Description of work
Provide firm level estimates from existing databases, such as those collated for OECD and other statistical sources.

Including Eurostat estimates of firm turnover.

Microdata based measures augment the EU-KLEMS database by including higher moments and covariances of the underlying micro-level distributions of variables. Examples of the measures that will be included are decompositions of productivity growth into between-firm reallocations and firm entry and exit, the average productivity level of the top quartile (in productivity) of firms, and average firm-level growth by initial productivity quartile and post-entry growth rates of firms. These indicators will vary by country, industry, and year.

Update recent literature suggesting that within-industry reallocations of resources are more important than between industry shifts, particularly in developed countries.

Use data to see if firms in an industry respond more to the productivity at the national frontier or to the global frontier as proxied by the highest productivity level among the top quartile of national firms across all countries.

Experiment with use of firm level data as an input into future updating and implementation of EU KLEMS Productivity Database, for example through alternative classifications of industries, labour components or asset types. This should also include a design of a protocol that will allow future updates of the productivity database with indicators aggregated up the micro-data sources in member countries

Primary Contact
Eric Bartelsman, Economic and Social Institute, Free University Amsterdam
E-mail: ebartelsman@feweb.vu.nl

Workpackage Material