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Estimating Capital Efficiency Schedules Within Production Functions

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  • Mark E Doms

Abstract

The appropriate method for aggregating capital goods across vintages to produce a single capital stock measure has long been a contentious issue, and the literature covering this topic is quite extensive. This paper presents a methodology that estimates efficiency schedules within a production function, allowing the data to reveal how the efficiency of capital goods evolve as they age. Specifically we insert a parameterized investment stream into the position of a capital variable in a production function, and then estimate the parameters of the production function simultaneously with the parameters of the investment stream. Plant level panel data for a select group of steel plants employing a common technology are used to estimate the model. Our primary finding is that when using a simple Cobb Douglas production function, the estimated efficiency schedules appear to follow a geometric pattern, which is consistent with the estimates of economic depreciation of Hulten and Wykoff (1981). Results from more flexible functional forms produced much less precise and unreliable estimates.

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Bibliographic Info

Paper provided by Center for Economic Studies, U.S. Census Bureau in its series Working Papers with number 92-4.

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Date of creation: May 1992
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Handle: RePEc:cen:wpaper:92-4

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Keywords: CES; economic; research; micro; data; microdata; chief; economist;

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References

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  1. Ariel Pakes & Zvi Griliches, 1982. "Estimating Distributed Lags in Short Panels with an Application to the Specification of Depreciation Patterns and Capital Stock Constructs," NBER Working Papers 0933, National Bureau of Economic Research, Inc.
  2. De Long, J Bradford & Summers, Lawrence H, 1991. "Equipment Investment and Economic Growth," The Quarterly Journal of Economics, MIT Press, vol. 106(2), pages 445-502, May.
  3. 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 111-30, February.
  4. repec:fth:coluec:465 is not listed on IDEAS
  5. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
  6. 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.
  7. 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.
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Cited by:
  1. Wayne B. Gray & Ronald J. Shadbegian, 2001. "Plant Vintage, Technology, and Environmental Regulation," NBER Working Papers 8480, National Bureau of Economic Research, Inc.
  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. Plutarchos Sakellaris & Daniel J. Wilson, 2001. "The production-side approach to estimating embodied technological change," Finance and Economics Discussion Series 2001-20, Board of Governors of the Federal Reserve System (U.S.).
  5. Gort, Michael & Wall, Richard A., 1998. "Obsolescence, input augmentation, and growth accounting," European Economic Review, Elsevier, vol. 42(9), pages 1653-1665, November.
  6. Sang Nguyen & B.K. Atrostic, 2005. "Computer Investment, Computer Networks and Productivity," Working Papers 05-01, Center for Economic Studies, U.S. Census Bureau.
  7. 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.
  8. 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.
  9. 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.
  10. Sang V Nguyen & Mary L Streitwieser, 1998. "Factor Substitution In U.S. Manufacturing: Does Plant Size Matter," Working Papers 98-6, Center for Economic Studies, U.S. Census Bureau.
  11. 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.
  12. 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.

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