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On the Relation between Innovation and Housing Prices – A Metro Level Analysis of the US Market

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Abstract

We examine the extent to which the quality of innovation created in different locations is related to subsequent changes in house prices in these metropolitan areas. Cities that foster a healthy quality of innovation are likely the home of many successful entrepreneurs and firms that provide high paying jobs. We hypothesize that the relation between innovation and changes in house prices is positive because, all else equal, locations with higher quality of innovation should not only be more desirable places to live, but also support higher rate of wealth and income growth, which allow for higher house price appreciation. We find results consistent with our hypothesis: there is a statistically and economically significant positive relation between innovation quality and subsequent house price appreciation. We find that this association runs from innovation quality to house price appreciation but not the reverse, and that the effect is stronger in areas with inelastic land supply.

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Notes

  1. According to the United States Patent and Trademark Office (USPTO) the number of patents issued in the U.S. surpassed 10 million in 2018.

  2. We use “local innovation quality” and “local innovativeness” interchangeably throughout our paper.

  3. As robustness checks, we also performed our analysis using alternative definitions of MSA innovativeness based on number of citations per inventor and number of citations per capita (we report these results in Table 10).

  4. In subsequent robustness tests (reported in Table 6), we present results in which the dependent variable are changes in house prices over one or two years. The results are quantitatively and qualitatively similar to using house price changes over three years.

  5. (ln(1 + 1)*0.016/0.0047) – 1 = 92%.

  6. The results are qualitatively and quantitatively similar when MSA fixed effects are removed.

  7. Saiz (2010) provides land supply elasticity values on 95 cities with population greater than 500,000. In our analysis we use an expanded dataset provided by Albert Saiz that includes land supply elasticity values for 267 U.S. cities.

  8. The results are qualitatively and quantitatively similar when using MSA Innovativeness measured through one to five years as in Tables 4 and 5.

  9. The adjusted rent-to-price ratio is calculated using the inverse of price-to-rent ratio for each MSA from Zillow and assuming 35% expenses relative to rent. For example, an area with a price-to-rent ratio of 12.5 will have an adjusted rent-to-price ratio of 5.2% ((100%/12.5)*(1–0.35)). This yield similar net rent income to values calculated using Himmelberg et al. (2005), suggesting that an individual annually faces property taxes of 1.5% of the property value and maintenance and insurance expenses of an additional 2% during the holding period. Moreover, our results are invariant to using a different expense ratio, given that different expense ratio assumptions simply result in a scalar shift to the total return variable.

  10. Note that we used only one observation from each year, instead of the quarter-level observations. The main reason for this choice is the inclusion of the lagged measures. Because both the innovativeness and the return measures are constructed using quarter-level data in a rolling-window fashion, using quarter-level observations for this purpose would lead to material overlap in the measures.

  11. We also performed tests while removing the top 20 MSAs by population, and find similar results.

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Acknowledgements

We would like to thank an anonymous referee whose insightful comments contributed to a much improved paper. All errors remain those of the authors.

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Authors and Affiliations

  1. Florida International University, Miami, FL, USA

    Eli Beracha

  2. University of New Hampshire, Durham, NH, USA

    ZhaoZhao He

  3. School of Business, University of Kansas, Lawrence, KS, USA

    M. Babajide Wintoki

  4. San Diego State University, San Diego, CA, USA

    Yaoyi Xi

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  1. Eli Beracha
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  2. ZhaoZhao He
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  4. Yaoyi Xi
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Correspondence to Eli Beracha.

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Appendices

Appendix 1

Table 11 Local Innovativeness and Housing Returns – Removing Large MSAs
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Appendix 2

Table 12 Local Innovativeness and Housing Returns – Removing Most Innovative MSAs
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Beracha, E., He, Z., Wintoki, M.B. et al. On the Relation between Innovation and Housing Prices – A Metro Level Analysis of the US Market. J Real Estate Finan Econ 65, 622–648 (2022). https://doi.org/10.1007/s11146-021-09852-2

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