Specification Test for Panel Data Models with Interactive Fixed Effects

By Liangjun Su, Sainan Jin, Yonghui Zhang. 2014

62 citations recorded by the source corpus.

In this paper, we propose a consistent nonparametric test for linearity in a large dimensional panel data model with interactive fixed effects. Both lagged dependent variables and conditional heteroskedasticity of unknown form are allowed in the model. We estimate the model under the null hypothesis of linearity to obtain the restricted residuals which are then used to construct the test statistic. We show that after being appropriately centered and standardized, the test statistic is asymptotically normally distributed under both the null hypothesis and a sequence of Pitman local alternatives by using the concept of conditional strong mixing that was recently introduced by Prakasa Rao (2009). To improve the finite sample performance, we propose a bootstrap procedure to obtain the bootstrap p-value. A small set of Monte Carlo simulations illustrates that our test performs well in finite samples. An application to an economic growth panel dataset indicates significant nonlinear relationships between economic growth, initial income level and capital accumulation.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/087b21d04b9384e1232ea5704232f2836d261571

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Xia Wang
2. Liangjun Su
3. Yiguo Sun
4. Xun Lu
5. Sainan Jin
6. Emir Malikov
7. Peter C. B. Phillips
8. Jihai Yu

Citations in the corpus

• Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects (2016, unknown): “13The only exception is Su et al. (2015), who apply a specification test of panel models with fixed effects to economic growth data.”
• On Time-Varying Factor Models: Estimation and Testing ∗ (2017, methodology): “…model via a Gibbs sampling procedure. nonparametric literature on time-varying models (see, e.g., Cai 2007, Robinson 2012, Chen and Hong 2012, Chen et al. 2012, Su et al. 2015) and model as a nonrandom function of : = ( ) where (·) is an unknown piece-wise smooth function of on (0 1] for each .”