What is the impact of autocorrelation on the likelihood of rejecting the nullhypothesis of no statistical significance of the model estimates?(a) It increases the likelihood of rejecting the null hypothesis.(b) It decreases the likelihood of rejecting the null hypothesis.(c) It has no effect on the likelihood of rejecting the null hypothesis.(d) It makes the estimates biased and increases the likelihood of rejecting the nullhypothesis.(e) It makes the estimates unbiased and decreases the likelihood of rejecting thenull hypothesis.

Autocorrelation, also known as serial correlation, is a statistical phenomenon where a variable is…

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ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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2. Consider the following regression model and the result of estimation: distance Bo + B,angle + u %3D Where: distance = distance (in feet) traveled by a baseball, angle = the angle (in degrees) the baseball was hit, %3! u= regression error. Dependent Variable: DISTANCE Method: Least Squares Sample: 1 13 Included observations: 13 Variable Coefficient Std. Error t-Statistic Prob. C. ANGLE 32.93084 0.785542 5.146819 1.981191 0.0003 0.0731 169.4891 1.556309 a) Breusch-Godfrey test has been performed that produced the following result. Discuss the test result. Breusch-Godfrey Serial Correlation LM Test: Null hypothesis: No serial correlation at up to 2 lags F-statistic 6.534685 Prob. F(2,9) 7.698535 Prob. Chi-Square(2) 0.0177 0.0213 Obs R-squared b) RESET test has been performed that produced the following result. Discuss the test result. Ramsey RESET Test Equation: EQ01 Specification: DISTANCE C ANGLE Omitted Variables: Powers of fitted values from 2 to 3 Value 475.8260 60.71504 df…
Problem 5. Based on a sample of 21 Monitoring the Future respondents (see table below), we present their racial/ethnic background and the number of school days missed in the past 4 weeks. White Black Hispanic 4 1 4 5 2 3 3 2 5 4 1 1 4 3 5 4 4 2 6 3 2 Complete the 5-step model for these data, and set alpha at 0.05. If alpha were set at 0.01, would your decision change? Explain.
The data below represent commute times (in minutes) and scores on a well-being survey. Complete parts (a) through (d) below. Commute Time (minutes), x Well-Being Index Score, y 5 72 105 20 25 35 60 69.2 68.0 67.5 67.1 65.9 66.0 63.8 (a) Find the least-squares regression line treating the commute time, x, as the explanatory variable and the index score, y, as the response variable. ŷ=x+ (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. First interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. OA. For every unit increase in commute time, the index score falls by (Round to three decimal places as needed.) OB. For every unit increase in index score, the commute time falls by (Round to three decimal places as needed.) 1 D. For an index score of zero, the commute time is predicted to be (Round to three decimal places as needed.) on average. on average. OC. For a commute time…
Consider the regression model Yi=bot Bi Xitui Suppose that you know Bo = 0. Derive the formula for the least squares estimator of B₁. The least squares objective function is O A. n O B. O C. O D. E (Yi-bo-b1Xi) i=1 n Σ (Yi-bo-biXi) i=1 2 n Σ (v₁²-bo-b₁x₁²) i=1 n E (Yi-bo-b+Xi) 3 i=1
If the model y = ßo + ß1x1 + ß2x2 + v satisfies the first Gauss-Markov assumptions, then v has: a. a zero mean and is correlated with only x1 b. C. a zero mean and is correlated with x₁ and x2 a zero mean and is correlated with only x2 d. a zero mean and is uncorrelated with X1 and X2 a. a O b. b О с. C ○ d. d
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In the model Y = Bo +B 1X 1 + B 2X 2 + 8, which of these parameters represents a coefficient of an independent variable? the Y the X1 the B1 the e
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Which of the following is true of heteroskedasticity? a) The R-squared statistic is affected by the presence of heteroskedasticity b) Heteroskedasticty causes inconsistency in the Ordinary Least Squares estimators c) The OLS estimators are not the best linear unbiased estimators if heteroskedasticity is present d) It is not possible to obtain F statistics that are robust to heteroskedasticity of an unknown form
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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
In multiple regression model: what is it means for a variable to be significant? Explain the meaning of the significant variable.

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