Arbeitspapier

Macroeconomic now- and forecasting based on the factor error correction model using targeted mixed frequency indicators

Since the influential paper of Stock and Watson (2002), the dynamic factor model (DFM) has been widely used for forecasting macroeconomic key variables such as GDP. However, the DFM has some weaknesses. For nowcasting, the dynamic factor model is modified by using the mixed data sampling technique. Other improvements are also studied mostly in two directions: a pre-selection is used to optimally choose a small number of indicators from a large number of indicators. The error correction mechanism takes into account the co-integrating relationship between the key variables and factors and, hence, captures the long-run dynamics of the non-stationary macroeconomic variables. This papers proposes the factor error correction model using targeted mixedfrequency indicators, which combines the three refinements for the dynamic factor model, namely the mixed data sampling technique, pre-selection methods, and the error correction mechanism. The empirical results based on euro-area data show that the now- and forecasting performance of our new model is superior to that of the subset models.

ISBN
978-3-95729-324-4
Language
Englisch

Bibliographic citation
Series: Bundesbank Discussion Paper ; No. 47/2016

Classification
Wirtschaft
Methodological Issues: General
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
Model Construction and Estimation
Model Evaluation, Validation, and Selection
Forecasting Models; Simulation Methods
Subject
Factor model
MIDAS
Lasso
Elastic Net
ECM
Nowcasting
Forecasting

Event
Geistige Schöpfung
(who)
Kurz-Kim, Jeong-Ryeol
Event
Veröffentlichung
(who)
Deutsche Bundesbank
(where)
Frankfurt a. M.
(when)
2016

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Kurz-Kim, Jeong-Ryeol
  • Deutsche Bundesbank

Time of origin

  • 2016

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