ENGR.ECONOMIC ANALYSIS
14th Edition
ISBN: 9780190931919
Author: NEWNAN
Publisher: Oxford University Press
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- "In the regression model InY=b0+b1*InX+u, the coefficient b1 is interpreted as" O the intercept O A covariance O A regressor O An elasticityarrow_forwardThe measure of standard error can also be applied to the parameter estimates resulting from linear regressions. For example, consider the following linear regression equation that describes the relationship between education and wage: WAGE: = Bo + B₁ EDUC; + &i where WAGE; is the hourly wage of person i (i.e., any specific person) and EDUC; is the number of years of education for that same person. The residual ₂ encompasses other factors that influence wage, and is assumed to be uncorrelated with education and have a mean of zero. Suppose that after collecting a cross-sectional data set, you run an OLS regression to obtain the following parameter estimates: WAGE;= -10.7+ 3.1 EDUC; If the standard error of the estimate of B₁ is 1.04, then the true value of B₁ lies between grows, you would expect this range to in size. and . As the number of observations in a data setarrow_forwardThe data for this question is given in the file 1.Q1.xlsx(see image) and it refers to data for some cities X1 = total overall reported crime rate per 1 million residents X3 = annual police funding in $/resident X7 = % of people 25 years+ with at least 4 years of college (a) Estimate a regression with X1 as the dependent variable and X3 and X7 as the independent variables. (b) Will additional education help to reduce total overall crime (lead to a statistically significant reduction in crime)? Please explain. (c) Will an increase in funding for the police departments help reduce total overall crime (lead to a statistically significant reduction in total overall crime)? Please explain. (d) If you were asked to recommend a policy to reduce crime, then, based only on the above regression results, would you choose to invest in education (local schools) or in additional funding for the police? Please explain.arrow_forward
- You extract approximately 5,000 observations from the Current Population Survey (CPS) and estimate the following regression function: AHE= 3.32 -0.45 x Age, R² =0.02, SER= 8.66 (1.00) (0.04) where AHE is average hourly earnings, and Age is the individual's age. Given the specification, your 95% confidence interval for the effect of changing age by 5 years is approximately: OA. [$2.32, $4.32]. B. [$1.86, $2.64]. C. [$1.35, $5.30]. D. Cannot be determined given the information provided.arrow_forwardSuppose you work for North Dakota DNR Grand Forks office. DNR would like to know whether they should set aside some conservation land, previously slated to be logged, for a potential state park. You are helping do a travel-cost analysis to estimate the benefits of the set-aside. You collected data from 500 visitors who came to a state park in a neighboring state. You ran regression analysis and controlled for these visitors' age, income, education, employment status, and other important factors that might affect the number of visits. With all the information, you have developed the following relationship: (a) (b) Cost to Visit $20 $40 $80 # of Visits Per Person Per Year 8 6 2 Graph the demand curve for the number of visits as a function of the "price" -- the travel cost. Based on demographic information about the people living in the vicinity of the proposed park, you have estimated that 10,000 people will take an average of 4 visits per year. For the average person, calculate: (1) The…arrow_forwardIn the regression equation, what is B0? Group of answer choices the population slope the sample y-intercept the sample slope the population y-interceptarrow_forward
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