Showing results 1 to 5 of approximately 5.(refine search)
Global Robust Bayesian Analysis in Large Models
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. The author develops a sequential Monte Carlo algorithm and uses 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 ...
Bubbles and the Value of Innovation
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 ...
Forecasting the COVID-19 Pandemic in the Fifth District
How many COVID-19 cases will there be in the coming days and months? While the Fifth District appears to be past the peak number of daily cases, a wide range of future outcomes is still possible.
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 ...
Survey Data and Subjective Beliefs in Business Cycle Models
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 ...