A real-time disaggregated forecasting model for euro area GDP

Forecasting GDP in the short term is a complex task, among other reasons, because the macroeconomic variables required are published with a substantial lag, and as a result the available data are incomplete or insufficient. In this context, real-time forecasting models have demonstrated that they are a useful way of selecting the signals obtained from the relevant monthly indicators and combining them into an overall vision of developments in GDP growth. Noteworthy in this field is the methodology developed by Camacho and Pérez Quirós (2008) and implemented in the EURO-STING model, which incorporates various relevant pieces of information for forecasting euro area GDP as this information becomes available. The EURO-STING and other related models have focused on forecasting changes in euro area GDP from an aggregate or direct perspective. Alternatively, however, an estimate of the growth in activity can be obtained indirectly by aggregating the forecasts for its different components. One of the further advantages of this approach is that it also provides very useful information for the conjunctural analysis since it evaluates separately the performance of the main sectors of production, of the expenditure components and of the various countries which make up the euro area. This is particularly important at times of change of cycle or of high uncertainty such as at present, when indicators, including economic agents’ sentiment, which are published with a longer lead and, consequently, are a basic part of forecasts, and those which reflect the actual performance of various sectors or quantitative indicators, on which the National Accounts are based, may provide a different vision of developments in activity at aggregate level. In this article a new forecasting model for euro area GDP growth is proposed, namely, EUROSTING DISAGGREGATED, which combines the direct and indirect approaches. Firstly, models are developed for each GDP component from the perspective of production, expenditure and the various countries. The forecasts obtained are aggregated according to the National Accounts rules in order to obtain three independent indirect estimates of quarter-on-quarter euro area GDP growth, to which the direct estimate obtained with the EURO-STING model is added [see Camacho and Pérez-Quirós (2008 and 2010)]. Next, these forecasts are mixed efficiently, taking into account their relative accuracy over time so as to extract a sign of activity growth in the most precise way. This methodology develops a broad enough model for the orderly inclusion of relevant information on the euro area and which, at the same time, is flexible since it efficiently combines four different approximations of GDP growth. According to the historic evaluation of its predictive power, on average, EURO-STING DISAGGREGATED produces the most exact forecasts of GDP growth in the euro area for the period 2004-2011 of all the alternatives considered, furthermore it is the model which captures best both the depth of the recent crisis and the subsequent recovery rate. The structure of the remainder of the article is as follows: the main indicators used for analysing economic activity in the euro area, as well as some of the problems faced by short-term forecasting in the recent period are described in section two; the model is outlined in section three; its predictive power and functioning as a forecasting tool at the Banco de España are assessed in section four; and the conclusions are included in the last section.