Estimation of multiple-regime regressions with least absolutes deviation

Jushan, Bai (1995): Estimation of multiple-regime regressions with least absolutes deviation. Published in: Journal of Statistical Planning and Inference , Vol. 74, No. 1 (October 1998): pp. 103-134.

Abstract

This 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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Multiple change points, multiple-regime regressions, least absolute deviation, asymptotic distribution
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions

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