Skill Mismatch and Skill Transferability: Review of Concepts and Measurements

The notion of skills plays an increasingly important role in a variety of research fields. Since the foundational work on human capital theory, economists have approached skills through the lens of education, training and work experience, whereas early work in evolutionary economics and management stressed the analogy between skills of individuals and the organizational routines of firms. We survey how the concept of skills has evolved into notions such as skills mismatch, skill transferability and skill distance or skill relatedness in labor economics, management, and evolutionary approaches to economics and economic geography. We find that these disciplines converged in embracing increasingly sophisticated approaches to measuring skills. Economists have expanded their approach from quantifying skills in terms of years of education to measuring them more directly, using skill tests, self-reported skills and job tasks, or skills and job tasks reported by occupational experts. Others have turned to administrative and other large-scale data sets to infer skill similarities and complementarities from the careers of sometimes millions of workers. Finally, a growing literature on team human capital and skill complementarities has started thinking of skills as features of collectives, instead of only of individuals. At the same time, scholars in corporate strategy have studied the micro-determinants of team formation. Combined, the developments in both strands of research may pave the way to an understanding of how individual-level skills connect to firm-level routines.

Network Backboning with Noisy Data

Networks are powerful instruments to study complex phenomena, but they become hard to analyze in data that contain noise. Network backbones provide a tool to extract the latent structure from noisy networks by pruning non-salient edges. We describe a new approach to extract such backbones. We assume that edge weights are drawn from a binomial distribution, and estimate the error-variance in edge weights using a Bayesian framework. Our approach uses a more realistic null model for the edge weight creation process than prior work. In particular, it simultaneously considers the propensity of nodes to send and receive connections, whereas previous approaches only considered nodes as emitters of edges. We test our model with real world networks of different types (flows, stocks, cooccurrences, directed, undirected) and show that our Noise-Corrected approach returns backbones that outperform other approaches on a number of criteria. Our approach is scalable, able to deal with networks with millions of edges.

The Mobility of Displaced Workers: How the Local Industry Mix Affects Job Search

Are there Marshallian externalities in job search? We study how workers who lose their jobs in establishment closures in Germany cope with their loss of employment. About a fifth of these displaced workers do not return to social-security covered employment within the next three years. Among those who do get re-employed, about two-thirds leave their old industry and one-third move out of their region. However, which of these two types of mobility responses workers will choose depends on the local industry mix in ways that are suggestive of Marshallian benefits to job search. In particular, large concentrations of one’s old industry makes it easier to find new jobs: in regions where the pre-displacement industry is large, displaced workers suffer relatively small earnings losses and find new work faster. In contrast, large local industries skill-related to the pre-displacement industry increase earnings losses but also protect against long-term unemployment. Analyzed through the lens of a job-search model, the exact spatial and industrial job-switching patterns reveal that workers take these Marshallian externalities into account when deciding how to allocate search efforts among industries.

Is Our Human Capital General Enough to Withstand the Current Wave of Technological Change?

The degree to which modern technologies are able to substitute for groups of job tasks has renewed fears of near-future technological unemployment. We argue that our knowledge, skills and abilities (KSA) go beyond the specific tasks we do at the job, making us potentially more adaptable to technological change than feared. The disruptiveness of new technologies depends on the relationships between the job tasks susceptible to automation and our KSA. Here we first demonstrate that KSA are general human capital features while job tasks are not, suggesting that human capital is more transferrable across occupations than what job tasks would predict. In spite of this, we document a worrying pattern where automation is not randomly distributed across the KSA space – it is concentrated among occupations that share similar KSA. As a result, workers in these occupations are making longer skill transitions when changing occupations and have higher probability of unemployment.

Why do Industries Coagglomerate? How Marshallian Externalities Differ by Industry and Have Evolved Over Time

The fact that firms benefit from close proximity to other firms with which they can exchange inputs, skilled labor or know-how helps explain why many industrial clusters are so successful. Studying the evolution of coagglomeration patterns, we show that which type of agglomeration benefits firms has drastically changed over the course of a century and differs markedly across industries. Whereas, at the beginning of the twentieth century, industries tended to colocate with their value chain partners, in more recent decades the importance of this channels has declined and colocation seems to be driven more by similarities industries’ skill requirements. By calculating industry-specific Marshallian agglomeration forces, we are able to show that, nowadays, skill-sharing is the most salient motive in location choices of services, whereas value chain linkages still explain much of the colocation patterns in manufacturing. Moreover, the estimated degrees to which labor and input-output linkages are reflected in an industry’s coagglomeration patterns help improve predictions of city-industry employment growth.

