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Heterogeneous spatial models in R: spatial regimes models

Author

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  • Gianfranco Piras

    (The Catholic University of America
    University of Chieti – Pescara)

  • Mauricio Sarrias

    (Universidad de Talca)

Abstract

This paper presents the progress made so far in the development of the R package hspm. The package hspm aims at implementing a variety of models and methods to control for heterogeneity in spatial models. Spatial heterogeneity can be specified in different ways, ranging from exogenous (or endogenous) spatial regimes models, to models with coefficients that potentially vary for each observations (i.e., continuous heterogeneity). We focus on a few R functions that allow for the estimation of a general spatial regimes model, as well as all of the nested specifications deriving from it. The models are estimated by instrumental variables and generalized method of moments techniques.

Suggested Citation

  • Gianfranco Piras & Mauricio Sarrias, 2023. "Heterogeneous spatial models in R: spatial regimes models," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-32, December.
    • Handle: RePEc:spr:jospat:v:4:y:2023:i:1:d:10.1007_s43071-023-00034-1
    DOI: 10.1007/s43071-023-00034-1
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Spatial model; Heterogeneity; GMM; R;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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