Structural change estimation in time series regressions with endogenous variables

Structural change estimation in time series regressions with endogenous variables

We propose to apply the group fused Lasso to estimate time series models with endogenous regressors and an unknown number of breaks. It can correctly determine the number of breaks and estimate the break dates asymptotically. Simulations and applications are given.

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Bibliographic Details
Main Authors: QIAN, Junhui, SU, Liangjun
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2014
Subjects:
Group fused Lasso
Multiple breaks
Penalized least squares
Penalized GMM
Structural change
Econometrics
Economics
Online Access:https://ink.library.smu.edu.sg/soe_research/1624
https://ink.library.smu.edu.sg/context/soe_research/article/2623/viewcontent/StructuralChangeEstTSREndoVar_2014.pdf
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Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/soe_research/1624
https://ink.library.smu.edu.sg/context/soe_research/article/2623/viewcontent/StructuralChangeEstTSREndoVar_2014.pdf

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