Uncertainty And Risk Analysis Of Macroeconomic Forecasts: Fan Charts Revisited

Since 1996 the Bank of England (BoE) has been publishing estimates of probability distribution of the future outcomes of inflation and output growth. These density forecasts, known as "fan charts", became very popular with other central banks (e.g. Riskbank) as a tool to quantify uncertainties and risks of conditional point forecasts. The BoE's procedure is mainly a methodology to determine the distribution of a linear combination of independent random variables. In this article we propose an alternative methodology that addresses two issues with the BoE procedure that may affect the estimation of the densities. The first issue relates to a statistical shortcut taken by the BoE that implicitly considers that the mode of the linear combination of random variables is the (same) linear combination of the modes of those variables. The second issue deals with the assumption of independence, which may be restrictive. An illustration of the new methodology is presented and its results compared with the BoE approach.

Hunting for Rare Romances in the Canary Islands

"What is a Rare Romance? Diego Catalán published in 1959 an article with this same title (1959a:445-77), dedicated to the Portuguese ballad tradition, in which he brought out the importance of that tradition for the knowledge of certain romances which because of their rarity were overlooked or lived in fragmented form in the oral life of other Hispanic traditions. Four romances were studied there, four very powerful examples of how an oral text, a single version, can be the key to the correct interpretation of several romances which tradition has not preserved very well. Here we should like to call attention to the Canarian tradition as one of the most extraordinary in its preservation of romances that are extremely rare in modern oral tradition."--Opening paragraph

Determining the number of factors in approximate factor models with global and group-specific factors

For an approximate factor model, in a static representation, with a common component comprising global factors and factors specific to groups of variables, the consistency of the principal components estimator is discussed. An extension of the well known Bai and Ng criteria is proposed for determining the number of global and group-specific factors. The consistency of the suggested criteria is established and the small sample properties are assessed through Monte Carlo simulations. As an empirical illustration, the proposed criteria is applied to estimate the number of global and country-specific macroeconomic factors for the major euro area countries.

Forecasting Using Targeted Diffusion Indexes

The simplicity of the standard diffusion index model of Stock and Watson has certainly contributed to its success among practitioners resulting in a growing body of literature on factor-augmented forecasts. However, as pointed out by Bai and Ng, the ranked factors considered in the forecasting equation depend neither on the variable to be forecasted nor on the forecasting horizon. We propose a refinement of the standard approach that retains the computational simplicity while coping with this limitation. Our approach consists of generating a weighted average of all the principal components, the weights depending both on the eigenvalues of the sample correlation matrix and on the covariance between the estimated factor and the targeted variable at the relevant horizon. This "targeted diffusion index" approach is applied to US data and the results show that it outperforms considerably the standard approach in forecasting several major macroeconomic series. Moreover, the improvement is more significant in the final part of the forecasting evaluation period.