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Spillover Effects of Public Capital Stock Using Spatial Frontier Analyses: A First Look at the Data

In: Productivity and Efficiency Analysis

Author

Listed:
  • Jaepil Han

    (Rice University)

  • Deockhyun Ryu

    (Chung-Ang University)

  • Robin C. Sickles

    (Rice University)

Abstract

This paper aims to investigate spillover effects of public capital stock in a production function model that accounts for spatial dependencies. Although there are a number of studies that estimate the output elasticity of public capital stock, they suffer from a failure to refine the output elasticity of public capital stock as well as to account for spillover effects of the public capital stock on the production efficiency when such spatial dependencies exist. For this purpose we employ a spatial autoregressive stochastic frontier model and analyze estimates with a time-varying spatial weights matrix. Using data for 21 OECD countries from 1960 to 2001, we found that spillover effects can be an important factor explaining variations in technical inefficiency across countries as well as discrepancies among various levels of output elasticity of public capital stock in traditional production function approaches.

Suggested Citation

  • Jaepil Han & Deockhyun Ryu & Robin C. Sickles, 2016. "Spillover Effects of Public Capital Stock Using Spatial Frontier Analyses: A First Look at the Data," Springer Proceedings in Business and Economics, in: William H. Greene & Lynda Khalaf & Robin Sickles & Michael Veall & Marcel-Cristian Voia (ed.), Productivity and Efficiency Analysis, edition 1, chapter 0, pages 83-97, Springer.
    • Handle: RePEc:spr:prbchp:978-3-319-23228-7_5
    DOI: 10.1007/978-3-319-23228-7_5
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    Cited by:

    1. Fusco, Elisa & Allegrini, Veronica, 2020. "The role of spatial interdependence in local government cost efficiency: An application to waste Italian sector," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    2. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2020. "A spatial stochastic frontier model with endogenous frontier and environmental variables," European Journal of Operational Research, Elsevier, vol. 286(1), pages 389-399.

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