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Using MLS Data for Hedonic Price Modeling: An Experiential Learning Activity.

Title: Using MLS Data for Hedonic Price Modeling: An Experiential Learning Activity.
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Name(s): Allen, Marcus T., author
Swaleheen, Mushfiq, author
Type of Resource: text
Genre: Article
Issuance: monographic
Date Issued: 2016-01-01
Extent: 1 online resource
Language(s): English
eng
Summary: 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.
Identifier: fgcu_ir_000628 (IID)
Links: http://ezproxy.fgcu.edu/login?url=https://search.proquest.com/docview/1807686578?accountid=10919
Persistent Link to This Record: http://purl.flvc.org/fgcu/fd/fgcu_ir_000628
Use and Reproduction: Copyright held by publisher.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FGCU
Is Part Of: Journal of Real Estate Practice and Education.