Firm-Heterogeneous Biased Technological Change: A nonparametric approach under endogeneity

Ruben Dewitte (1) , Michel Dumont (1) , Bruno Merlevede (1) , Glenn Rayp (1) , Marijn Verschelde (2)

1 UGENT - Universiteit Gent = Ghent University
2 LEM - Lille économie management - UMR 9221

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.

Mots clés: Productivity and competitiveness; Technological change; Firm heterogeneity; Nonparametric; Endogeneity

Domaines: Sciences de l'Homme et Société; Gestion et management

Ruben Dewitte, Michel Dumont, Bruno Merlevede, Glenn Rayp, Marijn Verschelde. Firm-Heterogeneous Biased Technological Change: A nonparametric approach under endogeneity. European Journal of Operational Research, 2020, 283 (3), pp.1172-1182. ⟨10.1016/j.ejor.2019.11.063⟩. ⟨hal-03001787⟩