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.

Sprache
Englisch

Erschienen in
Series: Cardiff Economics Working Papers ; No. E2015/2

Klassifikation
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
Thema
Bootstrap
DSGE
Indirect Inference
Likelihood Ratio
New Classical
New Keynesian
Wald statistic

Ereignis
Geistige Schöpfung
(wer)
Le, Vo Phuong Mai
Meenagh, David
Minford, Patrick
Wickens, Michael
Ereignis
Veröffentlichung
(wer)
Cardiff University, Cardiff Business School
(wo)
Cardiff
(wann)
2015

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Le, Vo Phuong Mai
  • Meenagh, David
  • Minford, Patrick
  • Wickens, Michael
  • Cardiff University, Cardiff Business School

Entstanden

  • 2015

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