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Capital Use Intensity and Productivity Biases

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  • Andersen, Matthew A.
  • Alston, Julian M.
  • Pardey, Philip G.

Abstract

Measures of productivity growth are often pro-cyclical. This paper focuses on measurement errors in capital inputs, associated with unobserved variations in capital utilization rates, as an explanation for the existence of pro-cyclical patterns in measures of productivity. Recently constructed national and state-specific indexes of inputs, outputs, and productivity in U.S. agriculture for 1949–2002 are used to estimate production functions that include proxy variables for changes in the utilization of durable inputs. The proxy variables include an index of farmers’ terms of trade and an index of local seasonal growing conditions. We find that utilization responses by farmers are significant and bias measures of productivity growth in a pro-cyclical pattern. We quantify the bias, adjust the measures of productivity for the estimated utilization responses, and compare the adjusted and conventional measures.

Suggested Citation

  • Andersen, Matthew A. & Alston, Julian M. & Pardey, Philip G., 2010. "Capital Use Intensity and Productivity Biases," Staff Papers 93143, University of Minnesota, Department of Applied Economics.
    • Handle: RePEc:ags:umaesp:93143
    DOI: 10.22004/ag.econ.93143
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    Cited by:

    1. Zheng, Yu & Alexandre, Gohin, 2018. "Agricultural productivity and price volatility in France: a dynamic stochastic partial equilibrium approach," 2018 Annual Meeting, August 5-7, Washington, D.C. 274354, Agricultural and Applied Economics Association.
    2. Youngjune Kim & Ji Yong Lee, 2020. "Effects of Government Payments on Agricultural Productivity: The Case of South Korea," Sustainability, MDPI, vol. 12(9), pages 1-11, April.
    3. Alejandro Plastina & Lilyan Fulginiti, 2012. "Rates of return to public agricultural research in 48 US states," Journal of Productivity Analysis, Springer, vol. 37(2), pages 95-113, April.
    4. Yu Sheng & Tom Jackson & Shiji Zhao & Dandan Zhang, 2017. "Measuring Output, Input and Total Factor Productivity in Australian Agriculture: An Industry-Level Analysis," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63, pages 169-193, February.
    5. Lin, Boqiang & Xie, Yongjing, 2023. "Does digital transformation improve the operational efficiency of Chinese power enterprises?," Utilities Policy, Elsevier, vol. 82(C).
    6. Andersen, Matthew A. & Alston, Julian M. & Pardey, Philip G., 2009. "Capital Service Flows: Concepts and Comparisons of Alternative Measures in U.S. Agriculture," Staff Papers 50098, University of Minnesota, Department of Applied Economics.
    7. Lence, Sergio H. & Plastina, Alejandro, 2020. "An Empirical Investigation of Productivity Spillovers along the Agricultural Supply Chain," ISU General Staff Papers 202001010800001066, Iowa State University, Department of Economics.
    8. Alston, Julian M. & Pardey, Philip G. & Ruttan, Vernon W., 2008. "Research Lags Revisited: Concepts and Evidence from U.S. Agriculture," Staff Papers 50091, University of Minnesota, Department of Applied Economics.

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    More about this item

    Keywords

    Productivity Analysis;

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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