IDEAS home Printed from https://ideas.repec.org/p/srt/wpaper/0618.html
   My bibliography  Save this paper

Estimating a non-neutral production function: a heterogeneous treatment effect approach

Author

Listed:
  • Davide Antonioli

    (Università degli Studi "G. D'Annunzio" di Chieti-Pescara)

  • Georgios Gioldasis

    (Università degli Studi di Ferrara)

  • Antonio Musolesi

    (Università degli Studi di Ferrara)

Abstract

This paper addresses the issue of estimating a production function that allows us to depart from the standard hypothesis of Hicks neutrality while also coping with the endogeneity of a dummy innovation variable. We consider specifications that relax Hicks neutrality, and we derive the testable conditions for common parametric approximations under which Hicks neutrality holds. The model is estimated through instrumental variables methods, allowing for a heterogeneous effect of innovation on the production process. The econometric analysis rejects Hicks neutrality and highlights three main features: i) a capital-saving technology of innovative with respect to non-innovative firms, ii) a locally progressive technical change and iii) fully heterogeneous technologies when comparing innovative to non-innovative firms.

Suggested Citation

  • Davide Antonioli & Georgios Gioldasis & Antonio Musolesi, 2018. "Estimating a non-neutral production function: a heterogeneous treatment effect approach," SEEDS Working Papers 0618, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2018.
    • Handle: RePEc:srt:wpaper:0618
    as

