Showing results 1 to 6 of approximately 6.(refine search)
Optimists and Pessimists in the Housing Market
Given momentum in house prices over business cycles, research on consumer beliefs since the financial crisis has honed in on the potential importance of extrapolative beliefs?myopically assuming trends in asset prices will continue. Extrapolation is frequently cited as a central reason for excessively optimistic expectations about future asset prices, featuring prominently, for example, in the irrational exuberance narrative of Shiller. Other influential work since the Great Recession has emphasized the outsized role that extrapolative optimists can have in bubble formation. In this post, we ...
How Well Does Economic Uncertainty Forecast Economic Activity?
Despite the enormous reach and influence of the literature on economic and economic policy uncertainty, one surprisingly under-researched topic has been the forecasting performance of economic uncertainty measures. We evaluate the ability of seven popular measures of uncertainty to forecast in-sample and out-of-sample over real and financial outcome variables. We also evaluate predictive content over different quantiles of the GDP growth distribution. Real-time data and estimation considerations are highly consequential, and we devote considerable attention to them. Four main findings ...
Inflation at Risk
We investigate how macroeconomic drivers affect the predictive inflation distribution as well as the probability that inflation will run above or below certain thresholds over the near term. This is what we refer to as Inflation-at-Risk–a measure of the tail risks to the inflation outlook. We find that the recent muted response of the conditional mean of inflation to economic conditions does not convey an adequate representation of the overall pattern of inflation dynamics. Analyzing data from the 1970s reveals ample variability in the conditional predictive distribution of inflation that ...
Predicting Operational Loss Exposure Using Past Losses
Operational risk models, such as the loss distribution approach, frequently use past internal losses to forecast operational loss exposure. However, the ability of past losses to predict exposure, particularly tail exposure, has not been thoroughly examined in the literature. In this paper, we test whether simple metrics derived from past loss experience are predictive of future tail operational loss exposure using quantile regression. We find evidence that past losses are predictive of future exposure, particularly metrics related to loss frequency.
Hedging and Pricing in Imperfect Markets under Non-Convexity
This paper proposes a robust approach to hedging and pricing in the presence of market imperfections such as market incompleteness and frictions. The generality of this framework allows us to conduct an in-depth theoretical analysis of hedging strategies for a wide family of risk measures and pricing rules, which are possibly non-convex. The practical implications of our proposed theoretical approach are illustrated with an application on hedging economic risk.
Decomposing Outcome Differences between HBCU and Non-HBCU Institutions
This paper investigates differences in outcomes between historically black colleges and universities (HBCU) and traditional college and universities (non-HBCUs) using a standard Oaxaca/Blinder decomposition. This method decomposes differences in observed educational and labor market outcomes between HBCU and non-HBCU students into differences in characteristics (both student and institutional) and differences in how those characteristics translate into differential outcomes. Efforts to control for differences in unobservables between the two types of students are undertaken through ...