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A Hybrid Land Conversion Model Incorporating Multiple End Uses

Published online by Cambridge University Press:  15 September 2016

Nikhil Kaza ,
Charles Towe  and
Xin Ye
Nikhil Kaza
Affiliation:
Department of City and Regional Planning at the University of North Carolina, Chapel Hill, North Carolina
Charles Towe
Affiliation:
Department of Agricultural and Resource Economics at the University of Maryland, College Park, Maryland
Xin Ye
Affiliation:
Department of City and Regional Planning at the University of North Carolina, Chapel Hill, North Carolina National Center for Smart Growth Research and Education at the University of Maryland, College Park, Maryland
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Abstract

The need for models that forecast land use change spans many disciplines and encompasses many approaches. Pattern-based models were the first in which projections of change at specific locations in actual landscapes could be predicted. In contrast, recent economic models have modeled the underlying behavioral process that produces land use change. This paper combines attributes from each approach into a hybrid model using a multiple discrete continuous extreme value formulation that allows for multiple conversion types, while also estimating the intensity of each type of conversion, which is an important but often overlooked dimension. We demonstrate the simulation routine, which successfully predicts a majority of growth by type, time, and location at a disaggregated scale, for a three-county region in Maryland.

Keywords

MDCEVland conversionregional planningurban growth policy
Type
Contributed Papers
Information
Agricultural and Resource Economics Review , Volume 40 , Issue 3 , December 2011 , pp. 341 - 359
Copyright
Copyright © 2011 Northeastern Agricultural and Resource Economics Association 

