というNBER論文が上がっている(H/T タイラー・コーエン)。原題は「Housing Demand and Remote Work」で、著者はJohn A. Mondragon(SF連銀)、Johannes Wieland(UCサンディエゴ)。

In this paper we show that the shift to remote work caused a large increase in housing demand. In turn, this increase in housing demand caused house prices and rents to increase sharply. Based on our cross-sectional estimates controlling for migration spillovers, we argue that remote work accounts for at least one half of the 24% increase in house prices from December 2019 to November 2021. While remote work also facilitated migration across cities and this migration was correlated with house price growth, the majority of the effect of remote work on house prices across CBSAs is due to the direct effects of the shift in demand. Our results suggest that the increase in house prices over this period largely reflect fundamentals rather than a speculative bubble, and that lower interest rates and fiscal stimulus were of lesser importance.
Our results also imply that the future path of housing costs may depend critically on the path of remote work. If remote work reverses, then there may be a general reversal in housing demand and potentially house prices. If remote work persists, we may expect important repercussions as increased housing costs feed into inflation and so affect the response of monetary policy. Given the macroeconomic importance of either outcome, policy makers need to pay close attention to the future evolution of remote work.


ちなみに少し前にペンシルベニア大のFernando V. FerreiraとMaisy Wongによる「Neighborhood Choice After COVID: The Role of Rents, Amenities, and Work-From-Home」というNBER論文が上がっているが、そちらは新卒が大学卒業後にどのような近隣地区を選好するか、というやや変わった切り口からコロナ禍の居住地域の選択への影響を調べている。以下はその要旨。

We investigate how neighborhood preferences and choices changed one year after the beginning of the COVID pandemic. We study a Neighborhood Choice Program that helped graduating students choose where to live by providing new information about rents and amenities. Using panel data on neighborhood rankings before and after information, we find that changes in rankings favor neighborhoods where social and professional network shares are higher by 2.2 percentage points, rents are lower by $432, and are 2.4 kilometers farther from the city center. Interestingly, we did not detect this movement away from downtowns when the program was offered prior to the pandemic. We then estimate a neighborhood choice model to recover MWTP for amenities both before and after the pandemic. Our estimates reveal that MWTP for network shares post COVID is markedly lower than prior to COVID. Finally, we perform counterfactuals to quantitatively assess how changes in preferences affect where people live, and find that weaker network preferences are most impactful, while heterogeneity by commute and work-from-home are less relevant.