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Nonlinear impact estimation in spatial autoregressive models

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  • Ay, Jean-Sauveur
  • Ayouba, Kassoum
  • Le Gallo, Julie

Abstract

This paper extends the literature on the calculation and interpretation of impacts for spatial autoregressive models. Using a Bayesian framework, we show how the individual direct and indirect impacts associated with an exogenous variable introduced in a nonlinear way in such models can be computed, theoretically and empirically. Rather than averaging the individual impacts, we suggest to graphically analyze them along with their confidence intervals calculated from Markov chain Monte Carlo (MCMC). We also explicitly derive the form of the gap between individual impacts in the spatial autoregressive model and the corresponding model without a spatial lag and show, in our application on the Boston dataset, that it is higher for spatially highly connected observations.

Suggested Citation

  • Ay, Jean-Sauveur & Ayouba, Kassoum & Le Gallo, Julie, 2018. "Nonlinear impact estimation in spatial autoregressive models," Economics Letters, Elsevier, vol. 163(C), pages 59-64.
  • Handle: RePEc:eee:ecolet:v:163:y:2018:i:c:p:59-64
    DOI: 10.1016/j.econlet.2017.11.031
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    References listed on IDEAS

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    1. Luc Anselin & Nancy Lozano-Gracia, 2009. "Errors in variables and spatial effects in hedonic house price models of ambient air quality," Studies in Empirical Economics, in: Giuseppe Arbia & Badi H. Baltagi (ed.), Spatial Econometrics, pages 5-34, Springer.
    2. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    3. Luc Anselin & Julie Le Gallo, 2006. "Interpolation of air quality measures in hedonic house price models : spatial aspects," Post-Print hal-00485017, HAL.
    4. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "The relative efficiencies of various predictors in spatial econometric models containing spatial lags," Regional Science and Urban Economics, Elsevier, vol. 37(3), pages 363-374, May.
    5. Harry Kelejian & George Tavlas & George Hondroyiannis, 2006. "A Spatial Modelling Approach to Contagion Among Emerging Economies," Open Economies Review, Springer, vol. 17(4), pages 423-441, December.
    6. Won Kim, Chong & Phipps, Tim T. & Anselin, Luc, 2003. "Measuring the benefits of air quality improvement: a spatial hedonic approach," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 24-39, January.
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    Cited by:

    1. Yuxue Sheng & James Paul LeSage, 2021. "Interpreting spatial regression models with multiplicative interaction explanatory variables," Journal of Geographical Systems, Springer, vol. 23(3), pages 333-360, July.

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    More about this item

    Keywords

    Spatial econometrics; Marginal impacts; Spline; Markov chain Monte Carlo;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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