论文标题
一致的分位数自动化测试
Consistent Specification Test of the Quantile Autoregression
论文作者
论文摘要
本文提出了对正确动态规范的联合假设进行测试，并且没有省略对分位数自动降低的潜在因素。如果拒绝复合零，我们继续解散拒绝原因，即动态错误指定或省略的变量。我们在相当弱的条件下建立了测试统计数据的渐近分布，并表明因子估计误差可以忽略不计。一项蒙特卡洛研究表明，建议的测试具有良好的有限样品特性。最后，我们对英国的GDP增长和CPI通胀进行了建模，在这里我们发现证据表明，与GDP增长相比，与其非增强的同行相比，正确指定了因子增强模型，同时还探索了生长和膨胀分布的不对称行为。
This paper proposes a test for the joint hypothesis of correct dynamic specification and no omitted latent factors for the Quantile Autoregression. If the composite null is rejected we proceed to disentangle the cause of rejection, i.e., dynamic misspecification or an omitted variable. We establish the asymptotic distribution of the test statistics under fairly weak conditions and show that factor estimation error is negligible. A Monte Carlo study shows that the suggested tests have good finite sample properties. Finally, we undertake an empirical illustration of modelling GDP growth and CPI inflation in the United Kingdom, where we find evidence that factor augmented models are correctly specified in contrast with their non-augmented counterparts when it comes to GDP growth, while also exploring the asymmetric behaviour of the growth and inflation distributions.
