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单整过程的线性与对数变换检验AI 解读

This article proposes nonnested tests of linear and logarithmic transformations of integrated processes against each other, where the innovations of both series follow autoregressive processes. It is shown that the null distributions of the test statistics for both the linear and logarithmic transformations are nonstandard when the processes have no drift, whereas they are asymptotically normal when the processes have positive drift. Monte Carlo experiments and illustrative…

单整过程的线性与对数变换检验AI 解读

This article proposes nonnested tests of linear and logarithmic transformations of integrated processes against each other, where the innovations of both series follow autoregressive processes. It is shown that the null distributions of the test statistics for both the linear and logarithmic transformations are nonstandard when the processes have no drift, whereas they are asymptotically normal when the processes have positive drift. Monte Carlo experiments and illustrative…

线性与对数线性回归中嵌套及非嵌套检验的解析功效比较AI 解读

This paper compares several tests for linear and loglinear regression models where both the dependent and independent variables are transformed. It is shown that the Lagrange multiplier test proposed by Godfrey and Wickens (1981, Review of Economic Studies 48, 487–496) in the framework of the Box–Cox regression model has the highest asymptotic power of the compared tests. The extended projection test of MacKinnon, White, and Davidson (1983, Journal of Econometrics 11,…

回归分析中非线性变换检验的功效AI 解读

This paper compares the local power of tests for a nonlinear transformation of the dependent variable in a regression model against the alternative hypothesis of a linear transformation. It is shown that the local power of the Cox test is higher than those of the extended projection test of MacKinnon, White, and Davidson, and Bera and McAleer's test. The theoretical result is supported by a Monte-Carlo experiment in testing for a regression model with a logarithmically…

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异方差下两个线性回归模型系数相等的界限检验AI 解读

This article proposes a small sample bounds test for equality between sets of coefficients in two linear regressions with unequal disturbance variances. The probability that our test is inconclusive is given under the null hypothesis. It is also shown that our test is more powerful than the Jayatissa test when the regression coefficients differ substantially.

扰动方差不等时两组线性回归系数相等性的界限检验AI 解读

This article considers the Wald test statistic for testing equality between sets of coefficients in two linear regressions when the disturbance variances are unequal. It is shown that the distribution of the test statistic under the null hypothesis is bounded, asymptotically up to the second order, by the distributions of two F variates multiplied by the number of the regressors.

一阶自相关误差下线性回归估计量的效率比较AI 解读

This article compares several estimators for linear regression models with first-order autocorrelated errors. Asymptotic variances of the estimators of regression coefficients are obtained up to order T −2 for the maximum likelihood, the iterated Prais-Winsten, and the iterated Cochrane—Orcutt methods. It is shown that the first two methods are equivalent in efficiency and that the last is less efficient. This loss in efficiency is due to the effect of the initial…