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Forecasting Economic Aggregates by Disaggregates
Hendry, David F; Hubrich, Kirstin - C.E.P.R. Discussion Papers - 2006
We explore whether forecasting an aggregate variable using information on its disaggregate components can improve the prediction mean squared error over first forecasting the disaggregates and then aggregating those forecasts, or, alternatively, over using only lagged aggregate information in...
Persistent link: https://www.econbiz.de/10005123796
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Examining the Success of the Central Banks in Inflation Targeting Countries: The Dynamics of Inflation Gap and the Institutional Characteristics
Ardakani, Omid; Kishor, N. Kundan - Volkswirtschaftliche Fakultät, … - 2014
This paper analyzes the performance of central banks in 27 inflation targeting countries by examining their success in achieving their explicit inflation targets. For this purpose, we decompose the inflation gap, the difference between actual inflation and inflation target, into predictable and...
Persistent link: https://www.econbiz.de/10011113487
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How Useful is Bagging in Forecasting Economic Time Series? A Case Study of US CPI Inflation
Inoue, Atsushi; Kilian, Lutz - C.E.P.R. Discussion Papers - 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...
Persistent link: https://www.econbiz.de/10005661494
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Do disaggregated CPI data improve the accuracy of inflation forecasts?
Ibarra, Raul - In: Economic Modelling 29 (2012) 4, pp. 1305-1313
In this paper, we evaluate the role of using consumer price index (CPI) disaggregated data to improve the accuracy of inflation forecasts. Our forecasting approach is based on extracting the factors from the subcomponents of the CPI at the highest degree of disaggregation. The data set contains...
Persistent link: https://www.econbiz.de/10010573296
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Oracle Efficient Estimation and Forecasting with the Adaptive LASSO and the Adaptive Group LASSO in Vector Autoregressions
Kock, Anders Bredahl; Callot, Laurent A.F. - School of Economics and Management, University of Aarhus - 2012
We show that the adaptive Lasso (aLasso) and the adaptive group Lasso (agLasso) are oracle efficient in stationary vector autoregressions where the number of parameters per equation is smaller than the number of observations. In particular, this means that the parameters are estimated...
Persistent link: https://www.econbiz.de/10010851261
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Forecasting Austrian Inflation
Moser, Gabriel; Rumler, Fabio; Scharler, Johann - Oesterreichische Nationalbank - 2004
In this paper we apply factor models proposed by Stock and Watson [18] and VAR and ARIMA models to generate 12-month … accuracy can be further improved by combining the information contained in factor and VAR models for some indices. With respect …
Persistent link: https://www.econbiz.de/10005802644
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Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?
Manzan, Sebastiano; Zerom, Dawit - Volkswirtschaftliche Fakultät, … - 2009
no predictability. In this paper, we expand the scope of inflation predictability and explore whether macroeconomic …, housing starts, and the term spread provide significant out-of-sample predictability for the distribution of core inflation … research shows that macroeconomic indicators do not add much to the predictability of the future mean inflation. This paper …
Persistent link: https://www.econbiz.de/10005836192
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Forecasting German Key Macroeconomic Variables Using Large Dataset Methods
Pirschel, Inske; Wolters, Maik - Institut für Weltwirtschaft (IfW) - 2014
of the different models, respectively. We find that overall the large Bayesian VAR and the Bayesian factor augmented VAR …
Persistent link: https://www.econbiz.de/10010887025
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Inflation forecasting using dynamic factor analysis. SAS 4GL programming approach
Jêdrzejczyk, Adam - Zakład Ekonometrii Stosowanej, Szkoła Główna … - 2012
The purpose of this article is to introduce an original macro code written in SAS 4GL. This macro is used to automate the process of forecasting with dynamic factor analysis. Automation of the process helps to save significant amounts of time and effort for the researcher. It also enables to...
Persistent link: https://www.econbiz.de/10010700705
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Forecasting inflation with dynamic factor model – the case of Poland
Kotlowski, Jacek - Zakład Ekonometrii Stosowanej, Szkoła Główna … - 2008
model, VAR model and the model with leading indicator from the business survey. We have used 92 monthly time series from the …
Persistent link: https://www.econbiz.de/10005113479