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Non-structural and Structural Models in Productivity Analysis: Study of the British Isles during the 2007-2009 Financial Crisis

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  • Gong, Binlei

    (Zhejiang University)

  • Sickles, Robin C.

    (Rice University)

Abstract

The paper reviews and provides an extension of the benefits and drawbacks of the non-structural Stochastic Frontier Analysis (SFA) paradigm, as well as other number index-based procedures that we will utilize in the analysis. We then compare SFA with two structural models: the Pakes McGuire Model (PMM) (Pakes, Gowrisankaran and McGuire 1993) and the Midrigan and Xu Model (MXM) (Midrigan and Xu 2014). All three methods are used to estimate changes in firm-level productivity in the British Isles before and after the 2007-2009 financial crisis under the canonical single production assumption. The empirical results indicate that overall productivity was not impacted to any substantial degree by the financial crisis, according to both SFA and the PMM. However, the productivity loss estimated by MXM due to financial friction from the recession was substantial.

Suggested Citation

  • Gong, Binlei & Sickles, Robin C., 2016. "Non-structural and Structural Models in Productivity Analysis: Study of the British Isles during the 2007-2009 Financial Crisis," Working Papers 16-004, Rice University, Department of Economics.
  • Handle: RePEc:ecl:riceco:16-004
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    1. Nazrul Islam, 1999. "International Comparison Of Total Factor Productivity: A Review," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 45(4), pages 493-518, December.
    2. Agrell, Per J. & Bogetoft, Peter, 2017. "Regulatory Benchmarking: Models, Analyses and Applications," Data Envelopment Analysis Journal, now publishers, vol. 3(1-2), pages 49-91, November.
    3. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    4. Giulia Faggio & Kjell G. Salvanes & John Van Reenen, 2010. "The evolution of inequality in productivity and wages: panel data evidence," Industrial and Corporate Change, Oxford University Press, vol. 19(6), pages 1919-1951, December.
    5. Robert Inklaar & Mary O'Mahony & Marcel Timmer, 2005. "ICT AND EUROPE's PRODUCTIVITY PERFORMANCE: INDUSTRY‐LEVEL GROWTH ACCOUNT COMPARISONS WITH THE UNITED STATES," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 51(4), pages 505-536, December.
    6. Ariel Pakes & Paul McGuire, 1994. "Computing Markov-Perfect Nash Equilibria: Numerical Implications of a Dynamic Differentiated Product Model," RAND Journal of Economics, The RAND Corporation, vol. 25(4), pages 555-589, Winter.
    7. Daniel J. Graham & Patricia S. Melo & Piyapong Jiwattanakulpaisarn & Robert B. Noland, 2010. "Testing For Causality Between Productivity And Agglomeration Economies," Journal of Regional Science, Wiley Blackwell, vol. 50(5), pages 935-951, December.
    8. Guariglia, Alessandra & Mateut, Simona, 2010. "Inventory investment, global engagement, and financial constraints in the UK: Evidence from micro data," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 239-250, March.
    9. Norsworthy, J R, 1984. "Growth Accounting and Productivity Measurement," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 30(3), pages 309-329, September.
    10. Gong, Binlei, 2018. "Agricultural reforms and production in China: Changes in provincial production function and productivity in 1978–2015," Journal of Development Economics, Elsevier, vol. 132(C), pages 18-31.
    11. John Van Reenen & Rupert Harrison & Rachel Griffith, 2006. "How Special Is the Special Relationship? Using the Impact of U.S. R&D Spillovers on U.K. Firms as a Test of Technology Sourcing," American Economic Review, American Economic Association, vol. 96(5), pages 1859-1875, December.
    12. Haskel, J & Goodridge, P & Wallis, G, 2012. "UK Innovation Index: productivity and growth in UK industries," Working Papers 9786, Imperial College, London, Imperial College Business School.
    13. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    14. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    15. Jagjit Chadha, 2016. "The UK Economy in the Long Expansion and its Aftermath," National Institute of Economic and Social Research (NIESR) Discussion Papers 473, National Institute of Economic and Social Research.
    16. Binlei Gong, 2020. "Effects of Ownership and Business Portfolio on Production in the Oil and Gas Industry," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    17. João Paulo Pessoa & John Van Reenen, 2014. "The UK Productivity and Jobs Puzzle: Does the Answer Lie in Wage Flexibility?," Economic Journal, Royal Economic Society, vol. 0(576), pages 433-452, May.
    18. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    19. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    20. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    21. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    22. J. Cummins & Xiaoying Xie, 2013. "Efficiency, productivity, and scale economies in the U.S. property-liability insurance industry," Journal of Productivity Analysis, Springer, vol. 39(2), pages 141-164, April.
    23. Mirko Draca & Stephen Machin & John Van Reenen, 2011. "Minimum Wages and Firm Profitability," American Economic Journal: Applied Economics, American Economic Association, vol. 3(1), pages 129-151, January.
    24. Chang-Tai Hsieh & Peter J. Klenow, 2009. "Misallocation and Manufacturing TFP in China and India," The Quarterly Journal of Economics, Oxford University Press, vol. 124(4), pages 1403-1448.
    25. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    26. Chadha,Jagjit S. & Crystal,Alec & Pearlman,Joe & Smith,Peter & Wright,Stephen (ed.), 2016. "The UK Economy in the Long Expansion and its Aftermath," Cambridge Books, Cambridge University Press, number 9781107147591.
    27. Kneip, Alois & Sickles, Robin C. & Song, Wonho, 2012. "A New Panel Data Treatment For Heterogeneity In Time Trends," Econometric Theory, Cambridge University Press, vol. 28(3), pages 590-628, June.