Original version of this paper was published in 2016.

Inter-industry Labor Flows

Using German social security data, we study inter-industry labor mobility to assess how industry-specific human capital is and to determine which industries have similar human capital requirements. We find that inter-industry labor flows are highly concentrated in just a handful of industry pairs. Consequently, labor flows connect industries in a sparse network. We interpret this network as an expression of industries similarities in human capital requirements, or skill relatedness. This skill-relatedness network is stable over time, similar for different types of workers and independent of whether workers switch jobs locally or over larger distances. Moreover, in an application to regional diversification and local industry growth, skill relatedness proves to be more predictive than colocation or value chain relations. To facilitate future research, we make detailed inter-industry relatedness matrices online available.

Agents of Structural Change: The Role of Firms and Entrepreneurs in Regional Diversification

Who introduces structural change in regional economies: Entrepreneurs or existing firms? And do local or nonlocal establishment founders create most novelty in a region? We develop a theoretical framework that focuses on the roles different agents play in regional transformation. We then apply this framework, using Swedish matched employer–employee data, to determine how novel the activities of new establishments are to a region. Incumbents mainly reinforce a region’s current specialization: incumbent’s growth, decline, and industry switching further align them with the rest of the local economy. The unrelated diversification required for structural change mostly originates via new establishments, especially via those with nonlocal roots. Interestingly, although entrepreneurs often introduce novel activities to a local economy, when they do so, their ventures have higher failure rates compared to new subsidiaries of existing firms. Consequently, new subsidiaries manage to create longer-lasting change in regions.

Last updated on 12/10/2021

Coworker complementarity

How important is working with people who complement one’s skills? Using administrative data that record which of 491 educational tracks each worker in Sweden absolved, I quantify the educational fit among coworkers along two dimensions: coworker match and coworker substitutability. Complementary coworkers raise wages with a comparable factor as does a college degree, whereas working with close substitutes is associated with wage penalties. Moreover, this coworker fit does not only account for large portions of the urban and large-plant wage premiums, but the returns to own schooling and the urban wage premium are almost completely contingent on finding complementary coworkers.

Exploring the Uncharted Export: An Analysis of Tourism-Related Foreign Expenditure with International Spend Data

Tourism is one of the most important economic activities in the world: for many countries it represents the single largest product in their export basket. However, it is a product difficult to chart: “exporters” of tourism do not ship it abroad, but they welcome importers inside the country. Current research uses social accounting matrices and general equilibrium models, but the standard industry classifications they use make it hard to identify which domestic industries cater to foreign visitors. In this paper, we make use of open source data and of anonymized and aggregated transaction data giving us insights about the spend behavior of foreigners inside two countries, Colombia and the Netherlands, to inform our research. With this data, we are able to describe what constitutes the tourism sector, and to map the most attractive destinations for visitors. In particular, we find that countries might observe different geographical tourists’ patterns – concentration versus decentralization -; we show the importance of distance, a country’s reported wealth and cultural affinity in informing tourism; and we show the potential of combining open source data and anonymized and aggregated transaction data on foreign spend patterns in gaining insight as to the evolution of tourism from one year to another.

Agglomeration Economies: The Heterogeneous Contribution of Human Capital and Value Chains

**Updated version of this paper published here**

We document the heterogeneity across sectors in the impact labor and input-output links have on industry agglomeration. Exploiting the available degrees of freedom in coagglomeration patterns, we estimate the industry-specic benefits of sharing labor needs and supply links with local firms. On aggregate, coagglomeration patterns of services are at least as strongly driven by input-output linkages as those of manufacturing, whereas labor linkages are much more potent drivers of coagglomeration in services than in manufacturing. Moreover, the degree to which labor and input-output linkages are reflected in an industry’s coagglomeration patterns is relevant for predicting patterns of city-industry employment growth.