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This article investigates spatial linkages in returns, idiosyncratic risks and volatilities across 19 U.S. regional housing markets. Using Case & Shiller housing price indices from 1995 through 2009, we find that interconnections across markets can be “wider” and “stronger” than would normally be expected. They are “wider” because, in addition to geographic closeness, economic proximity is also an important source of influence; they are “stronger” because of the significant contagion effects during the 2007–2009 subprime and financial crises. The increased comovement and interdependence, especially among more geographically diverse regions with similar economic conditions, may help explain the failure of geographic portfolio diversification strategies.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may Non-Technical SummaryOne of the important lessons from the 2007-2009 financial crisis is that systemic risk and spillover effects are significantly underestimated in most widely used risk measures and that standard risk measurement instruments, such as value-at-risk (VaR), need to be adjusted to adequately reflect overall risk. In this paper, we propose a state-dependent sensitivity (SDS) VaR for quantifying risk spillovers among sets of different financial institutions.We estimate a system of quantile regressions for four sets of financial institutions (commercial banks, investment banks, hedge funds, and insurance companies), in which each type of financial institution is represented by an index of several firms. In addition, our empirical model explicitly accounts for the effects of different market states (tranquil, normal, and volatile) on the magnitude of risk spillovers. We trace out the time path of how shocks move through the system using impulse response functions. The SDSVaR model explicitly reveals the magnitude of risk spillovers at a certain point in time. Moreover, in contrast to dynamic correlations, we are able to obtain the direction of spillovers from one set of institutions to another. Hence, the approach permits a delineation of spillover effects from shocks affecting the financial sector as a whole.As opaque and highly leveraged investment partnerships, hedge funds recently received attention as a potential source of contagion, a transmission channel of risk between different asset classes and as a potential amplifier of systemic risk in financial markets. If highly leveraged hedge funds are forced to liquidate large position at fire-sale prices, counterparties sustain heavy losses. This may lead to further defaults or threaten systemically important institutions not only directly as counterparties or creditors but also indirectly through asset price adjustments (Bernanke, 2006). While most observers tend to agree that hedge funds have some systemic importance, little evidence exists on the magnitude of potential spillover effects. In this paper we provide the first empirical estimates of the size of intra-month spillover effects from hedge funds to other financial institutions.In contrast to other recently proposed measures (e.g. Adrian and Brunnermeier 2010), the SDSVaR proposed in this paper models the distribution of the value-at-risk. After calculating the VaR for each set of institutions...

As symbolized by vacant office buildings, empty shopping malls and abandoned flats in metropolitan areas, the new coronavirus disease 2019 has severely impacted real estate markets. This paper provides a comprehensive literature review of the latest academic insights into how this pandemic has affected the housing, commercial real estate and the mortgage market. Moreover, these findings are linked to comprehensive statistics of each real estate sector’s performance during the crisis. Finally, the paper includes an outlook and discusses possible future developments in each real estate segment.