Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/22252 
Authors: 
Year of Publication: 
2003
Series/Report no.: 
SFB 373 Discussion Paper No. 2003,37
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
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.
Subjects: 
constrained optimization
epi-convergence
linear programming estimator
M-estimator
point processes
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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