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Social and Behavioral Sciences Commons

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Singapore Management University

Research Collection School Of Economics

2016

Adaptive Lasso

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Full-Text Articles in Social and Behavioral Sciences

Shrinkage Estimation Of Common Breaks In Panel Data Models Via Adaptive Group Fused Lasso, Junhui Qian, Liangjun Su Mar 2016

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

Research Collection School Of Economics

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 …


Shrinkage Estimation Of Dynamic Panel Data Models With Interactive Fixed Effects, Xun Lu, Liangjun Su Jan 2016

Shrinkage Estimation Of Dynamic Panel Data Models With Interactive Fixed Effects, Xun Lu, Liangjun Su

Research Collection School Of Economics

We consider the problem of determining the number of factors and selecting the proper regressors in linear dynamic panel data models with interactive fixed effects. Based on the preliminary estimates of the slope parameters and factors a la Bai (2009) and Moon and Weidner (2015), we propose a method for simultaneous selection of regressors and factors and estimation through the method of adaptive group Lasso (least absolute shrinkage and selection operator). We show that with probability approaching one, our method can correctly select all relevant regressors and factors and shrink the coefficients of irrelevant regressors and redundant factors to zero. …