While the literature has already widely documented the effects of macroeconomic news announcements on asset prices, as well as their asymmetric impact during good and bad times, we focus on the reaction to news based on the description of the state of the economy as painted by the Federal Open...

We estimate monetary policy surprises (sentiment) from the perspective of three different textual sources: direct central bank communication (FOMC statements and press conferences), news articles, and Twitter posts during FOMC announcement days. Textual sentiment across sources is highly...

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...

Survey of forecasters, containing respondents' predictions of future values of growth, inflation and other key macroeconomic variables, receive a lot of attention in the financial press, from investors, and from policy makers. They are apparently widely perceived to provide useful information...

We use the dynamic Gordon-growth model to decompose the rent-price ratio for owner-occupied housing in the U.S., four Census regions, and twenty-three metropolitan areas into three components: The expected present value of real rental growth, real interest rates, and future housing premia. We...

We propose a framework to evaluate the conditionality of forecasts. The crux of our framework is the observation that a forecast is conditional if revisions to the conditioning factor are faithfully incorporated into the remainder of the forecast. We consider whether the Greenbook, Blue Chip,...

Linear GARCH(1,1) and threshold GARCH(1,1) processes are established as regularly varying, meaning their heavy tails are Pareto like, under conditions that allow the innovations from the, respective, processes to be skewed. Skewness is considered a stylized fact for many financial returns...

DSGE models are a prominent tool for forecasting at central banks and the competitive forecasting performance of these models relative to alternatives-including official forecasts has been documented. When evaluating DSGE models on an absolute basis, however, we find that the benchmark estimated...

This paper proposes a new nonparametric mixed data sampling (MIDAS) model and develops a framework to infer clusters in a panel regression with mixed frequency data. The nonparametric MIDAS estimation method is more flexible and substantially simpler to implement than competing approaches. We...

Survey based measures of inflation expectations are not informationally efficient yet carry important information about future inflation. This paper explores the economic significance of informational inefficiencies of survey expectations. A model selection algorithm is applied to the inflation...