A Conditionally Parametric Probit Model of Microdata Land Use in Chicago

25 Pages Posted: 10 Jun 2015

See all articles by Daniel McMillen

Daniel McMillen

University of Illinois at Urbana-Champaign - Department of Economics

Maria Edisa Soppelsa

University of Illinois at Urbana-Champaign - Department of Economics

Date Written: June 2015

Abstract

Spatial data sets pose challenges for discrete choice models because the data are unlikely to be independently and identically distributed. A conditionally parametric spatial probit model is amenable to very large data sets while imposing far less structure on the data than conventional parametric models. We illustrate the approach using data on 474,170 individual lots in the City of Chicago. The results suggest that simple functional forms are not appropriate for explaining the spatial variation in residential land use across the entire city.

Suggested Citation

McMillen, Daniel and Soppelsa, Maria Edisa, A Conditionally Parametric Probit Model of Microdata Land Use in Chicago (June 2015). Journal of Regional Science, Vol. 55, Issue 3, pp. 391-415, 2015, Available at SSRN: https://ssrn.com/abstract=2616546 or http://dx.doi.org/10.1111/jors.12174

Daniel McMillen (Contact Author)

University of Illinois at Urbana-Champaign - Department of Economics ( email )

410 David Kinley Hall
1407 W. Gregory
Urbana, IL 61801
United States

Maria Edisa Soppelsa

University of Illinois at Urbana-Champaign - Department of Economics ( email )

410 David Kinley Hall
1407 W. Gregory
Urbana, IL 61801
United States

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