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Econometrics Commons

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Liangjun Su

Penalized least squares

Articles 1 - 3 of 3

Full-Text Articles in Econometrics

Identifying Latent Structures In Panel Data, Liangjun Su, Zhentao Shi, Peter C. B. Phillips Feb 2017

Identifying Latent Structures In Panel Data, Liangjun Su, Zhentao Shi, Peter C. B. Phillips

Liangjun Su

in multiple linear regression models via group fused Lasso (least absolute shrinkage


Structural Change Estimation In Time Series Regressions With Endogenous Variables, Junhui Qian, Liangjun Su Feb 2017

Structural Change Estimation In Time Series Regressions With Endogenous Variables, Junhui Qian, Liangjun Su

Liangjun Su

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.


Shrinkage Estimation Of Common Breaks In Panel Data Models Via Adaptive Group Fused Lasso, Junhui Qian, Liangjun Su Feb 2017

Shrinkage Estimation Of Common Breaks In Panel Data Models Via Adaptive Group Fused Lasso, Junhui Qian, Liangjun Su

Liangjun Su

In this paper we consider estimation and inference of common breaks in panel data models via adaptive group fused Lasso. We consider two approaches—penalized least squares (PLS) for first-differenced models without endogenous regressors, and penalized GMM (PGMM) for first-differenced models with endogeneity. We show that with probability tending to one, both methods can correctly determine the unknown number of breaks and estimate the common break dates consistently. We establish the asymptotic distributions of the Lasso estimators of the regression coefficients and their post Lasso versions. We also propose and validate a data-driven method to determine the tuning parameter used in …