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Firm-heterogeneous biased technological change : a nonparametric approach under endogeneity

Ruben Dewitte (UGent) , Michel Dumont (UGent) , Bruno Merlevede (UGent) , Glenn Rayp (UGent) and Marijn Verschelde
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Abstract
We propose a fully nonparametric framework to test to what extent technological change is factor-biased and heterogeneous. We show in a Monte Carlo simulation that our framework resolves the endogeneity issue between productivity and input choice and provides accurate estimates of firm-specific biases. For all Belgian manufacturing industries analyzed, we reject the predominant assumption of Hicks-neutral technological change over the period 1996–2015. We find that technological change is skill-biased, capital saving and domestic materials using. Moreover, we find significant heterogeneity in the pattern of technological change between and within industries. Relying on a rich dataset of firm characteristics, we provide robust indications that firm-level technological change can be attributed to specific firm strategies and technological characteristics.
Keywords
Management Science and Operations Research, Modelling and Simulation, Information Systems and Management

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Please use this url to cite or link to this publication:

MLA
Dewitte, Ruben, et al. “Firm-Heterogeneous Biased Technological Change : A Nonparametric Approach under Endogeneity.” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2019.
APA
Dewitte, R., Dumont, M., Merlevede, B., Rayp, G., & Verschelde, M. (2019). Firm-heterogeneous biased technological change : a nonparametric approach under endogeneity. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH.
Chicago author-date
Dewitte, Ruben, Michel Dumont, Bruno Merlevede, Glenn Rayp, and Marijn Verschelde. 2019. “Firm-Heterogeneous Biased Technological Change : A Nonparametric Approach under Endogeneity.” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH.
Chicago author-date (all authors)
Dewitte, Ruben, Michel Dumont, Bruno Merlevede, Glenn Rayp, and Marijn Verschelde. 2019. “Firm-Heterogeneous Biased Technological Change : A Nonparametric Approach under Endogeneity.” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH.
Vancouver
1.
Dewitte R, Dumont M, Merlevede B, Rayp G, Verschelde M. Firm-heterogeneous biased technological change : a nonparametric approach under endogeneity. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH. 2019;
IEEE
[1]
R. Dewitte, M. Dumont, B. Merlevede, G. Rayp, and M. Verschelde, “Firm-heterogeneous biased technological change : a nonparametric approach under endogeneity,” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2019.
@article{8642634,
  abstract     = {We propose a fully nonparametric framework to test to what extent technological change is factor-biased and heterogeneous. We show in a Monte Carlo simulation that our framework resolves the endogeneity issue between productivity and input choice and provides accurate estimates of firm-specific biases. For all Belgian manufacturing industries analyzed, we reject the predominant assumption of Hicks-neutral technological change over the period 1996–2015. We find that technological change is skill-biased, capital saving and domestic materials using. Moreover, we find significant heterogeneity in the pattern of technological change between and within industries. Relying on a rich dataset of firm characteristics, we provide robust indications that firm-level technological change can be attributed to specific firm strategies and technological characteristics.},
  author       = {Dewitte, Ruben and Dumont, Michel and Merlevede, Bruno and Rayp, Glenn and Verschelde, Marijn},
  issn         = {0377-2217},
  journal      = {EUROPEAN JOURNAL OF OPERATIONAL RESEARCH},
  keywords     = {Management Science and Operations Research,Modelling and Simulation,Information Systems and Management},
  language     = {eng},
  title        = {Firm-heterogeneous biased technological change : a nonparametric approach under endogeneity},
  url          = {http://dx.doi.org/10.1016/j.ejor.2019.11.063},
  year         = {2019},
}

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