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Untested Assumptions and Data Slicing: A Critical Review of Firm-Level Production Function Estimators

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  • Markus Eberhardt
  • Christian Helmers

Abstract

This paper surveys the most popular parametric and semi-parametric estimators for Cobb-Douglas production functions arising from the econometric literature of the past two decades. We focus on the different approaches dealing with 'transmission bias' in firm-level studies, which arises from firms' reaction to unobservable productivity realisations when making input choices. The contribution of the paper is threefold: we provide applied economists with (i) an in-depth discussion of the estimation problem and the solutions suggested in the literature; (ii) a detailed empirical example using FAME data for UK high-tech firms, emphasising analytical tools to investigate data properties and the robustness of the empirical results; (iii) a powerful illustration of the impact of estimator choice on TFP estimates, using matched data on patents in 'TFP regressions'. Our discussion concludes that while from a theoretical point of view the different estimators are conceptually very similar, in practice, the choice of the preferred estimator is far from arbitrary and instead requires in-depth analysis of the data properties rather than blind belief in asymptotic consistency.�

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Bibliographic Info

Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 513.

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Date of creation: 01 Nov 2010
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Handle: RePEc:oxf:wpaper:513

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Keywords: Productivity; production function; UK firms; panel data estimates;

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References

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Citations

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Cited by:
  1. Markus Eberhardt & Francis Teal, . "Aggregation versus Heterogeneity in Cross-Country Growth Empirics," Discussion Papers 11/08, University of Nottingham, CREDIT.
  2. Markus Eberhardt & Christian Helmers & Hubert Strauss, . "Do Spillovers Matter When Estimating Private Returns to R&D?," Discussion Papers 11/22, University of Nottingham, GEP.
  3. Monica Correa Lopez & Rafael Domenech, 2014. "Does anti-competitive service sector regulation harm exporters? Evidence from manufacturing firms in Spain," Working Papers 1413, BBVA Bank, Economic Research Department.
  4. d'Artis Kancs & Boriss Siliverstovs, 2012. "R&D and Non-linear Productivity Growth of Heterogeneous Firms," LICOS Discussion Papers 32112, LICOS - Centre for Institutions and Economic Performance, KU Leuven.
  5. Marin, Giovanni, 2014. "Do eco-innovations harm productivity growth through crowding out? Results of an extended CDM model for Italy," Research Policy, Elsevier, vol. 43(2), pages 301-317.
  6. Serafinelli, Michel, 2013. "Good Firms, Worker Flows and Productivity," MPRA Paper 47508, University Library of Munich, Germany.
  7. Francesco Venturini & Ana Rincon-Aznar & Dr Michela Vecchi, 2013. "ICT as a general purpose technology: spillovers, absorptive capacity and productivity performance," NIESR Discussion Papers 11717, National Institute of Economic and Social Research.
  8. repec:ial:wpaper:3 is not listed on IDEAS
  9. Markus Eberhardt & Andrea Presbitero, 2013. "This Time They Are Different: Heterogeneity and Nonlinearity in the Relationship Between Debt and Growth," IMF Working Papers 13/248, International Monetary Fund.
  10. Markus Eberhardt, 2013. "Nonlinearities in the Relationship between Debt and Growth: Evidence from Co-Summability Testing," Discussion Papers 2013/06, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  11. Bena Jan & Ondko Peter & Vourvachaki Evangelia, 2011. "Productivity Gains from Services Liberalization in Europe," EERC Working Paper Series 11/15e, EERC Research Network, Russia and CIS.
  12. Laurin Janes, 2013. "Can capital grants help microenterprises reach the productivity level of SMEs? Evidence from an experiment in Sri Lanka," CSAE Working Paper Series 2013-18, Centre for the Study of African Economies, University of Oxford.

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