Time-series models

This chapter gives an introduction to time-series models. The chapter highlights some of the potential problems that are common in time-series models, including autocorrelation and nonstationarity. There is a discussion of practical corrections for these problems when they exist, with a simpler approach sometimes being advised. The concepts are then applied to time-series models (e.g., Granger Causality and Vector Autoregression models), with applications on the relationship between oil prices and the stock market and between President Trump’s weekly tweets and his approval rating. And, there is a discussion on forecasting future values of a time-series variable.