Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?

Time series econometrics and forecasting constitute a dynamic research area that combines sophisticated statistical methodologies with economic theory to model, interpret and predict economic and ...

The purpose of the American Journal of Agricultural Economics is to provide a forum for creative and scholarly work in agricultural economics. Submitted manuscripts focus on the economics of natural ...

This paper discusses nonparametric models for panels of time series. There is already a substantial literature on nonlinear models and nonparametric methods in a regression and time series setting.

The paper introduces “system priors”, their use in Bayesian analysis of econometric time series, and provides a simple and illustrative application. System priors were devised by Andrle and Benes ...