02095cam a22002537 4500001000600000003000500006005001700011008004100028100002100069245015500090260006600245490005100311500001800362520104700380530006101427538007201488538003601560700002201596700002201618710004201640830008601682856003701768856003601805t0186NBER20160824065908.0160824s1995 mau||||fs|||| 000 0 eng d1 aImbens, Guido W.10aInformation Theoretic Approaches to Inference in Moment Condition Modelsh[electronic resource] /cGuido W. Imbens, Phillip Johnson, Richard H. Spady. aCambridge, Mass.bNational Bureau of Economic Researchc1995.1 aNBER technical working paper seriesvno. t0186 aOctober 1995.3 aOne-step efficient GMM estimation has been developed in the recent papers of Back and Brown (1990), Imbens (1993) and Qin and Lawless (1994). These papers emphasized methods that correspond to using Owen's (1988) method of empirical likelihood to reweight the data so that the reweighted sample obeys all the moment restrictions at the parameter estimates. In this paper we consider an alternative KLIC motivated weighting and show how it and similar discrete reweightings define a class of unconstrained optimization problems which includes GMM as a special case. Such KLIC-motivated reweightings introduce M auxiliary `tilting' parameters, where M is the number of moments; parameter and overidentification hypotheses can be recast in terms of these tilting parameters. Such tests, when appropriately conditioned on the estimates of the original parameters, are often startlingly more effective than their conventional counterparts. This is apparently due to the local ancillarity of the original parameters for the tilting parameters. aHardcopy version available to institutional subscribers. aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web.1 aJohnson, Phillip.1 aSpady, Richard H.2 aNational Bureau of Economic Research. 0aTechnical Working Paper Series (National Bureau of Economic Research)vno. t0186.4 uhttp://www.nber.org/papers/t018641uhttp://dx.doi.org/10.3386/t0186