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A Richer Understanding of Australia's Productivity Performance in the 1990s: Improved Estimates Based Upon Firm-Level Panel Data


Australian industry is characterised by differences across firms, entry of new firms and exit of unsuccessful firms. These facts highlight the inappropriateness of measuring productivity using aggregate production functions based upon representative firms. In this study, we model heterogeneous firms which change over time. We model the interrelationship between productivity shocks, input choices and decisions to cease production. Firm-level data provides production function estimates for 25 two-digit Australian industries. A new aggregation method for industry-level data allows us to separate productivity changes from output composition changes. Our study sheds new light on the Australian productivity performance. Copyright © 2008 The Economic Society of Australia.

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Article provided by The Economic Society of Australia in its journal Economic Record.

Volume (Year): 84 (2008)
Issue (Month): 265 (06)
Pages: 157-176

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Handle: RePEc:bla:ecorec:v:84:y:2008:i:265:p:157-176
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  1. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," Review of Economic Studies, Oxford University Press, vol. 70(2), pages 317-341.
  2. Amil Petrin & James Levinsohn, 2005. "Measuring Aggregate Productivity Growth Using Plant-Level Data," NBER Working Papers 11887, National Bureau of Economic Research, Inc.
  3. Nina Pavcnik, 2002. "Trade Liberalization, Exit, and Productivity Improvements: Evidence from Chilean Plants," Review of Economic Studies, Oxford University Press, vol. 69(1), pages 245-276.
  4. Andrews, Donald W K, 1991. "Asymptotic Normality of Series Estimators for Nonparametric and Semiparametric Regression Models," Econometrica, Econometric Society, vol. 59(2), pages 307-45, March.
  5. Muendler, Marc-Andreas, 2004. "Estimating Production Functions When Productivity Change Is Endogenous," University of California at San Diego, Economics Working Paper Series qt0w02f5tw, Department of Economics, UC San Diego.
  6. Hopenhayn, Hugo & Rogerson, Richard, 1993. "Job Turnover and Policy Evaluation: A General Equilibrium Analysis," Journal of Political Economy, University of Chicago Press, vol. 101(5), pages 915-38, October.
  7. James Levinsohn & Amil Petrin, 2000. "Estimating Production Functions Using Inputs to Control for Unobservables," NBER Working Papers 7819, National Bureau of Economic Research, Inc.
  8. George S Olley & Ariel Pakes, 1992. "The Dynamics Of Productivity In The Telecommunications Equipment Industry," Working Papers 92-2, Center for Economic Studies, U.S. Census Bureau.
  9. Chiara Criscuolo & Ralf Martin, 2004. "Multinationals and U.S. Productivity Leadership: Evidence from Great Britain," OECD Science, Technology and Industry Working Papers 2004/5, OECD Publishing.
  10. Eric J. Bartelsman & Mark Doms, 2000. "Understanding productivity: lessons from longitudinal microdata," Finance and Economics Discussion Series 2000-19, Board of Governors of the Federal Reserve System (U.S.).
  11. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
  12. Ericson, Richard & Pakes, Ariel, 1995. "Markov-Perfect Industry Dynamics: A Framework for Empirical Work," Review of Economic Studies, Wiley Blackwell, vol. 62(1), pages 53-82, January.
  13. Muendler, Marc-Andreas, 2004. "Trade, Technology, and Productivity: A Study of Brazilian Manufacturers, 1986-1998," University of California at San Diego, Economics Working Paper Series qt6m96c2r7, Department of Economics, UC San Diego.
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  15. Blalock, Garrick & Gertler, Paul J., 2004. "Learning from exporting revisited in a less developed setting," Journal of Development Economics, Elsevier, vol. 75(2), pages 397-416, December.
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