Employment Protection, Technology Choice, and Worker Allocation

Abstract

Using a country-industry panel dataset (EUKLEMS) we uncover a robust empirical regularity, namely that high-risk innovative sectors are relatively smaller in countries with strict employment protection legislation (EPL). To understand the mechanism, we develop a two-sector matching model where …rms endogenously choose between a safe technology with known productivity and a risky technology with productivity subject to sizeable shocks. Strict EPL makes the risky technology relatively less attractive because it is more costly to shed workers upon receiving a low productivity draw. We calibrate the model using a variety of aggregate, industry and micro-level data sources.We then simulate the model to re ‡ect both the observed di¤erences across countries in EPL and the observed increase since the mid-1990s in the variance of …rm performance associated with the adoption of information and communication technology. The simulations produce a di¤erential response to the Acknowledgements: We would like to thank Wouter den Haan, Egbert Jongen, Roland Luttens, Marcel Jansen, participants of CAED, Tokyo and ECB/CEPR Labour Market Workshop, Frankfurt as well as seminar participants at the University of Copenhagen, CPB, the Tinbergen Institute, VU Universiy, University of Maastricht and Nederlandsche Bank for useful comments and suggestions. 1 arrival of risky technology between low-and high-EPL countries that coincides with the …ndings in the data. The described mechanism can explain a considerable portion of the slowdown in productivity in the EU relative to the US since 1995.

Heterogeneity, selection and labor market disparities

“…These values are similar to those reported in Krueger et al (2010). 9 Focusing on college educated workers only, the variance of the log of residual wages is 0.32 in the United States and 0.17 in Italy. 10 These …gures have been computed for 2007.…”

“…8 Even after controlling for workers'characteristics, the variance of the logarithms of residual wages is 0.26 in the United States and 0.12 in Italy. 9 Unemployment is also lower in the United States, especially for skilled workers. For example, the unemployment rate of U.S. college graduate is about half of that of the total workforce, while in Italy it is about 70% of the mean (OECD 2013).…”

Digital Technology Adoption and Jobs: A Model of Firm Heterogeneity

“…Employment protection legislation can also be viewed as discouraging to undertaking risky activities such as investment in innovation and in ICT-intensive sectors, as in Bartelsman, Gautier and de Wind (2016), Saint Paul (2002), Koeniger (2005), Bartelsmand and Hinloopen (2005), and Samainego (2006). Bartelsman et al (2016) argue that, because of the experimentation and changes required in organizational structure, the outcome of investment in ICT is highly uncertain. This is supported by the empirical finding that productivity is more dispersed in ICT-intensive sectors (Brynjolfsson et al, 2008).…”

“…Using a cross-industry and cross-country panel dataset of the US and the EU (EUKLEMS), Bartelsman et al (2016) show that high-risk ICT-intensive sectors are smaller in terms of employment in countries with stricter labor regulations. These empirical facts hold when comparing the EU to the US, where labor regulations are more flexible, and when comparing countries within the EU.…”

The Jobs Potential of a Shift Towards a Low-Carbon Economy

“…Incremental innovation increases productivity, but to a lesser extent than radical innovation, hence the possibility of retraining and upskilling existing production workers. Likewise, Bartelsman, Gautier and de Wind (2010) suggest that differences in EP stringency can explain why the United States was better able to explore the benefits of the new information technology starting in the mid 1990s. This past research suggests that the return to R&D investments in green industries or services will differ depending on the national EP and PMR in force.…”