 Simulated Asymptotic Least Squares TheoryRamdan Dridi STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE Abstract: We develop in this paper a general econometric methodology referred to as the Simulated Asymptotic Least Squares (SALS). It is shown that this approach provides a unifying theory for 'approximation-based' or simulation-based inference methods and nests the Simulated Nonlinear Least Squares (SSNLS), the Simulated Pseudo Maximum Likelihood (SPML), the Simulated Method of Moments (SMM) in both parametric and semiparametric settings, the Indirect Inference (II) and the Efficient Method of Moments (EMM). We produce a new notion of Efficiency Bounds in Direction and provide a general study of the efficiency in the SALS framework. In the particular case of the II and the EMM methods and when the instrumental model is of a GMM type, we characterise a new weighting matrix for a more efficient estimation about the structural parameters of interest ?0. This new weighting matrix does no longer correspond, in the general case, to the classical one as characterised by Hansen (1982). Generalized global specification tests extending the previous existing ones are also proposed. Keywords: Simulated Asymptotic Least Squares; Approximation-based and Simulation-based estimation; Efficiency Bounds in Direction; GMM; SNLS; SPML; SMM; II; GII; EMM. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:396 Access Statistics for this paper More papers in STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE |
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