Arbeitspapier
Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis
Dynamic factor models based on Kalman Filter techniques are frequently used to nowcast GDP. This study deals with the selection of indicators for this practice. We propose a two-tiered mechanism which is shown in a case study to produce more accurate nowcasts than a benchmark stochastic process and a standard model including extreme bounds fragile indicators. Nowcasting accuracy nearly measures up to the one of real-time forecasts by an institution with an interest in high-quality nowcasts.
- Language
-
Englisch
- Bibliographic citation
-
Series: Working Paper ; No. 152
- Classification
-
Wirtschaft
Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
Forecasting Models; Simulation Methods
- Subject
-
dynamic factor
Kalman Filter
extreme bounds analysis
- Event
-
Geistige Schöpfung
- (who)
-
Duarte, Pablo
Süßmuth, Bernd
- Event
-
Veröffentlichung
- (who)
-
Universität Leipzig, Wirtschaftswissenschaftliche Fakultät
- (where)
-
Leipzig
- (when)
-
2018
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Duarte, Pablo
- Süßmuth, Bernd
- Universität Leipzig, Wirtschaftswissenschaftliche Fakultät
Time of origin
- 2018
Other Objects (12)
Approximate Solutions to Dynamic Models
Sensitivity analysis using approximate moment condition models
Approximate Distance Sensitivity Oracles in Subquadratic Space
Intelligent Questionnaires Using Approximate Dynamic Programming
Markdown Optimization via Approximate Dynamic Programming
Approximate solutions to dynamic models: linear methods
Model Selection in Approximate and Dynamic Factor Models
Approximate dynamic programming for liner shipping network design
Implementing US GDP in Chained Prices for Cross-country GDP Growth and Sectoral Comparisons: Application to Selected ASEAN Countries
A dynamic factor model for nowcasting Canadian GDP growth
Forecasting Austrian GDP using the generalized dynamic factor model
Essays on the large dimensional approximate dynamic factor model
Approximate Solutions to Dynamic Models
Sensitivity analysis using approximate moment condition models
Approximate Distance Sensitivity Oracles in Subquadratic Space
Intelligent Questionnaires Using Approximate Dynamic Programming
Markdown Optimization via Approximate Dynamic Programming
Approximate solutions to dynamic models: linear methods
Model Selection in Approximate and Dynamic Factor Models
Approximate dynamic programming for liner shipping network design
Implementing US GDP in Chained Prices for Cross-country GDP Growth and Sectoral Comparisons: Application to Selected ASEAN Countries
A dynamic factor model for nowcasting Canadian GDP growth
Forecasting Austrian GDP using the generalized dynamic factor model
Essays on the large dimensional approximate dynamic factor model
Approximate Solutions to Dynamic Models
Sensitivity analysis using approximate moment condition models
Approximate Distance Sensitivity Oracles in Subquadratic Space
Intelligent Questionnaires Using Approximate Dynamic Programming
Markdown Optimization via Approximate Dynamic Programming
Approximate solutions to dynamic models: linear methods
Model Selection in Approximate and Dynamic Factor Models
Approximate dynamic programming for liner shipping network design
Implementing US GDP in Chained Prices for Cross-country GDP Growth and Sectoral Comparisons: Application to Selected ASEAN Countries
A dynamic factor model for nowcasting Canadian GDP growth
Forecasting Austrian GDP using the generalized dynamic factor model