Estimation of multiple-regime regressions with least absolutes deviation
AbstractThis paper considers least absolute deviations estimation of a regression model with multiple change points occurring at unknown times. Some asymptotic results, including rates of convergence and asymptotic distributions, for the estimated change points and the estimated regression coefficient are derived. Results are obtained without assuming that each regime spans a positive fraction of the sample size. In addition, the number of change points is allowed to grow as the sample size increases. Estimation of the number of change points is also considered. A feasible computational algorithm is developed. An application is also given, along with some monte carlo simulations.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 32916.
Date of creation: Feb 1995
Date of revision: Feb 1998
Publication status: Published in Journal of Statistical Planning and Inference 1.74(1998): pp. 103-134
Multiple change points; multiple-regime regressions; least absolute deviation; asymptotic distribution;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
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- Zhongjun Qu & Tatsushi Oka, 2010.
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Boston University - Department of Economics - Working Papers Series
WP2010-052, Boston University - Department of Economics.
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