This paper develops a set of time series models to provide short-term forecasts (6 to 18 months ahead) of international trade both at the global level and for selected regions. Our results compare favourably to other forecasts, notably by the International Monetary Fund, as measured by standard...

This paper proposes a simple procedure to obtain monthly assessments of short-run perspectives for quarterly world GDP and trade. It combines emerging and advanced countries' high frequency information to explain quarterly national accounts variables through bridge models. The union of all...

This paper develops a set of time series models to provide short-term forecasts (6 to 18 months ahead) of international trade both at the global level and for selected regions. Our results compare favourably to other forecasts, notably by the International Monetary Fund, as measured by standard...

Common approaches to test for the economic value of directional forecasts are based on the classical Chi-square test for independence, Fisher’s exact test or the Pesaran and Timmerman (1992) test for market timing. These tests are asymptotically valid for serially independent observations....

Forecasting the world economy is a difficult task given the complex interrelationships within and across countries. This paper proposes a number of approaches to forecast short-term changes in selected world economic variables and aims, first, at ranking various forecasting methods in terms of...

In a globalised world economy, global factors have become increasingly important to explain trade flows at the expense of country-specific determinants. This paper shows empirically the superiority of direct forecasting methods, in which world trade is directly forecasted at the aggregate...

This paper develops a set of time series models to provide short-term forecasts (6 to 18 months ahead) of international trade both at the global level and for selected regions. Our results compare favourably to other forecasts, notably by the International Monetary Fund, as measured by standard...

We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are designed to account for changes in customer behaviour and in utility production efficiencies. The model is periodic: it consists of different equations and different parameters for...

Long-term forecasts are of key importance for the car industry due to the lengthy period of time required for the development and production processes. With this in mind, this paper proposes new multivariate models to forecast monthly car sales data using economic variables and Google online...

ARFIMAX models are applied in estimating the intra-day realized volatility of the CAC40 and DAX30 indices. Volatility clustering and asymmetry characterize the logarithmic realized volatility of both indices. ARFIMAX model with time-varying conditional heteroscedasticity is the best performing...