The great advantage of time series regression analysis is that it can both explain the past and predict the future behavior of variables. This volume explores the regression (or structural equation) approach to the analysis of time series data. It also introduces the Box-Jenkins time series method in an attempt to bridge partially the gap between the two approaches.

About the Author:

Charles W. Ostrom, Jr. is a Professor of Political Science. Professor Ostrom joined the MSU faculty in 1974 and taught in the Political Science Department continuously with the exception of sabbaticals at the University of Minnesota (1982-83), University of Nebraska-Lincoln (1992-93), and National Center for State Courts (2000-2001). Professor Ostrom received his Ph.D. from Indiana University in 1975. Professor Ostrom’s current professional interests are focused on US trial courts. His work includes work on criminal sentencing, racial discrimination, trial court culture, judicial workload, and court performance. The aforementioned work has been funded by the National Institute of Justice. Professor Ostrom received the American Council on Education Fellowship for the 1992-93 class.

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Time Series Analysis: Regression Techniques

Ostrom, Charles W.

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