IV Estimation of Heterogeneous Spatial Dynamic Panel Models with Interactive Effects

Jia Chen, Guowei Cui, Vasilis Sarafidis and Takashi Yamagata

Papers from arXiv.org

Abstract: This paper develops a Mean Group Instrumental Variables (MGIV) approach for spatial dynamic panel data models with interactive effects, under large N and T asymptotics. Unlike existing approaches that typically impose slope-parameter homogeneity, MGIV accommodates cross-sectional heterogeneity in slope coefficients. The proposed estimator is linear, making it computationally efficient and robust. Furthermore, it enables asymptotically valid inferences without requiring bias correction. The Monte Carlo experiments indicate strong finite-sample performance of the MGIV approach across various sample sizes and parameter configurations. The practical utility of the methodology is illustrated through an application to regional economic growth in Europe. Our results provide evidence of conditional convergence in regional growth dynamics. Spillovers are shown to play a dominant role, particularly for investment rates where nearly four-fifths of the total effect on GDP per capita growth originates from neighboring regions.

Date: 2025-01, Revised 2026-09
New Economics Papers: this item is included in nep-ecm, nep-geo and nep-ure
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Citations: View citations in EconPapers (2)

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Working Paper: IV Estimation of Heterogeneous Spatial Dynamic Panel Models with Interactive Effects (2025)
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