IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v68y2025i3d10.1007_s00181-024-02670-4.html
   My bibliography  Save this article

Revisiting the Productivity Effects of Public Capital

Author

Listed:
  • Zhezhi Hou

    (Southwestern University of Finance and Economics)

  • Shunan Zhao

    (Oakland University)

  • Subal C. Kumbhakar

    (State University of New York
    Czech University of Life Sciences Prague)

Abstract

We explore various production functions and estimators to examine the productivity effects of public capital using US state-level data from 1986 to 2005. We show how the estimated effects vary with several factors, including the use of flexible nonparametric and semiparametric production functions, the decomposition of the total effect into Hicks-neutral and non-neutral effects, the control of cross-sectional dependence using factor models, and the disaggregation of public capital into its components. In general, we find a positive overall average effect of public capital. However, considerable heterogeneity exists, and incorporating factor models into the production function leads to insignificant public capital effects. We complement our investigation by conducting additional robustness checks on the results.

Suggested Citation

  • Zhezhi Hou & Shunan Zhao & Subal C. Kumbhakar, 2025. "Revisiting the Productivity Effects of Public Capital," Empirical Economics, Springer, vol. 68(3), pages 1233-1264, March.
    • Handle: RePEc:spr:empeco:v:68:y:2025:i:3:d:10.1007_s00181-024-02670-4
    DOI: 10.1007/s00181-024-02670-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-024-02670-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00181-024-02670-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Simon Reese & Joakim Westerlund, 2016. "Panicca: Panic on Cross‐Section Averages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 961-981, September.
    2. Ulrich Doraszelski & Jordi Jaumandreu, 2018. "Measuring the Bias of Technological Change," Journal of Political Economy, University of Chicago Press, vol. 126(3), pages 1027-1084.
    3. Feng, Qu & Wu, Guiying Laura, 2018. "On the reverse causality between output and infrastructure: The case of China," Economic Modelling, Elsevier, vol. 74(C), pages 97-104.
    4. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    5. Mika Kortelainen & Simo Leppänen, 2013. "Public and private capital productivity in Russia: a non-parametric investigation," Empirical Economics, Springer, vol. 45(1), pages 193-216, August.
    6. Kapetanios, G. & Pesaran, M. Hashem & Yamagata, T., 2011. "Panels with non-stationary multifactor error structures," Journal of Econometrics, Elsevier, vol. 160(2), pages 326-348, February.
    7. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    8. Fanti, Luciano & Gori, Luca, 2011. "Public health spending, old-age productivity and economic growth: Chaotic cycles under perfect foresight," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1), pages 137-151.
    9. Nikos Benos & Nikolaos Mylonidis & Stefania Zotou, 2017. "Estimating production functions for the US states: the role of public and human capital," Empirical Economics, Springer, vol. 52(2), pages 691-721, March.
    10. Alicia H. Munnell, 1990. "How does public infrastructure affect regional economic performance?," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, vol. 34, pages 69-112.
    11. César Calderón & Enrique Moral‐Benito & Luis Servén, 2015. "Is infrastructure capital productive? A dynamic heterogeneous approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 177-198, March.
    12. Pesaran, M. Hashem & Vanessa Smith, L. & Yamagata, Takashi, 2013. "Panel unit root tests in the presence of a multifactor error structure," Journal of Econometrics, Elsevier, vol. 175(2), pages 94-115.
    13. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    14. Holtz-Eakin, Douglas, 1994. "Public-Sector Capital and the Productivity Puzzle," The Review of Economics and Statistics, MIT Press, vol. 76(1), pages 12-21, February.
    15. Andersson, Roland & Quigley, John M. & Wilhelmsson, Mats, 2009. "Urbanization, productivity, and innovation: Evidence from investment in higher education," Journal of Urban Economics, Elsevier, vol. 66(1), pages 2-15, July.
    16. Wu, Guiying Laura & Feng, Qu & Wang, Zhifeng, 2021. "A structural estimation of the return to infrastructure investment in China," Journal of Development Economics, Elsevier, vol. 152(C).
    17. Daniel J. Henderson & Subal C. Kumbhakar, 2006. "Public and Private Capital Productivity Puzzle: A Nonparametric Approach," Southern Economic Journal, John Wiley & Sons, vol. 73(1), pages 219-232, July.
    18. Garcia-Mila, Teresa & McGuire, Therese J & Porter, Robert H, 1996. "The Effect of Public Capital in State-Level Production Functions Reconsidered," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 177-180, February.
    19. Chen, Been-Lon, 2006. "Public capital, endogenous growth, and endogenous fluctuations," Journal of Macroeconomics, Elsevier, vol. 28(4), pages 768-774, December.
    20. Antonio Musolesi & Giada Andrea Prete & Michel Simioni, 2022. "Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a crosssectionally dependent panel framework," Working Papers hal-03685558, HAL.
    21. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    22. Baltagi, Badi H & Pinnoi, Nat, 1995. "Public Capital Stock and State Productivity Growth: Further Evidence from an Error Components Model," Empirical Economics, Springer, vol. 20(2), pages 351-359.
    23. Artūras Juodis & Simon Reese, 2022. "The Incidental Parameters Problem in Testing for Remaining Cross-Section Correlation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1191-1203, June.
    24. Barro, Robert J, 1990. "Government Spending in a Simple Model of Endogenous Growth," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 103-126, October.
    25. Musolesi, Antonio & Prete, Giada Andrea & Simioni, Michel, 2022. "Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," TSE Working Papers 22-1335, Toulouse School of Economics (TSE).
