nep-for New Economics Papers
on Forecasting
Issue of 2023‒06‒19
two papers chosen by
Rob J Hyndman
Monash University

  1. Dynamic time series modelling and forecasting of COVID-19 in Norway By Gunnar Bårdsen; Ragnar Nymoen
  2. Forecasting banknote circulation during the COVID-19 pandemic using structural time series models By Nikolaus Bartzsch; Marco Brandi; Lucas Devigne; Raymond de Pastor; Gianluca Maddaloni; Diana Posada Restrepo; Gabriele Sene

  1. By: Gunnar Bårdsen (Department of Economics, Norwegian University of Science and Technology and Department of Economics, University of Oslo); Ragnar Nymoen (Department of Economics, University of Oslo)
    Abstract: A framework for forecasting new COViD-19 cases jointly with hospital admissions and hospital beds with COVID-19 cases is presented. This project, dubbed CovidMod, produced 21-days ahead forecasts each working day from March 2021 to April 2022, and forecast errors that were used to assess forecast accuracy. A comparison with the forecasts of the Norwegian Institute of Public Health (NIPH), with dates of origin in the same period, favours the CovidMod forecasts in terms of lower RMSFEs (Root Mean Squared Forecast Errors), both for new cases and for hospital beds. Another comparison, with the short term forecasts (7 day horizon) produced by a forecasting project at the University of Oxford, shows only little difference in terms of the RMSFEs of new cases. Next, we present a further development of the model which allows the effects of policy responses to a central model parameter to be forecasted by an estimated smooth-transition function. The forecasting performance of the resulting non-linear model is demonstrated, and it is suggested as a possible way forward in the development of relevant forecasting tools in general and for pandemics in particular.
    JEL: C32 C53 C54
    Date: 2023–05–23
    URL: http://d.repec.org/n?u=RePEc:nst:samfok:19623&r=for
  2. By: Nikolaus Bartzsch (Deutsche Bundesbank); Marco Brandi (Banca d'Italia); Lucas Devigne (Banque de France); Raymond de Pastor (Banque de France); Gianluca Maddaloni (Banca d'Italia); Diana Posada Restrepo (Banco de España); Gabriele Sene (Banca d'Italia)
    Abstract: As part of the Eurosystem’s annual banknote production planning, the national central banks draw up forecasts estimating the volumes of national-issued banknotes in circulation for the three years ahead. As at the end of 2021, more than 80 per cent of euro banknotes in circulation (cumulated net issuance) had been issued by the national central banks of France, Germany, Italy and Spain (‘4 NCBs’). To date, the 4 NCBs have been using ARIMAX models to forecast the banknotes issued nationally in circulation by denomination (‘benchmark models’). This paper presents the structural time series models developed by the 4 NCBs as an additional forecasting tool. The forecast accuracy measures used in this study show that the structural time series models outperform the benchmark models currently in use at each of the 4 NCBs for most of the denominations. However, it should be borne in mind that the statistical informative value of this comparison is limited by the fact the projection period is only twelve months.
    Keywords: euro, demand for banknotes, forecast of banknotes in circulation, structural time series models, ARIMA models, intervention variables
    JEL: C22 E41 E47 E51
    Date: 2023–05
    URL: http://d.repec.org/n?u=RePEc:bdi:opques:qef_771_23&r=for

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