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Valuating Residential Real Estate Using Parametric Programming

S. C. Narula, J. F. Wellington, S. A. Lewis

Published in the European Journal of Operational Research, 2012

How To Use This Information
Data and results addressed in the paper titled "Valuating Residential Real Estate Using Parametric Programming" by S. C. Narula, J. F. Wellington, and S. A. Lewis are available by selecting the files below.
File Name
 Contents

Format
Data
 The real estate data for the n=54 observations (residential properties) on k=10 hedonic features of each property and its' current valuation.
Excel (.xlsx)
Betas

b1, …, b10 parameter estimates for the single equation linear regression model under the criteria of:
1. quantile regression (QR).
2. least squares (LS).
3. minimum sum of absolute errors (MSAE).
4. multiple estimation criteria (MC).
Excel (.xlsx)
Figures
 Data displayed in Figures 1-4.
Excel (.xlsx)
Table 1
 Data displayed in Table 1.
PDF (.pdf)
Table 2
 Data displayed in Table 2.
PDF (.pdf)
Table A.1
 Data displayed in Table A.1.
PDF (.pdf)
Manuscript
 The manuscript as of July 31, 2011.
PDF (.pdf)

The data is presented in formats that lend it to analysis by popular statistical packages such as SPSS.
The Excel file named "Betas.xlsx" contains a calculator that allows the user to copy the values of b1, …, b10 under any estimation criterion to a cell range that produces the performance measures of the model. These include the following:
  1. net gain in valuations,
  2. maximum change in property valuation,
  3. minimum change in property valuation,
  4. maximum percent change in property valuation,
  5. minimum percent change in property valuation,
  6. number of valuations increased 10% or more, and
  7. number of valuations increased 20% or more.


Updated: August 18, 2013.
Contact: wellingj@ipfw.edu