We provide a methodology that efficiently combines the statistical models of nowcasting with the survey information for improving the (density) nowcasting of US real GDP. Specifically, we use the conventional dynamic factor model together with a stochastic volatility component as the baseline...

We propose an event-study research design to identify the nature and propagation of large unusual shocks in DSGE models and apply it to study the macroeconomic effects of the Covid shock. The initial outbreak is represented as the onset of a new shock process where the shock loads on wedges...

The Chicago Fed dynamic stochastic general equilibrium (DSGE) model is used for policy analysis and forecasting at the Federal Reserve Bank of Chicago. This guide describes its specification, estimation, dynamic characteristics, and how it is used to forecast the U.S. economy. In many respects...

By incorporating the Harvey accumulator into the large approximate dynamic factor framework of Doz et al. (2006), we are able to construct a coincident index of financial conditions from a large unbalanced panel of mixed frequency financial indicators. We relate our financial conditions index,...

This paper examines maximum likelihood estimation via hill climbing and the expectations maximization (EM) algorithm in the context of Hamilton's Markov switching framework. The techniques are explained in detail and are followed by a discussion of both analytic and computational issues. Both...

Markov models introduce persistence in the mixture distribution. In time series analysis, the mixture components relate to different persistent states characterizing the state-specific time series process. Model specification is discussed in a general form. Emphasis is put on the functional form...

Mixed frequency Bayesian vector autoregressions (MF-BVARs) allow forecasters to incorporate a large number of mixed frequency indicators into forecasts of economic activity. This paper evaluates the forecast performance of MF-BVARs relative to surveys of professional forecasters and investigates...

Rationality of early release data is typically tested using linear regressions. Thus, failure to reject the null does not rule out the possibility of nonlinear dependence. This paper proposes two tests that have power against generic nonlinear alternatives. A Monte Carlo study shows that the...

In this paper, we empirically assess the extent to which early release inefficiency and definitional change affect prediction precision. In particular, we carry out a series of ex-ante prediction experiments in order to examine: the marginal predictive content of the revision process, the...

Originally presented as an empirical regularity, a variety of microeconomic derivations of the Phillips tradeoff between inflation and real output have been developed. Since these new Phillips curve models are expressed in terms of unobserved variables and expectations, we develop estimates of...