We began this book by suggesting that scholars in the social sciences are often interested in how processes – whether political, economic, or social – changeover time. Throughout, we have emphasized that although many of our theories discuss that change, often our empirical models do not give the concept of change the same pride of place. Time series elements in data are often treated as a nuisance – something to cleanse from otherwise meaningful information – rather than part and parcel of the data-generating process that we attempt to describe with our theories.

We hope this book is an antidote to this thinking. Social dynamics are crucial to all of the social sciences. We have tried to provide some tools to model and therefore understand some of these social dynamics. Rather than treat temporal dynamics as a nuisance or a problem to be ameliorated, we have emphasized that the diagnosis, modeling, and analysis of those dynamics are key to the substance of the social sciences. Knowing a unit root exists in a series tell us something about the data-generating process: shocks to the series permanently shift the series, integrating into it. Graphing the autocorrelation functions of a series can tell us whether there are significant dynamics at one lag (i.e., AR(1))or for more lags (e.g., an AR(3)). Again, this tells us something about the underlying nature of the data: how long does an event hold influence?

The substance of these temporal dynamics is even more important when thinking about the relationships between variables.