    28. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    29. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    30. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
    31. Daniel J. Graham, 2007. "Agglomeration, Productivity and Transport Investment," Journal of Transport Economics and Policy, University of Bath, vol. 41(3), pages 317-343, September.
    32. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    33. Miguel Boucinha & Nuno Ribeiro & Thomas Weyman-Jones, 2013. "An assessment of Portuguese banks’ efficiency and productivity towards euro area participation," Journal of Productivity Analysis, Springer, vol. 39(2), pages 177-190, April.
    34. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    35. T. K. Rymes, 1983. "More On The Measurement Of Total Factor Productivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 29(3), pages 297-316, September.
    36. Abdelkader Derbali, 2017. "Systemic risk ranking of US financial institutions," International Journal of Management and Network Economics, Inderscience Enterprises Ltd, vol. 4(1), pages 1-41.
    37. Claudia Curi & Ana Lozano-Vivas, 2015. "Financial center productivity and innovation prior to and during the financial crisis," Journal of Productivity Analysis, Springer, vol. 43(3), pages 351-365, June.
    38. Maskin, Eric & Tirole, Jean, 1988. "A Theory of Dynamic Oligopoly, II: Price Competition, Kinked Demand Curves, and Edgeworth Cycles," Econometrica, Econometric Society, vol. 56(3), pages 571-599, May.
    39. Burnside, Craig, 1996. "Production function regressions, returns to scale, and externalities," Journal of Monetary Economics, Elsevier, vol. 37(2-3), pages 177-201, April.
    40. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    41. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    42. Richard Ericson & Ariel Pakes, 1992. "An Alternative Theory of Firm and Industry Dynamics," Cowles Foundation Discussion Papers 1041, Cowles Foundation for Research in Economics, Yale University.
    43. Maskin, Eric & Tirole, Jean, 1988. "A Theory of Dynamic Oligopoly, I: Overview and Quantity Competition with Large Fixed Costs," Econometrica, Econometric Society, vol. 56(3), pages 549-569, May.
    44. Vincenzo Mollisi & Gabriele Rovigatti, 2017. "Theory and Practice of TFP Estimation: the Control Function Approach Using Stata," CEIS Research Paper 399, Tor Vergata University, CEIS, revised 14 Feb 2017.
    45. Christian Helmers & Mark RogersPhilipp Schautschick, 2011. "Intellectual Property at the Firm-Level in the UK: The Oxford Firm-Level Intellectual Property Database," Economics Series Working Papers 546, University of Oxford, Department of Economics.
    46. Michiel Van Dijk & Adam Szirmai, 2011. "The Micro‐Dynamics Of Catch‐Up In Indonesian Paper Manufacturing," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 57(1), pages 61-83, March.
    47. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    48. Perelman, Sergio, 1995. "R&D, Technological Progress and Efficiency Change in Industrial Activities," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 41(3), pages 349-366, September.
    49. Mette Asmild & Tomas Baležentis & Jens Leth Hougaard, 2016. "Multi-directional productivity change: MEA-Malmquist," Journal of Productivity Analysis, Springer, vol. 46(2), pages 109-119, December.
    50. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    51. Markus Eberhardt & Christian Helmers, 2010. "Untested Assumptions and Data Slicing: A Critical Review of Firm-Level Production Function Estimators," Economics Series Working Papers 513, University of Oxford, Department of Economics.
    52. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    53. Gong, Binlei, 2018. "Different behaviors in natural gas production between national and private oil companies: Economics-driven or environment-driven?," Energy Policy, Elsevier, vol. 114(C), pages 145-152.
    54. Virgiliu Midrigan & Daniel Yi Xu, 2014. "Finance and Misallocation: Evidence from Plant-Level Data," American Economic Review, American Economic Association, vol. 104(2), pages 422-458, February.
    55. Kumbhakar, Subal C. & Wang, Hung-Jen, 2005. "Estimation of growth convergence using a stochastic production frontier approach," Economics Letters, Elsevier, vol. 88(3), pages 300-305, September.
    56. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    57. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    58. Richard Harris & Qian Cher Li, 2008. "Evaluating the Contribution of Exporting to UK Productivity Growth: Some Microeconomic Evidence," The World Economy, Wiley Blackwell, vol. 31(2), pages 212-235, February.
    59. Sickles, Robin C., 2005. "Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings," Journal of Econometrics, Elsevier, vol. 126(2), pages 305-334, June.
    60. Helmers, Christian & Rogers, Mark, 2011. "Does patenting help high-tech start-ups?," Research Policy, Elsevier, vol. 40(7), pages 1016-1027, September.
    61. J. R. Norsworthy, 1984. "Growth Accounting And Productivity Measurement," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 30(3), pages 309-329, September.
    62. Kutlu, Levent, 2018. "A distribution-free stochastic frontier model with endogenous regressors," Economics Letters, Elsevier, vol. 163(C), pages 152-154.
    63. V. Ball & Carlos San-Juan-Mesonada & Camilo Ulloa, 2014. "State productivity growth in agriculture: catching-up and the business cycle," Journal of Productivity Analysis, Springer, vol. 42(3), pages 327-338, December.
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    3. Gong, Binlei, 2020. "Agricultural productivity convergence in China," China Economic Review, Elsevier, vol. 60(C).

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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • G01 - Financial Economics - - General - - - Financial Crises
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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