Understanding and forecasting aggregate and disaggregate price dynamics

The issue of forecast aggregation is to determine whether it is better to forecast a series directly or instead construct forecasts of its components and then sum these component forecasts. Notwithstanding some underlying theoretical results, it is generally accepted that forecast aggregation is an empirical issue. Empirical results in the literature often go unexplained. This leaves forecasters in the dark when confronted with the option of forecast aggregation. We take our empirical exercise a step further by considering the underlying issues in more detail. We analyse two price datasets, one for the United States and one for the Euro Area, which have distinctive dynamics and provide a guide to model choice. We also consider multiple levels of aggregation for each dataset. The models include an autoregressive model, a factor augmented autoregressive model, a large Bayesian VAR and a time-varying model with stochastic volatility. We find that once the appropriate model has been found, forecast aggregation can significantly improve forecast performance. These results are robust to the choice of data transformation. JEL Classification: E17, E31, C11, C38Aggregation, forecasting, inflation

Are sectoral stock prices useful for predicting euro area GDP?

This paper evaluates how well sectoral stock prices forecast future economic activity compared to traditional predictors such as the term spread, dividend yield, exchange rates and money growth. The study is applied to euro area financial asset prices and real economic growth, covering the period 1973 to 2006. The paper finds that the term spread is the best predictor of future growth in the period leading up to the introduction of Monetary Union. After 1999, however, sectoral stock prices in general provide more accurate forecasts than traditional asset price measures across all forecast horizons. JEL Classification: C52, C53asset prices, forecasting models

Comparing alternative predictors based on large-panel factor models

This paper compares the predictive ability of the factor models of Stock and Watson (2002) and Forni, Hallin, Lippi, and Reichlin (2005) using a "large" panel of US macroeconomic variables. We propose a nesting procedure of comparison that clarifies and partially overturns the results of similar exercises in the literature. As in Stock and Watson (2002), we find that effciency improvements due to the weighting of the idiosyncratic components do not lead to significant more accurate forecasts. In contrast to Boivin and Ng (2005), we show that the dynamic restrictions imposed by the procedure of Forni, Hallin, Lippi, and Reichlin (2005) are not harmful for predictability. Our main conclusion is that for the dataset at hand the two methods have a similar performance and produce highly collinear forecasts. JEL Classification: C31, C52, C53Factor models, forecasting, Large Cross-Section

Federal Reserve Information during the Great Moderation

Using data from the period 1970-1991, Romer and Romer (2000) showed that Federal Reserve forecasts of inflation and output were superior to those provided by commercial forecasters. In this paper, we show that this superior forecasting performance deterio- rated after 1991. Over the decade 1992-2001, the superior forecast accuracy of the Fed held only over a very short time horizon and was limited to its forecasts of inflation. In addition, the performance of both the Fed and the commercial forecasters in pre- dicting inflation and output, relative to that of “naive” benchmark models, dropped remarkably during this period.

The Measurement of Rank Mobility

In this paper we investigate the problem of measuring social mobility when the social status of individuals is given by their rank. In order to sensibly represent the rank mobility of subgroups within a given society, we address the problem in terms of partial permutation matrices which include standard (“global”) matrices as a special case. We first provide a characterization of a partial ordering on partial matrices which, in the standard case of global matrices, coincides with the well-known “concordance” ordering. We then provide a characterization of an index of rank mobility based on partial matrices and show that, in the standard case of comparing two global matrices, it is equivalent to Spearman’s index.Mobility measurement, Concordance, Partial matrices, Sperman's index.

Macroeconomic forecasting and structural change

The aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts. We produce real time out-of-sample forecasts for inflation, the unemployment rate and the interest rate using a Time-Varying Coefficients VAR with Stochastic Volatility (TV-VAR) for the US. The model generates accurate predictions for the three variables. In particular for inflation the TV-VAR outperforms, in terms of mean square forecast error, all the competing models: fixed coefficients VARs, Time-Varying ARs and the na¨ıve random walk model. These results are also shown to hold over the most recent period in which it has been hard to forecast inflation. JEL Classification: C32, E37, E47forecasting, inflation, stochastic volatility, Time Varying Vector Autoregression

Can we declare military Keynesianism dead?

This paper empirically tests the Keynesian hypothesis that government defence spending positively impacts on aggregate output, by using a long run equilibrium model for the US and the UK. Our contribution, with respect to previous works, is twofold. First, our inferences are adjusted for structural breaks exhibited by the data concerning fiscal and monetary variables. Second, we take into account different dynamics between defence spending on aggregate output, showing that the results are sensitive to sub-sample choices. Though the estimated elasticities in both countries show a lack of significance in the more recent years of the sample, defence spending priorities addressed to international security may revitalize pro-cyclical effects in the UK, by an industrial policy of defence shared with the EU members.Military spending, Output, Long run models

The Italian block of the ESCB multi-country model

This paper documents the structure, estimation and simulation properties of the Italian block of the ESCB-multi-country model (MCM). The model is used regularly as an input into Eurosystem projection exercises and, to a lesser extent, in simulation analysis. The specification of the Italian model follows closely that of the Area-Wide Model (AWM) and indeed the other MCM country blocks (in terms of specification and accounting framework). The MCM is a quarterly estimated structural macroeconomic model that treats the economy in a relatively closed manner. It has a long-run classical equilibrium with a vertical Phillips curve but with some short-run frictions in price/wage setting and factor demands. Consequently, activity is demand-determined in the short-run but supply-determined in the longer run with employment having converged to a level consistent with an exogenously given level of equilibrium unemployment. The precise properties of the model are illustrated using a number of standard variant simulations. JEL Classification: C3, C5, E1, E2Italy, Macro-econometric Modelling

Scaling in the Lattice Gas Model

A good quality scaling of the cluster size distributions is obtained for the Lattice Gas Model using the Fisher's ansatz for the scaling function. This scaling identifies a pseudo-critical line in the phase diagram of the model that spans the whole (subcritical to supercritical) density range. The independent cluster hypothesis of the Fisher approach is shown to describe correctly the thermodynamics of the lattice only far away from the critical point.Comment: 4 pages, 3 figure