C22 Single Equation Models; Single Variables: Time-Series Models

July 1, 2009

In addition to quantitative assessment of economic growth using econometric models, business cycle analyses have been proved to be helpful to practitioners in order to assess current economic conditions or to anticipate upcoming fluctuations. In this paper, we focus on the acceleration cycle in the euro area, namely the peaks and troughs of the growth rate which delimitate the slowdown and acceleration phases of the economy. Our aim is twofold: First, we put forward a reference turning point chronology of this cycle on a monthly basis, based on gross domestic product and industrial production index. We consider both euro area aggregate level and country specific cycles for the six main countries of the zone. Second, we come up with a new turning point indicator, based on business surveys carefully watched by central banks and short-term analysts, in order to follow in real-time the fluctuations of the acceleration cycle.

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September 1, 2009

We use TVP models and real-time data to describe the evolution of the leading properties of the yield spread for output growth in five European economies and in the US. We evaluate the predictive performance of benchmark term-structure models and identify structural breaks in the marginal processes of term spreads and government bond yields to shed light on the characteristics of inflation risk incorporated in bond markets and inflation expectations. Econometric analysis shows that: (i) the marginal predictive content of the term spread is not always significant over time and across countries; (ii) to some extent, the term spread contributes to the forecast performance of simple growth regressions in Europe, not in the US; (iii) inflation risk exhibits instability and generally declines over time. In some countries, among which the US, this decline is accompanied by vanishing leading properties.

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January 1, 2005

The Paper presents a model in which the exogenous money supply causes changes in the inflation rate and the output growth rate. While inflation and growth rate changes occur simultaneously, the inflation acts as a tax on the return to human capital and in this sense induces the growth rate decrease. Shifts in the model’s credit sector productivity cause shifts in the income velocity of money that can break the otherwise stable relation between money, inflation, and output growth. Applied to two accession countries, Hungary and Poland, a VAR system is estimated for each that incorporates endogenously determined multiple structural breaks. Results indicate Granger causality positively from money to inflation and negatively from inflation to growth for both Hungary and Poland, as suggested by the model, although there is some feedback to money for Poland. Three structural breaks are found for each country that are linked to changes in velocity trends, and to the breaks found in the other country.

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October 1, 2005

This paper explores the usefulness of bagging methods in forecasting economic time series from linear multiple regression models. We focus on the widely studied question of whether the inclusion of indicators of real economic activity lowers the prediction mean-squared error of forecast models of US consumer price inflation. We study bagging methods for linear regression models with correlated regressors and for factor models. We compare the accuracy of simulated out-of-sample forecasts of inflation based on these bagging methods to that of alternative forecast methods, including factor model forecasts, shrinkage estimator forecasts, combination forecasts and Bayesian model averaging. We find that bagging methods in this application are almost as accurate or more accurate than the best alternatives. Our empirical analysis demonstrates that large reductions in the prediction mean squared error are possible relative to existing methods, a result that is also suggested by the asymptotic analysis of some stylized linear multiple regression examples.

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October 1, 2005

We document the empirical properties of revisions to major macroeconomic variables in the United States. Our findings suggest that they do not satisfy simple desirable statistical properties. In particular, we find that these revisions do not have a zero mean, which indicates that the initial announcements by statistical agencies are biased. We also find that the revisions are quite large compared to the original variables and they are predictable using the information set at the time of the initial announcement, which means that the initial announcements of statistical agencies are not rational forecasts. We also provide evidence that professional forecasters ignore this predictability.

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October 1, 2005

National accounts statistics undergo a process of revisions over time because of the accumulation of information and, less frequently, of deeper changes, as new definitions, new methodologies etc. are implemented. In this paper we try to characterise the revision process of the data of Italian GDP as published by the national statistical office (ISTAT) in the stream of the noise models literature. The analysis shows that this task can be better accomplished by concentrating on the growth rates of the data instead of the levels. Another issue tackled in the paper concerns the informative content of the preliminary releases vis a vis an intermediate vintage supposed to embody all statistical information (or no longer revisable as far as purely statistical changes are concerned) and the latest vintage of the data, supposed to be the definitive one. The analysis of the news models in differences is based on the comparison of the forecasting performance of the preliminary releases with that of a number of one step ahead forecasts computed from alternative models, ranging from very simple univariate to multivariate specifications based on indicators (bridge models). Results show that, for the intermediate vintage, the preliminary version is the better forecast, while the latest vintage, which embodies statistical as well as definitional revisions, may be better characterised by considering both the preliminary version and the bridge models forecasts.

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