Asymptotic theory for M-estimators of boundaries
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.
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- B. Nielsen & N. Shephard, 2003.
"Likelihood analysis of a first-order autoregressive model with exponential innovations,"
Journal of Time Series Analysis,
Wiley Blackwell, vol. 24(3), pages 337-344, 05.
- Bent Nielsen & Neil Shephard, 1999. "Likelihood Anlaysis of a First Order Autoregressive Model with Exponential Innovations," Economics Series Working Papers 1999-W08, University of Oxford, Department of Economics.
- Donald, Stephen G. & Paarsch, Harry J., 2002. "Superconsistent estimation and inference in structural econometric models using extreme order statistics," Journal of Econometrics, Elsevier, vol. 109(2), pages 305-340, August.
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
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