We develop a new permutation test for inference on a subvector of coefficients in linear models. The test is exact when the regressors and the error terms are independent. Then, we show that the test is consistent and has power against local alternatives when the independence condition is relaxed, under two main conditions. The first is a slight reinforcement of the usual absence of correlation between the regressors and the error term. The second is that the number of strata, defined by values of the regressors not involved in the subvector test, is small compared to the sample size. Simulations and an empirical illustration suggest that the test has good power in practice.

翻译：我们为线性模型中系数子值的推论开发了新的变位测试。 精确的测试是当递减器和误差条件是独立的时进行的。 然后, 我们显示, 在两个主要条件下, 当独立条件放松时, 测试是一致的, 并且对本地的替代物具有力量。 首先是稍稍加强通常情况下, 递减器和误差术语之间没有关联性。 其次, 由未参与子体试验的递减器的数值定义的层数, 与样本大小相比是很小的。 模拟和实验性说明表明, 测试在实际中具有良好的力量 。