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A Conditionally Parametric Probit Model of Micro-Data Land Use in Chicago Daniel McMillen Maria Soppelsa

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Overview Residential v. Commercial/Industrial Land Use in Chicago, 2010 A conditionally parametric (CPAR) approach produces smooth estimates over space Target points chosen using an adaptive decision tree approach (Loader, 1999) Interpolation from 182 target points to all 583,063 individual parcels in the data set

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Estimation Procedures Case (1992). Special From for W McMillen (1992). EM Algorithm Pinkse and Slade (1998). GMM for spatial error model. LeSage (2000). Bayesian approach Klier and McMillen (2007). Linearized version of GMM probit/logit for spatial AR model.

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GMM Probit

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Linearized GMM Probit

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CPAR Probit

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Spatial AR v. LWR

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Data Individual parcels in Chicago, 2010 Major Classes: 1.Vacant Land (33,139) 2.Residential, 6 units or fewer (728,541, 539,975 after geocoding) 3.Multi-Family Residential (11,529) 4.Non-Profit (316) 5.Commercial and Industrial (50,508, 43,088 after geocoding) 6.“Incentive Classes” (1,487)

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Explanatory Variables Distance from parcel centroid to: 1.CBD 2.Lake Michigan 3.EL line 4.EL stop 5.Rail line 6.Major street 7.Park 8.Highway

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Rogers Park

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Descriptive Statistics VariableMeanStd. Dev.MinMax Residential Lot0.9260.2620.0001.000 Distance from CBD7.5183.4330.02217.006 Distance from Lake Michigan4.1162.7160.00512.321 Distance from EL Line1.3581.2770.0016.265 Distance from EL Stop1.2141.0810.0016.265 Distance from Rail Line0.4280.2940.0011.997 Distance from Major Street0.0800.0570.0000.508 Distance from Park0.2330.1530.0002.999 Distance from Highway1.4761.0270.0114.809

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Probit Models, Probability Residential Standard ProbitCPAR Probit VariableCoef.Std. ErrorMeanStd. Dev. Intercept0.0610.0460.3511.008 Distance from CBD0.1320.0070.1010.266 Distance from Lake Michigan-0.0950.007-0.0860.308 Distance from EL Line0.0020.013-0.4231.168 Distance from EL Stop-0.0910.0130.5111.263 Distance from Rail Line0.6260.0140.6490.686 Distance from Major Street8.7480.07011.5706.427 Distance from Park-1.0990.020-0.8810.994 Distance from Highway0.2120.0070.0480.351 Log-likelihood-131518.9-120714.1 Pseudo-R 2 0.1440.215

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Probability of Residential Land Use: Standard Probit

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Probability of Residential Land Use: CPAR Probit, 10% Window Size

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Difference, CPAR Probability – Standard Probit Probability

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Kernel Density Estimates for CPAR Coefficients

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LWR Estimates of CPAR Coefficients

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Marginal Probabilities

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Rogers Park

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Rogers Park, n = 3,193 StandardGMMCPAR CoefStd. Err.CoefStd. Err.MeanStd. dev. Intercept49.97911.99942.97712.5920.0252.445 CBD-1.8040.462-1.5490.480 Lake Michigan-7.6211.672-6.5551.814-0.7265.314 EL Line-3.3240.651-2.9010.723-4.4499.934 EL Stop3.1270.6542.6980.7396.5939.706 Rail Line1.9060.3951.6590.4281.6754.059 Major Street7.1230.8375.9921.34615.9009.561 Park-1.7970.514-1.5940.525 Highway-7.2071.743-6.1971.809 Metra Stop0.0380.2160.0240.178 ρ0.1550.167 pseudo-R 2 0.084 0.343

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Correlations, Predicted Probabilities StandardGMMCPAR Standard10.570.99 GMM0.571 CPAR0.990.571

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Standard Probit Probabilities

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CPAR Probit Probabilities

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Standard Probit: Southwest

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CPAR – Standard: Southwest

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Standard Probit: Southeast

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CPAR – Standard: Southeast

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Standard Probit: Northwest

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CPAR – Standard: Northwest

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Standard Probit: Northeast

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CPAR – Standard: Southeast

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