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Keywords:Time-Varying Parameters 

Working Paper
How To Go Viral: A COVID-19 Model with Endogenously Time-Varying Parameters

This paper estimates a panel model with endogenously time-varying parameters for COVID-19 cases and deaths in U.S. states. The functional form for infections incorporates important features of epidemiological models but is flexibly parameterized to capture different trajectories of the pandemic. Daily deaths are modeled as a spike-and-slab regression on lagged cases. The paper's Bayesian estimation reveals that social distancing and testing have significant effects on the parameters. For example, a 10 percentage point increase in the positive test rate is associated with a 2 percentage point ...
Working Paper , Paper 20-10

Working Paper
Modeling Time-Variation Over the Business Cycle (1960-2017): An International Perspective

In this paper, I explore the changes in international business cycles with quarterly data for the eight largest advanced economies (U.S., U.K., Germany, France, Italy, Spain, Japan, and Canada) since the 1960s. Using a time-varying parameter model with stochastic volatility for real GDP growth and inflation allows their dynamics to change over time, approximating nonlinearities in the data that otherwise would not be adequately accounted for with linear models (Granger et al. (1991), Granger (2008)). With that empirical model, I document a period of declining macro volatility since the 1980s, ...
Globalization Institute Working Papers , Paper 348

Working Paper
Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models

We document five novel empirical findings on the well-known potential ordering drawback associated with the time-varying parameter vector autoregression with stochastic volatility developed by Cogley and Sargent (2005) and Primiceri (2005), CSP-SV. First, the ordering does not affect point prediction. Second, the standard deviation of the predictive densities implied by different orderings can differ substantially. Third, the average length of the prediction intervals is also sensitive to the ordering. Fourth, the best ordering for one variable in terms of log-predictive scores does not ...
Working Papers , Paper 21-21

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