Asymptotic theory for M-estimators of boundaries

Keith Knight

No 2003,37, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Abstract: We consider some asymptotic distribution theory for M-estimators of the parameters of a linear model whose errors are non-negative; these estimators are the solutions of constrained optimization problems and their asymptotic theory is non-standard. Under weak conditions on the distribution of the errors and on the design, we show that a large class of estimators have the same asymptotic distributions in the case of i.i.d. errors; however, this invariance does not hold under non-i.i.d. errors.

Keywords: constrained optimization; epi-convergence; linear programming estimator; M-estimator; point processes (search for similar items in EconPapers)
Date: 2003
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