For the specific national income model given Y= C + I, + G, C=60 + 0.9(Y-T) T=30+0.2Y where I, =31 and G, = 20, find the values of the endogenous variables solving by matrix inversion
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For the specific national income model given
Y= C + I, + G,
C=60 + 0.9(Y-T)
T=30+0.2Y
where I, =31 and G, = 20, find the values of the endogenous variables solving by matrix inversion
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Solved in 2 steps
- Write first-order model relating E(y) to four quantitative independent variables.Suppose the researcher considers the following model : Wage = Bo+B,Female + u, and runs OLS, using wage data on 250 randomly selected male workers and 280 female workers. The researcher has obtained the estimated equation as Wage = 15 (1.00) 3 Female, R = 0.05. (0.5) In the equation, Wage is measured in dollars per hour, Female is a binary variable that is equal to 1 if the person is a female and O if the person is a male. The numbers in the parentheses are the standard errors of the coefficients. Which Statement is NOT correct? The coefficient of Female, -3.00, is statistically significant at 5%. O The p-value for the test that Ho: B = 0, H : B 0 is less than 0.05. This regression may suffer omitted variable bias. R Since insignificant. is too low, the wage difference between men and women is The researcher can increase R- by including more regressors in the model.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
- Consider the following Cobb-Douglas production function for the bus transportation system in a city: Q = Lβ1Fβ2Bβ3 Where L = labour input in worker hours F = fuel input in gallons B = capital input in number of buses Q = output measured in millions of bus miles Suppose that the parameters (α, β1, β2 and β3) of this model were estimated using annual data for the past 25 years. The following results were obtained: β1 = 0.45, β2 = 0.20 and β3 = 0.30 a. Determine the (i) labour, (ii) fuel, and (iii) capital-input production elasticitiesA 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 0Bureau of Economic Analysis in the USA is responsible for construction and maintenance of national income and product accounts (NIPA). Measurement began in the 1930s due to frustration of Roosevelt and Hoover trying to design policies to combat the Great Depression. Simon Kuznets (Nobel laureate) was commissioned to develop initial methodology and estimates. In 1947, the process became much more consistent. Methodologies have frequently been changed (improved?) as a result of advances in economics, accounting, and data collection. Past data are then revised to reflect new definitions. On the following information, calculate GNP at factor cost. Whether GNPFC derive from income method equivalent to expenditure method? S.No. Items Rs. (In Crores) 1 Private final consumption expenditure 1000 2 Net domestic capital formation (Investment) 200 3 Profit 400 4 Compensation of employers (Wages and salaries) 800 5 Rent 250 6 Government final consumption expenditure…
- Consider the following regression model: wage-Bi+Bamalerpumalexedu Buedutu, where wage is the hourly wage measured in dollars: male is a dummy variable for males edu is the years of education: maleedu is the interaction of male and edu variables. The parameter estimates for B parameters are P-1.27: B1.29: Br-0,16: Be-0.82. What is the predicted marginal effect of years of education for males?Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 3200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 69? Answer:The following relationships between wage (W) and education (EDU) are estimated using a sample of 100 individuals. Excel results are reported below Model 1: W=4.3-0.07 EDU+0.9 EDU2 ; se (4.9) (0.07) (0.03) SSR=0.74; SSE=22.7; SST=23.44; Model 2: W=894-21.96 EDU+0.6 EDU2-75.0 What2+6.5 What3; se (885) (25.54) (0.06) (85.0) (3.2) SSR=0.82; SSE=21.68; SST=22.50; where W is wage and What is the fitted value of W. 1. In Model 1 test the hypothesis that education has no effect on wage 2. Test the adequacy of model W=B1+B2 EDU+B3 EDU?
- The OLS estimators of the coefficients in multiple regression will have omitted variable bias: a. i only if an omitted determinant of b. if an omitted variable is correlated with at least one of the regressors, even though it is not a determinant of the dependent variable. C. only if the omitted variable is not normally distributed. d. if an omitted determinant of is a continuous variable. Y; i is correlated with at least one of the regressors. e. if the degree of freedom is less than 50.We are interested in understanding consumption of pork in the U.S. so we run a regression of annual per capita consumption of pork on a series of independent variables using data from 1990 to 2018 and obtain the following regression results (standard errors in parenthesis) CPt = -330.3 + 49.1 In Inct − 0.34 PPt + 0.33PBt (7.40) (0.13) (0.12) R²=0.71 DW=0.94 Where CPt is the annual per capita pounds of pork consumed in the U.S. in year t InInc, is the log of per capita disposable income in the U.S. in year t PP, is the average annualized real wholesale price of pork in the U.S. in year t (in cents per pound) PB, is the average annualized real wholesale price of beef in the U.S. in year t (in cents per pound) a. Interpret the partial slope coefficients. Does the sign on the coefficients agree or disagree with your a priori assumptions? Explain b. Using a two-sided test at the 5% significant level, determine if the partial slopes are statistically significant. c. Test the presence of…Romer Model Exercise: Consider the Romer model, Y = A,Nyt, AAt+1 Ão = 10,1 = 0.01, z = 0.035, Ñ = 100. ZAĄNat, and parameter values are: (a) What is the growth rate of GDP per capita? What is the per capita GDP at period 60, Yt=60? (b) Suppose at period 60, the number of researchers decrease by 50% permanently. Draw a graph to show the impact. What is the value of per capita GDP, y4=60, now? (c) Suppose now the production function is still Y; = A¿Nyt, but the accumulation of ideas becomes AAt+1 = ZA?$ Nat. What is the growth rate of ideas? (d) Following from (c), what is the growth rate of output per capita at period 1?