    26. Antonio Musolesi & Giada Andrea Prete & Michel Simioni, 2022. "Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," SEEDS Working Papers 0522, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2022.
    27. John G. Fernald, 1999. "Roads to Prosperity? Assessing the Link between Public Capital and Productivity," American Economic Review, American Economic Association, vol. 89(3), pages 619-638, June.
    28. Li, Mingyang & Jin, Man & Kumbhakar, Subal C., 2022. "Do subsidies increase firm productivity? Evidence from Chinese manufacturing enterprises," European Journal of Operational Research, Elsevier, vol. 303(1), pages 388-400.
    29. Burton A. Weisbrod, 1962. "Education and Investment in Human Capital," NBER Chapters, in: Investment in Human Beings, pages 106-123, National Bureau of Economic Research, Inc.
    30. Su, Liangjun & Jin, Sainan, 2012. "Sieve estimation of panel data models with cross section dependence," Journal of Econometrics, Elsevier, vol. 169(1), pages 34-47.
    31. Burton A. Weisbrod, 1962. "Education and Investment in Human Capital," Journal of Political Economy, University of Chicago Press, vol. 70(5), pages 106-106.
    32. Yin‐fang Zhang & Kai Sun, 2019. "How Does Infrastructure Affect Economic Growth? Insights From A Semiparametric Smooth Coefficient Approach And The Case Of Telecommunications In China," Economic Inquiry, Western Economic Association International, vol. 57(3), pages 1239-1255, July.
    33. Holl, Adelheid, 2016. "Highways and productivity in manufacturing firms," Journal of Urban Economics, Elsevier, vol. 93(C), pages 131-151.
    34. Man Jin & Huiting Tian & Subal C. Kumbhakar, 2020. "How to survive and compete: the impact of information asymmetry on productivity," Journal of Productivity Analysis, Springer, vol. 53(1), pages 107-123, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nikos Benos & Nikolaos Mylonidis & Stefania Zotou, 2017. "Estimating production functions for the US states: the role of public and human capital," Empirical Economics, Springer, vol. 52(2), pages 691-721, March.
    2. Josep Lluís Carrion-i-Silvestre & Laura Surdeanu, 2016. "Productivity, Infrastructure and Human Capital in the Spanish Regions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 11(4), pages 365-391, October.
    3. Musolesi, Antonio & Prete, Giada Andrea & Simioni, Michel, 2022. "Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," TSE Working Papers 22-1335, Toulouse School of Economics (TSE).
    4. Soberon, Alexandra & Mazzanti, Massimiliano & Musolesi, Antonio & Rodriguez-Poo, Juan M., 2025. "Efficient estimation of a partially linear panel data model with cross-sectional dependence," Journal of Multivariate Analysis, Elsevier, vol. 206(C).
    5. Antonio Musolesi & Giada Andrea Prete & Michel Simioni, 2022. "Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," SEEDS Working Papers 0522, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2022.
    6. Luca Margaritella & Joakim Westerlund, 2023. "Using information criteria to select averages in CCE," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 405-421.
    7. Quynh Chau Pham Holland & Benjamin Liu & Eduardo Roca, 2019. "International funding cost and heterogeneous mortgage interest-rate pass-through: a bank-level analysis," Empirical Economics, Springer, vol. 57(4), pages 1255-1289, October.
    8. Angel De la Fuente, 2010. "Infrastructures and productivity: an updated survey," Working Papers 1018, BBVA Bank, Economic Research Department.
    9. Khanna, Rupika & Sharma, Chandan, 2021. "Does infrastructure stimulate total factor productivity? A dynamic heterogeneous panel analysis for Indian manufacturing industries," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 59-73.
    10. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    11. Juodis, Artūras & Karabiyik, Hande & Westerlund, Joakim, 2021. "On the robustness of the pooled CCE estimator," Journal of Econometrics, Elsevier, vol. 220(2), pages 325-348.
    12. Markus Eberhardt & Francis Teal, 2008. "Modeling Technology and Technological Change in Manufacturing: How do Countries Differ?," CSAE Working Paper Series 2008-12, Centre for the Study of African Economies, University of Oxford.
    13. Fedderke, J.W. & Bogetic, Z., 2009. "Infrastructure and Growth in South Africa: Direct and Indirect Productivity Impacts of 19 Infrastructure Measures," World Development, Elsevier, vol. 37(9), pages 1522-1539, September.
    14. Wei Zou & Fen Zhang & Ziyin Zhuang & Hairong Song, 2008. "Transport Infrastructure, Growth, and Poverty Alleviation: Empirical Analysis of China," Annals of Economics and Finance, Society for AEF, vol. 9(2), pages 345-371, November.
    15. Markus Eberhardt & Christian Helmers & Hubert Strauss, 2013. "Do Spillovers Matter When Estimating Private Returns to R&D?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 436-448, May.
    16. Andreas Stephan, 2003. "Assessing the contribution of public capital to private production: Evidence from the German manufacturing sector," International Review of Applied Economics, Taylor & Francis Journals, vol. 17(4), pages 399-417.
    17. Anna Bottaso & Carolina Castagnetti & Maurizio Conti, 2011. "And Yet they Co-Move! Public Capital and Productivity in OECD: A Panel Cointegration Analysis with Cross-Section Dependence," Quaderni di Dipartimento 154, University of Pavia, Department of Economics and Quantitative Methods.
    18. Markus Eberhardt & Francis Teal, 2010. "Aggregation versus Heterogeneity in Cross-Country Growth Empirics," CSAE Working Paper Series 2010-32, Centre for the Study of African Economies, University of Oxford.
    19. Constantinescu, Mihnea & Lastauskas, Povilas, 2018. "The knotty interplay between credit and housing," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 241-266.

    More about this item

    Keywords

    Public capital; Productivity; Semiparametric and nonparametric estimation; Cross-sectional dependence; Decomposition;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:empeco:v:68:y:2025:i:3:d:10.1007_s00181-024-02670-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.