Time Series Analysis: Method and Substance Introductory Workshop on Time Series Analysis

U.S. Monthly Presidential Approval Data, 1978:1-2004:7

OLS Strategies

• When you first learned about serial correlation when taking an OLS class, you probably learned about techniques like generalized least squares (GLS) to correct the problem.
• This is not ideal because we can improve our explanatory and forecasting abilities by modeling the dynamics in Yt, Xt, and εt.
• The naïve OLS approach can also produce spurious results when we do not account for temporal dynamics.

Properties of Time Series Data

• Property #2: Time series data often have time-dependent moments (e.g. mean, variance, skewness, kurtosis).
• The mean or variance of many time series increases over time.
• This is a property of time series data called nonstationarity.
• As Granger & Newbold (1974) demonstrated, if two independent, nonstationary series are regressed on each other, the chances for finding a spurious relationship are very high.