Inflation in the European Monetary Union is measured by the Harmonized Indices of Consumer Prices (HICP) and it can be analysed by breaking down the aggregate index in two different ways. One refers to the breakdown into price indexes corresponding to big groups of markets throughout the European countries and another considers the HICP by countries. Both disaggregations are of interest because in each one, the component prices are not fully cointegrated, having more than one common factor in their trends. The paper shows that the breakdown by group of markets improves the European inflation forecasts and constitutes a framework in which general and specific indicators can be introduced for further improvements.

Differencing is a very popular stationary transformation for series with stochastic trends. Moreover, when the differenced series is heteroscedastic, authors commonly model it using an ARMA-GARCH model. The corresponding ARIMA-GARCH model is then used to forecast future values of the original series. However, the heteroscedasticity observed in the stationary transformation should be generated by the transitory and/or the long-run component of the original data. In the former case, the shocks to the variance are transitory and the prediction intervals should converge to homoscedastic intervals with the prediction horizon.We show that, in this case, the prediction intervals constructed from the ARIMA-GARCH models could be inadequate because they never converge to homoscedastic intervals. All of the results are illustrated using simulated and real time series with stochastic levels.Publicad

In this article we propose a methodology for estimating the GDP of a country’s different regions, providing quarterly profiles for the annual official observed data. Thus the article offers a new instrument for short-term monitoring that allows the analysts to quantify the degree of synchronicity among regional business cycles. Technically, we combine time-series models with benchmarking methods to process short-term quarterly indicators and to estimate quarterly regional GDPs ensuring their temporal and transversal consistency with the National Accounts data. The methodology addresses the issue of nonadditivity, explicitly taking into account the transversal constraints imposed by the chain-linked volume indexes used by the National Accounts, and provides an efficient combination of structural as well as short-term information. The methodology is illustrated by an application to the Spanish economy, providing real-time quarterly GDP estimates, that is, with a minimum compilation delay with respect to the national quarterly GDP. The estimated quarterly data are used to assess the existence of cycles shared among the Spanish regions.

This paper focuses on the provision of consistent forecasts for an aggregate economic indicator, such as a consumer price index and its components. The procedure developed is a disaggregated approach based on single-equation models for the components, which take into account the stable features that some components share, such as a common trend and common serial correlation. Our procedure starts by classifying a large number of components based on restrictions from common features. The result of this classification is a disaggregation map, which may also be useful in applying dynamic factors, defining intermediate aggregates or formulating models with unobserved components. We use the procedure to forecast inflation in the Euro area, the UK and the US. Our forecasts are significantly more accurate than either a direct forecast of the aggregate or various other indirect forecasts.Antoni Espasa acknowledges financial support from Ministerio de Educacin y Ciencia, proyect ECO 2009-0810