Modeling multivariate time series in economics: Autoregressions versus Recurrent Neural Networks
On August 23-24, 2018 the CMSA hosted our fourth annual Conference on Big Data. The Conference featured many speakers from the Harvard community as well as scholars from across the globe, with talks focusing on computer science, statistics, math and physics, and economics.
Speaker: Sergiy Verstyuk
Title: Modeling multivariate time series in economics: Autoregressions versus Recurrent Neural Networks
Abstract: Non-structural empirical modeling is important in economics. It is used extensively for such tasks as forecasting and policy analysis. I apply vector autoregression and multivariate recurrent neural network methods to economic variables and compare their results.