We propose the dynamic network effect (DNE) model for the study of high-dimensional multivariate time series data. Cross-sectional dependencies between units are captured via one or multiple observed networks and a low-dimensional vector of latent stochastic network effects. The...

Understanding the relationship between macroeconomic variables and the stock market is important because macroeconomic variables have a systematic effect on stock market returns. This study uses monthly data from India for the period from April 1994 to July 2018 to examine the long-run...

We develop an algorithm to construct approximate decision rules that are piecewise-linear and continuous for DSGE models with an occasionally binding constraint. The functional form of the decision rules allows us to derive a conditionally optimal particle filter (COPF) for the evaluation of...