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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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  • Mark E Doms, 1992. "Estimating Capital Efficiency Schedules Within Production Functions," Working Papers 92-4, Center for Economic Studies, U.S. Census Bureau.
    • Handle: RePEc:cen:wpaper:92-4
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    Cited by:

    1. Doms, Mark & Dunne, Timothy & Roberts, Mark J., 1995. "The role of technology use in the survival and growth of manufacturing plants," International Journal of Industrial Organization, Elsevier, vol. 13(4), pages 523-542, December.
    2. 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.
    3. Douglas W Dwyer, 1995. "Whittling Away At Productivity Dispersion," Working Papers 95-5, Center for Economic Studies, U.S. Census Bureau.
    4. Gorbunov, Vladimir & Lvov, Alexander, 2021. "Анализ Малого И Среднего Предпринимательства: Построение Производственных Функций С Оценкой Эффективных Фондов [Analysis of small and medium business: The constructing production functions with est," MPRA Paper 109157, University Library of Munich, Germany, revised 14 Jul 2021.
    5. Vladimir Gorbunov & Alexander Lvov, 2018. "Effective Production Funds and Production Functions of Regional Small Business," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(2), pages 502-515.
    6. Jakub Boratyński & Jacek Osiewalski, 2021. "Bayesian Estimation of Capital Stock and Depreciation in the Production Function Framework," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(4), pages 455-486, December.
    7. 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.
    8. 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.
    9. 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.
    10. Gort, Michael & Wall, Richard A., 1998. "Obsolescence, input augmentation, and growth accounting," European Economic Review, Elsevier, vol. 42(9), pages 1653-1665, November.
    11. 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.
    12. Sang Nguyen & B.K. Atrostic, 2005. "Computer Investment, Computer Networks and Productivity," Working Papers 05-01, Center for Economic Studies, U.S. Census Bureau.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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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