Encompassing and indirect inference |
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Authors: | Christian Gouriéroux Alain Monfort |
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Institution: | (1) ENSAE-CREST, 12, Rue Boulette, 75014 Paris, France;(2) Unité de Recherche INSEE, Boulevard Adolphe Pinard, 75, 675 Paris, France |
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Abstract: | Summary In the literature on encompassing see e.g. Mizon-Richard (1986), Hendry-Richard (1990), Florens-Hendry-Richard (1987)] there
is a basic contradiction: on the one hand it is said that it is not possible to assume that the true distribution belongs
to one of two competing modelM
1 andM
2, but, on the other hand, this assumption is made in the study of encompassing tests. In this paper we first propose a formal
definition of encompassing, we then briefly examine the properties of this notion and we propose encompassing tests which
do not assume that the true distribution belongs toM
1 orM
2; these tests are based on simulations. Finally, generalizing an idea used in the definition of an encompassing test (the
GET test) we propose a new kind of inference, called indirect inference, which allows for estimation and test procedures when
the model is too complicated to be treated by usual methods (for instance maximum likelihood methods); the only assumption
made on the model is that it can be simulated, which seems to be a minimal requirement. This new class of inference methods
can be used in a large number of domains and some examples are given. The present paper is based on Gouriéroux-Monfort (1992),
and Gouriéroux-Monfort-Renault (1993), respectively GM and GMR hereafter.
Invited paper at the Conference on ?Statistical Tests: Methodology and Econometric Applications?, held in Bologna, Italy,
27–28 May 1993. |
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Keywords: | |
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