Persistence in time series Could someone tell me what the term 'persistence' mean in time series analysis? It's regarding econometrics and applied regression.
 A: Roughly speaking, the term persistence in time series context is often related to the notion of memory properties of time series. To put it another way, you have a persistent time series process if the effect of infinitesimally (very) small shock will be influencing the future predictions of your time series for a very long time. Thus the longer the time of influence the longer is the memory and the extremely persistence. You may consider an integrated process I(1) as an example of highly persistent process (information that comes from the shocks never dies out). Though fractionally integrated (ARFIMA) processes would be more interesting examples of persistent processes. Probably it would be useful to read about Measuring Conditional Persistence in Time Series in G.Kapetanios article.
A: A persistent series is one where the value of the variable at a certain date is closely related to the previous value. The two basic measures of persistence are the autocovariance and the autocorrelation coefficient.
