1．rvin Greene is interested in modeling the sales of the retail industry. He collected data on aggregate sales and found the following: Salest = 0.345 + 1.0 Salest-1 The standard error of the slope coefficient is 0.15, and the number of observations is 60. Given a level of significance of 5 percent, which of the following can we NOT conclude about this model? A) The slope on lagged sales is not significantly different from one. B) The model has a unit root. C) The model is covariance stationary. D) There is a positive trend in sales over time. The correct answer was C) The test of whether the slope is different from one indicates failure to reject the null H0: b1=1 (t-critical with df = 58 is approximately 2.000, t-calculated = (1.0 - 1.0)/0.15 = 0.0). This is a 2-tailed test and we cannot reject the null since 0.0 is not greater than 2.000. This model is nonstationary because the 1.0 coefficient on Salest-1 is a unit root. Any time series that has a unit root is not covariance stationary which can be corrected through the first-differencing process. 2．ich of the following statements regarding unit roots in a time series is FALSE? A) A time series that is a random walk has a unit root. B) Time series with unit roots are common in economic and financial models. C) A time series with a unit root is not covariance stationary. D) Even if a time series has a unit root, the predictions from the estimated model are valid. The correct answer was D) 3． AR(1) autoregressive time series model: A) cannot be used to test for a unit root. B) can be used to test for a unit root, which exists if the slope coefficient is less than one. C) can be used to test for a unit root, which exists if the intercept coefficient is greater than one. D) can be used to test for a unit root, which exists if the slope coefficient equals one. The correct answer was D) If you estimate the following model xt = b0 + b1 × xt-1 + et and get b1 = 1, then the process has a unit root and is nonstationarity. | 
发表于 2008-4-16 17:37
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