I have a data set including annual real oil prices (variable P) for the period 1883-1970. I run the Stata command: .dfuller oil What is the formula for the regression that is being run by this command? Ο ΔΡ. β.Ρ. Ο ΔΡ.βο + βαρι Ο Ρίβο βιΔΡΑ Ο Ρ, Β.ΔΡ. Ρ,-β.ΔΡ.+β ΔΡ. 1

I have a data set including annual real oil prices (variable P) for the period 1883-1970. I run the Stata command: .dfuller oil What is the formula for the regression that is being run by this command? Ο ΔΡ. β.Ρ. Ο ΔΡ.βο + βαρι Ο Ρίβο βιΔΡΑ Ο Ρ, Β.ΔΡ. Ρ,-β.ΔΡ.+β ΔΡ. 1

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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An analyst working for your firm provided an estimated log-linear demand function based on the natural logarithm of the quantity sold, price, and the average income of consumers. Results are summarized in the following table: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept LN Price LN Income df 0.968 0.937 0.933 0.003 30 SS MS F 2 0.003637484 0.001818742 202.48598 0.000242516 8.98206E-06 27 29 0.00388 Coefficients Standard Error 0.57 0.00 0.13 0.51 -0.08 0.15 t Stat 0.90 -19.50 1.13 P-value 0.37 0.00 0.27 Significance F 5.55598E-17 Lower 95% -0.65 -0.09 -0.12 How would a 4 percent increase in income impact the demand for your product? Demand would increase by 60 percent. Demand would increase by 0.6 percent. Demand would decrease by 60 percent. Demand would decrease by 0.6 percent. Upper 95% 1.68 -0.07 0.41
How Regression models are used for Forecasting purpose?
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Yi = B1 + B2xi2 + · · · + Brxik + ei, i = 1, . .., N, var (e; X) = var (y:|X) = o? Which property of linear regression model is most appropriate for the above regression? Select one: O a. heteroskedasticity O b. strict exogeneity c. autocorrelation O d. model mis-specification
7. The Stata data set "college_gpa" has data on students' college GPAS, high school GPAS, ACT scores, lectures skipped during the academic year, and other characteristics. We wish to examine the predictors of college GPAS. You must submit your do-file (commands). a) Regress college GPA on high school GPA and write the estimated regression line. b) Interpret the intercept of your regression in a sentence. Does this coefficient make sense?n Explain c) Interpret the coefficient on high school GPA in a sentence. Does this coefficient make sense? Explain. reg colGPA hsGPA Source df MS Number of obs 141 %3D F(1, 139) 33.80 Model 5.58478164 1 5.58478164 Prob > F e.0000 Residual 22.9668501 139 .165229138 R-squared Adj R-squared 0.1956 %3D 0.1898 %3D Total 28.5516318 140 .203940227 Root MSE .40648 colGPA Coef. Std. Err. t P>|t| [95% Conf. Interval] hsGPA .6242948 .1073816 5.81 0.000 .4119822 .8366073 _cons 890254 3669263 2.43 0.017 647755
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5. Choose the correct answer!