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Full-Text Articles in Social and Behavioral Sciences
Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su
Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su
Research Collection School Of Economics
We consider a panel cointegration model with latent group structures that allows for heterogeneous long-run relationships across groups. We extend Su, Shi, and Phillips’ (2016) classifier-Lasso (C-Lasso) method to the nonstationary panels and allow for the presence of endogeneity in both the stationary and nonstationary regressors in the model. In addition, we allow the dimension of the stationary regressors to diverge with the sample size. We show that we can identify the individuals’ group membership and estimate the group-specific long-run cointegrated relationships simultaneously. We demonstrate the desirable property of uniform classification consistency and the oracle properties of both the C-Lasso …
Identifying Latent Grouped Patterns In Panel Data Models With Interactive Fixed Effects, Liangjun Su, Gaosheng Ju
Identifying Latent Grouped Patterns In Panel Data Models With Interactive Fixed Effects, Liangjun Su, Gaosheng Ju
Research Collection School Of Economics
We consider the estimation of latent grouped patterns in dynamic panel data models with interactive fixed effects. We assume that the individual slope coefficients are homogeneous within a group and heterogeneous across groups but each individual’s group membership is unknown to the researcher. We consider penalized principal component (PPC) estimation by extending the penalized-profile-likelihood-based C-Lasso of Su, Shi, and Phillips (2016) to panel data models with cross section dependence. Given the correct number of groups, we show that the C-Lasso can achieve simultaneous classification and estimation in a single step and exhibit the desirable property of uniform classification consistency. The …