| 模型 | 模型答案 | 正确答案 |
|---|---|---|
| 金声玉亮2.0 | B. The variables are not cointegrated. The Engle-Granger test is used to determine if two or more time series are cointegrated, meaning that they have a long-run equilibrium relationship. The null hypothesis of the Engle-Granger test is that the variables are not cointegrated, meaning that there is no long-run equilibrium relationship between them. If the null hypothesis is rejected, it suggests that the variables are cointegrated. |
B |
| deepseekr1 | B. The variables are not cointegrated **Answer:** B |
B |
| gpto1 | B | B |
| GPT-4o | B. The variables are not cointegrated | B |
| llama3.1-70B-Instruct | B |
B |
| llama3.1-405B-Instruct | B. The variables are not cointegrated. The Engle-Granger test is used to determine if two or more time series are cointegrated, meaning that they have a long-run equilibrium relationship. The null hypothesis of the Engle-Granger test is that the residuals of the cointegrating regression are non-stationary, which implies that the variables are not cointegrated. If the null hypothesis is rejected, it suggests that the residuals are stationary, and therefore the variables are cointegrated. |
B |
| DeepSeek-Coder-V2 | B | B |
| Qwen2-72B-Instruct | B. The variables are not cointegrated | B |
| baichuan4 | B. The variables are not cointegrated | B |
| doubao | B. The variables are not cointegrated. The Engle-Granger test is used to test for cointegration. The null hypothesis of the Engle-Granger test typically assumes that the variables are not cointegrated. |
B |
| minimax | B. The variables are not cointegrated | B |
| kimi | B. The variables are not cointegrated | B |
| wenxinyiyan | B Explanation: The Engle-Granger test, also known as the Augmented Dickey-Fuller (ADF) test applied to the residuals, is used to test for the presence of a unit root in the residuals of a regression model. If the null hypothesis of a unit root in the residuals cannot be rejected, it suggests that the regression model may be misspecified, possibly due to omitted variables or a misspecified functional form. In the context of cointegration, if two or more time series are cointegrated, it means that although each series may be non-stationary individually, there exists a linear combination of them that is stationary. The Engle-Granger test on the residuals of a potentially cointegrating regression tests whether the residuals are stationary. The null hypothesis of the Engle-Granger test is that the residuals have a unit root, implying non-stationarity. If we reject the null hypothesis, it suggests that the residuals are stationary, which supports the cointegration relationship between the variables in the regression model. Therefore, when applied to residuals: * Rejecting the null hypothesis (i.e., finding that the residuals are stationary) supports the idea that the variables are cointegrated. * Failing to reject the null hypothesis (i.e., finding that the residuals have a unit root) suggests that the variables may not be cointegrated as assumed in the model. Since the question asks about the interpretation of the null hypothesis specifically, it is that the residuals have a unit root, which implies that the variables may not be cointegrated as postulated in the regression model. Hence, the answer is B: The variables are not cointegrated. This reflects the fact that under the null hypothesis of the Engle-Granger test, the residuals are assumed to be non-stationary, indicating a potential problem with the cointegration assumption in the model. |
B |
| zhipu | B. The variables are not cointegrated In the Engle-Granger test, the null hypothesis states that the residuals from the potentially cointegrating regression are non-stationary, implying that the variables are not cointegrated. If the null hypothesis is rejected, it suggests that the residuals are stationary, indicating that the variables are cointegrated. |
B |
| gpto1 | B | B |