    Download full text from publisher

    File URL: http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0618.pdf
    File Function: First version, 2018
    Download Restriction: no
    File URL: http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0618.pdf
    File Function: Revised version, 2018
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joshua D. Angrist & Alan B. Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 69-85, Fall.
    2. Mairesse, Jacques & Mohnen, Pierre, 2010. "Using Innovation Surveys for Econometric Analysis," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 1129-1155, Elsevier.
    3. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
    4. Crepon, B. & Duguet, E. & Mairesse, J., 1998. "Research Investment, Innovation and Productivity: An Econometric Analysis at the Firm Level," Papiers d'Economie Mathématique et Applications 98.15, Université Panthéon-Sorbonne (Paris 1).
    5. Steedman, Ian, 1985. "On the 'Impossibility' of Hicks-Neutral Technical Change," Economic Journal, Royal Economic Society, vol. 95(379), pages 746-758, September.
    6. Zvi Griliches, 1998. "Productivity and R&D at the Firm Level," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 100-133, National Bureau of Economic Research, Inc.
    7. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343, National Bureau of Economic Research, Inc.
    8. Bronwyn Hall & Francesca Lotti & Jacques Mairesse, 2009. "Innovation and productivity in SMEs: empirical evidence for Italy," Small Business Economics, Springer, vol. 33(1), pages 13-33, June.
    9. Basu, Susanto & Fernald, John G, 1997. "Returns to Scale in U.S. Production: Estimates and Implications," Journal of Political Economy, University of Chicago Press, vol. 105(2), pages 249-283, April.
    10. J. R. Hicks, 1963. "The Theory of Wages," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-349-00189-7, March.
    11. Jacques Mairesse, 2008. "Employment, innovation, and productivity: evidence from Italian microdata," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 17(4), pages 813-839, August.
    12. Zvi Griliches, 1984. "R&D, Patents, and Productivity," NBER Books, National Bureau of Economic Research, Inc, number gril84-1.
    13. Angrist, J.D., 1991. "Linear Instrumental Variables Estimation Of Average Treatment Effects In Nonlinear Models," Harvard Institute of Economic Research Working Papers 1542, Harvard - Institute of Economic Research.
    14. Ariel Pakes & Zvi Griliches, 1984. "Patents and R&D at the Firm Level: A First Look," NBER Chapters, in: R&D, Patents, and Productivity, pages 55-72, National Bureau of Economic Research, Inc.
    15. Wooldridge, Jeffrey M., 2003. "Further results on instrumental variables estimation of average treatment effects in the correlated random coefficient model," Economics Letters, Elsevier, vol. 79(2), pages 185-191, May.
    16. Parisi, Maria Laura & Schiantarelli, Fabio & Sembenelli, Alessandro, 2006. "Productivity, innovation and R&D: Micro evidence for Italy," European Economic Review, Elsevier, vol. 50(8), pages 2037-2061, November.
    17. G. M.P. Swann, 2009. "The Economics of Innovation," Books, Edward Elgar Publishing, number 13211.
    18. Ronald W. Jones, 2018. "The Structure of Simple General Equilibrium Models," World Scientific Book Chapters, in: International Trade Theory and Competitive Models Features, Values, and Criticisms, chapter 4, pages 61-84, World Scientific Publishing Co. Pte. Ltd..
    19. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    20. Zvi Griliches, 1998. "R&D and Productivity: The Econometric Evidence," NBER Books, National Bureau of Economic Research, Inc, number gril98-1.
    21. Kennedy, Charles & Thirlwall, A P, 1972. "Technical Progress: A Survey," Economic Journal, Royal Economic Society, vol. 82(325), pages 11-72, March.
    22. Hall, B.H., 2011. "Innovation and productivity," MERIT Working Papers 2011-028, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    23. Joshua D. Angrist, 1991. "Instrumental Variables Estimation of Average Treatment Effects in Econometrics and Epidemiology," NBER Technical Working Papers 0115, National Bureau of Economic Research, Inc.
    24. Pierre Mohnen & Bronwyn Hall, 2013. "Innovation and Productivity: An Update," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 3(1), pages 47-65, June.
    25. Joshua Angrist & Alan Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Working Papers 834, Princeton University, Department of Economics, Industrial Relations Section..
    26. Antonio Musolesi & Jean-Pierre Huiban, 2010. "Innovation and productivity in knowledge intensive business services," Journal of Productivity Analysis, Springer, vol. 34(1), pages 63-81, August.
    27. Bruno Crepon & Emmanuel Duguet & Jacques Mairesse, 1998. "Research, Innovation And Productivity: An Econometric Analysis At The Firm Level," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 7(2), pages 115-158.
    28. Chambers,Robert G., 1988. "Applied Production Analysis," Cambridge Books, Cambridge University Press, number 9780521314275, September.
    29. Giovanni Cerulli, 2014. "ivtreatreg: A command for fitting binary treatment models with heterogeneous response to treatment and unobservable selection," Stata Journal, StataCorp LP, vol. 14(3), pages 453-480, September.
    30. Daron Acemoglu, 2015. "Localised and Biased Technologies: Atkinson and Stiglitz's New View, Induced Innovations, and Directed Technological Change," Economic Journal, Royal Economic Society, vol. 0(583), pages 443-463, March.
    31. Kennedy, Charles & Thirlwall, A P, 1977. "Extended Hicks Neutral Technical Change-A Comment," Economic Journal, Royal Economic Society, vol. 87(348), pages 768-768, December.
