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Estimating regression coefficients by W-based and latent variables spatial autoregressive models in the presence of spillovers from hotspots: evidence from Monte Carlo simulations

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  • An Liu
  • Henk Folmer
  • Johan Oud

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  • An Liu & Henk Folmer & Johan Oud, 2011. "Estimating regression coefficients by W-based and latent variables spatial autoregressive models in the presence of spillovers from hotspots: evidence from Monte Carlo simulations," Letters in Spatial and Resource Sciences, Springer, vol. 4(1), pages 71-80, March.
    • Handle: RePEc:spr:lsprsc:v:4:y:2011:i:1:p:71-80
    DOI: 10.1007/s12076-010-0047-3
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    References listed on IDEAS

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    1. Henk Folmer & Johan Oud, 2008. "How to Get Rid of W: A Latent Variables Approach to Modelling Spatially Lagged Variables," Environment and Planning A, , vol. 40(10), pages 2526-2538, October.
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    Cited by:

    1. An Liu & Henk Folmer & Johan H L Oud, 2014. "Estimation of Autoregressive Models with Two Types of Weak Spatial Dependence by Means of the W-Based and the Latent Variables Approach: Evidence from Monte Carlo Simulations," Environment and Planning A, , vol. 46(1), pages 186-202, January.

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    More about this item

    Keywords

    Spatial autoregressive model; Monte Carlo simulation; Bias; RMSE; C01; C13; C51;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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