VoxEU Column Labour Markets

Matching skills of individuals and firms along the career path

Workers who switch firms can lose firm-specific human capital. This column presents evidence of how moving to occupationally specialised firms can compensate workers for wage losses that are caused by ‘specific human capital’. When switches occur between firms that are very distant from each other in terms of their knowledge structure, occupationally specialised firms are prepared to pay a wage premium that can outweigh the costs of such long-distance switches.

Along everyone’s career path, the question surfaces at least once of what would happen if one were to switch jobs. But how can one achieve good job matches along a career path? In light of increasing job volatility and regular organisational changes, there is a constant interest in transferable skills because they improve workers’ employability. However, what are these transferable skills and how costly does switching jobs become when most skills are not transferable?

Becker (1964) suggested that firm knowledge increases with tenure and that all firm knowledge is lost in the case of a firm switch – the notion of firm-specific human capital and its opposite, transferable skills. Empirical research has used the variable firm tenure to prove the lack of transferability of firm knowledge. Yet this method narrows the analysis down to a strict dichotomous classification – an either/or situation – and neglects that firm knowledge might also be transferable. In the event of a firm switch, such as from a university in one city to a university in another, knowledge about university structures such as committee work continues to be useful while knowledge about, for example, special state laws regulating refunding of travel expenses may not continue to be helpful. Similarities between the previous and future employers determine whether knowledge continues to be useful after a switch. This also implies that not all firm knowledge has to be specific, but rather that it can also be general. Lazear (2009) provides a different method of modeling firm-specific knowledge by letting firms place different weights on general skills. The weights generate firm-specific skill portfolios that can be compared to each other, assuming that a certain amount of all knowledge is transferable across firms. Gathmann and Schönberg (2010) test and provide evidence for this approach by investigating the relationship between occupational knowledge and wages. To date, there has been no investigation of the degree to which firm knowledge is portable across establishments and hence of Becker’s suggestion that all firm knowledge is specific.

Advantages and disadvantages of firm switches

Lazear’s (2009) theory suggests that firm switches are less costly if firms place the same weights on skills. In a recent paper (Bublitz 2015), I show that knowledge structures of firms, representing skill weights, play a decisive role in determining wages. I make use of a recent methodological improvement – namely, tasks data (Autor et al. 2003, Poletaev and Robinson 2008, Gathmann and Schönberg 2010) – to make visible what is otherwise often regarded as a black box: occupational and firm knowledge. In addition, representative data covering labour market histories of 1.5 million individuals in Germany, provided by the German Federal Employment Agency, are accessed.

Starting with an analytical framework, I conduct an empirical investigation. A typical employment career as derived from the analytical framework is illustrated in Figure 1, showing that workers accumulate more and more knowledge along their career path. In the case of job switches, the amount of transferred knowledge increases along the career path.

Figure 1 A typical employment career

The empirical analysis starts with a factor analysis to categorise tasks into groups. The task composition of firms is determined via the occupational composition of the workforce. The relative task importance results from the share that a selected task makes up against all tasks of all employees, regardless of their occupation. The task distance between firms is calculated using the angular separation. My analyses confirm that firm knowledge consists of a sticky and a portable component. Individuals try to switch between more similar firms, and the low-skilled cover longer distances (see Figure 2).  Long-distance firm switches occur more often early in careers than later on (see Figure 3). Multivariate regressions show that the type of knowledge that can be transferred and to what extent depends on the qualification level of workers. In the case of joint firm and occupation switches, firm- and occupation-specific knowledge both matter for wages. The evidence indicates that firm-specific knowledge matters less than occupation-specific knowledge.

 Figure 2 Distribution of joint switches across firm distance intervals

Notes: Data are grouped by qualification level: LQ is low qualification, MQ is medium qualification, HQ is high qualification.
Source: Bublitz (2015).

Figure 3 Relationship between work experience and firm distance

Notes: Data are grouped by qualification level: LQ is low qualification, MQ is medium qualification, HQ is high qualification.
Source: Bublitz (2015).

Regarding the incentives to switch, the analysis considers a new variable for the specific knowledge structure of firms by measuring the occupational structure with the share of occupational peers at the firm level (occupational intensity). Interestingly, it can be shown that individuals start work in firms that have a relatively higher share of employees in the same occupational group, i.e. a high occupational intensity, and that this share decreases with increasing work experience (Figure 4). Taking this a step further in OLS estimations reveals that a lower occupational intensity is associated with higher wages. However, workers might strategically select into firms with a certain occupational composition. To control for this selection problem, occupational intensity is instrumented with occupational diversity on the industry level. In the two-stage least squares regression results, occupational intensity now shows a positive effect on wages for medium- and high-skilled workers and becomes insignificant for low-skilled employees. Surprisingly, the sizes of the coefficients (based on standardised variables) suggest that the benefits of occupational intensity can clearly outweigh the costs of both distance measures. This effect supports the notion that a high occupational intensity shows a higher demand for an occupational tasks set, which is reflected in higher wages. The overall results generally hold for both men and women. They are further robust to various control variables and alternative model specifications.

Figure 4 The relationship between work experience and occupational intensity

Notes: Data are grouped by qualification level: LQ is low qualification, MQ is medium qualification, HQ is high qualification.
Source: Bublitz (2015).


In sum, my paper contributes to the literature by showing that the specificity of firm knowledge is determined by context. All firm knowledge can, thus, become either specific or general. In addition, the results suggest that both firm and occupational knowledge matter for wages after switches. The analysis further shows potential advantages resulting from switches into occupationally intensive firms. This helps to better understand which individuals will travel longer distances between firms and thus, due to this greater flexibility, might be easier to match to new jobs. Also, human capital theory predicts that costs of general on-the-job training should be borne by the worker, while in reality specific training costs seem to be covered partly by workers and partly by firms. If the specificity depends on where workers move next, then this might explain why the empirical studies differ from the theoretical predictions (e.g. Barron and Berger 1999, Parent 1999).  


Autor, D. H., F. Levy and R. J. Murnane (2003), “The Skill Content of Recent Technological Change: An Empirical Exploration”, Quarterly Journal of Economics 118(4), 1279–1333.

Barron, J. M. and M. C. Berger (1999), “Do workers pay for on-the-job training?”, Journal of Human Resources 34(2), 235-252.

Becker, G. S. (1964), Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education, Chicago: University of Chicago Press.

Bublitz, E. (2015), “Matching Skills of Individuals and Firms along the Career Path”, HWWI Research Paper No. 165, Hamburg Institute of International Economics.

Gathmann, C. and U. Schönberg (2010), “How General Is Human Capital? A Task-Based Approach”, Journal of Labor Economics 28(1), 1–49.

Lazear, E. P. (2009), “Firm-Specific Human Capital: A Skill-Weights Approach”, Journal of Political Economy 117(5), 914–940.

Parent, D. (1999), “Wages and Mobility: The Impact of Employer-Provided Training”, Journal of Labor Economics 17(2), 298-317.

Poletaev, M. and C. Robinson (2008), “Human Capital Specificity: Evidence from the Dictionary of Occupational Titles and Displaced Worker Surveys, 1984-2000”, Journal of Labor Economics 26(3), 387-420.

525 Reads