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经济时间序列能通过差分变得平稳吗？AI 解读

This paper considers a class of nonstationary varying coefficient autoregressive models which allow stochastic variability in the autoregressive root. It is argued that such models provide a better description of the behaviour of macroeconomic variables than fixed unit root autoregressive models as they allow more general forms of nonstationarity. We construct a test of the null hypothesis of a fixed unit root against the alternative of a fixed unit root against the…

时间序列差分平稳性的检验AI 解读

This paper addresses the problem of testing the hypothesis that an observed series is difference stationary. The alternative hypothesis is that the series is another nonstationary process; in particular, an autoregressive model with a random parameter is used. A locally best invariant test is developed assuming Gaussianity, and a representation of its asymptotic distribution as a mixture of Brownian motions is found. The performance of the test in finite samples is…

一种一致的单位根检验AI 解读

This article investigates several U.S. macroeconomic time series for the presence of a unit root using a newly developed test. This test has stationarity as its null hypothesis and the alternative is a unit-root process. The test is shown to be consistent and its asymptotic null distribution is determined. The authors' findings contrast sharply with those obtained via the standard unit-root tests.

非线性回归模型中的参数随机变动检验AI 解读

SUMMARY This paper addresses the problem of testing for purely random parameter variation in nonlinear regression models. Based on different approximations to the true density of the data, score-type tests are constructed and their asymptotic distributions are derived. The local power of the tests is investigated both theoretically and via Monte Carlo simulation. An empirical testing example, involving a well-known non-linear aggregate demand for money function, is also…

系数恒定性检验统计量的分布AI 解读

This paper investigates the distribution of the locally best invariant test for coefficient constancy, against the random walk alternative, in a regression model which may contain nonvarying coefficients. Unfortunately, the distribution of the locally best invariant test depends critically on the exogenous variables of the model, even asymptotically. A modification is suggested which has a known asymptotic distribution regardless of the regression effect.

若干系数恒定性检验统计量的分布AI 解读

This paper investigates the distribution of the locally best invariant test for coefficient constancy, against the random walk alternative, in a regression model which may contain nonvarying coefficients. Unfortunately, the distribution of the locally best invariant test depends critically on the exogenous variables of the model, even asymptotically. A modification is suggested which has a known asymptotic distribution regardless of the regression effect.

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基于普通最小二乘残差的异方差检验AI 解读

Two variants of a test for heteroscedasticity based on ordinary least squares residuals are proposed: a bounds test and an “exact” test. Both variants are parametric and make use of tables of the F distribution. Under a variety of circumstances, the power of the bounds test compares favorably with the powers of the tests of Goldfeld and Quandt, Theil, and Harvey and Phillips. The computational simplicity of the bounds test compared with other tests makes it a particularly…

摘要暂缺

异方差下的自相关：Durbin–Watson、Geary 与 Henshaw 检验的稳健性AI 解读

The paper reports on a Monte Carlo experiment investigating the effect of the simultaneous occurrence of autocorrelation and heteroscedasticity on the powers of the Durbin-Wateon, Geary and Henshaw tests.