Consistent GMM Residuals-Based Tests of Functional Form
提出一种基于广义矩方法残差的一致检验，用于检测时间序列模型的函数形式误设，在大样本下能检测任何形式的误设，且原假设下渐近卡方分布，模拟显示随机选择冗余参数比上确界检验功效更高。
This paper presents a consistent Generalized Method of Moments (GMM) residuals-based test of functional form for time series models. By relating two moments we deliver a vector moment condition in which at least one element must be nonzero if the model is misspecified. The test will never fail to detect misspecification of any form for large samples, and is asymptotically chi-squared under the null, allowing for fast and simple inference. A simulation study reveals randomly selecting the nuisance parameter leads to more power than supremum-tests, and can obtain empirical power nearly equivalent to the most powerful test for even relatively small n.