This paper illustrates how to handle a sequence of extreme observations--such as those recorded during the COVID-19 pandemic--when estimating a Vector Autoregression, which is the most popular time-series model in macroeconomics. Our results show that the ad-hoc strategy of dropping these...

We evaluate the impact of government mandated proof of vaccination requirements for access to public venues and non-essential businesses on COVID-19 vaccine uptake. We find that the announcement of a mandate is associated with a rapid and significant surge in new vaccinations (more than 60\%...

While this is typically ignored, the properties of the stochastic process followed by aggregate consumption affect the estimates of the costs of fluctuations. This paper pursues two approaches to modelling aggregate consumption dynamics and to measuring how much society dislikes fluctuations,...

I estimate a model in which new technology entails random adjustment costs. Rapid adjustments may cause productivity slowdowns. These slowdowns last longer when retooling is costly. The model explains why growth-rate disasters are more likely than miracles, and why volatility of growth relates...

We develop analytic asymptotic methods to characterize time series properties of nonlinear dynamic stochastic models. We focus on a stochastic growth model which is representative of the models underlying much of modern macroeconomics. Taking limits as the stochastic shocks become small, we...

Over the postwar, the U.S., Europe and Japan have experienced what may be thought of as medium frequency oscillations between persistent periods of robust growth and persistent periods of relative stagnation. These medium frequency movements, further, appear to bear some relation to the high...

Making inferences about aggregate business cycles from regional variation alone is difficult because of economic channels and shocks that differ between regional and aggregate economies. However, we argue that regional business cycles contain valuable information that can help discipline models...

We make four contributions in this paper. First, we provide a core of macroeconomic time series usable for systematic research on China. Second, we document, through various empirical methods, the robust findings about striking patterns of trend and cycle. Third, we build a theoretical model...

A central challenge in asset pricing is the weak connection between stock returns and observable economic fundamentals. We provide evidence that this connection is stronger than previously thought. We use a modified version of the Bry-Boschan algorithm to identify long-run swings in the stock...

This paper develops a framework for inferring common Markov-switching components in a panel data set with large cross-section and time-series dimensions. We apply the framework to studying similarities and differences across U.S. states in the timing of business cycles. We hypothesize that there...