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Social and Behavioral Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Economics

Singapore Management University

2015

Interactive fixed effects

Articles 1 - 4 of 4

Full-Text Articles in Social and Behavioral Sciences

Panel Data Models With Interactive Fixed Effects And Multiple Structural Breaks, Degui Li, Junhui Qian, Liangjun Su Nov 2015

Panel Data Models With Interactive Fixed Effects And Multiple Structural Breaks, Degui Li, Junhui Qian, Liangjun Su

Research Collection School Of Economics

In this paper we consider estimation of common structural breaks in panel data models with unobservable interactive fixed effects. We introduce a penalized principal component (PPC) estimation procedure with an adaptive group fused LASSO to detect the multiple structural breaks in the models. Under some mild conditions, we show that with probability approaching one the proposed method can correctly determine the unknown number of breaks and consistently estimate the common break dates. Furthermore, we estimate the regression coefficients through the post-LASSO method and establish the asymptotic distribution theory for the resulting estimators. The developed methodology and theory are applicable to …


Specification Test For Panel Data Models With Interactive Fixed Effects, Liangjun Su, Sainan Jin, Yonghui Zhang May 2015

Specification Test For Panel Data Models With Interactive Fixed Effects, Liangjun Su, Sainan Jin, Yonghui Zhang

Research Collection School Of Economics

In this paper, we propose a consistent nonparametric test for linearity in panel data models with interactive fixed effects. To construct the test statistic, we need to estimate the model under the null hypothesis of linearity and then obtain the restricted residuals. We show that after being appropriately centered and standardized, the test statistic is asymptotically normally distributed both under the null hypothesis and a sequence of Pitman local alternatives. To improve the finite sample performance, we propose a bootstrap procedure to obtain the bootstrap p-values. A small set of Monte Carlo simulations illustrates that our test performs well in …


Nonparametric Testing For Anomaly Effects In Empirical Asset Pricing Models, Sainan Jin, Liangjun Su, Yonghui Zhang Feb 2015

Nonparametric Testing For Anomaly Effects In Empirical Asset Pricing Models, Sainan Jin, Liangjun Su, Yonghui Zhang

Research Collection School Of Economics

In this paper, we propose a class of nonparametric tests for anomaly effects in empirical asset pricing models in the framework of nonparametric panel data models with interactive fixed effects. Our approach has two prominent features: one is the adoption of nonparametric functional form to capture the anomaly effects of some asset-specific characteristics and the other is the flexible treatment of both observed/constructed and unobserved common factors. By estimating the unknown factors, betas, and nonparametric function simultaneously, our setup is robust to misspecification of functional form and common factors and avoids the well-known "error-in-variable" problem associated with the commonly used …


Shrinkage Estimation Of Dynamic Panel Data Models With Interactive Fixed Effects, Xun Lu, Liangjun Su Feb 2015

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 and Ng (2009) and Moon and Weidner (2014a), 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 …