The Research Roundup: A Review of Recently Published Real Estate Economics Papers
This is the first in a series of articles listing what, in the opinion of the Kukun Economics Team, are the most industry-relevant papers published in the last month. While the quality of the research is a major factor, it is not the only one we will be considering; we will also consider the usefulness of the paper in question to the real estate industry, modelers, investors, and businesses. There are many fine papers that can’t be translated into business success, and while many of these papers are interesting, professionals must prioritize those they can use.
Business Strategy
1) The Impact of Property Clustering on REIT Operational Efficiency and Firm Value | The Journal of Real Estate Finance and Economics)
from the Journal of Real Estate Finance and Economics.
This article provides REITs guidance regarding how best to balance the economies of scale that come from concentrating in particular markets and diversification across markets. Their results suggest that the 35th percentile of REITS measured from the least to the most diversification hit the sweet spot. A logical consequence of this is that most REITs are over-diversified and fail to take advantage of the efficiencies that come from concentrating in particular markets. That said, diversification should not be abandoned entirely.
2) Geographic Diversification and Real Estate Firm Value: Where Firms Diversify Matter: Journal of Real Estate Research: Vol 45, No 4
While the previous article suggests that the economies that come from specialization in local markets count for more than diversification, its findings still suggest that diversification is important.
This article provides valuable guidance on how to optimize one’s diversification strategy. While the study looks at the Chinese market, its lessons apply to the US market as well. Its primary finding is that the value of diversification goes down as the markets in question show higher levels of socioeconomic development and “momentum.” In short, the hot markets are not the ones that provide the greatest benefits in terms of risk diversification. Investors should consider investing in more moderate markets and looking at local industries whose profitability is not positively correlated.
Modeling and Analytics:
3) A flexible method of housing price index construction using repeat‐sales aggregates – Real Estate Economics
Given the low transaction volumes we have seen recently and the fact that high interest rates are pricing many out of the lower end of the market (just one form of what the study refers to as “non-random sampling”), more robust methods for building home price indices are needed. This paper offers a partial solution to the problems this, quite frankly weird, market presents us with and then actually uses the method described to publish a new index.
This paper compares two methods for estimating a city-level index: the conventional city-level pooled regression and an alternative approach called the “repeat-sales aggregation index” (RSAI). The RSAI involves treating a city as a collection of distinct submarkets, assigning each submarket’s change in price a weighted value, and summing these to create a city-level index. The weights assigned to submarkets play a crucial role in defining the index, allowing for various weighting schemes to generate alternative target indices.
The authors emphasize the need for different submarket weights and heterogeneous appreciation rates for the target indices to differ. The section concludes by detailing an estimation procedure, addressing challenges related to sparse transaction counts by developing an algorithm based on urban economic theory to create period-specific submarket aggregations, enabling appreciation rate estimation, and facilitating aggregation under less restrictive assumptions.
4) Assessing the Explanatory Power of Dwelling Condition in Automated Valuation Models
The title of this paper might make it sound like an exercise in obviousness; however, it does more than just explain the importance of property condition when building an AVM—it both quantifies it and decomposes it into particular features, i.e. it shows which aspects of a home provide the most lift to value. While it lacks the granularity and market-specific accuracy of Kukun’s cost estimator, its findings can be used by both economists and flippers to focus efforts on the parts of the home that matter most to consumers. We here at Kukun found it helpful as a confirmation of the research I did using permit data and price lift.
5) Changing the Location Game – Improving Location Analytics with the Help of Explainable AI: Journal of Real Estate Research: Vol 0, No 0
The phrase “location, location, location” has been repeated ad infinitum: And while the structure contributes more to home value than most people realize, it is much easier to value than location is. However, despite the crucial role location plays, there has been a notable absence of automated methods for evaluating the quality of real estate locations. This gap stems from the intricate nature, multitude of interactions, and non-linearities inherent in defining the quality of a particular location. Addressing this void, this blog post delves into a groundbreaking paper introducing the SHAP location score.
By leveraging an innovative machine learning algorithm and the Shapley Additive Explanations method, this innovative approach unravels the complexities associated with real estate location assessment. The SHAP location score stands out as an intuitive and adaptable methodology. Its results, even when derived from a machine learning model, can be transformed into location fixed effects which more traditional models can use.
There was a lot of interesting research published over the last quarter, but these seemed to offer the most value to actual real estate professionals. If you notice a piece of research that you think ought to be part of our roundup, do not hesitate to contact me at Franklin.Caroll@mykukun.com; while we can’t promise to agree with the reader’s assessment, we appreciate your help in surveying the literature.
Franklin Carroll
Franklin Carroll is Kukun's VP of Modelling and Analytics; After finishing his studies at the University of Chicago, he worked at Fannie Mae where he helped build Collateral Underwriter, roll out the Value Verify initiative, and specialized in collateral related and credit related policy.
Published February 7, 2024
