We can calculate the marginal effect of a change in external flexibility on labour productivity growth
for empirical values of the Schumpeter II indicator, using the equation: . Subdividing the Schumpeter II indicator into 4 quartiles, it turned out that, as expected, in the first two quartiles (that is, ‘garage business’ firms), changes in shares of flexible labour had only negligible effects. However, in the upper two quartiles (that is, among ‘routinised innovators’) we found significantly negative effects.
Even if labour markets were deregulated, firms could of course still try to maintain ‘high road’ or ‘collaborative’ HRM policies which, according to Rizov/Croucher (2009), tends to be positively related to firm performance. They also report, however, that the relationship between ‘collaborative HRM’ and firm performance is weaker if firm-level policies are not supported by national institutional and normative settings. This could lead firms to abandon ‘collaborative’ HRM policies in response to ‘structural reforms’ of labour markets.
In its highly influential evaluation of political party programs for the 2012 national elections, the Netherlands Bureau for Economic Policy Analysis (CPB) attributed positive productivity effects to proposals for easier firing that allow for a higher labour turnover, although empirical findings (for example, Lucidi/Kleinknecht 2010) point exactly in the opposite direction. What a pity for our empirical outcomes that they are inconsistent with the theoretical assumptions in the CPB's econometric models!
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APPENDIX 1: OUR THREE DATA SOURCES
Our main source is The Netherlands Employers Work Survey 2008 (NEWS, in Dutch: Werkgevers Enquête Arbeid 2008) database, which was gathered in October 2008 (Oeij et al. 2009). The NEWS is a large-scale, bi-annual and representative questionnaire survey among Dutch companies. For this survey, a total of 15 233 Dutch companies with at least two employees were approached through the Dutch LISA classification register. The sample is stratified by industry and company size. Respondents were first contacted by telephone and then received an internet link to an online questionnaire. The net response rate (35 per cent) consisted of 5387 affiliations of companies and (not-for-profit and public) institutions. The respondents were directors or HR managers. The response group is representative of the population of all organisations in the country that employ labour. For more information, we refer to the report Employers Labour Survey 2008: Methodology and Descriptive Results (www.tno.nl/wea). From this database we use data for our indicator of internal flexibility and for all the control variables.
The NEWS sample was merged with balance-sheet data and wage-tax registration statistics from Statistics Netherlands. The balance-sheet database covers all firms with a balance total of > €23 million and a random sample of firms with a balance total of < €23 million. The matching process of our NEWS 2008 data with the balance-sheet data leads to a substantial reduction of numbers of observations. There are two main reasons for the reduction of observations. First, the balance-sheet data are at enterprise level, while many observation units in the NEWS sample are affiliations. The latter had to be omitted for the sake of consistency. Second, both the NEWS and the balance-sheet data are sampling smaller firms with a balance total of < €23 million which directly implies that we lose many observations. Furthermore, we eliminated outliers according to the method proposed by Aubert/Crepon (2006) and removed not-for-profit and public sector organisations as the latter have no measurable productivity performance. Finally, we only included companies that had no item non-response on the relevant variables. All in all, this resulted in a data set with 377 valid observations. We tested representativeness of the matched subsample in an earlier study (Dhondt et al. 2012) by comparing the distribution of firms over sectors, firm size classes and other indicators with that of the total WEA sample. We found that the shape of the distributions are roughly similar. Only smaller companies and companies in manufacturing, construction, and transport & logistics are slightly overrepresented.
Balance Sheet Statistics for Non-Financial Firms (in Dutch: Statistiek Niet-Financiële Ondernemingen, NFO) were obtained from Statistics Netherlands (CBS). The data consist of a sample of balance sheet and annual account data for smaller and larger firms. For smaller firms, the data set covers a sample of 150 000 firms; for larger firms the data consist of a registration of 2500 firms. We constructed our measure for value added (as a component of labour productivity) from this database.
Wage-Tax Registrations Statistics (in Dutch: Loonaangifte statistieken, LA) are also collected by Statistics Netherlands. This data set covers all income tax statistics of all taxed employees in the Netherlands. We constructed our objective measure for external flexibility and the number of FTEs per firm from the latter database. We calculated labour productivity as the ratio of value added over employees (full-time equivalents) at firm level.