1.An analyst is trying to determine whether stock market returns are related to size and the market-to-book ratio, through the use of multiple regression. However, the analyst uses returns of portfolios of stocks instead of individual stocks in the regression. Which of the following is a valid reason why the analyst uses portfolios? The use of portfolios:
A) will increase the power of the test by giving the test statistic more degrees of freedom.
B) will remove the existence of serial correlation from the data, reducing the likelihood of type II error.
C) will remove the existence of multicollinearity from the data, reducing the likelihood of type II error.
D) reduces the standard deviation of the residual, which will increase the power of the test.
The correct answer was D)
The use of portfolios reduces the standard deviation of the returns, which reduces the standard deviation of the residuals.
2.An analyst is interested in forecasting the rate of employment growth and instability for 254 metropolitan areas around the United States. The analyst’s main purpose for these forecasts is to estimate the demand for commercial real estate in each metro area. The independent variables in the analysis represent the percentage of employment in each industry group. Regression of Employment Growth Rates and Employment Instability
on Industry Mix Variables for 254 U.S. Metro Areas |
| Model 1 | Model 2 | Dependent Variable | Employment Growth Rate | Relative Employment Instability | Independent Variables | Coefficient
Estimate | t-value | Coefficient
Estimate | t-value | Intercept | –2.3913 | –0.713 | 3.4626 | 0.623 | % Construction Employment | 0.2219 | 4.491 | 0.1715 | 2.096 | % Manufacturing Employment | 0.0136 | 0.393 | 0.0037 | 0.064 | % Wholesale Trade Employment | –0.0092 | –0.171 | 0.0244 | 0.275 | % Retail Trade Employment | –0.0012 | –0.031 | –0.0365 | –0.578 | % Financial Services Employment | 0.0605 | 1.271 | –0.0344 | –0.437 | % Other Services Employment | 0.1037 | 2.792 | 0.0208 | 0.338 |
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| R2 | 0.289 |
| 0.047 |
| Adjusted R2 | 0.272 |
| 0.024 |
| F-Statistic | 16.791 |
| 2.040 |
| Standard error of estimate | 0.546 |
| 0.345 |
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Based on the data given, which independent variables have both a statistically and an economically significant impact (at the 5% level) on metropolitan employment growth rates?
A) "% Construction Employment" and "% Other Services Employment" only.
B) "% Wholesale Trade Employment" and "% Retail Trade" only.
C) "% Manufacturing Employment," "% Financial Services Employment," "% Wholesale Trade Employment," and "% Retail Trade" only.
D) "% Construction Employment," "% Other Services Employment," "% Manufacturing Employment," and "% Financial Services Employment" only.
The correct answer was A)
The percentage of construction employment and the percentage of other services employment have a statistically significant impact on employment growth rates in U.S. metro areas. The t-statistics are 4.491 and 2.792, respectively, and the critical t is 1.96 (95% confidence and 247 degrees of freedom). In terms of economic significance, construction and other services appear to be significant. In other words, as construction employment rises 1%, the employment growth rate rises 0.2219%. The coefficients of all other variables are too close to zero to ascertain any economic significance, and their t-statistics are too low to conclude that they are statistically significant. Therefore, there are only two independent variables that are both statistically and economically significant: percentage of construction employment and the percentage of other services employment. Some may argue, however, that financial services employment is also economically significant even though it is not statistically significant because of the magnitude of the coefficient. Economic significance can occur without statistical significance if there are statistical problems. For instance, the multicollinearity makes it harder to say that a variable is statistically significant.
3.The coefficient standard error for the independent variable “% Construction Employment” under the relative employment instability model is closest to:
A) 0.0818.
B) 0.3595.
C) 2.2675.
D) 12.2216.
The correct answer was A)
The t-statistic is computed by t-statistic = slope coefficient/coefficient standard error. Therefore, the coefficient standard error =
= slope coefficient/the t-statistic = 0.1715/2.096 = 0.0818.
4.Which of the following best describes how to interpret the R2 for the employment growth rate model? Changes in the value of the:
A) independent variables cause 28.9% of the variability of the employment growth rate.
B) independent variables explain 28.9% of the variability of the employment growth rate.
C) employment growth rate cause 28.9% of the variability of the independent variables.
D) employment growth rate explain 28.9% of the variability of the independent variables.
The correct answer was B)
The R2 indicates the percent variability of the dependent variable that is explained by the variability of the independent variables. In the employment growth rate model, the variability of the independent variables explains 28.9% of the variability of employment growth. Regression analysis does not establish a causal relationship.
5.Using the following forecasts for Cedar Rapids, Iowa, the forecasted employment growth rate for that city is closest to: Construction employment
| 10% | Manufacturing | 30% | Wholesale trade
| 5% | Retail trade
| 20% | Financial services
| 15% | Other services
| 20% |
A) 3.22%.
B) 3.15%.
C) 5.54%.
D) 5.61%.
The correct answer was B)
The forecast uses the intercept and coefficient estimates for the model. The forecast is:
= –2.3913 + (0.2219)(10) + (0.0136)(30) + (–0.0092)(5) + (–0.0012)(20) + (0.0605)(15) + (0.1037)(20) = 3.15%
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发表于 2008-4-12 16:12
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