IDEAS home Printed from https://ideas.repec.org/p/ulp/sbbeta/2011-11.html
   My bibliography  Save this paper

Increasing Returns to Scale in U.S. manufacturing industries: evidence from direct and reverse regression

Author

Listed:
  • Xi Chen

Abstract

In this paper, I compare the OLS and IV estimators for the direct and reverse regression models in the context of estimating returns to scale and technical progress. It shows that the direct and reverse OLS estimators are inconsistent, that the direct OLS is always more precise than the reverse OLS under the normality assumption, and that the direct IV estimator and its reverse counterpart are consistent and asymptotically equivalent. Working with data from U.S. manufacturing industries over the last half-century, the estimation results show that in most industries increasing returns to scale are important and technical progress is small when it comes to explaining productivity growth.

Suggested Citation

  • Xi Chen, 2011. "Increasing Returns to Scale in U.S. manufacturing industries: evidence from direct and reverse regression," Working Papers of BETA 2011-11, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    • Handle: RePEc:ulp:sbbeta:2011-11
    as

    Download full text from publisher

    File URL: http://beta.u-strasbg.fr/WP/2011/2011-11.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jones, Charles I., 2005. "Growth and Ideas," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 16, pages 1063-1111, Elsevier.
    2. Koebel, Bertrand M. & Laisney, François, 2010. "The aggregate Le Chatelier Samuelson principle with Cournot competition," ZEW Discussion Papers 10-009, ZEW - Leibniz Centre for European Economic Research.
    3. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    4. Diewert, W. Erwin & Fox, Kevin J., 2008. "On the estimation of returns to scale, technical progress and monopolistic markups," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 174-193, July.
    5. 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.
    6. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
    7. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    8. Arthur S. Goldberger, 1984. "Reverse Regression and Salary Discrimination," Journal of Human Resources, University of Wisconsin Press, vol. 19(3), pages 293-318.
    9. Hall, Robert E, 1988. "The Relation between Price and Marginal Cost in U.S. Industry," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 921-947, October.
    10. Subal C. Kumbhakar & Efthymios G. Tsionas, 2011. "Stochastic error specification in primal and dual production systems," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(2), pages 270-297, March.
    11. Farmer Roger E. A. & Guo Jang-Ting, 1994. "Real Business Cycles and the Animal Spirits Hypothesis," Journal of Economic Theory, Elsevier, vol. 63(1), pages 42-72, June.
    12. Pakes, Ariel, 1982. "On the Asymptotic Bias of Wald-Type Estimators of a Straight Line When Both Variables Are Subject to Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(2), pages 491-497, June.
    13. Bartelsman, Eric J., 1995. "Of empty boxes: Returns to scale revisited," Economics Letters, Elsevier, vol. 49(1), pages 59-67, July.
    14. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
    15. John Shea, 1997. "Instrument Relevance in Multivariate Linear Models: A Simple Measure," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 348-352, May.
    16. Teugels, Jozef L., 1987. "Stochastic modelling and analysis: A computational approach,: Henk C. Thijms, Wiley Series in Probability and Mathematical Statistics (Wiley, New York, 1986) pp. xii + 418, [UK pound]19.95," Insurance: Mathematics and Economics, Elsevier, vol. 6(3), pages 233-234, July.
    17. Mundlak, Yair, 1996. "Production Function Estimation: Reviving the Primal," Econometrica, Econometric Society, vol. 64(2), pages 431-438, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dai, Meixing, 2011. "Motivations and strategies for a real revaluation of the Yuan," MPRA Paper 30440, University Library of Munich, Germany.
    2. Houda Ghaya, 2011. "Board of Directors’ Involvement in Strategic Decision Making Process: Definition and Literature Review," Working Papers of BETA 2011-22, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    3. Julien Jacob, 2011. "Innovation and diffusion in risky industries under liability law: the case of “double-impact” innovations," Working Papers of BETA 2011-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    4. Jenny Monheim-Helstroffer & Marie Obidzinski, 2011. "The EU legislation game: the case of asylum law," Working Papers of BETA 2011-16, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.

