A paper titled ‘On statistical inference in time series analysis of the evolution of road safety co-authored by J.Commandeur, F.Bijleveld, R.Bergel-Hayat, C.Antoniou, G.Yannis and E.Papadimitriou is published in the Accident Analysis and Prevention Journal. Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The objective if this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them.