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Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a cross-sectionally dependent panel framework

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  • Musolesi, Antonio
  • Prete, Giada Andrea
  • Simioni, Michel

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  • 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).
    • Handle: RePEc:tse:wpaper:126928
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    References listed on IDEAS

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    1. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2016. "Exponent of Cross‐Sectional Dependence: Estimation and Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 929-960, September.
    2. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    3. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    4. 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.
    5. 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.
    6. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    7. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    8. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521828284.
    9. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    10. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    11. 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.
    12. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
    13. Frees, Edward W., 1995. "Assessing cross-sectional correlation in panel data," Journal of Econometrics, Elsevier, vol. 69(2), pages 393-414, October.
    14. 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.
    15. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521535380.
    16. Simon N. Wood, 2013. "On p-values for smooth components of an extended generalized additive model," Biometrika, Biometrika Trust, vol. 100(1), pages 221-228.
    17. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2021. "Interactive R&D Spillovers: An estimation strategy based on forecasting-driven model selection," SEEDS Working Papers 0621, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jun 2021.
    18. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2023. "Interactive R&D spillovers: an estimation strategy based on forecasting-driven model selection," Post-Print hal-03476599, HAL.
    19. Bai, Jushan & Ng, Serena, 2010. "Panel Unit Root Tests With Cross-Section Dependence: A Further Investigation," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1088-1114, August.
    20. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2021. "Interactive R&D Spillovers: an estimation strategy based on forecasting-driven model selection," Working Papers hal-03224910, HAL.
    21. 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.
    22. Giovanni Millo, 2019. "Private returns to R&D in the presence of spillovers, revisited," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(1), pages 155-159, January.
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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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