    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. Bertrand Koebel & François Laisney, 2016. "Aggregation with Cournot Competition: An Empirical Investigation," Annals of Economics and Statistics, GENES, issue 121-122, pages 91-119.
    2. W. Diewert & Kevin Fox, 2010. "Malmquist and Törnqvist productivity indexes: returns to scale and technical progress with imperfect competition," Journal of Economics, Springer, vol. 101(1), pages 73-95, September.
    3. Wilson, Daniel J., 2000. "Estimating Returns to Scale: Lo, Still No Balance," Journal of Macroeconomics, Elsevier, vol. 22(2), pages 285-314, April.
    4. Diewert, W. Erwin & Fox, Kevin J., 2008. "On the estimation of returns to scale, technical progress and monopolistic markups," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 174-193, July.
    5. Lundin, Magnus & Gottfries, Nils & Lindström, Tomas, 2004. "Price and Investment Dynamics: An Empirical Analysis of Plant Level Data," Working Paper Series 2004:7, Uppsala University, Department of Economics.
    6. Susanto Basu & John Fernald, 2001. "Why Is Productivity Procyclical? Why Do We Care?," NBER Chapters, in: New Developments in Productivity Analysis, pages 225-302, National Bureau of Economic Research, Inc.
    7. Jean-Marie Dufour, 2003. "Identification, weak instruments, and statistical inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 767-808, November.
    8. Paul Schreyer & María Belén Zinni, 2021. "Productivity Measurement, R&D Assets, and Mark‐Ups in OECD Countries," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 787-809, December.
    9. Richard Startz & Charles Nelson & Eric Zivot, 1999. "Improved Inference for the Instrumental Variable Estimator," Working Papers 0039, University of Washington, Department of Economics.
    10. Dufour, Jean-Marie & Taamouti, Mohamed, 2007. "Further results on projection-based inference in IV regressions with weak, collinear or missing instruments," Journal of Econometrics, Elsevier, vol. 139(1), pages 133-153, July.
    11. Jean-Marie Dufour & Mohamed Taamouti, 2005. "Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments," Econometrica, Econometric Society, vol. 73(4), pages 1351-1365, July.
    12. Fuhrer, Jeffrey C. & Rudebusch, Glenn D., 2004. "Estimating the Euler equation for output," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1133-1153, September.
    13. Hervé Boulhol, 2005. "Why haven't price-cost margins decreased with globalization?," Cahiers de la Maison des Sciences Economiques bla06007, Université Panthéon-Sorbonne (Paris 1).
    14. Grant Hillier & Giovanni Forchini, 2004. "Ill-posed Problems and Instruments' Weakness," Econometric Society 2004 Australasian Meetings 357, Econometric Society.
    15. Kevin J Fox, 2005. "Returns to Scale, Technical Progress and Total Factor Productivity Growth in New Zealand Industries," Treasury Working Paper Series 05/04, New Zealand Treasury.
    16. Lindström, Tomas, 1999. "External Economies at the Firm Level: Evidence from Swedish Manufacturing," Working Paper Series 89, Sveriges Riksbank (Central Bank of Sweden).
    17. Dollar, David & Kraay, Aart, 2003. "Institutions, trade, and growth : revisiting the evidence," Policy Research Working Paper Series 3004, The World Bank.
    18. Vieira, Flávio & MacDonald, Ronald & Damasceno, Aderbal, 2012. "The role of institutions in cross-section income and panel data growth models: A deeper investigation on the weakness and proliferation of instruments," Journal of Comparative Economics, Elsevier, vol. 40(1), pages 127-140.
    19. Hilber, Christian A.L., 2010. "New housing supply and the dilution of social capital," Journal of Urban Economics, Elsevier, vol. 67(3), pages 419-437, May.
    20. Milo Bianchi & Paolo Buonanno & Paolo Pinotti, 2012. "Do Immigrants Cause Crime?," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1318-1347, December.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    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:ulp:sbbeta:2011-11. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bestrfr.html .

    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.