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Paradoxes of the public sector productivity measurement

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  • Timo Kuosmanen
  • Xun Zhou

Abstract

This paper critically investigates standard total factor productivity (TFP) measurement in the public sector, where output information is often incomplete or distorted. The analysis reveals fundamental paradoxes under three common output measurement conventions. When cost-based value added is used as the aggregate output, measured TFP may paradoxically decline as a result of genuine productivity-enhancing changes such as technical progress and improved allocative and scale efficiencies, as well as reductions in real input prices. We show that the same problems carry over to the situation where the aggregate output is constructed as the cost-share weighted index of outputs. In the case of distorted output prices, measured TFP may move independently of any productivity changes and instead reflect shifts in pricing mechanisms. Using empirical illustrations from the United Kingdom and Finland, we demonstrate that such distortions are not merely theoretical but are embedded in widely used public productivity statistics. We argue that public sector TFP measurement requires a shift away from cost-based aggregation of outputs and toward non-market valuation methods grounded in economic theory.

Suggested Citation

  • Timo Kuosmanen & Xun Zhou, 2025. "Paradoxes of the public sector productivity measurement," Papers 2509.14795, arXiv.org, revised Oct 2025.
  • Handle: RePEc:arx:papers:2509.14795
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    References listed on IDEAS

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    1. Amit Gandhi & Salvador Navarro & David A. Rivers, 2020. "On the Identification of Gross Output Production Functions," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 2973-3016.
    2. Sheng Dai & Timo Kuosmanen & Xun Zhou, 2025. "Can Omitted Carbon Abatement Explain Productivity Stagnation?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 71(2), May.
    3. Kenneth Y. Chay & Michael Greenstone, 2005. "Does Air Quality Matter? Evidence from the Housing Market," Journal of Political Economy, University of Chicago Press, vol. 113(2), pages 376-424, April.
    4. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    5. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    6. Chambers, Robert G. & Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity Growth in APEC Countries," Working Papers 197843, University of Maryland, Department of Agricultural and Resource Economics.
    7. Kuosmanen, Timo & Zhou, Xun, 2021. "Shadow prices and marginal abatement costs: Convex quantile regression approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 666-675.
    8. Jens Hainmueller & Michael J. Hiscox & Sandra Sequeira, 2015. "Consumer Demand for Fair Trade: Evidence from a Multistore Field Experiment," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 242-256, May.
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