I have a data set that was sampled at a high frequency relative to the speed over which changes are expected to occur. This has resulted in high autocorrelation between adjacent values upto a lag of 200-300. The goal of my project is to measure the magnitude of intervention effects on this large time series.
Initially I tried to use a linear regression with autoregressive coefficents, but switch to an arima with exogenous regressors. What is the practical difference in the use of these two approaches?or are they effectively equivalent? I have been hard pressed trying to find direct comparisons of the benefits and costs of each.