We estimate a multisector sticky-price model for the U.S. economy in which the degree of price stickiness is allowed to vary across sectors. For this purpose, we use a specification that allows us to extract information about the underlying cross-sectional distribution from aggregate data....

We estimate two-factor equilibrium models on different parts of the yield curve. In this exploration of the term structure of interest rates, we use two-factor affine yield models as our diagnostic tool. The exercise provides insights on how to reconcile the time-series dynamics of interest...

Some recent time-series applications use probit models to measure the forecasting power of a set of variables. Correct inferences about the significance of the variables requires a consistent estimator of the covariance matrix of the estimated model coefficients. A potential source of...

The standard linear technique of impulse response function analysis is extended to the nonlinear case by defining a generalized impulse response function. Measures of persistence and asymmetry in response are constructed for a wide class of time series.

In a factor-augmented regression, the forecast of a variable depends on a few factors estimated from a large number of predictors. But how does one determine the appropriate number of factors relevant for such a regression? Existing work has focused on criteria that can consistently estimate the...

Various methods are available to extract the "business cycle component" of a given time series variable. These methods may be derived as solutions to frequency extraction or signal extraction problems and differ in both their handling of trends and noise and their assumptions about the ideal...

This paper develops a new approach to change-point modeling that allows for an unknown number of change points in the observed sample. Our model assumes that regime durations have a Poisson distribution. The model approximately nests the two most common approaches: the time-varying parameter...

Recent developments in nonlinear time series modelling are reviewed. Three main types of nonlinear models are discussed: Markov Switching, Threshold Autoregression and Smooth Transition Autoregression. Classical and Bayesian estimation techniques are described for each model. Parametric tests...

Recent vector autoregression (VAR) studies have shown that monetary policy shocks have had a reduced effect on the economy since the beginning of the 1980s. This paper investigates the causes of this change. First, we estimate an identified VAR over the pre- and post-1980 periods, and...

Many modeling issues and policy debates in macroeconomics depend on whether macroeconomic times series are best characterized as linear or nonlinear. If departures from linearity exist, it is important to know whether these are endogenously generated (as in, for example, a threshold...