Testing a linear dynamic panel data model against nonlinear alternatives
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针对非线性备择的线性动态面板模型检验
- 研究问题
- 当截面与时间维度均较大时，如何检验动态面板条件均值的线性设定和滞后设定，并允许不同个体具有不同形式的误设？
- 方法与思路
- 作者提出基于残差的非参数检验，检查大量滞后，允许固定或随机双向效应及非平衡面板，推导原假设下渐近正态性并开展增长应用。
- 材料陈述的贡献
- 摘要称，检验可捕捉多类条件均值误设，允许误设异质性且无需平滑参数随样本增大；模拟支持渐近近似，增长应用发现显著非线性。
- 阅读关注点
- 应核对大截面与长时间维度的相对增长条件、依赖结构、滞后数量及平滑参数要求，以及非平衡面板和增长方程的具体处理。
- 阅读边界
- 所给出版社摘要未提供正则条件、模拟数值或非线性形式；增长方程被拒绝不能直接定位误设来源，也不能建立非线性的因果解释。
原文摘要
The most popular econometric models in the panel data literature are the class of linear panel data models with unobserved individual- and/or time-specific effects. The consistency of parameter estimators and the validity of their economic interpretations as marginal effects depend crucially on the correct functional form specification of the linear panel data model. In this paper, a new class of residual-based tests is proposed for checking the validity of dynamic panel data models with both large cross-sectional units and time series dimensions. The individual and time effects can be fixed or random, and panel data can be balanced or unbalanced. The tests can detect a wide range of model misspecifications in the conditional mean of a dynamic panel data model, including functional form and lag misspecification. They check a large number of lags so that they can capture misspecification at any lag order asymptotically. No common alternative is assumed, thus allowing for heterogeneity in the degrees and directions of functional form misspecification across individuals. Thanks to the use of panel data with large N and T, the proposed nonparametric tests have an asymptotic normal distribution under the null hypothesis without requiring the smoothing parameters to grow with the sample sizes. This suggests better nonparametric asymptotic approximation for the panel data than for time series or cross sectional data. This is confirmed in a simulation study. We apply the new tests to test linear specification of cross-country growth equations and found significant nonlinearities in mean for OECD countries’ growth equation for annual and quintannual panel data.