In this paper, we develop a state-dependent sensitivity value-at-risk (SDSVaR) approach that enables us to quantify the direction, size, and duration of risk spillovers among financial institutions as a function of the state of financial markets (tranquil, normal, and volatile). Within a system of quantile regressions for four sets of major financial institutions (commercial banks, investment banks, hedge funds, and insurance companies) we show that while small during normal times, equivalent shocks lead to considerable spillover effects in volatile market periods. Commercial banks and, especially, hedge funds appear to play a major role in the transmission of shocks to other financial institutions. Using daily data, we can trace out the spillover effects over time in a set of impulse response functions and find that they reach their peak after 10 to 15 days.
This paper examines the long-term impact and short-term dynamics of macroeconomic variables on international housing prices. Since adequate housing market data are generally not available and usually of low frequency we apply a panel cointegration analysis consisting of 15 countries over a period of 30 years. Pooling the observations allows us to overcome the data restrictions which researchers face when testing long-term relationships among single real estate time series. This study does not only confirm results from previous studies, but also allows for a comparison of single country estimations in an integrated equilibrium framework. The empirical results indicate house prices to increase in the long-run by 0.6% in response to a 1% increase in economic activity while construction costs and the long-term interest rate show average long-term effects of approximately 0.6% and ?0.3%, respectively. Contrary to current literature our estimates suggest only about 16% adjustment per year. Thus the time to full recovery may be much slower than previously stated, so that deviations from the long-term equilibrium result in a dynamic adjustment process that may take up to 14 years.
In the current stand of literature on the rental adjustment process starting with Hendershott et al. (Real Estate Economics, 30, 165-183, 2002a, Journal of Real Estate Finance and Economics, 24, 59-87, 2002b) it has become practice to treat the compound variable "occupied stock" as a supply variable. In this study we show that this variable deserves a more critical investigation and that the general view of a supply variable may be misleading. Using panel data covering 30 urban areas for 17 years, we investigate the rental adjustment process in the German office market. The application of recently developed cointegration techniques for non-stationary panel data in conjunction with the corresponding error correction model (ECM) enables us to overcome the data limitations, particularly existent for most European real estate markets. Hence, our primary motivation is (a) to demonstrate how "occupied stock" should be interpreted correctly and (b) to provide useful insights into the long-term relationships and short-run dynamics of real office prime rents. The empirical evidence suggests that a one percent rise in office employment increases real rents on average by 1.64% through higher demand for office space. On the other hand, a one percent increase in the supply of office space decreases real rents in the long run by 2.25%. The results from the error correction model show that deviations from the long-run equilibrium lead to an adjustment process which restores equilibrium within approximately 3 years.
