Are GDP forecasts optimal? Evidence on European countries

Alessandro Giovannelli and Filippo Maria Pericoli

International Journal of Forecasting, 2020, vol. 36, issue 3, 963-973

Abstract: We assess the accuracy of real GDP growth forecasts released by governments and international organizations for European countries in the years 1999–2017. We implement three testing procedures characterized by different assumptions on the forecasters’ loss functions. First, we test forecast rationality within the traditional approach based on a quadratic loss function (Mincer and Zarnowitz, 1969). Second, following Elliott, Timmermann and Komunjer (2005), we test rationality by allowing for a flexible loss function where the shape parameter driving the extent of asymmetry is unknown and estimated from the empirical distribution of forecast errors. Lastly, we implement the tests proposed by Patton and Timmermann (2007a) that hold regardless of the functional form of the loss function. We conclude that governmental forecasts are biased and not rational under a symmetric and quadratic loss function, but they are optimal under more general assumptions on the loss function. We also find that the preferences of forecasters change with the forecasting horizon: when moving from one- to two-year-ahead forecasts, the optimistic bias increases and the parameter of asymmetry in the loss function significantly increases.

Keywords: Forecast optimality; Asymmetric loss function; Quantile-based test; Spline-based test; GMM estimation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:36:y:2020:i:3:p:963-973

DOI: 10.1016/j.ijforecast.2019.12.003

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