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Estimation of industry-level productivity with cross-sectional dependence by using spatial analysis

Author

Listed:
  • Jaepil Han

    (Chungnam National University)

  • Robin C. Sickles

    (Rice University)

Abstract

In this paper, we incorporate spatial analysis to estimate industry-level productivity in the presence of inter-sectoral linkages. Since each industry plays a role in providing intermediate goods to other sectors, the interdependence of economic activities across industries is inevitable. We exploit the linkage patterns from the input-output relationship to define cross-industry dependencies in economic space. We propose a spatial stochastic frontier model, which extends the stochastic frontier model to a spatially dependent specification. The models are estimated using quasi-maximum likelihood methods. Applying the approach to U.S. industry-level data from 1947 to 2010, we find that sectoral dependencies are the consequences of indirect effects via the supply chain network of industries resulting in larger output elasticities as well as scale effects for the networked production processes. However, productivity growth is estimated comparably across different spatial and non-spatial model specifications.

Suggested Citation

  • Jaepil Han & Robin C. Sickles, 2024. "Estimation of industry-level productivity with cross-sectional dependence by using spatial analysis," Journal of Productivity Analysis, Springer, vol. 62(1), pages 29-52, August.
    • Handle: RePEc:kap:jproda:v:62:y:2024:i:1:d:10.1007_s11123-023-00718-8
    DOI: 10.1007/s11123-023-00718-8
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    More about this item

    Keywords

    Cross-sectional dependence; Spatial panel model; Spatial weights matrix; Stochastic frontier analysis; Industry-level productivity;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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