A Monte Carlo Exploration of the Vertical Property Tax Inequity Models: Searching for a 'Best' Model

33 Pages Posted: 19 Nov 2012

See all articles by Joshua Fairbanks

Joshua Fairbanks

Texas Tech University - Rawls College of Business

Paul R. Goebel

Texas Tech University - Area of Finance

Michael Morris

Oklahoma State University - Tulsa - Business & Economics

William H. Dare

Oklahoma State University - Tulsa

Date Written: November 13, 2012

Abstract

This paper examines the empirical complexities of using linear, log-linear, and nonlinear models to test for vertical property tax inequity in residential real estate data. We apply the existing vertical inequity models to real estate data from Lubbock, Texas. Subsequently, we use Monte Carlo simulations to explore the performance of each inequity model on a variety of different predetermined inequity patterns. Using the Lubbock data as a starting point, we generate eight different contrived inequity patterns from three different data generating processes, which create 24 stylized data sets. The first data generating process treats assessed values as a noisy function of sale prices, which reflect home values. The second process considers the sale price as a noisy function of assessed values. The final process considers both sale prices and assessed values to be a noisy measure of home values. Although our findings do not yield a “best” model, the results do allow us to draw some conclusions and provide practitioners and academics with a road map to test for vertical tax inequity in future real estate data.

Keywords: Monte Carlo Simulation, Vertical Tax Inequity, Real Estate

JEL Classification: H20, C15, P43

Suggested Citation

Fairbanks, Joshua and Goebel, Paul and Morris, Michael and Dare, William H., A Monte Carlo Exploration of the Vertical Property Tax Inequity Models: Searching for a 'Best' Model (November 13, 2012). Journal of Real Estate Literature, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2178205

Joshua Fairbanks (Contact Author)

Texas Tech University - Rawls College of Business ( email )

Lubbock, TX 79409
United States
806.834.7687 (Phone)

Paul Goebel

Texas Tech University - Area of Finance ( email )

Area of Finance
Lubbock, TX 79409
United States
806-742-3339 (Phone)
806-742-2099 (Fax)

Michael Morris

Oklahoma State University - Tulsa - Business & Economics ( email )

United States

William H. Dare

Oklahoma State University - Tulsa ( email )

700 North Greenwood
Tulsa, OK 74106
United States

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