to experience] the wage profile will be different for different jobs.…”

Section: Introductionmentioning

confidence: 99%

Worker and Firm Heterogeneity in Wage Growth: An AKM Approach

Sørensen

Vejlin

2011

Labour

Self Cite

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This paper estimates a wage growth equation containing human capital variables known from the traditional Mincerian wage equation with year, worker and firm fixed effects included as well. The paper thus contributes further to the large empirical literature on unobserved heterogeneity following the work of Abowd, Kramarz, and Margolis (1999). Our main contribution is to extend the analysis from wage levels to wage growth. The specification enables us to estimate the individual specific and firm specific fixed effects and their degree of explanation on wage growth. The analysis is conducted using Danish longitudinal matched employer-employee data from 1980 to 2006. We find that the worker fixed effect dominates both the firm fixed effect and the effect of the observed covariates. Worker effects are estimated to explain seven to twelve per cent of the variance in wage growth while firm effects are estimated to explain four to ten per cent. We furthermore find a negative correlation between the worker and firm effects, as do nearly all authors examining wage level equations.

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Return to Experience and Initial Wage Level: Do Low Wage Workers Catch Up?

Cited by 11 publications

References 21 publications

CCE in fixed‐T panels

CCE in fixed‐T panels

Decomposing the structure of wages into firm and worker effects

Worker and Firm Heterogeneity in Wage Growth: An AKM Approach

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