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Full-Text Articles in Economics
Nonparametric Dynamic Panel Data Models: Kernel Estimation And Specification Testing, Liangjun Su, Xun Lu
Nonparametric Dynamic Panel Data Models: Kernel Estimation And Specification Testing, Liangjun Su, Xun Lu
Research Collection School Of Economics
Motivated by the first-differencing method for linear panel data models, we propose a class of iterative local polynomial estimators for nonparametric dynamic panel data models with or without exogenous regressors. The estimators utilize the additive structure of the first-differenced model—the fact that the two additive components have the same functional form, and the unknown function of interest is implicitly defined as a solution of a Fredholm integral equation of the second kind. We establish the uniform consistency and asymptotic normality of the estimators. We also propose a consistent test for the correct specification of linearity in typical dynamic panel data …
Nonparametric Dynamic Panel Data Models With Interactive Fixed Effects: Sieve Estimation And Specification Testing, Liangjun Su, Yonghui Zhang
Nonparametric Dynamic Panel Data Models With Interactive Fixed Effects: Sieve Estimation And Specification Testing, Liangjun Su, Yonghui Zhang
Research Collection School Of Economics
In this paper we analyze nonparametric dynamic panel data models with interactive fixed effects, where the predetermined regressors enter the models nonparametrically and the common factors enter the models linearly but with individual specific factor loadings. We consider the issues of estimation and specification testing when both the cross-sectional dimension and the time dimension are large. We propose sieve estimation for the nonparametric function by extending Bai’s (2009) principal component analysis (PCA) to our nonparametric framework. Based on the asymptotic expansion of the Gaussian quasi-log-likelihood function, we derive the convergence rate for the sieve estimator and establish its asymptotic normality. …
Testing Monotonicity In Unobservables With Panel Data, Liangjun Su, Stefan Hoderlein, Halbert White
Testing Monotonicity In Unobservables With Panel Data, Liangjun Su, Stefan Hoderlein, Halbert White
Research Collection School Of Economics
Monotonicity in a scalar unobservable is a crucial identifying assumption for an important class of nonparametric structural models accommodating unobserved heterogeneity. Tests for this monotonicity have previously been unavailable. This paper proposes and analyzes tests for scalar monotonicity using panel data for structures with and without time-varying unobservables, either partially or fully nonseparable between observables and unobservables. Our nonparametric tests are computationally straightforward, have well behaved limiting distributions under the null, are consistent against precisely specified alternatives, and have standard local power properties. We provide straightforward bootstrap methods for inference. Some Monte Carlo experiments show that, for empirically relevant sample …
Nonparametric Dynamic Panel Data Models: Kernel Estimation And Specification Testing, Liangjun Su, Xun Lu
Nonparametric Dynamic Panel Data Models: Kernel Estimation And Specification Testing, Liangjun Su, Xun Lu
Research Collection School Of Economics
Motivated by the first differencing method for linear panel data models, we propose a class of iterative local polynomial estimators for nonparametric dynamic panel data models with or without exogeous regressors. The estimators utilize the additive structure of the first-differenced model, the fact that the two additive components have the same functional form, and the unknown function of interest is implicitly defined as a solution of a Fredholm integral equation of the second kind. We establish the uniform consistency and asymptotic normality of the estimators. We also propose a consistent test for the correct specification of linearity in typical dynamic …