Arbeitspapier

Comparing Indirect Inference and likelihood testing: Asymptotic and small sample results

Indirect Inference has been found to have much greater power than the Likelihood Ratio in small samples for testing DSGE models. We look at asymptotic and large sample properties of these tests to understand why this might be the case. We find that the power of the LR test is undermined when reestimation of the error parameters is permitted; this offsets the effect of the falseness of structural parameters on the overall forecast error. Even when the two tests are done on a like-for-like basis Indirect Inference has more power because it uses the distribution restricted by the DSGE model being tested.

Language
Englisch

Bibliographic citation
Series: Cardiff Economics Working Papers ; No. E2015/8

Classification
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
Indirect Inference
Likelihood Ratio
DSGE model
structural parameters
error processes

Event
Geistige Schöpfung
(who)
Meenagh, David
Minford, Patrick
Wickens, Michael
Xu, Yongdeng
Event
Veröffentlichung
(who)
Cardiff University, Cardiff Business School
(where)
Cardiff
(when)
2015

Handle
Last update
10.03.2025, 11:41 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Meenagh, David
  • Minford, Patrick
  • Wickens, Michael
  • Xu, Yongdeng
  • Cardiff University, Cardiff Business School

Time of origin

  • 2015

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