| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP14415 |
| DP14415 Hypothesis tests with a repeatedly singular information matrix | |
| Dante Amengual; Xinyue Bei; ENRIQUE SENTANA | |
| 发表日期 | 2020-02-17 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | We study score-type tests in likelihood contexts in which the nullity of the information matrix under the null is larger than one, thereby generalizing earlier results in the literature. Examples include multivariate skew normal distributions, Hermite expansions of Gaussian copulas, purely non-linear predictive regressions, multiplicative seasonal time series models and multivariate regression models with selectivity. Our proposal, which involves higher order derivatives, is asymptotically equivalent to the likelihood ratio but only requires estimation under the null. We conduct extensive Monte Carlo exercises that study the finite sample size and power properties of our proposal and compare it to alternative approaches. |
| 主题 | Financial Economics |
| 关键词 | Generalized extremum tests Higher-order identifiability Likelihood ratio test Non-gaussian copulas Predictive regressions Skew normal distributions |
| URL | https://cepr.org/publications/dp14415 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/543309 |
| 推荐引用方式 GB/T 7714 | Dante Amengual,Xinyue Bei,ENRIQUE SENTANA. DP14415 Hypothesis tests with a repeatedly singular information matrix. 2020. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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