开发者:上海品职教育科技有限公司 隐私政策详情

应用版本:4.2.11(IOS)|3.2.5(安卓)APP下载

FrankSun · 2021年10月09日

麻烦解答一下

* 问题详情,请 查看题干

NO.PZ201709270100000502

问题如下:

2. Based on the regression output in Exhibit 1, the first-differenced series used to run Regression 2 is consistent with:

选项:

A.

a random walk.

B.

covariance stationarity.

C.

a random walk with drift.

解释:

B is correct. The critical t-statistic at a 5% confidence level is 1.98. As a result, neither the intercept nor the coefficient on the first lag of the first-differenced exchange rate in Regression 2 differs significantly from zero. Also, the residual autocorrelations do not differ significantly from zero. As a result, Regression 2 can be reduced to yt = εt with a mean-reverting level of b0/(1 b1) = 0/1 = 0.

Therefore, the variance of yt in each period is Var(εt) = σ2. The fact that the residuals are not autocorrelated is consistent with the covariance of the times series, with itself being constant and finite at different lags. Because the variance and the mean of yt are constant and finite in each period, we can also conclude that yt is covariance stationary.

题干描述“neither the intercept nor the coefficient on the first lag of the first-differenced exchange rate in Regression 2 differs significantly from zero”,这句话的意思是方程 yt=b0+b1yt-1+εt的系数假设检验结果为:b0=0,b1=0。

为什么呢?

1 个答案

星星_品职助教 · 2021年10月10日

同学你好,

你列出来的这句话已经说了截距和自变量(the first lag)的系数都不是(neither)“ differs significantly from zero”,即结论为b0=0,b1=0

  • 1

    回答
  • 0

    关注
  • 615

    浏览
相关问题

NO.PZ201709270100000502 问题如下 2. Baseon the regression output in Exhibit 1, the first-fferenceseries useto run Regression 2 is consistent with: A.a ranm walk. B.covarianstationarity. C.a ranm walk with ift. B is correct. The critict-statistic a 5% confinlevel is 1.98. a result, neither the intercept nor the coefficient on the first lof the first-fferenceexchange rate in Regression 2 ffers significantly from zero. Also, the resiautocorrelations not ffer significantly from zero. a result, Regression 2 creceto yt = εt with a mean-reverting level of b0/(1 – b1) = 0/1 = 0.Therefore, the varianof yt in eaperiois Var(εt) = σ2. The faththe resials are not autocorrelateis consistent with the covarianof the times series, with itself being constant anfinite fferent lags. Because the variananthe meof yt are constant anfinite in eaperio we calso conclu thyt is covarianstationary. 为什么不是ranm walk with a aft ,题目中t统计值为0.4504 ,接受H0:G=0,存在单位根,请助教讲解答疑

2024-09-03 16:29 1 · 回答

NO.PZ201709270100000502 问题如下 2. Baseon the regression output in Exhibit 1, the first-fferenceseries useto run Regression 2 is consistent with: A.a ranm walk. B.covarianstationarity. C.a ranm walk with ift. B is correct. The critict-statistic a 5% confinlevel is 1.98. a result, neither the intercept nor the coefficient on the first lof the first-fferenceexchange rate in Regression 2 ffers significantly from zero. Also, the resiautocorrelations not ffer significantly from zero. a result, Regression 2 creceto yt = εt with a mean-reverting level of b0/(1 – b1) = 0/1 = 0.Therefore, the varianof yt in eaperiois Var(εt) = σ2. The faththe resials are not autocorrelateis consistent with the covarianof the times series, with itself being constant anfinite fferent lags. Because the variananthe meof yt are constant anfinite in eaperio we calso conclu thyt is covarianstationary. 具体的视频讲解在哪里可以找到

2024-08-25 11:28 1 · 回答

NO.PZ201709270100000502 问题如下 2. Baseon the regression output in Exhibit 1, the first-fferenceseries useto run Regression 2 is consistent with: A.a ranm walk. B.covarianstationarity. C.a ranm walk with ift. B is correct. The critict-statistic a 5% confinlevel is 1.98. a result, neither the intercept nor the coefficient on the first lof the first-fferenceexchange rate in Regression 2 ffers significantly from zero. Also, the resiautocorrelations not ffer significantly from zero. a result, Regression 2 creceto yt = εt with a mean-reverting level of b0/(1 – b1) = 0/1 = 0.Therefore, the varianof yt in eaperiois Var(εt) = σ2. The faththe resials are not autocorrelateis consistent with the covarianof the times series, with itself being constant anfinite fferent lags. Because the variananthe meof yt are constant anfinite in eaperio we calso conclu thyt is covarianstationary. yt = εt 为什么不是随机游走

2024-08-09 22:28 1 · 回答

NO.PZ201709270100000502 问题如下 2. Baseon the regression output in Exhibit 1, the first-fferenceseries useto run Regression 2 is consistent with: A.a ranm walk. B.covarianstationarity. C.a ranm walk with ift. B is correct. The critict-statistic a 5% confinlevel is 1.98. a result, neither the intercept nor the coefficient on the first lof the first-fferenceexchange rate in Regression 2 ffers significantly from zero. Also, the resiautocorrelations not ffer significantly from zero. a result, Regression 2 creceto yt = εt with a mean-reverting level of b0/(1 – b1) = 0/1 = 0.Therefore, the varianof yt in eaperiois Var(εt) = σ2. The faththe resials are not autocorrelateis consistent with the covarianof the times series, with itself being constant anfinite fferent lags. Because the variananthe meof yt are constant anfinite in eaperio we calso conclu thyt is covarianstationary. 老师,还是不太明白,题目中“Conclusion 1: The varianof xt increases over time.”,不是说明Xt方差不稳定吗,为什么会选B呢?

2023-07-28 17:18 1 · 回答

NO.PZ201709270100000502 问题如下 2. Baseon the regression output in Exhibit 1, the first-fferenceseries useto run Regression 2 is consistent with: A.a ranm walk. B.covarianstationarity. C.a ranm walk with ift. B is correct. The critict-statistic a 5% confinlevel is 1.98. a result, neither the intercept nor the coefficient on the first lof the first-fferenceexchange rate in Regression 2 ffers significantly from zero. Also, the resiautocorrelations not ffer significantly from zero. a result, Regression 2 creceto yt = εt with a mean-reverting level of b0/(1 – b1) = 0/1 = 0.Therefore, the varianof yt in eaperiois Var(εt) = σ2. The faththe resials are not autocorrelateis consistent with the covarianof the times series, with itself being constant anfinite fferent lags. Because the variananthe meof yt are constant anfinite in eaperio we calso conclu thyt is covarianstationary. 请问本题是否直接可以从b1判断,即因为题目中b1给了不等于1,所以不是unit root或者说是 covariance-stationary?

2023-04-12 09:41 1 · 回答