Abstract

Nowcasting is a phenomenon that has recently become widely researched area in the context of official statistics. The main reason is an exploration of new data sources that can be used in the early estimation of the economic activity. A digital system that records passages of vehicles through highways generates such big data of early available information. It assembles high-frequency data, which can be collected relatively shortly afterwards, that holds information related to transport of goods, commodities and population through roads. A transportation of goods and commodities, usually carried out by trucks, through roads can provide an early indicator of the economic activity for industries that rely on the road transport. The objective of this paper is to estimate an index, which measures monthly changes of the number of vehicles on highways. The truck-passage index is able to provide a nowcasting estimate of the economic output for industries that heavily rely on the road transport. In the empirical study, we use toll data from the Slovak digital highway system that capture in-and-out passages of all passing trucks through monitored sections of highways. The truck-passage index is then compared to a monthly industrial production index that aims to validate its accuracy, and, potentially, provide its early nowcasting indicator. Furthermore, we use an empirical mode decomposition to extract a business cycle and de-trend time series of both truck-passage and industrial production indices that allows for the in-depth analysis of fluctuations of economic time series.