Assessing Property Value Assessments
Assessing Property Value Assessments
Gabriel Wimmer
Thomas Jefferson High School for Science and Technology
This article was originally included in the 2019 print publication of Teknos Science Journal.
For many families, the purchase of a home will be the largest investment of their lives. Regardless of whether someone is renting an apartment or purchasing a house, they are paying a price that is proportional to that property’s value. Despite the magnitude of these purchases and the possible long-term mortgage commitment, almost no analytic rigor is applied to them. For most residential real estate transactions, the only analysis performed is done by the lending company providing the mortgage. This analysis is in the form of a home appraisal, the estimation of a house’s value by an analysis of the sale prices of two to four nearby homes.
This process works because at the time of the appraisal, all variables are held constant. Any variables that can change over time are held in place and effectively ignored. Yet, as the nation learned in 2008, these ignored variables can be of great importance. The 2008 financial crisis proved two important things. The first is that more analytical rigor is needed to understand the housing market, and the second is that the impact of the crisis varied greatly from area to area. During the crisis, property values dropped at different rates in different areas, and following the crisis, they began to rise at varying rates. Even across the same city, the rate at which the housing market recovered varied drastically [4]. Because the same strategy for determining property value was being used across the country, the many minute differences in each location were never even considered.
The issue is not that data pertaining to the variables that impact real estate does not exist, but that it is not being collected and presented in an understandable manner. The goal for my Computer Systems research lab is to create a tool that will analyze these external variables for any given house. These variables include population density, Gross Domestic Product (GDP), access to amenities, and interest rates. Research done by Luca D’Acci in Turin, Italy, shows that, along with location relative to the center of a city, factors such as pollution, view, and accessibility all play a role in the evaluation of housing prices [2]. By recording the zip code or address to ensure that the data I collect is location-specific, I can account for changes in property value that would result from differences in location.
In order to determine which variables have had the largest impact on property value, regressions must be conducted. Researchers have studied the efficacy of such regressions as indicators of real estate value. Costa and Cazassa have conducted research in the Brazilian real estate market on the use of historical information and regressions to create models of the market. While their study was solely on the housing market in a city in Brazil, my tool will enable any house for which I have data to be analyzed using similar regressions that consider historical data points and prices. Another variable that Costa and Cazassa considered in their study were traditional stock indices [1]. Seeing as many cities have economies that are directly tied to certain industries, it may be wise to incorporate similar indices into my tool.
It is prudent to ensure that the proper statistical procedures are being followed when analyzing the data. Mariusz Kubus, who has conducted multi-linear regressions on the real estate market in Kraków, Poland, has documented several precautions that must be taken to ensure your model is as accurate as possible. He explains that great effort must be put into the removal of redundant variables. If, for example, you include two variables that are closely tied to each other, such as 15-year and 30-year interest rates, and included them in the same multi-linear regression, you would greatly decrease the stability of the model and get a result worse than if you had just chosen to use one of the variables. Kubus verifies that this method of using multi-linear regressions to model real estate markets can be very effective, and is even more effective if these redundant variables are removed.
When analyzing this data, it is important to understand what the listed value of a house really means. Newspaper articles, such as the one written by Lisa Gordon for Realtor, have aimed to educate home buyers on the many things to consider before purchasing a house. Gordon elaborates on the difference between market value and assessed value and the confusion they can bring. Market value is the value a purchaser will pay, and assessed value is the value that the government determines for tax purposes [3]. Seeing as I am using the assessed value for my tool (as it is calculated every year as opposed to every time the property is purchased), I must consider the risks that come with it. Assessed value is calculated by the government, and as such, is subject to restrictions and jurisdiction. Some counties have limits on the rate at which assessed values can increase or decrease and I must consider these specific limitations. Qi Shi states in his analysis of a new real estate model, “No model is perfect and capable of explaining all patterns of portfolios” [7]. He ensures that these anomalies are put to the test and that obscure use cases, such as the one described with the limitations on assessment value increase, are understood and considered [6]. Similarly, I will need to have contextual information for houses that are analyzed by my tool so that these differences can be explained and better understood.
To better understand the differences between assessed and market value, I contacted the Fairfax County Department of Tax Administration to learn how they created property tax assessments. Laura Mills, an analyst in their Real Estate Division, explained that assessments are created automatically using a combination of house characteristics and comparable sales [6]. I learned that tax assessors face problems that are similar to mine. Due to an inability to break down the components that make up a property’s value, they must use the sale prices of comparable houses to make an estimate. Therefore, I must be careful when using assessed value, as it often varies greatly from market value. However, by using several comparables to determine the value of a single house, that single house price is more representative of the local real estate market as a whole.
As of now, there is very little statistical rigor being put into the real estate market that can be used by a common home buyer. While there is research being done that sheds light on the effect of external variables on real estate value, it is, at most, being used by large firms with large real estate portfolios and not the common home buyer. My goal is to make this statistical information both accessible and understandable to the home buyer. By empowering buyers with the possible variables that can impact their property’s value, they can hopefully make more informed decisions and understand what risks they are undertaking when making a real estate purchase.
References
[1] Costa, O., & Cazassa, E. (2018). How relevant are generalist real estate indices in emerging markets? RAUSP Management Journal, 53(2). https://doi.org/10.1016/j.rauspm.2017.06.006
[2] D’Acci, L. (2018). Quality of urban area, distance from city centre, and housing value. Case study on real estate values in Turin. Cities The International Journal of Urban Policy and Planning, 81. https://doi.org/10.1016/j.cities.2018.11.008
[3] Gordon, L. (2017, April 4). Assessed Value vs. Market Value: What’s the Difference? Realtor. Retrieved from https://www.realtor.com/advice/sell/assessed-value-vs-market-value-difference/
[4] Housing Price Index. (2019, January). Retrieved January 17, 2019, from Proximity One website: http://proximityone.com/hpi.htm
[5] Kubus, M. (2016). Assessment of Predictor Importance with the Example of the Real Estate Market. Folia Oeconomica Stetinensia, 16(2). http://dx.doi.org/10.1515/foli-2016-0023
[6] Mills, Laura. Interview. By Gabriel Wimmer. 6 Dec. 2018.
[7] Shi, Q. (2018). A much robust and updated evidences of the alternative real-estate based asset pricing. The North American Journal of Economics and Finance, 46. https://doi.org/10.1016/j.najef.2018.10.013
