02066cam a22002657 4500001000600000003000500006005001700011008004100028100002000069245011600089260006600205490005100271500001500322520084600337530006101183538007201244538003601316690011001352690011501462700002201577710004201599830008601641856003701727856003601764t0198NBER20161206153356.0161206s1996 mau||||fs|||| 000 0 eng d1 aStock, James H.10aAsymptotics for GMM Estimators with Weak Instrumentsh[electronic resource] /cJames H. Stock, Jonathan Wright. aCambridge, Mass.bNational Bureau of Economic Researchc1996.1 aNBER technical working paper seriesvno. t0198 aJuly 1996.3 aThis paper develops asymptotic distribution theory for generalized method of moments (GMM) estimators and test statistics when some of the parameters are well identified, but others are poorly identified because of weak instruments. The asymptotic theory entails applying empirical process theory to obtain a limiting representation of the (concentrated) objective function as a stochastic process. The general results are specialized to two leading cases, linear instrumental variables regression and GMM estimation of Euler equations obtained from the consumption-based capital asset pricing model with power utility. Numerical results of the latter model confirm that finite sample distributions can deviate substantially from normality, and indicate that these deviations are captured by the weak instrument asymptotic approximations. aHardcopy version available to institutional subscribers. aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web. 7aC1 - Econometric and Statistical Methods and Methodology: General2Journal of Economic Literature class. 7aC3 - Multiple or Simultaneous Equation Models • Multiple Variables2Journal of Economic Literature class.1 aWright, Jonathan.2 aNational Bureau of Economic Research. 0aTechnical Working Paper Series (National Bureau of Economic Research)vno. t0198.4 uhttp://www.nber.org/papers/t019841uhttp://dx.doi.org/10.3386/t0198