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GARCH 与非对称幂 GARCH 模型矩存在的充要条件AI 解读

Although econometricians have been using Bollerslev's (1986, Journal of Econometrics 31, 307–327) GARCH( r , s ) model for over a decade, the higher order moment structure of the model remains unresolved. The sufficient condition for the existence of the higher order moments of the GARCH( r , s ) model was given by Ling (1999a, Journal of Applied Probability 36, 688–705). This paper shows that Ling's condition is also necessary. As an extension, the necessary and sufficient…

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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,…

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将定性调查回答转化为定量预期的方法：澳大利亚制造业应用AI 解读

Abstract This paper analyses and extends alternative procedures for converting qualitative expectations responses to quantitative expectations. A number of conversion procedures is investigated, including the probability model, the time‐varying parameter probability model, and the regression approach. The informational content of the survey expectations is compared with simple time series models. It is found that the expectations models are superior for many series, both in…

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局部假设下非嵌套模型联合与成对检验的功效比较AI 解读

This paper compares the asymptotic local power properties of some tests of a null model against a single nonnested alternative and against multiple nonnested alternatives, denoted hereafter as paired and joint tests, respectively. It is demonstrated that the ranking of tests on the basis of asymptotic local powers depends on the choice of local hypothesis. When a local null hypothesis is employed, it is not possible to rank the Wald and Cox-type paired or joint tests.…

时间序列模型适切性检验的蒙特卡洛研究AI 解读

In this article, we conduct a Monte Carlo experiment of several computationally attractive tests of model adequacy in time series analysis. The experiment is designed to examine the small-sample properties of tests of fitted autoregressive and moving average models, to compare the performances of asymptotically equivalent procedures, to consider the effects on estimated significance levels and powers of testing against both appropriate and inappropriate alternatives, to…

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针对非嵌套备择模型的精确检验AI 解读

This note applies the results of Milliken and Graybill (1970) to non-nested regression models. A test proposed by Fisher and McAleer (1981) is shown to have the t-distribution in small samples. An extended version of that test is developed for testing a model against several non-linear non-nested alternatives, and is shown to have the central F-distribution.

针对非嵌套备择模型的精确检验AI 解读

The results of Milliken & Graybill (1970) are used to develop a general procedure for obtaining exact tests of a linear model against several nonnested and nonlinear alternatives simultaneously. The procedure may be extended to test a null model against alternatives in which the dependent variable is subjected to different data transformations. Arguments are presented in favour of multiple tests.

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