C22

Single Equation Models; Single Variables: Time-Series Models

Autoregressions in Small Samples, Priors about Observables and Initial Conditions

JEL codes: 
C11, C22, C32
Version Date: 
Sep 2010
Abstract: 

We propose a benchmark prior for the estimation of vector autoregressions: a prior about initial growth rates of the modeled series.

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Identification of slowdowns and accelerations for the euro area economy

JEL codes: 
C22, C52, E32
Version Date: 
Jun 2009
Abstract: 

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.

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GDP Growth Predictions through the Yield Spread. Time-Variation and Structural Breaks

JEL codes: 
C22, C32, C53, E37, E43, E47
Version Date: 
Feb 2011
Author/s: 
Abstract: 

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 over the last decades and until the third quarter of 2010.

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Granger Causality of the Inflation-Growth Mirror in Accession Countries

JEL codes: 
C22, E31, O42
Version Date: 
Dec 2004
Author/s: 
Abstract: 

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.

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Short-Run Italian GDP Forecasting and Real-Time Data

JEL codes: 
C22, C53, C82, E10
Version Date: 
Sep 2005
Abstract: 

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.

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Data Revisions Are Not Well-Behaved

JEL codes: 
C22, C53, C82
Version Date: 
Sep 2005
Abstract: 

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.

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How Useful is Bagging in Forecasting Economic Time Series? A Case Study of US CPI Inflation

JEL codes: 
C22, C52, C53
Version Date: 
Sep 2005
Author/s: 
Abstract: 

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.

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