A VAR model of the Finnish national economy for short-term forecasting

Abstract

This study examined short-term forecasting of the Finnish national economy using unrestricted vector autoregressive models (VAR models). The aim is to make use of the constructed VAR models in the research institute’s short-term forecasting practice in the autumn and spring. Quarterly data from 1990 onwards were collected for the purposes of estimation. In specifying the models, the criterion of model fit used was the accuracy of out-of-sample forecasting as measured by the root mean squared error (RMSE) or the sum of squared forecast errors of annual growth rates. The models that forecast most accurately shared the characteristics of a small number of lags and estimation beginning from the earliest possible period. In addition, the seven models that performed best in all out-of-sample forecast comparisons included as variables Finland’s adjusted GDP (a certain type of Nokia adjustment), the European Union’s GDP, and the ratio of nominal compensation per employee in Finland and in the EU15, as well as at most three of the following variables: private investment, the unemployment rate, and labour costs per employee. Forecasts for 2017 and 2018 were produced using the constructed models. Forecasts were made starting from the periods 2017Q1, 2017Q2, and 2017Q4. In forecasts starting from 2017Q4, the average estimate for the growth rate of Finland’s gross domestic product is 3.1 percent in 2017 and 1.7 percent in 2018. (AI translation)

• ISSN: 1795-1801 (Online)
• ISBN: 978-952-209-171-0 (Online)
• Publication in PDF-format