Journal of Econometrics, Forthcoming
We estimate 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. Our 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 increase in the death rate among reported cases. The model forecasts perform well, even relative to models from epidemiology and statistics.
New Zealand Economic Papers, 2020, 1-8
We estimate a statistical model for COVID-19 cases and deaths in New Zealand. New Zealand is an important test case for statistical and theoretical research into the dynamics of the global pandemic since it went through a full cycle of infections. We choose functional forms for infections and deaths that incorporate important features of epidemiological models but allow for flexible parameterization to capture different trajectories of the pandemic. Our Bayesian estimation reveals that the simple statistical framework we employ fits the data well and allows for a transparent characterization of the uncertainty surrounding the trajectories of infections and deaths.
Revise and Resubmit, Review of Economic Studies
This paper develops a theory of subjective beliefs that departs from rational expectations, and shows that biases in household beliefs have quantitatively large effects on macroeconomic aggregates. The departures are formalized using model-consistent notions of pessimism and optimism and are disciplined by data on household forecasts. The role of subjective beliefs is quantified in a business cycle model with goods and labor market frictions. Consistent with the survey evidence, an increase in pessimism generates upward biases in unemployment and inflation forecasts and lowers economic activity. The underlying belief distortions reduce aggregate demand and propagate through frictional goods and labor markets. As a by-product of the analysis, solution techniques that preserve the effects of time-varying belief distortions in the class of linear solutions are developed.
Episodes of booming innovation coincide with intense speculation in financial markets leading to bubbles—increases in market valuations and firm creation followed by a crash. We provide a framework reproducing these facts that makes a rich set of predictions on how speculation changes both the private and social values of innovation. We confirm the theory in the universe of U.S. patents issued from 1926 through 2010. Measures based on financial market information indicate that speculation increases the private value of innovation and reduces negative spillovers to competing firms. No commensurate change occurs in measures grounded in real outcomes.
This paper develops a tool for global prior sensitivity analysis in large Bayesian models. Without imposing parametric restrictions, the methodology provides bounds for posterior means or quantiles given any prior close to the original in relative entropy, and reveals features of the prior that are important for the posterior statistics of interest. We develop a sequential Monte Carlo algorithm and use approximations to the likelihood and statistic of interest to implement the calculations. Applying the methodology to the error bands for the impulse response of output to a monetary policy shock in the New Keynesian model of Smets and Wouters (2007), we show that the upper bound of the error bands is very sensitive to the prior but the lower bound is not, with the prior on wage rigidity playing a particularly important role.
We highlight a reason for the vast range of estimates for the effect of demographics on interest rates: the magnitudes are not well-identified without often omitted data on capital and life-cycle consumption. Using nonparametric prior sensitivity analysis for an overlapping generations model estimated through Bayesian methods, we show small changes in the prior for the discount rate, intertemporal elasticity of substitution, and depreciation rate can shift posterior quantiles for the effects of demographics by up to 1.5 percentage points. Capital-output ratio data substantially tighten estimates of the depreciation rate but not the discount rate. Life-cycle consumption informs all three parameters.
Federal Reserve Bank of Richmond Economic Brief, January 2021, No. 21-03
Federal Reserve Bank of Richmond Economic Brief, September 2020, No. 20-10
Federal Reserve Bank of Richmond Special Report, May 8, 2020
Regional Matters, April 23, 2020