Musolesi, Antonio, Prete, Giada Andrea and 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 Paper, n. 22-1335, Toulouse

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This paper provides a broad replication of Calderón et al. (2015). We address some complex and relevant issues, namely functional form, non-stationary variables and cross-sectional depen- dence. In particular, by adopting the CCE framework, we consider both parametric - static and dynamic - and non-parametric specifications, thus allowing for different degrees of flexibility. Contrary to Calderón et al. (2015), we find a lack of significance of the infrastructure index, with an estimated elasticity very close to zero for all estimates. Moreover, by employing the data-driven model selection procedure proposed by Gioldasis et al. (2021), it is found that non-parametric specifications provide the best predictive performance and that CCE models always overperform with respect to traditional panel data methods that employ cross-sectional demeaning to account for cross-sectional dependence.

Item Type: Monograph (Working Paper)
Language: English
Date: May 2022
Place of Publication: Toulouse
JEL Classification: C23 - Models with Panel Data
C5 - Econometric Modeling
O4 - Economic Growth and Aggregate Productivity
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 20 May 2022 07:36
Last Modified: 01 Jun 2022 09:57
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