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on Forecasting |
| By: | Assenmacher-Wesche , Katrin (Swiss National Bank); Pesaran, and M. Hashem (University of Cambridge) |
| Abstract: | This paper uses vector error correction models of Switzerland for forecasting output, inflation and the short-term interest rate. It considers three different ways of dealing with forecast uncertainties. First, it investigates the effect on forecasting performance of averaging over forecasts from different models. Second, it considers averaging forecasts from different estimation windows. It is found that averaging over estimation windows is at least as effective as averaging over different models and both complement each other. Third, it examines whether using weighting schemes from the machine learning literature improves the average forecast. Compared to equal weights the effect of alternative weighting schemes on forecast accuracy is small in the present application. |
| Keywords: | Bayesian model averaging; choice of observation window; longrun structural vector autoregression |
| JEL: | C32 C53 |
| Date: | 2008–04–29 |
| URL: | http://d.repec.org/n?u=RePEc:ris:snbwpa:2008_003&r=for |
| By: | Clive Bowsher; Roland Meeks |
| Abstract: | The class of Functional Signal plus Noise (FSN) models is introduced that provides a new, general method for modelling and forecasting time series of economic functions. The underlying, continuous economic function (or 'signal') is a natural cubic spline whose dynamic evolution is driven by a cointegrated vector autoregression for the ordinates (or 'y-values') at the knots of the spline. The natural cubic spline provides flexible cross-sectional fit and results in a linear, state space model. This FSN model achieves dimension reduction, provides a coherent description of the observed yield curve and its dynamics as the cross-sectional dimension N becomes large, and can feasibly be estimated and used for forecasting when N is large. The integration and cointegration properties of the model are derived. The FSN models are then applied to forecasting 36-dimensional yield curves for US Treasury bonds at the one month ahead horizon. The method consistently outperforms the Diebold and Li (2006) and random walk forecasts on the basis of both mean square forecast error criteria and economically relevant loss functions derived from the realised profits of pairs trading algorithms. The analysis also highlights in a concrete setting the dangers of attempts to infer the relative economic value of model forecasts on the basis of their associated mean square forecast errors. |
| Keywords: | FSN-ECM models, functional time series, term structure, forecasting interest rates, natural cubic spline, state space form. |
| JEL: | C33 C51 C53 E47 G12 |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:sbs:wpsefe:2008fe24&r=for |
| By: | Stéphane Dées (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.); Matthias Burgert (Humboldt University, Berlin and ENSAE. Address - ENSAE, 3, avenue Pierre Larousse, 92245 Malakoff Cedex, France.) |
| Abstract: | In a globalised world economy, global factors have become increasingly important to explain trade-flows at the expense of country-specifc determinants. This paper shows empirically the superiority of direct forecasting methods, in which world trade is directly forecasted at the aggregate levels, relative to "bottom-up" approaches, where world trade results from an aggregation of country-specifc forecasts. Factor models in particular prove rather accurate, where the factors summarise large-scale datasets relevant in the determination of trade-flows. JEL Classification: C53, C32, E37, F17. |
| Keywords: | World trade, Factor models, Forecasts, Time series models. |
| Date: | 2008–03 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20080882&r=for |
| By: | Amstad, Marlene (Swiss National Bank); Fischer, Andreas (CEPR) |
| Abstract: | Are weekly inflation forecasts informative? Although several central banks review and discuss monetary policy issues on a bi-weekly basis, there have been few attempts by analysts to construct systematic estimates of core inflation that supports such a decision-making schedule. The timeliness of news releases and macroeconomic revisions are recognized to be an important information source in real-time estimation. We incorporate real-time information from macroeconomic releases and revisions into our weekly updates of monthly Swiss core inflation using a common factor procedure. The weekly estimates for Swiss core inflation find that it is worthwhile to update the forecast at least twice a month. |
| Keywords: | Inflation; Common Factors; Sequential Information Flow |
| JEL: | E52 E58 |
| Date: | 2008–01–29 |
| URL: | http://d.repec.org/n?u=RePEc:ris:snbwpa:2008_005&r=for |
| By: | Maximo Camacho (Universidad de Murcia); Gabriel Perez-Quiros (Banco de España) |
| Abstract: | We propose a model to compute short-term forecasts of the Euro area GDP growth in real-time. To allow for forecast evaluation, we construct a real-time data set that changes for each vintage date and includes the exact information that was available at the time of each forecast. In this context, we provide examples that show how data revisions and data availability affect point forecasts and forecast uncertainty. |
| Keywords: | business cycles, output growth, time series |
| JEL: | E32 C22 E27 |
| Date: | 2008–04 |
| URL: | http://d.repec.org/n?u=RePEc:bde:wpaper:0807&r=for |