Using MLS Data for Hedonic Price Modeling: An Experiential Learning Activity. Issue 1 (1st January 2016)

• Record Type: Journal Article
• Authors: Allen, Marcus T.; Swaleheen, Mushfiq
• Is Part Of: Journal of real estate practice and education. Volume 19:Issue 1(2016)
• Page Start: 1
• Page End: 14
• Publication Date: 2016-01-01
• Subjects: Real estate business -- Study and teaching -- Periodicals; Real estate business -- Research -- Periodicals; 333.33071
• DOI: 10.1080/10835547.2016.12091755
• Languages: English
• ISSNs: 1930-8914

Abstract

Abstract : Multiple Listing Service (MLS) data are notoriously cumbersome for empirical analysis due to inaccuracies and incompleteness. Applied real estate market analysis using MLS data requires a diligent effort to identify and address data limitations. This paper describes a learning activity that provides students with an opportunity to work with a large, real-world MLS dataset to answer research questions about house price determinants using hedonic price modeling with OLS regression. The activity is designed for use with Microsoft Excel due to its ready availability. Available instructor resources include a dataset with 20, 126 residential listings from a well-defined market covering a three-year time period with 85 data fields, directions for students, and a model answer. All instructor resources (password controlled) are available online at: http://tinyurl.com/mlscasestudy .