ABC and Indirect Inference

Authored by: Christopher C. Drovandi

Handbook of Approximate Bayesian Computation

Print publication date:  August  2018
Online publication date:  August  2018

Print ISBN: 9781439881507
eBook ISBN: 9781315117195
Adobe ISBN:

10.1201/9781315117195-7

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Abstract

Indirect inference (II) is a classical method for estimating the parameter of a complex model when the likelihood is unavailable or too expensive to evaluate. The idea was popularised several years prior to the main developments in approximate Bayesian computation (ABC) by Gourieroux et al. (1993); Smith (1993), where interest was in calibrating complex time series models used in financial applications. The II method became a very popular approach in the econometrics literature [e.g. Smith (1993); Monfardini (1998); Dridi et al. (2007)] in a similar way to the ubiquitous application of ABC to models in population genetics. However, the articles by Jiang and Turnbull (2004) and Heggland and Frigessi (2004) have allowed the II approach to be known and appreciated by the wider statistical community.

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