    32. Hansen, Christian & Hausman, Jerry & Newey, Whitney, 2008. "Estimation With Many Instrumental Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 398-422.
    33. Griliches, Zvi, 1998. "R&D and Productivity," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226308869, September.
    34. repec:fth:prinin:455 is not listed on IDEAS
    35. José Luis Montiel Olea & Carolin Pflueger, 2013. "A Robust Test for Weak Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 358-369, July.
    36. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    37. Atkinson, Anthony B & Stiglitz, Joseph E, 1969. "A New View of Technological Change," Economic Journal, Royal Economic Society, vol. 79(315), pages 573-578, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Baumann, Julian & Kritikos, Alexander S., 2016. "The link between R&D, innovation and productivity: Are micro firms different?," Research Policy, Elsevier, vol. 45(6), pages 1263-1274.
    2. Wadho, Waqar & Chaudhry, Azam, 2020. "Innovation Strategies and Productivity Growth in Developing Countries: Evidence from Pakistan," GLO Discussion Paper Series 466, Global Labor Organization (GLO).
    3. David B. Audretsch & Alexander S. Kritikos & Alexander Schiersch, 2020. "Microfirms and innovation in the service sector," Small Business Economics, Springer, vol. 55(4), pages 997-1018, December.
    4. Hall, B.H., 2011. "Innovation and productivity," MERIT Working Papers 2011-028, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Wadho, Waqar & Chaudhry, Azam, 2022. "Innovation strategies and productivity growth in developing countries: Firm-level evidence from Pakistani manufacturers," Journal of Asian Economics, Elsevier, vol. 81(C).
    6. Burcu Fazlıoğlu & Başak Dalgıç & Ahmet Burçin Yereli, 2019. "The effect of innovation on productivity: evidence from Turkish manufacturing firms," Industry and Innovation, Taylor & Francis Journals, vol. 26(4), pages 439-460, April.
    7. Audretsch, David & Hafenstein, Marian & Kritikos, Alexander S. & Schiersch, Alexander, 2018. "Firm Size and Innovation in the Service Sector," IZA Discussion Papers 12035, Institute of Labor Economics (IZA).
    8. Bettina Peters & Rebecca Riley & Iulia Siedschlag & Priit Vahter & John McQuinn, 2018. "Internationalisation, innovation and productivity in services: evidence from Germany, Ireland and the United Kingdom," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 154(3), pages 585-615, August.
    9. Bronwyn Hall & Francesca Lotti & Jacques Mairesse, 2009. "Innovation and productivity in SMEs: empirical evidence for Italy," Small Business Economics, Springer, vol. 33(1), pages 13-33, June.
    10. Viroj Jienwatcharamongkhol & Sam Tavassoli, 2015. "Closing the gap: empirical evidence on firms’ innovation, productivity and exports," Chapters, in: Charlie Karlsson & Urban Gråsjö & Sofia Wixe (ed.), Innovation and Entrepreneurship in the Global Economy, chapter 12, pages 281-309, Edward Elgar Publishing.
    11. Wadho, Waqar & Chaudhry, Azam, 2018. "Innovation and firm performance in developing countries: The case of Pakistani textile and apparel manufacturers," Research Policy, Elsevier, vol. 47(7), pages 1283-1294.
    12. Antonelli, Cristiano, 2017. "Digital knowledge generation and the appropriability trade-off," Telecommunications Policy, Elsevier, vol. 41(10), pages 991-1002.
    13. Cui, Jingbo & Li, Xiaogang, "undated". "Innovation and Firm Productivity: Evidence from the US Patent Data," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235603, Agricultural and Applied Economics Association.
    14. Cristiano Antonelli & Alessandra Colombelli, 2017. "The locus of knowledge externalities and the cost of knowledge," Regional Studies, Taylor & Francis Journals, vol. 51(8), pages 1151-1164, August.
    15. Pierre Mohnen & Bronwyn Hall, 2013. "Innovation and Productivity: An Update," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 3(1), pages 47-65, June.
    16. Hans Loof & Almas Heshmati, 2006. "On the relationship between innovation and performance: A sensitivity analysis," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 15(4-5), pages 317-344.
    17. repec:lic:licosd:20308 is not listed on IDEAS
    18. Ugur, Mehmet & Trushin, Eshref & Solomon, Edna & Guidi, Francesco, 2016. "R&D and productivity in OECD firms and industries: A hierarchical meta-regression analysis," Research Policy, Elsevier, vol. 45(10), pages 2069-2086.
    19. Montresor, Sandro & Vezzani, Antonio, 2015. "The production function of top R&D investors: Accounting for size and sector heterogeneity with quantile estimations," Research Policy, Elsevier, vol. 44(2), pages 381-393.
    20. Grigorii V. Teplykh, 2018. "Innovations and productivity: the shift during the 2008 crisis," Industry and Innovation, Taylor & Francis Journals, vol. 25(1), pages 53-83, January.
    21. Antonelli, Cristiano & David, Paul, 2015. "The Generation of Knowledge as an Emergent System Property: An Introduction," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201540, University of Turin.

    More about this item

    Keywords

    Biased technical change; Hicks neutrality; Innovation; Productivity; Knowledge production function; CDM model; Instrumental variables; heterogeneous treatment effect;
    All these keywords.

    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:srt:wpaper:0618. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Alessandro Palma (email available below). General contact details of provider: http://www.sustainability-seeds.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.