Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP

41 Pages Posted: 11 Mar 2009

See all articles by Vladimir Kuzin

Vladimir Kuzin

German Institute for Economic Research (DIW Berlin)

Massimiliano Giuseppe Marcellino

European University Institute; European University Institute - Robert Schuman Centre for Advanced Studies (RSCAS); Bocconi University - Department of Economics; Centre for Economic Policy Research (CEPR)

Christian Schumacher

Deutsche Bundesbank

Multiple version iconThere are 2 versions of this paper

Date Written: March 2009

Abstract

This paper discusses pooling versus model selection for now- and forecasting in the presence of model uncertainty with large, unbalanced datasets. Empirically, unbalanced data is pervasive in economics and typically due to different sampling frequencies and publication delays. Two model classes suited in this context are factor models based on large datasets and mixed-data sampling (MIDAS) regressions with few predictors. The specification of these models requires several choices related to, amongst others, the factor estimation method and the number of factors, lag length and indicator selection. Thus, there are many sources of mis-specification when selecting a particular model, and an alternative could be pooling over a large set of models with different specifications. We evaluate the relative performance of pooling and model selection for now- and forecasting quarterly German GDP, a key macroeconomic indicator for the largest country in the euro area, with a large set of about one hundred monthly indicators. Our empirical findings provide strong support for pooling over many specifications rather than selecting a specific model.

Keywords: factor models, forecast combination, forecast pooling, MIDAS, mixed-frequency data, model selection, nowcasting

JEL Classification: C53, E37

Suggested Citation

Kuzin, Vladimir and Marcellino, Massimiliano and Schumacher, Christian, Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP (March 2009). CEPR Discussion Paper No. DP7197. Available at SSRN: https://ssrn.com/abstract=1356426

Vladimir Kuzin

German Institute for Economic Research (DIW Berlin) ( email )

Mohrenstra├če 58
Berlin, 10117
Germany

Massimiliano Marcellino (Contact Author)

European University Institute ( email )

Villa Schifanoia
133 via Bocaccio
Firenze (Florence), Tuscany 50014
Italy

European University Institute - Robert Schuman Centre for Advanced Studies (RSCAS) ( email )

Villa La Fonte, via delle Fontanelle 18
50016 San Domenico di Fiesole
Florence, Florence 50014
Italy

Bocconi University - Department of Economics ( email )

Via Gobbi 5
Milan, 20136
Italy

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

Christian Schumacher

Deutsche Bundesbank ( email )

Wilhelm-Epstein-Str. 14
Frankfurt/Main, 60431
Germany

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