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Working Paper
Specification Choices in Quantile Regression for Empirical Macroeconomics
Quantile regression has become widely used in empirical macroeconomics, in particular for estimating and forecasting tail risks to macroeconomic indicators. In this paper we examine various choices in the specification of quantile regressions for macro applications, for example, choices related to how and to what extent to include shrinkage, and whether to apply shrinkage in a classical or Bayesian framework. We focus on forecasting accuracy, using for evaluation both quantile scores and quantile-weighted continuous ranked probability scores at a range of quantiles spanning from the left to ...
Working Paper
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 ...
Working Paper
Capital Flows in Risky Times: Risk-On / Risk-Off and Emerging Market Tail Risk
This paper characterizes the implications of risk-on/risk-off shocks for emerging market capital flows and returns. We document that these shocks have important implications not only for the median of emerging markets flows and returns but also for the left tail. Further, while there are some differences in the effects across bond vs. equity markets and flows vs. asset returns, the effects associated with the worst realizations are generally larger than on the median realization. We apply our methodology to the COVID-19 shock to examine the pattern of flow and return realizations: the sizable ...
Working Paper
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 ...