The good forecasting performance of factor models has been well documented in the literature. While many studies focus on a very limited set of variables (typically GDP and inflation), this study evaluates forecasting performance at disaggregated levels to examine the source of the improved...

In this paper we consider the value of Google Trends search data for nowcasting (and forecasting) GDP growth for a developed (U.S.) and emerging-market economy (Brazil). Our focus is on the marginal contribution of "Big Data" in the form of Google Trends data over and above that of traditional...

This paper examines the likely growth of U.S. GDP in the decade beginning in 2010. I analyze the two components of the rise in GDP over this ten year period: (1) the recovery from the substantially depressed level of economic activity at the start of the decade; and (2) the rise in potential GDP that...

We assess the forecasting performance of the nowcasting model developed at the New York FED. We show that the observation regarding a striking difference in the model's predictive ability across business cycle phases made earlier in the literature also applies here. During expansions, the...

Not all of that extra output will remain in the United States. If the trade deficit is reduced by three percent of GDP, the rise in exports and decline in imports will reduce output available for U.S. consumption and investment by about 0.3 percent a year

This paper presents a novel dynamic factor model for non-stationary data. We begin by constructing a simple dynamic stochastic general equilibrium growth model and show that we can represent and estimate the model using a simple linear-Gaussian (Kalman) filter. Crucially, consistent estimation...