Real Time Monitoring World GDP and Trade

By Roberto Golinelli and Giuseppe Parigi

The assessment of current and future world economic developments is a central concern for international financial institutions, governments and central banks. The recent failures in assessing present and future global economic developments has called for frequent forecast updates, all the more necessary in a rapidly changing environment. However, updating predictions may be very complicated, as it implies the maintenance and estimation of large models, as well as a very complex database, whose dimension is increasing due to the greater importance of emerging countries, such as Brazil, Russia, India and China (the so called BRIC).

For the group of advanced countries (essentially the G7 countries), reliable methods are available to exploit the timely information content of monthly cyclical indicators which can be used for the prediction of the more comprehensive - but delayed - releases of quarterly National Account data (GDP and its main components; see - among the others - Baffigi et al., 2004 for bridge models; Stock and Watson, 2006, for factor models; Clements and Galvao, 2008, for MIDAS regressions; Camacho and Perez-Quiros, 2010, for approximate Kalman filter models).

For emerging economies the situation is completely different, as the literature on short term forecasting is still in its infancy. Recent contributions are concentrated on the extrapolation of world economic trends  through either the G7 or the OECD group of countries (see Arouba et al., 2010, Kose et al.,2008, Golinelli and Parigi, 2007, and Chauvet and Yu, 2006). Matheson (2010), and Borin et al. (2102) are first attempts to enlarge the scope of the analysis, as they consider not only the advanced countries but a set of 19 developing countries (the first), and the Asian economies plus Brazil and Russia (the second). In both analyses; the target variable is world GDP, while world trade developments are completely ignored. In all cases, all the contributions in the literature, both recent and older, are based on ex post latest available data, with no explicit consideration of real time issues, which may be very important especially for trade data.

The aim of this paper is to devise an easy, semi-automatic, procedure to obtain a monthly assessment of global, short run  perspectives for quarterly world GDP and trade by combining BRIC and developed countries statistical information. While the econometric tools used in this paper are not new for the analysis of advanced countries, this is the first time to our knowledge that monthly forecasts of GDP and trade growth rates are computed both for advanced and emerging countries on the basis of a fully real-time database made of more than 5 thousands time series.

We estimate a quarterly bridge model for 10 countries (France, Italy, Germany, Japan, UK, US, Brazil, Russia, India, and China) for each month over the period March 2006-May 2012 (i.e. 75 times), using real time data. Each country model includes seven equations: domestic demand in real terms and prices, imports in volume, and exports prices (based only on short run monthly country-specific soft and hard indicators), exports in volume and import prices (based on the imports in volume and the export prices estimated from the other countries' bridge models) and the GDP identity in real terms.
The GDP forecasts from the country-specific models are finally aggregated, to obtain an estimate of the world GDP. Similarly, the exports and imports country-specific forecasts are aggregated into the two definitions of the world trade, from the exports and the imports side, respectively.

The last step allows to assess the forecasting ability of the system of country-specific bridge models as a whole, over an horizon of up to four quarters ahead. In line with previous findings, we find that the use of indicator information can improve the forecasting ability of world GDP one-quarter ahead over benchmark models by about 30%. An even larger improvement of about 40-45% is obtained for world trade, confirming the importance of considering simultaneously the short run information in all countries.