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How to Measure Spillover Effects of Public Capital Stock: A Spatial Autoregressive Stochastic Frontier Model

In: Spatial Econometrics: Qualitative and Limited Dependent Variables

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  • Jaepil Han
  • Deockhyun Ryu
  • Robin Sickles

Abstract

This paper aims to investigate spillover effects of public capital stock in a production function model that accounts for spatial dependencies. In many settings, ignoring spatial dependency yields inefficient, biased and inconsistent estimates in cross country panels. Although there are a number of studies aiming to estimate the output elasticity of public capital stock, many of those fail to reach a consensus on refining the elasticity estimates. We argue that accounting for spillover effects of the public capital stock on the production efficiency and incorporating spatial dependences are crucial. For this purpose, we employ a spatial autoregressive stochastic frontier model based on a number of specifications of the spatial dependency structure. Using the data of 21 OECD countries from 1960 to 2001, we estimate a spatial autoregressive stochastic frontier model and derive the mean indirect marginal effects of public capital stock, which are interpreted as spillover effects. We found that spillover effects can be an important factor explaining variations in technical inefficiency across countries as well as in explaining the discrepancies among various levels of output elasticity of public capital stock in traditional production function approaches.

Suggested Citation

  • Jaepil Han & Deockhyun Ryu & Robin Sickles, 2016. "How to Measure Spillover Effects of Public Capital Stock: A Spatial Autoregressive Stochastic Frontier Model," Advances in Econometrics, in: Spatial Econometrics: Qualitative and Limited Dependent Variables, volume 37, pages 259-294, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-905320160000037017
    DOI: 10.1108/S0731-905320160000037017
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    1. 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.
    2. Alfredo M. Pereira & Jorge M. Andraz, 2013. "On The Economic Effects Of Public Infrastructure Investment: A Survey Of The International Evidence," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 38(4), pages 1-37, December.
    3. J. Paul Elhorst & Sandy Fréret, 2009. "Evidence Of Political Yardstick Competition In France Using A Two‐Regime Spatial Durbin Model With Fixed Effects," Journal of Regional Science, Wiley Blackwell, vol. 49(5), pages 931-951, December.
    4. Douglas Holtz-Eakin & Amy Schwartz, 1995. "Spatial productivity spillovers from public infrastructure: Evidence from state highways," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 2(3), pages 459-468, October.
    5. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    6. Delorme, Charles Jr. & Thompson, Herbert Jr. & Warren, Ronald Jr., 1999. "Public Infrastructure and Private Productivity: A Stochastic-Frontier Approach," Journal of Macroeconomics, Elsevier, vol. 21(3), pages 563-576, July.
    7. Aschauer, David Alan, 1989. "Is public expenditure productive?," Journal of Monetary Economics, Elsevier, vol. 23(2), pages 177-200, March.
    8. Patrick Sevestre & Laszlo Matyas, 2008. "The Econometrics of Panel Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00279977, HAL.
    9. John A. Tatom, 1991. "Public capital and private sector performance," Review, Federal Reserve Bank of St. Louis, issue May, pages 3-15.
    10. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    11. Pereira, Alfredo Marvao & Roca-Sagales, Oriol, 2003. "Spillover effects of public capital formation: evidence from the Spanish regions," Journal of Urban Economics, Elsevier, vol. 53(2), pages 238-256, March.
    12. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, January.
    13. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    14. Lung-fei Lee & Jihai Yu, 2012. "QML Estimation of Spatial Dynamic Panel Data Models with Time Varying Spatial Weights Matrices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 31-74, March.
    15. Pavlyuk, Dmitry, 2012. "Maximum Likelihood Estimator for Spatial Stochastic Frontier Models," MPRA Paper 43390, University Library of Munich, Germany.
    16. Lee, Lung-fei & Yu, Jihai, 2010. "A Spatial Dynamic Panel Data Model With Both Time And Individual Fixed Effects," Econometric Theory, Cambridge University Press, vol. 26(2), pages 564-597, April.
    17. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, July-Dece.
    18. Wang, Yi-Chia, 2014. "Evidence of public capital spillovers and endogenous growth in Taiwan," Economic Modelling, Elsevier, vol. 39(C), pages 314-321.
    19. Morakinyo Adetutu & Anthony Glass & Karligash Kenjegalieva & Robin Sickles, 2015. "The effects of efficiency and TFP growth on pollution in Europe: a multistage spatial analysis," Journal of Productivity Analysis, Springer, vol. 43(3), pages 307-326, June.
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    Cited by:

    1. Orea, Luis & Álvarez, Inmaculada C., 2019. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Journal of Econometrics, Elsevier, vol. 213(2), pages 556-577.
    2. Han, Jaepil & Sickles, Robin C., 2019. "Estimation of Industry-level Productivity with Cross-sectional Dependence by Using Spatial Analysis," Working Papers 19-002, Rice University, Department of Economics.
    3. Gong, Binlei, 2018. "Interstate competition in agriculture: Cheer or fear? Evidence from the United States and China," Food Policy, Elsevier, vol. 81(C), pages 37-47.
    4. Sung, Bongsuk & Soh, Jin Young & Park, Chun Gun, 2022. "Comparing government support, firm heterogeneity, and inter-firm spillovers for productivity enhancement: Evidence from the Korean solar energy technology industry," Energy, Elsevier, vol. 246(C).
    5. Yuan, Lingran & Zhang, Qizheng & Wang, Shuo & Hu, Weibin & Gong, Binlei, 2022. "Effects of international trade on world agricultural production and productivity: evidence from a panel of 126 countries 1962-2014," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 25(2), March.
    6. Adjin, K. Christophe & Henning, Christian H. C. A., 2020. "Climate variability and farm inefficiency: A spatial stochastic frontier analysis of Senegalese agriculture," Working Papers of Agricultural Policy WP2020-09, University of Kiel, Department of Agricultural Economics, Chair of Agricultural Policy.
    7. Gong, Binlei, 2020. "Multi-dimensional interactions in the oilfield market: A jackknife model averaging approach of spatial productivity analysis," Energy Economics, Elsevier, vol. 86(C).

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    More about this item

    Keywords

    Public capital; spillover effect; stochastic frontier model; spatial panel model; time-varying spatial weights; C23; D24; O47;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • 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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