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References

Bhat, C. 2005. “A Multiple Discrete-Continuous Extreme Value (MDCEV) Model: Formulation and Application to Discretionary Time-Use Decisions.” Transportation Research Part B 39(8): 679–707.Google Scholar
Bhat, C. 2008. “The Multiple Discrete-Continuous Extreme Value (MDCEV) Model: Role of Utility Function Parameters, Identification Considerations, and Model Extensions.” Transportation Research Part B 42(3): 274–303.Google Scholar
Bhat, C. and Sen, S. 2006. “Household Vehicle Type Holdings and Usage: An Application of the Multiple Discrete-Continuous Extreme Value (MDCEV) Model.” Transportation Research Part B 40(1): 35–53.Google Scholar
Bivand, R. (with contributions from Altman, M. Anselin, L. Assunção, R. Berke, O. Bernat, A. Blankmeyer, E. Carvalho, M. Chun, Y. Christensen, B. Dormann, C. Dray, S. Halbersma, R. Krainski, E. Lewin-Koh, N. Li, H. Ma, J. Millo, G. Mueller, W. Ono, H. Peres-Neto, P. Piras, G. Reder, M. Tiefelsdorf, M. and Yu), D. 2010. “spdep: Spatial dependence: weighting schemes, statistics and models. R package version 0.5-11.” Available at http://CRAN.R-project.org/package=spdep (accessed August 15, 2010).Google Scholar
Brownstone, D. and De Vany, A. 1991. “Zoning, Returns to Scale, and the Value of Undeveloped Land.” The Review of Economics and Statistics 73(4): 699–704.Google Scholar
Byrd, R.H. Lu, P. Nocedal, J. and Zhu, C. 1995. “A Limited Memory Algorithm for Bound Constrained Optimization.” SIAM Journal on Scientific Computing 16(5): 1190–1208.Google Scholar
Capozza, D.R. and Helsley, R. 1990. “The Stochastic City.” Journal of Urban Economics 28(2): 187–203.Google Scholar
Capozza, D. and Li, Y. 1994. “The Intensity and Timing of Investment: The Case of Land.” The American Economic Review 84(4): 889–904.Google Scholar
Carrion-Flores, C. and Irwin, E. 2004. “Determinants of Residential Land Use Conversion and Sprawl at the Rural-Urban Fringe.” American Journal of Agricultural Economics 86(4): 889–904.Google Scholar
Cunningham, C.R. 2007. “Growth Controls, Real Options and Land Development.” Review of Economics and Statistics 89(2): 343–358.Google Scholar
Fujita, M. and Ogawa, H. 1982. “Multiple Equilibria and Structural Transition of Non-Monocentric Urban Configurations.” Regional Science and Urban Economics 12(2): 161–196.Google Scholar
Furrer, R. 2010. “spam: SPArse Matrix. R package version 0.22-0.” Available at http://CRAN.R-project.org/package=spam (accessed August 15, 2010).Google Scholar
Irwin, E.G. 2010. “New Directions for Urban Economic Models of Land Use Change: Incorporating Spatial Dynamics and Heterogeneity.” Journal of Regional Science 50(1): 65–91.Google Scholar
Irwin, E. and Bockstael, N. 2002. “Interacting Agents, Spatial Externalities and the Evolution of Land Use Change.” Journal of Economic Geography 2(1): 31–54.Google Scholar
Kaza, N. Knaap, G. and Meade, D. 2008. “Exploring Alternative Futures Using a Spatially Explicit Econometric Model.” Paper presented at the 55th annual North American meetings of the Regional Science Association, New York (November).Google Scholar
Kim, J. Allenby, G.M. and Rossi, P.E. 2002. “Modeling Consumer Demand for Variety.” Marketing Science 229–250.Google Scholar
Kline, J.D. 2003. “Characterizing Land Use Change in Multidisciplinary Landscape-Level Analyses.” Agricultural and Resource Economics Review 32(1): 103–115.Google Scholar
Krugman, P. 1991. “Increasing Returns and Economic Geography.” Journal of Political Economy 99(3): 438–499.Google Scholar
Lynch, L. and Musser, W.N. 2001. “A Relative Efficiency Analysis of Farmland Preservation Programs.” Land Economics 77(4): 577–594.Google Scholar
Mills, E.S. 1967. “An Aggregative Model of Resource Allocation in a Metropolitan Area.” The American Economic Review 57(2): 197–210.Google Scholar
Muth, R.F. 1969. Cities and Housing: The Spatial Pattern of Urban Residential Land Use. Chicago: University of Chicago Press.Google Scholar
Parks, P. 1995. “Explaining ‘Irrational’ Land Use: Risk Aversion and Marginal Agricultural Land.” Journal of Environmental Economics and Management 28(1): 34–47.Google Scholar
Phaneuf, D.J. Kling, C.L. and Herriges, J.A. 2000. “Estimation and Welfare Calculations in a Generalized Corner Solution Model with an Application to Recreation Demand.” Review of Economics and Statistics 82(1): 83–92.Google Scholar
Phaneuf, D.J. and Smith, V.K. 2005. “Recreation Demand Models.” In Maler, K.-G. and Vincent, J.R. eds., Handbook of Environmental Economics (Vol. 2). Amsterdam: Elsevier.Google Scholar
R Development Core Team. 2010. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing (ISBN No. 3-900051-07-0). Available at http://www.R-project.org (accessed August 15, 2010).Google Scholar
Robinson, D. Brown, D. Parker, D. Schreinemachers, P. Janssen, M. Huigen, M. Wittmer, H. Gotts, N. Promburom, P. Irwin, E. Berger, T. Gatzweiler, F. and Barnaud, C. 2007. “Comparison of Empirical Methods for Building Agent-Based Models in Land Use Science.” Journal of Land Use Science 2(1): 31–55.Google Scholar
Schelling, T.C. 1969. “Models of Segregation.” American Economic Review 59(2): 448–493.Google Scholar
Schelling, T.C. 1971. “Dynamic Models of Segregation.” Journal of Mathematical Sociology 1(2): 143–186.Google Scholar
Stavins, R. and Jaffe, A. 1990. “Unintended Impacts of Public Investments on Private Decisions: The Depletion of Forested Wetlands.” The American Economic Review 80(3): 337–352.Google Scholar
Steen, R.C. 1986. “Nonubiquitous Transportation and Urban Population Density Gradients.” Journal of Urban Economics 20(1): 97–106.Google Scholar
Titman, S. 1985. “Urban Land Prices under Uncertainty.” The American Economic Review 75(3): 505–514.Google Scholar
Towe, C. 2008. “Testing the Effect of Neighboring Open Space on Development Using Propensity Score Matching.” Paper presented at the annual meetings of the Southern Economics Association, Washington, D.C. (November).Google Scholar
Towe, C. Nickerson, C. and Bockstael, N. 2008. “An Empirical Examination of the Timing of Land Conversions in the Presence of Farmland Preservation Programs.” American Journal of Agricultural Economics 90(3): 613–626.Google Scholar
von Haefen, R.H. and Phaneuf, D.J. 2005. “Kuhn-Tucker De-and System Approaches to Nonmarket Valuation.” In Scarpa, R. and Alberini, A.A. eds., Applications of Simulation Methods in Environmental and Resource Economics. Dorrecht: Kluwer Academic Publishers.Google Scholar
von Haefen, R.H. Phaneuf, D.J. and Parsons, G.R. 2004. “Estimation and Welfare Analysis with Large Demand Sysems.” Journal of Business and Economic Statistics 22(2): 194–205.Google Scholar
Yee, T.W. 2010. “The VGAM Package for Categorical Data Analysis.” Journal of Statistical Software 32(10): 1–34.Google Scholar