Analyzing Real Estate Data Problems Using the Gibbs Sampler

John Ross Knight, C.F. Sirmans, Alan E. Gelfand and Sujit K. Ghosh

Real Estate Economics, 1998, vol. 26, issue 3, pages 469-492

Abstract: Real estate data are often characterized by data irregularities: missing data, censoring or truncation, measurement error, etc. Practitioners often discard missing- or censored-data cases and ignore measurement error. We argue here that an attractive remedy for these irregularity problems is simulation-based model fitting using the Gibbs sampler. The style of the paper is primarily pedagogic, employing a simple illustration to convey the essential ideas, unobscured by implementation complications. Focusing on the missing-data problem, we show dramatic improvement in inference by retaining rather than deleting cases of partially observed data. We also detail Gibbs-sampler usage for other data problems. Copyright American Real Estate and Urban Economics Association.

Date: 1998

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