Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/171860 
Year of Publication: 
2016
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 4 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2016 [Pages:] 1-16
Publisher: 
MDPI, Basel
Abstract: 
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.
Subjects: 
functional coefficients
local linear regression
nonparametric 2SLS estimator
series estimator
Solow economic growth convergence model
spatial Durbin model
JEL: 
C14
C21
O47
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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