Time Series Analysis
- Sara Mitchell, University of Iowa
- Clayton Webb, Texas A&M University
Both the ICPSR courses Regression Analysis II: Linear Models and Mathematics for Social Scientists II are prerequisites for this course. This four-week workshop begins by focusing on the autoregressive and moving average components of time series, and then turns to estimation of univariate time series models using the Box-Jenkins approach. Intervention analysis and more general transfer function models build on this tradition, often referred to as the statistical analysis of time series. The course then focuses on the econometric (regression) analysis of time series, historically quite distinct from the statistical tradition. In recent years, regression analysis has borrowed much from the statistical tradition, and the connections between the two are important for understanding how social scientists should analyze time series data. Analysis of integrated time series, including unit root econometrics and error correction models, focuses on recent econometric advances in dealing with nonstationary data. Mill's Time Series Analysis for Economists, McCleary and Hay's Applied Time Series Analysis for Social Scientists, and Harvey's Econometric Analysis of Time Series include much of the material that will be covered in this course.
Fees: Consult the fee structure.
Location: ICPSR -- Ann Arbor, MI
Date(s): June 22 - July 17
Time: 1:00 PM - 3:00 PM