We develop an R package panelView and a Stata package panelview for panel data visualization. They are designed to assist causal analysis with panel data and have three main functionalities: (1) they plot the treatment status and missing values in a panel dataset; (2) they visualize variables of...

The unprecedented fiscal and monetary policy responses during the COVID-19 crisis have increased uncertainty about inflation. During crises periods, the strength of the transmission of inflation uncertainty shocks from one country to another tends to intensify. This paper examines empirical...

Herein we attempt to quantify Tom McClellan’s notion of Dance Steps between two series of data, often of differing time periods (a current, or dependent and a previous, or independent period data series), looking for similarities in the turning points to use as a reference for the future...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

This paper examines the econometric causal model for policy analysis developed by the seminal ideas of Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two popular causal frameworks: Neyman-Holland causal model and the do-calculus. The Neyman-Holland causal model...