在大数据时代背景下，随着微观和宏观层面数字信息的不断丰富完善，面板数据模型在实证研究中正受到日益广泛的重视和应用，各种基于面板数据特征的计量方法不断涌现，并被应用于解决经济中的重要现实问题。面板数据模型可以有效地处理个体和时间异质性效应，而在个体和时间维度较大的情形下，相应的计量估计会因高维数据而产生有别于以往传统方法的新特性。而现有的研究往往忽视了高维环境下面板模型的新特征，从而可能会得出谬误的研究结论。本书汇集了作者对面板模型的三类重要问题提出的检验理论方法，重点探讨了当待估或待检验参数维度增大的情况下，如何构造有效的计量检验加以甄别，从而对实证研究中特定方法的适用性问题提出建设性的科学建议。

Chapter 1 Introduction
1.1 Introduction
Chapter 2 A Practical Test for Strict Exogeneity in Linear Panel Data Models with Fixed Effects
2.1 Introduction
2.2 The hypothesis
2.3 The test statistic
2.4 The asymptotic properties of the test statistic
2.5 Monte Carlo simulations
2.5.1 Data generating processes
2.5.2 Simulation results
2.6 An application to agricultural production
2.7 Conclusions
2.8 Appendix
Chapter 3 A Robust Test of Slope Homogeneity in Panel Data Models with Power Enhancement
3.1 Introduction
3.2 The model and estimation
3.2.1 The panelARDL model
3.2.2 The CCE representation
3.2.3 Estimation
3.3 Testing
3.3.1 The hypothesis and asymptotic distribution of our test statistic
3.3.2 A bootstrap version of our test
3.4 Power Enhancement
3.4.1 The composed test statistic
3.4.2 Asymptotic properties of PE
3.5 Simulations
3.5.1 Data Generating Process
3.5.2 Findings
3.6 Empirical Application
3.7 Conclusion
3.8 Proofs for main theorems
3.9 Technical Lemmas
Chapter 4 Semiparametric Estimation and Specification Testing of Dynamic Panel Count Data Models
4.1 Introduction
4.2 Estimation of semiparametric panel count data models
4.2.1 Sieve Minimum Distance Estimation
4.2.2 Kernel estimation based on a nonlinear in- tegral equation
4.3 Asymptotic properties
4.3.1 Asymptotic properties for the SMD estimator
4.3.2 Asymptotic properties for the local smoothing estimator of g (.)
4.4 A specification test for the linear function form of g(.)
4.4.1 Hypotheses
4.4.2 The test statistic and asymptotic properties
4.4.3 A bootstrap version of the test
4.5 Monte Carlo simulations
4.5.1 Data generating processes and implementation
4.5.2 Simulation results
4.6 Empirical application
4.6.1 Data and implementation
4.6.2 Estimation and testing results
4.7 Conclusion
4.8 Description of variables in empirical study
4.9 Proof of main results