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Theory and Application of Dynamic Spatial Time Series Models Andree, B.P.J.
2020
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Andree, B. P. J. (2020). Theory and Application of Dynamic Spatial Time Series Models.
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Download date: 11. Oct. 2021
Stochastic economic processes are often characterized by dynamic interactions between variables that are dependent in both space and time. Analyzing these processes raises a number of questions about the econometric methods used that are both practically and theoretically interesting. This work studies econometric approaches to analyze spatial data that evolves dynamically over time.
The book provides a background on least squares and maximum likelihood estimators, and discusses some of the limits of basic econometric theory.
It then discusses the importance of addressing spatial heterogeneity in policies.
The next chapters cover parametric modeling of linear and nonlinear spatial time series, non-parametric modeling of nonlinearities in panel data, modeling of multiple spatial time series variables that exhibit long and short memory, and probabilistic causality in spatial time series settings.
Bo P.J. Andrée holds a BSc in Geology and Economics and an MSc in Spatial, Transport and Environmental Economics from the Free University Amsterdam.
He performed studies for the World Bank, United Nations, OECD, European Commission, Asian Development Bank and the Dutch Government. His most recent project was on food crisis prediction with the Chief Economist of the World Bank. He currently lives in Amsterdam with his wife.
Vrije Universiteit Amsterdam
Theory and Application of Dynamic Spatial Time Series Models Bo Pieter Johannes Andrée
Bo Pieter Johannes Andrée
Theory and Application of Dynamic Spatial Time Series Models
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