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Accounting for Spatial Heterogeneity and Autocorrelation in Spatial Discrete Choice Models: Implications for Behavioral Predictions

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  • Kurt E. Schnier
  • Ronald G. Felthoven

Abstract

The random utility model (RUM) is commonly used in the land-use and fishery economics literature. This research investigates the affect that spatial heterogeneity and spatial autocorrelation have within the RUM framework using alternative specifications of the multinomial logit, multinomial probit, and spatial multinomial probit models. Using data on the spatial decisions of fishermen, the results illustrate that ignoring spatial heterogeneity in the unobservable portion of the RUM dramatically affects model performance and welfare estimates. Furthermore, accounting for spatial autocorrelation in addition to spatial heterogeneity increases the performance of the RUM.

Suggested Citation

  • Kurt E. Schnier & Ronald G. Felthoven, 2011. "Accounting for Spatial Heterogeneity and Autocorrelation in Spatial Discrete Choice Models: Implications for Behavioral Predictions," Land Economics, University of Wisconsin Press, vol. 87(3), pages 382-402.
    • Handle: RePEc:uwp:landec:v:87:y:2011:iii:1:p:382-402
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    1. Timmins, Christopher & Murdock, Jennifer, 2007. "A revealed preference approach to the measurement of congestion in travel cost models," Journal of Environmental Economics and Management, Elsevier, vol. 53(2), pages 230-249, March.
    2. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    3. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
    4. Elena G. Irwin, 2002. "Interacting agents, spatial externalities and the evolution of residential land use patterns," Journal of Economic Geography, Oxford University Press, vol. 2(1), pages 31-54, January.
    5. Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
    6. Hicks, Robert L. & Horrace, William C. & Schnier, Kurt E., 2012. "Strategic substitutes or complements? The game of where to fish," Journal of Econometrics, Elsevier, vol. 168(1), pages 70-80.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, November.
    8. Nancy E. Bockstael, 1996. "Modeling Economics and Ecology: The Importance of a Spatial Perspective," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(5), pages 1168-1180.
    9. Bolduc, Denis, 1999. "A practical technique to estimate multinomial probit models in transportation," Transportation Research Part B: Methodological, Elsevier, vol. 33(1), pages 63-79, February.
    10. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    11. Hicks, Robert L. & Schnier, Kurt E., 2010. "Spatial regulations and endogenous consideration sets in fisheries," Resource and Energy Economics, Elsevier, vol. 32(2), pages 117-134, April.
    12. Heng Z. Chen & Stephen R. Cosslett, 1998. "Environmental Quality Preference and Benefit Estimation in Multinomial Probit Models: A Simulation Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(3), pages 512-520.
    13. Bell, Kathleen P. & Irwin, Elena G., 2002. "Spatially explicit micro-level modelling of land use change at the rural-urban interface," Agricultural Economics, Blackwell, vol. 27(3), pages 217-232, November.
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    Cited by:

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    2. Meyerhoff, Jürgen, 2013. "Do turbines in the vicinity of respondents' residences influence choices among programmes for future wind power generation?," Journal of choice modelling, Elsevier, vol. 7(C), pages 58-71.
    3. Hutniczak, Barbara & Münch, Angela, 2018. "Fishermen's location choice under spatio-temporal update of expectations," Journal of choice modelling, Elsevier, vol. 28(C), pages 124-136.

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    More about this item

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • Q22 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Fishery

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