Munich Personal RePEc Archive

Technological innovation and employment in derived labour demand models: A hierarchical meta-regression analysis

Ugur, Mehmet and Awaworyi, Sefa and Solomon, Edna (2016): Technological innovation and employment in derived labour demand models: A hierarchical meta-regression analysis.

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Abstract

The effect of technological innovation on employment is of major concern for workers and their unions, policy-makers and academic researchers. We aim to provide a quantitative synthesis of the evidence base and the extent of heterogeneity therein. Analysing 567 estimates from 35 primary studies that estimate a derived labour demand model we report the following findings: (i) the effect on employment is positive but small and highly heterogeneous; (ii) publication selection bias reflects a tendency to support the twin hypotheses that process innovation is associated with job destruction whereas product innovation is associated with job creation; (iii) the effects of process and product innovations do not conform to theoretical predictions or narrative review findings after selection bias is controlled for; (iv) only a small part of the residual heterogeneity is explained by moderating factors; (v) country-specific effect-size estimates are related to labour-market and product-market regulation in six OECD countries in a U-shaped fashion; and (vi) OLS estimates reflect upward bias whereas those based on time-differenced or within estimators reflect a downward bias. Our findings bridge the evidence gap in the research field and point out to data quality and modeling issues that should be considered in future research.

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