Arbeitspapier
Small sample performance of indirect inference on DSGE models
Using Monte Carlo experiments, we examine the performance of indirect inference tests of DSGE models in small samples, using various models in widespread use. We compare these with tests based on direct inference (using the Likelihood Ratio). We find that both tests have power so that a substantially false model will tend to be rejected by both; but that the power of the indirect inference test is by far the greater, necessitating re-estimation to ensure that the model is tested in its fullest sense. We also find that the small-sample bias with indirect estimation is around half of that with maximum likelihood estimation.
- Language
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Englisch
- Bibliographic citation
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Series: Cardiff Economics Working Papers ; No. E2015/2
- Classification
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Wirtschaft
Hypothesis Testing: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Model Evaluation, Validation, and Selection
- Subject
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Bootstrap
DSGE
Indirect Inference
Likelihood Ratio
New Classical
New Keynesian
Wald statistic
- Event
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Geistige Schöpfung
- (who)
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Le, Vo Phuong Mai
Meenagh, David
Minford, Patrick
Wickens, Michael
- Event
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Veröffentlichung
- (who)
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Cardiff University, Cardiff Business School
- (where)
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Cardiff
- (when)
-
2015
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
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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
- Le, Vo Phuong Mai
- Meenagh, David
- Minford, Patrick
- Wickens, Michael
- Cardiff University, Cardiff Business School
Time of origin
- 2015
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