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Estimating Capital Efficiency Schedules within Production Functions

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  • Doms, Mark E

Abstract

The author estimates capital efficiency schedules within a production function, allowing the data to reveal how the efficiency of capital goods evolves as they age. A parameterized investment stream is used as a capital variable in a production function and the parameters of the production function are estimated simultaneously with the parameters of the investment stream. Plant-level panel data for steel plants employing a common technology are used to estimate the model. The author finds that the estimated efficiency schedules appear to follow a geometric pattern, which is consistent with the estimates of economic depreciation of C. Hulten and F. Wykoff (1981). Copyright 1996 by Oxford University Press.

Suggested Citation

  • Doms, Mark E, 1996. "Estimating Capital Efficiency Schedules within Production Functions," Economic Inquiry, Western Economic Association International, vol. 34(1), pages 78-92, January.
  • Handle: RePEc:oup:ecinqu:v:34:y:1996:i:1:p:78-92
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    References listed on IDEAS

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    1. AriƩl Pakes & Zvi Griliches, 1984. "Estimating Distributed Lags in Short Panels with an Application to the Specification of Depreciation Patterns and Capital Stock Constructs," Review of Economic Studies, Oxford University Press, vol. 51(2), pages 243-262.
    2. Epstein, L. & Denny, M., 1980. "Endogenous capital utilization in a short-run production model : Theory and an empiral application," Journal of Econometrics, Elsevier, vol. 12(2), pages 189-207, February.
    3. W. Erwin Diewert, 1980. "Aggregation Problems in the Measurement of Capital," NBER Chapters,in: The Measurement of Capital, pages 433-538 National Bureau of Economic Research, Inc.
    4. Kim, Moshe, 1988. "The Structure of Technology with Endogenous Capital Utilization," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(1), pages 111-130, February.
    5. J. Bradford De Long & Lawrence H. Summers, 1991. "Equipment Investment and Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 106(2), pages 445-502.
    6. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    7. Prucha, Ingmar R. & Nadiri, M. Ishaq, 1996. "Endogenous capital utilization and productivity measurement in dynamic factor demand models Theory and an application to the U.S. electrical machinery industry," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 343-379.
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    Cited by:

    1. Vladimir Gorbunov & Vladimir Krylov, 2015. "Region Effective Production Assets and their Assessment by the Production Function Method," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 334-347.
    2. Douglas W Dwyer, 1995. "Whittling Away At Productivity Dispersion," Working Papers 95-5, Center for Economic Studies, U.S. Census Bureau.
    3. Drucker, Joshua & Feser, Edward, 2012. "Regional industrial structure and agglomeration economies: An analysis of productivity in three manufacturing industries," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 1-14.
    4. Richard Harris & Catherine Robinson, 2005. "Impact of Regional Selective Assistance on sources of productivity growth: Plant-level evidence from UK manufacturing, 1990-98," Regional Studies, Taylor & Francis Journals, vol. 39(6), pages 751-765.
    5. Sanghamitra Das & Ramprasad Sengupta, 2004. "Projection pursuit regression and disaggregate productivity effects: the case of the Indian blast furnaces," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(3), pages 397-418.
    6. Gort, Michael & Wall, Richard A., 1998. "Obsolescence, input augmentation, and growth accounting," European Economic Review, Elsevier, vol. 42(9), pages 1653-1665, November.
    7. Adela Luque, 2000. "An Option-Value Approach to Technology in U.S. Maufacturing: Evidence from Plant-Level Data," Working Papers 00-12, Center for Economic Studies, U.S. Census Bureau.
    8. Sang Nguyen & B.K. Atrostic, 2005. "Computer Investment, Computer Networks and Productivity," Working Papers 05-01, Center for Economic Studies, U.S. Census Bureau.
    9. Sang V Nguyen & Mary L Streitwieser, 1997. "Capital-Energy Substitution Revisted: New Evidence From Micro Data," Working Papers 97-4, Center for Economic Studies, U.S. Census Bureau.
    10. Nguyen, Sang V & Streitwieser, Mary L, 1999. "Factor Substitution in U.S. Manufacturing: Does Plant Size Matter?," Small Business Economics, Springer, vol. 12(1), pages 41-57, February.
    11. Gray, Wayne B. & Shadbegian, Ronald J., 2003. "Plant vintage, technology, and environmental regulation," Journal of Environmental Economics and Management, Elsevier, vol. 46(3), pages 384-402, November.
    12. Plutarchos Sakellaris & Dan Wilson, 2000. "The Production-Side Approach to Estimating Embodied Technological Change," Electronic Working Papers 00-002, University of Maryland, Department of Economics.
    13. Adela Luque, 2002. "An option-value approach to technology adoption in U.S. manufacturing: Evidence from microdata," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 11(6), pages 543-568.
    14. Martin, Sheila Ann, 1992. "The effectiveness of state technology incentives: evidence from the machine tool industry," ISU General Staff Papers 1992010108000011381, Iowa State University, Department of Economics.

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