(a)Heteroscedasticity can lead to A. smaller t values B. all of the statements are correct C. larger t values D. more narrow confidence intervals E. wider confidence intervals F. none of the statements is correct (b)Homoscedasticity is likely to be found in regressions dealing with A. high income countries only B. All the options are correct C. None of the options is correct D. low income countries only E. medium income countries only

(a)Heteroscedasticity can lead to A. smaller t values B. all of the statements are correct C. larger t values D. more narrow confidence intervals E. wider confidence intervals F. none of the statements is correct (b)Homoscedasticity is likely to be found in regressions dealing with A. high income countries only B. All the options are correct C. None of the options is correct D. low income countries only E. medium income countries only

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

See similar textbooks

Similar questions

E3
1. Consider the following regression model y = x3 + u. (1) Let 3 denote the Ordinary Least Squares (OLS) estimator of B. The so-called Gauss- Markov assumptions are: • MLR.1: The true model in the population is given by (1). • MLR.2: We have a random sample of n observations {(ri, Yi), i = 1, 2, .., n} following the population model in (1). .... • MLR.3: No one explanatory variable can be written as a linear combination of the remaining explanatory variables that is, there is no perfectcollinearity. • MLR.4: In the population, the error u has an expected value of zero given any values of the explanatory variables, that is Elu|x] = 0. • MLR.5: In the population, the error u has the same variance given any values of the explanatory variables, that is Var[u|x] = o? , an unknown finite, positive constant. In the following scenarios, state whether B is an unbiased and consistent estimator of 3, and provide a brief justification for your answer in each case - but no formal mathematical…
Consider a simple linear regression model, y = Bo + Bix+u.. What does the zero conditional mean assumption imply? The estimated average value of 31 is zero The expected value of the explained variable, y, is zero, regardless of what the value of the explanatory variable, x, is The expected value of the error term, u, is zero, regardless of what the value of the explanatory variable, x, is The estimated average value of 30 is zero
Q1. Suppose the government is considering an increase in the toll on a certain stretch of highway from $3 to $4. At present, 1 million cars per week use that highway stretch; after the toll is imposed, the number of cars per week will change according to its price elasticity of demand of -0.8 (this elasticity value is estimated based on the initial-value method). If the marginal cost of highway use is constant (i.e., the supply curve is horizontal) and equal to $3 per car, what is the net annual cost to society attributable to the increase in the toll? (your answer must be rounded off to the nearest million dollars per year, i.e., no decimal places; there are 52 weeks in a year)
When Y is regressed on X, B, > 0, sx+ 0, sy # 0, and the fraction of the variation in Y explained by the least-squares regression of Y on X does not equal 1. In this example, the sum of the squares of the deviations of the actual Y-values from their mean would definitely be greater than the sum of the squares of the deviations of the predicted Y-values from their mean. 1 A) B) true false 4. When Y is regressed on X, the sample slope is negative, sx + 0, sy + 0, and Y; = Y; for every observation. In this example, the sum of the squares of the deviations of the predicted Y-values from their mean would definitely be less than the sum of the squares of the deviations of the actual Y-values from their mean. A) В) true false 3.
Write first-order model relating E(y) to four quantitative independent variables.
With Panel Data, if we assume that the individual effects vi are not correlated with the regressors Xit (i.e. E(vi|Xit) = 0), which one of the following statements is correct: The Fixed Effects estimator is not consistent. Both the OLS and the Random Effects estimators are not consistent. The OLS estimator is not consistent, but the Random Effects estimator is consistent. The OLS and the Random Effects estimator are consistent. All of the above. None of the above
A researcher investigating whether government expenditure crowds out investment estimates a regression on data for 30 countries. I-investment; G-government recurrent expenditure; Y=gross domestic product; all measured in $US billion. P= population measured in million. Standard errors are in parentheses. Î= 18.10 (7.79) R² = 0.99 1.07G + 36Y (0.14) (0.02) She suspects that countries with higher GDP may have more variability in their investment. She sorts the observations by increasing size of gdp per capita (Y)and estimates the regression again for the 11 countries with the lowest gdp(Y)and the 11 countries with the largest gdp(Y). The RSS1 from the first regression is 7186. The RSS2 from the second regresison is 28101. Perform a Goldfeld-Quandt Test at a 5% significance level. a. The test statistic for this test is 0.256 b. The critical value defining the rejection region for Ho is 3.18 c. Is there heterscedasticity? Yes=1 or No-0. The answer is 0
Explain what multicollinearity . What are the main problems that multicollinearity creates for OLS estimation results ? Give two ways to detect multicollinearity problem and the hypothesis that are tested ?
Question 8/27 With Logit model, an estimated econometric model has information as follows: Dependent variable is the probability to be in the labor force (inlbforce): Inlbforce: =1 if being in the labor force; 2 independent variables: Age: age in years; Educ: education level; Kids6: number of kids less than 6 years old. All indep variables are statistically significant. The estimated coefficient of Age equals -0.035; The estimated coefficient of Edh equals 0.0261; The estimated coefficient of Kids6 equals -0.103; Intercept coefficient equals-1.283 The right value of z when age = 45, educ = 13, kids6 = 2 equals: O -2.7247 O -3.7256 O 3.7247 Go to question * PREVIOUS NEXT > Address
Q. 30 The t test can be used for testing the JOINT significance of ALL explanatory variables x2, x3, and x4 in a multiple regression model. O True O False
Describe the recommended approach towards determining model specification.How does the R2 help in determining an appropriate model? Is theideal model the one with the highest R2? Should a regressor be included in the model if it increases the model R2?