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In a recent issue of Political Analysis, Grant and Lebo authored two articles that forcefully argue against the use of the general error correction model (GECM) in nearly all time series applications of political data. We reconsider Grant and Lebo’s simulation results based on five common time series data scenarios. We show that Grant and Lebo’s simulations (as well as our own additional simulations) suggest the GECM performs quite well across these five data scenarios common in political science. The evidence shows that the problems Grant and Lebo highlight are almost exclusively the result of either incorrect applications of the GECM or the incorrect interpretation of results. Based on the prevailing evidence, we contend the GECM will often be a suitable model choice if implemented properly, and we offer practical advice on its use in applied settings

Don’t jettison the general error correction model just yet: A practical guide to avoiding spurious regression with the GECM