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Comparing estimation methods for spatial econometrics techniques using R

Author

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  • Bivand, Roger

    (Dept. of Economics, Norwegian School of Economics and Business Administration)

Abstract

Recent advances in spatial econometrics model fitting techniques have made it more desirable to be able to compare results and timings. Results should correspond between implementations using different applications, while timings are more readily compared within a single application. A broad range of model fitting techniques are provided by the contributed R packages for spatial econometrics. These model fitting techniques are associated with methods for estimating impacts and some tests, which will also be presented and compared. This review constitutes an up-to-date demonstration of techniques now available in R, and mentions some that will shortly become more generally available.

Suggested Citation

  • Bivand, Roger, 2010. "Comparing estimation methods for spatial econometrics techniques using R," Discussion Paper Series in Economics 26/2010, Norwegian School of Economics, Department of Economics.
    • Handle: RePEc:hhs:nhheco:2010_026
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    Citations

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    Cited by:

    1. Basile, Roberto & Durbán, María & Mínguez, Román & María Montero, Jose & Mur, Jesús, 2014. "Modeling regional economic dynamics: Spatial dependence, spatial heterogeneity and nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 229-245.
    2. Marco Helbich & Wolfgang Brunauer & Eric Vaz & Peter Nijkamp, 2014. "Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria," Urban Studies, Urban Studies Journal Limited, vol. 51(2), pages 390-411, February.
    3. Suesse, Thomas, 2018. "Marginal maximum likelihood estimation of SAR models with missing data," Computational Statistics & Data Analysis, Elsevier, vol. 120(C), pages 98-110.
    4. Thomas Suesse, 2018. "Estimation of spatial autoregressive models with measurement error for large data sets," Computational Statistics, Springer, vol. 33(4), pages 1627-1648, December.

    More about this item

    Keywords

    Spatial autoregression; Econometric software.;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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

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