2.9. Based on price statistics of 26 properties sold (Y USD/m² ) linear correlation coefficients were calculated with potential explanatory variables X,,X3,X3,X4. Vector Ro and matrix R are listed below 0,3 0,6 0,5 1 Ro R = -0,7 0,6 0,6 1 [- 0,4_ [0,8 0,8 0,7 1] The critical value of the linear correlation coefficient was assumed to be r*=0, 55. Perform the selection of explanatory variables for the model using the correlation coefficient analysis method.

2.9. Based on price statistics of 26 properties sold (Y USD/m² ) linear correlation coefficients were calculated with potential explanatory variables X,,X3,X3,X4. Vector Ro and matrix R are listed below 0,3 0,6 0,5 1 Ro R = -0,7 0,6 0,6 1 [- 0,4_ [0,8 0,8 0,7 1] The critical value of the linear correlation coefficient was assumed to be r*=0, 55. Perform the selection of explanatory variables for the model using the correlation coefficient analysis method.

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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Consider the following estimated regression for 220 home sales from a community in 2019 (estimated standard errors in parentheses) Price = 119.2 + 0.485BDR + 23.4Bath + 0.156Hsize + 0.002Lsize + 0.09Age (0.011) (2.61) (8.94) (0.00048) (0.311) R2 = 0.72 where Price denote the selling house price (measured in $1000s), BDR denote the number of bedrooms, Bath denote the number of bathrooms, Hsize denote the size of the house (in square feet), Lsize denote the lot size (in square feet), and Age denote the age of the house (in years).
(a) Obtain the value of x in the equation: 2x + 1 = e3 (b) Consider the following equation: y = x7x-4. Solve for the value of y when x = 0.8.
Using Excel, Big Poppa's estimates the weekly demand function for its BBQ sandwiches to be QD = 1,385.63 - 22.30P. In reference to the estimated slope coefficient for price, which of the following standard errors gives you the most confidence (i.e., largest t-statistics) that the estimated slope coefficient is close to the true slope coefficient? 37) _____ A) -22.0 B) 2.15 C) 1.12 D) 22.0 Could you put some explanations please.
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…
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(e) Suppose you have been given the following ordinary least squares (OLS) regression result. Estimated Long Run Coefficients using the ARDL Approach ARDL (1,2,2,2,0,2) selected based on Akaike Information Criterion Dependent variable is LY 33 observations used for estimation from 1987 to 2019 T-Ratio [Prob.] 4.6671[0.000] 4.6678[0.051] 7.9897[0.043] -4.802[0.009] 2.3898[0.028] 1.0498[0.308] Regressor Coefficient Standard Error 0.36068 0.45447 LK 0.077280 LM 0.097363 0.48751 -0.41208 0.19057 0.52521 LE 0.061017 LF 0.085800 LT 0.079744 C 0.500320 where, Y = Economic growth K = Capital M = Employment E = Electricity consumption F = Foreign direct investment T= Technology (i) Write the regression equation. Interpret the estimated coefficients. (ii) Which explanatory variables are significant at the 1%, 5% and 10% level? Which variables are insignificant? Briefly explain.
The following question refers to this regression equation (standard errors for each of the estimated coefficients are in parenthesis). Q=8,400-8" P+5" A+ 4** Px +0.05**1, (1,732) (2.29) (1.36) (1.75) (0.15) Q = Quantity demanded P = Price 1,100 Advertising expenditures, in thousands = 20 P = price of competitor's good = 600/= average monthly income 10,000 What is the advertising elasticity of demand? Round your answer to two decimal places. Your Answer: The t-statistic is computed by dividing the regression coefficient by the standard error of the coefficient. dividing the regression coefficient by the standard error of the estimate. dividing the standard error of the coefficient by the regression coefficient. dividing the R2 by the F-statistic. none of the specified answers are correct.
Q4. The Omantel firm has estimate the Sales of fibre internet connections in Oman with the related to advertising expenditure made by the company over the past 26 months. Following is the firm estimated results of the regression equation. DEPENDENT VARIABLE: Y R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 26 0.85121212 8.747 0.0187 PARAMETER STANDARD VARIABLE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 7.6 6.33232 1.200 0.2643969 3.53 0.52228 ? 0.0001428 a. What is the dependent and independent variables in the above regression equation of Omantel firm? b. Calculate the estimated t-ratio. Test the slope estimates for statistical significance at the 10 percent significance level. d. Interpret the coefficient of determination.
1) Production function for agricultural sector of a country is specified as the following, log Y=B1 + B2 log K+ ß3 log L+u. where Y represents wheat output, K capital stock and L employment (labor). The model is estimated using annual data over 1980-2020 (n=41) periods. The results are reported below. p-values are given in squared parentheses. loĝ Y = 4.17 +0.67 log K+ 0.35 log L p-value [0.015] [0.18] R² = 0.81 1.a) Test if each slope coefficient is significant individually (one by one) using the p-values in parentheses and interpret the results. (
Y 70 12 50 9 57 60 14 43 9 52 11 i. Find the estimators for Bi and B2 correct to decimal points and fit the regression equation for X and Y when X is the explanatory variable. Interpret the results from the obtained equation. calculate the sum of error squared. Find the variance of the sum square error ii. iii. iv. Find the standard error for B2 Find the coefficient of correlation and give its interpretation V. vi.
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