Macroeconomic forecasting in the euro area using predictive
combinations of DSGE models

J 2023

Macroeconomic forecasting in the euro area using predictive combinations of DSGE models

ČAPEK, Jan, Jesús CRESPO CUARESMA, Niko HAUZENBERGER and Vlastimil REICHEL

Basic information

Original name

Macroeconomic forecasting in the euro area using predictive combinations of DSGE models

Authors

ČAPEK, Jan (203 Czech Republic, guarantor, belonging to the institution), Jesús CRESPO CUARESMA (724 Spain, belonging to the institution), Niko HAUZENBERGER (40 Austria, belonging to the institution) and Vlastimil REICHEL (203 Czech Republic, belonging to the institution)

Edition

INTERNATIONAL JOURNAL OF FORECASTING, NETHERLANDS, ELSEVIER, 2023, 0169-2070

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

50202 Applied Economics, Econometrics

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 7.900 in 2022

RIV identification code

RIV/00216224:14560/23:00134014

Organization unit

Faculty of Economics and Administration

DOI

http://dx.doi.org/10.1016/j.ijforecast.2022.09.002

UT WoS

001075115800001

Keywords in English

Forecasting; Model averaging; Prediction pooling; DSGE models; Macroeconomic variables

Abstract

V originále

We provide a comprehensive assessment of the predictive power of combinations of dynamic stochastic general equilibrium (DSGE) models for GDP growth, inflation, and the interest rate in the euro area. We employ a battery of static and dynamic pooling weights based on Bayesian model averaging principles, prediction pools, and dynamic factor representations, and entertain six different DSGE specifications and five prediction weighting schemes. Our results indicate that exploiting mixtures of DSGE models produces competitive forecasts compared to individual specifications for both point and density forecasts over the last three decades. Although these combinations do not tend to systematically achieve superior forecast performance, we find improvements for particular periods of time and variables when using prediction pooling, dynamic model averaging, and combinations of forecasts based on Bayesian predictive synthesis.

Links

GA17-14263S, research and development project

Name: Dynamické průměrování předpovědí makroekonomických modelů

Investor: Czech Science Foundation

GA21-10562S, research and development project

Name: O časově proměnné prediktivní schopnosti teoretických a empirických makroekonomických modelů

Investor: Czech Science Foundation

Files attached

1-s2.0-S0169207022001224-main.pdf

Citovat

ČAPEK, Jan, Jesús CRESPO CUARESMA, Niko HAUZENBERGER and Vlastimil REICHEL. Macroeconomic forecasting in the euro area using predictive combinations of DSGE models. INTERNATIONAL JOURNAL OF FORECASTING. NETHERLANDS: ELSEVIER, 2023, vol. 39, No 4, p. 1820-1838. ISSN 0169-2070. Available from: https://dx.doi.org/10.1016/j.ijforecast.2022.09.002.

@article{2227365,
   author = {Čapek, Jan and Crespo Cuaresma, Jesús and Hauzenberger, Niko and Reichel, Vlastimil},
   article_location = {NETHERLANDS},
   article_number = {4},
   doi = {http://dx.doi.org/10.1016/j.ijforecast.2022.09.002},
   keywords = {Forecasting; Model averaging; Prediction pooling; DSGE models; Macroeconomic variables},
   language = {eng},
   issn = {0169-2070},
   journal = {INTERNATIONAL JOURNAL OF FORECASTING},
   note = {in press},
   title = {Macroeconomic forecasting in the euro area using predictive combinations of DSGE models},
   url = {https://www.sciencedirect.com/science/article/pii/S0169207022001224},
   volume = {39},
   year = {2023}
}

TY  - JOUR
ID  - 2227365
AU  - Čapek, Jan - Crespo Cuaresma, Jesús - Hauzenberger, Niko - Reichel, Vlastimil
PY  - 2023
TI  - Macroeconomic forecasting in the euro area using predictive combinations of DSGE models
JF  - INTERNATIONAL JOURNAL OF FORECASTING
VL  - 39
IS  - 4
SP  - 1820
EP  - 1820
PB  - ELSEVIER
SN  - 01692070
N1  - in press
KW  - Forecasting
KW  - Model averaging
KW  - Prediction pooling
KW  - DSGE models
KW  - Macroeconomic variables
UR  - https://www.sciencedirect.com/science/article/pii/S0169207022001224
N2  - We provide a comprehensive assessment of the predictive power of combinations of dynamic stochastic general equilibrium (DSGE) models for GDP growth, inflation, and the interest rate in the euro area. We employ a battery of static and dynamic pooling weights based on Bayesian model averaging principles, prediction pools, and dynamic factor representations, and entertain six different DSGE specifications and five prediction weighting schemes. Our results indicate that exploiting mixtures of DSGE models produces competitive forecasts compared to individual specifications for both point and density forecasts over the last three decades. Although these combinations do not tend to systematically achieve superior forecast performance, we find improvements for particular periods of time and variables when using prediction pooling, dynamic model averaging, and combinations of forecasts based on Bayesian predictive synthesis.
ER  -

ČAPEK, Jan, Jesús CRESPO CUARESMA, Niko HAUZENBERGER and Vlastimil REICHEL. Macroeconomic forecasting in the euro area using predictive combinations of DSGE models. \textit{INTERNATIONAL JOURNAL OF FORECASTING}. NETHERLANDS: ELSEVIER, 2023, vol.~39, No~4, p.~1820-1838. ISSN~0169-2070. Available from: https://dx.doi.org/10.1016/j.ijforecast.2022.09.002.

Detailed Information on Publication Record