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Spatial dynamic models with intertemporal optimization: Specification and estimation
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DOI：10.1016/j.jeconom.2019.10.012.png)
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In this paper, we introduce a dynamic spatial interaction econometric model. There are n forward-looking agents of whom each has a parametric linear-quadratic payoff, and they interact with their neighbors through a spatial network. Considering a Markov perfect equilibrium (MPE), we derive a unique Nash equilibrium equation and construct a new spatial dynamic panel data (SDPD) model. For estimation, we suggest mainly the quasi-maximum likelihood (QML) method. Asymptotic properties of the QML estimator are investigated. In a Monte Carlo study, we estimate the model's parameters and compare the results with those from traditional SDPD models. The model is applied to an empirical study on counties' public safety spending in North Carolina. (C) 2020 Elsevier B.V. All rights reserved.
Keyword:
Dynamic interaction
Intertemporal optimization
Markov perfect equilibrium
SDPD models
QML estimation
County's public safety spending
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