Forecasting vs. Nowcasting, economic analysis in the age of coronavirus

Economic data are quantitative or qualitative measures, which are used to describe a real, past or present economic situation. In the digital age, where everything is just a click away and available immediately, the work of economists becomes even more difficult, given the amount of data to analyse on the one hand and, on the other hand, the increased demands of society for timely economic analysis. Moreover, due to the pandemic crisis, economic analysis experts are now called upon to measure the impact of the exceptional event on the economy, when, in normal times, economic analysis are typically made on a quarterly basis. How can we analyse the present, near future or near past?

View of the rail freight terminal in Chiasso

“Nowcasting” – i.e. the prediction of the present, the very near future, and the very recent past state of an economic indicator – is increasingly popular among economic analists and researchers. Nowadays, in fact, traditional measures used to analyse the state of an economy (e.g. gross domestic product, GDP) are only determined after a long period of time and are also subject to subsequent revisions. In Switzerland, during the lockdown period caused by the coronavirus pandemic, a group of economists from the KOF (ETH Zürich Institute), SECO and other institutions in Switzerland developed trendEcon, a model that uses Google searches for specific keywords to obtain certain trend indicators almost in real time. But does this system work for economic analysis at the regional level?

“The difficulty of conducting surveys at regional level lies in the adequacy of the number of observations available”, says Davide Arioldi, researcher at the USI Institute of Economic Research (IRE, Faculty of Economics), interviewed during a RSI tv report on “Tempi moderni” (see embedded video below). For example, in order to observe the so-called ‘demographic trend’ of companies, the IRE has developed its own system that exploits the digitisation of the Ticino Trade Register, from which information on companies is taken and then cross-referenced with data from other sources. “With this system we can obtain timely indications that can be used by public institutions to take action in a more targeted way, for example in the field of corporate taxation to attract companies”.

Source: Università della Svizzera

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