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Functional-coefficient spatial Durbin models with nonparametric spatial weights: An application to economic growth

This paper considers a functional-coefficient spatial Durbin model with nonparametric spatial weights. Applying the series approximation method, we estimate the unknown functional coefficients and spatial weighting functions via a nonparametric two-stage least squares (or 2SLS) estimation method. To further improve estimation accuracy, we also construct a second-step estimator of the unknown functional coefficients by a local linear regression approach. Some Monte Carlo simulation results are reported to assess the finite sample performance of our proposed estimators. We then apply the proposed model to re-examine national economic growth by augmenting the conventional Solow economic growth convergence model with unknown spatial interactive structures of the national economy, as well as country-specific Solow parameters, where the spatial weighting functions and Solow parameters are allowed to be a function of geographical distance and the countries' openness to trade, respectively.
Year of publication:
2016
Authors: Koroglu, Mustafa ; Sun, Yiguo
Published in:
Econometrics. - Basel : MDPI, ISSN 2225-1146. - Vol. 4.2016, 1, p. 1-16
Publisher: Basel : MDPI
Subject: functional coefficients | local linear regression | nonparametric 2SLS estimator | series estimator | Solow economic growth convergence model | spatial Durbin model
Type of publication: Article
Type of publication (narrower categories): Article
Language: English
Other identifiers:
10.3390/econometrics4010006 [DOI]
863304478 [GVK]
hdl:10419/171860 [Handle]
Classification: C14 - Semiparametric and Nonparametric Methods ; C21 - Cross-Sectional Models; Spatial Models ; O47 - Measurement of Economic Growth; Aggregate Productivity
Source:
Persistent link: https://ebvufind01.dmz1.zbw.eu/10011755314
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