The way we analyze time series data has changed a lot since the 1980s. We now use multiple time series models to understand how different variables interact for policy and forecasting. Vector autoregressions are now a common method in this analysis. Another important development was the idea of cointegration in economic time series, which helped solve some problems with traditional approaches. Now, we often use vector error correction models to incorporate relationships between variables over time.