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Singapore Management University

Series

2014

Penalized GMM

Articles 1 - 2 of 2

Full-Text Articles in Economics

Structural Change Estimation In Time Series Regressions With Endogenous Variables, Junhui Qian, Liangjun Su Dec 2014

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

Research Collection School Of Economics

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.


Identifying Latent Structures In Panel Data, Liangjun Su, Zhentao Shi, Peter C. B. Phillips Aug 2014

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

Research Collection School Of Economics

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized regression techniques. We focus on linear models where the slope parameters are heterogeneous across groups but homogenous within a group and the group membership is unknown. Two approaches are considered — penalized least squares (PLS) for models without endogenous regressors, and penalized GMM (PGMM) for models with endogeneity. In both cases we develop a new variant of Lasso called classifier-Lasso (C-Lasso) that serves to shrink individual coefficients to the unknown group-specific coefficients. C-Lasso achieves simultaneous classification and consistent estimation in a single …