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The Journal of Real Estate Finance and Economics

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03.02.2018

The Impact of TOM on Prices in the US Housing Market

verfasst von: Darren K. Hayunga, R. Kelley Pace

Erschienen in: The Journal of Real Estate Finance and Economics | Ausgabe 3/2019

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Abstract

Search theory shows that real property prices and marketing durations are simultaneously determined and positively related. Yet, empirical studies find positive, negative, and insignificant parameter estimates on the time-on-the-market (TOM) variable in price models. Using a dataset well suited to the research question, this article investigates reasons for the divergence between the theoretical and empirical results. Our test equations examine the quality of instrumental variables, severe overpricing, atypicality, structure quality, loss aversion, market tightness as well as measures unique to our data such as sellers’ income levels, reasons for sale, and urgency. We find that weak instrumental variables account for the varied empirical relations between transaction prices and TOM.

Nächster Artikel Sample Selection Approaches to Estimating and Allocating House Transaction Funding Price Differentials

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Appendix 1 provides a brief summary of search models.

Some house price studies examine research topics that fit data aggregated at the census tract, county, or larger spatial area. Similar to the NAR dataset, these data usually offer more information about the social, economic, and demographic characteristics of market participants summarized at the geographic area of interest. However, these data are not individual transactions. The American Housing Survey is a source of buyers’ and sellers’ demographic information along with property-level information but does not record marketing durations.

We also do not observe sales when the buyer does not purchase another home. By the nature of the survey, this is another necessary trade-off in order to use the rich information provided by the survey responses.

Since the surveys are sent to individual sellers, there are no transactions for REO or foreclosed properties.

See Angrist and Pischke (2008, pp. 189–192) for a more recent discussion of this.

Appendix 3 provides a brief explanation of the econometric issues with simultaneity and omitted variable bias in housing studies as well as IV test statistics.

Similar to market tightness, considering an additional market characteristic in the form of varying arrival rates of buyers is consistent with search theory. For instance, the static model of Wheaton (1990) allows for changes in the rate of matching, which is shown to impact TOM. In the quasi-steady state model of Williams (1995), the pricing function is derived in continuous time, which allows changes in local employment or income. Comparative statics of the Williams (1995) model also show that an increase in buyers’ arrival rate increases liquidity. Additionally, Krainer and LeRoy (2002) use standard search theory to motivate two states of nature, hot and cold markets.

Parente and Santos Silva (2012) caution that an insignificant statistic on the overidentifying-restrictions test does not preclude a lack of power of the test due to invalid instruments. Kiviet (2017) highlights the importance of an unambiguous hypothesis to mitigate model misspecification as a reason for the insignificant test statistic. Accordingly, the test hypothesis of our paper is solely focused on the relation of TOM in price equations.

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Titel: The Impact of TOM on Prices in the US Housing Market
verfasst von: Darren K. Hayunga
R. Kelley Pace
Publikationsdatum: 03.02.2018
Verlag: Springer US
Erschienen in: The Journal of Real Estate Finance and Economics / Ausgabe 3/2019
Print ISSN: 0895-5638
Elektronische ISSN: 1573-045X
DOI: https://doi.org/10.1007/s11146-018-9657-0

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