Applied Time Series Analysis for the Social Sciences

Acknowledgments

First and foremost, I'm deeply grateful to my former students. Many were social scientists without strong math backgrounds, and their intelligence and inquisitiveness were a powerful drive behind my attempt to find clearer ways of explaining the concepts behind time series analysis without burying them in advanced mathematics.

The majority of them were students in the time series courses I taught for the Interuniversity Consortium for Political and Social Research (ICPSR) Summer Program. It was an honor to be part of such a distinguished faculty and a vaunted training program that drew students from all over the world. Thank you, Hank Heitowit, for providing that opportunity.

Before I was promoted to lecturer for the course, I was a teaching assistant for three fascinatingly different but stellar time series professors at ICPSR. Greg Markus made the tricky fundamentals of dynamic equations seem intuitive. B. Dan Wood specialized in ARIMA models at the time and made sure that his students understood every fine detail of sound analysis and interpretation. Jim Granato was an enthusiastic supporter of the London School of Economics (LSE) approach and responsible for introducing many of us who thought we already knew time series to these newer methodologies and to Vector Autoregression.

Professor Markus was generous enough to read several draft chapters long after he hoped to be happily retired. John Elder kindly answered my cold call and provided helpful, thorough ...