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Land Use Change: A Spatial Multinomial Choice Analysis

Author

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  • Carrion-Flores, Carmen E.
  • Flores-Lagunes, Alfonso
  • Guci, Ledia

Abstract

Urban decentralization and dispersion trends have led to increased conversion of rural lands in many urban peripheries and exurban regions of the U.S. The growth of the exurban areas has outpaced growth in urban and suburban areas, resulting in growth pressures at the urban-rural fringe. A thorough analysis of land use change patterns and the ability to predict these changes are necessary for the effective design of regional environmental, growth, and development policies. We estimate a multinomial discrete choice model with spatial dependence using parcel-level data from Medina County, Ohio. Accounting for spatial dependence should result in improved statistical inference about land use changes. Our spatial model extends the binary choice “linearized logit” model of Klier and McMillen (2008) to a multinomial setting. A small Monte Carlo simulation indicates that this estimator performs reasonably well. Preliminary results suggest that the location of new urban development is guided by a preference over lower density areas, yet in proximity to current urban development. In addition, we find significant evidence of spatial dependence in land use decisions.

Suggested Citation

  • Carrion-Flores, Carmen E. & Flores-Lagunes, Alfonso & Guci, Ledia, 2009. "Land Use Change: A Spatial Multinomial Choice Analysis," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49403, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea09:49403
    DOI: 10.22004/ag.econ.49403
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    Cited by:

    1. Cho, Seong-Hoon & Lee, Juhee & Roberts, Roland & Yu, Edward T. & Armsworth, Paul R., 2018. "Impact of market conditions on the effectiveness of payments for forest-based carbon sequestration," Forest Policy and Economics, Elsevier, vol. 92(C), pages 33-42.
    2. Levente Tímár, 2011. "Rural Land Use and Land Tenure in New Zealand," Working Papers 11_13, Motu Economic and Public Policy Research.
    3. Brasington, David & Flores-Lagunes, Alfonso & Guci, Ledia, 2016. "A spatial model of school district open enrollment choice," Regional Science and Urban Economics, Elsevier, vol. 56(C), pages 1-18.
    4. Lee, Juhee & Cho, Seong-Hoon & Kim, Taeyoung & Yu, Tun-Hsiang & Armsworth, Paul Robert, 2015. "Exploring tax-based payment approach for forest carbon sequestration," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196873, Southern Agricultural Economics Association.
    5. Cho, Seong-Hoon & Soh, Moonwon & English, Burton C. & Yu, T. Edward & Boyer, Christopher N., 2019. "Targeting payments for forest carbon sequestration given ecological and economic objectives," Forest Policy and Economics, Elsevier, vol. 100(C), pages 214-226.
    6. Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2022. "Bayesian estimation of multivariate panel probits with higher‐order network interdependence and an application to firms' global market participation in Guangdong," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1356-1378, November.

    More about this item

    Keywords

    Community/Rural/Urban Development; Land Economics/Use; Research Methods/ Statistical Methods;
    All these keywords.

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