On Parameter Estimation for Semi-linear Errors-in-Variables Models


This paper studies a semi-linear errors-in-variables model of the formYi=x'i[beta]+g(Ti)+ei,Xi=xi+ui(1[less-than-or-equals, slant]i[less-than-or-equals, slant]n). The estimators of parameters[beta],[sigma]2and of the smooth functiongare derived by using the nearest neighbor-generalized least square method. Under some weak conditions, it is shown that the estimators of unknown vector[beta]and the unknown parameter[sigma]2are strongly consistent and asymptotically normal. The estimator ofgalso achieves an optimal rate of convergence.semi-linear errors-in-variables model, asymptotic normality, rate of convergence

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Research Papers in Economics

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Last time updated on 7/6/2012

This paper was published in Research Papers in Economics.

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