(f) Regression line drawn by the method of Least square is called as the line of (g) Link Relatives method measures variations. (h) index is known as the ideal formula for constructing index numbers. (i) has assigned weights to the commodities on the basis of current year quantities in the construction of price index number. (i) In random method of sampling, the various items of the sample are selected from the Universe purely on a basis. Part – I| 2. Answer any four of the following questions within two or three sentences each : 4x4 16 %3D

(f) Regression line drawn by the method of Least square is called as the line of (g) Link Relatives method measures variations. (h) index is known as the ideal formula for constructing index numbers. (i) has assigned weights to the commodities on the basis of current year quantities in the construction of price index number. (i) In random method of sampling, the various items of the sample are selected from the Universe purely on a basis. Part – I| 2. Answer any four of the following questions within two or three sentences each : 4x4 16 %3D

Microeconomic Theory

12th Edition

ISBN:9781337517942

Author:NICHOLSON

Publisher:NICHOLSON

Chapter9: Production Functions

Section: Chapter Questions

Problem 9.6P

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Consider the following log-wage regression results for women (W) and men (M) where wages are predicted by schooling (S) and age (A). wW = 2.23 + 0.077Sw + 0.017Aw and wM = 2.33 + 0.0745SM + 0.026AM. Sample means for the variables by gender are: women average a logged wage of 3.90, 12.7 years of schooling, and 40.8 years-old; men average a logged wage of 4.53, 14.2 years of schooling, and 43.9 years-old. Decompose the raw difference in average logged wages using the Oaxaca-Blinder decomposition. Specifically, decompose the raw difference into the portion due to differences in schooling, differences in age, and the portion left unexplained, possibly due to gender discrimination.
An attempt was made to evaluate the inflation rate as a predictor of the spot rate in the German treasury bill market. For a sample of 79 quarterly observations, the estimated linear regressionŷ = 0.0027 + 0.7916xwas obtained, wherey = actual change in the spot ratex = change in the spot rate predicted by the inflation rateThe coefficient of determination was 0.097, and the estimated standard deviation of the estimator of the slope of the population regression line was 0.2759.a. Interpret the slope of the estimated regression line.b. Interpret the coefficient of determination.c. Test the null hypothesis that the slope of the population regression line is 0 against the alternative that the true slope is positive, and interpret your result.d. Test, against a two-sided alternative, the null hypothesis that the slope of the population regression line is 1, and interpret your result.
2. Which of the following types of regressions will always have a binary outcome variable? (A) Probit (B) Difference-in-differences (C) Regression discontinuity (D) (A) and (B) will both have binary outcome variables
Hello, please help me to solve the question (c) and (d) below.Consider this regression model (1) : Yt = β0 + β1 Ut + β2 Vt + β3 Wt + β4 Xt + εt ; where t= 1, ..., 75.We use OLS to estimate the parameters, producing the following model:Ŷt = 1.115 + 0.790 Ut − 0.327 Vt + 0.763 Wt + 0.456 Xt (0.405) (0.178) (0.088) (0.274) (0.017) Given that:R2 = 0.941; Durbin Watson stat DW = 1.907; RSS = 0.0757.(To answer the question, use the 5% level of significance, state clearly H0 and H1 that are tested, the test statistics that are used, and interpret the decisions.) (a) Describe the concepts of unbiasedness and efficiency. State the conditions required of regression (1) in order that the OLS estimators of the model parameters possess these properties. (b) Perform the following tests on the parameters of regression (1): (i) test whether the parameters β1, β2, β3 and β4 are individually statistically significant; (ii) test the overall significance of the regression model;…
Q5. Show that µY = Yµ − µY · 1. Data Mining Regression Evaluation chapter
As a manager of a small software retailing company, you are concerned with projected profit next year. While profit can be determined as the difference between sales and maintenance cost, or in symbols, P = S - M, where P is profit, S is sales, and M is maintenance cost including technical support. It is argues that when sales goes up so does maintenance cost because the cost of technical support will go up. Further, it is measured that the correlation between S and M is 0.8. Now given the figure that sales next year is expected to be $300 thousand with standard deviation of $4 thousand and maintenance cost is expected to be $150 thousand with standard deviation of $6 thousand, what would be the expected profit and its standard deviation you will include in your report?
Suppose that a coffee producing firm estimated the following regression of thedemand for its brand of coffee:Qc = 1.5 − 3.0Pc + 0.8Y + 2.0Pb − 0.6PS +1.2 Awhere Qc = sales of coffee brand C, in dollarsper pound Pc = price of coffee brand C,in dollars per poundY = personal disposable income, in millions of dollars per yearPb = price of the competitive brand of coffee, in dollarsper pound Ps = price of sugar, in dollars per poundA = advertising expenditures for coffee brand C, in hundreds of thousands ofdollars per year.Suppose also that this year, Pc = $2, Y = $2.5, Pb = $1.80,Ps = $1 and A =$1.a. Interpret the results of the estimated demand.b. Compute point price elasticity of demand for the firm’s brand of coffeewith respect to its price.c. Compute the cross-price elasticity of demand for coffee with respect to theprice of competitive coffee brand b.d. At the current price level, would it be viable for the firm to increase the pricelevel of its brand of coffee? Support your answer.…
It is known that the ABC oil company supplies consumers with 150 tons of products per day. The company produces only two types of products - gasoline and diesel fuel. The limiting transformation ratio of diesel fuel relative to gasoline is 0.5. a) Draw a line of the company's monthly production capacity for gasoline and diesel. b) With the advent of new technologies, production increased by 20%, and the availability of gasoline increased by 30%. Explain how the company's new product line differs from the previous one. c) If we put the gasoline production on the X-axis of the graph, what percentage of the slope capacity of the production line is different from the slope ratio of the previous production line?
Suppose output (Q) is related to labor (L) and capital (K) in the following nonlinear way: Q = aLbKc When taking log to this equation, it is transformed into a linear LnQ = lna + b ln(L) + c Ln (K) One hundred twenty-three observations are used to obtain the following regression results: Dependant Variable: Q R-square F-ratio p-value on F Observations: 123 0.7547 184.56 0.00001 Variable Parameter Estimate Standard error t-ratio p-value Intercept 5.5215 0.9750 5.66 0.0001 L 0.650 0.2950 2.20 0.0295 K 0.350 0.1450 2.41 0.0173 A. Write the regression equation based on the output either in the transformed linear form or the original non-linear form. B. How do we interpret the coefficient of labor (L)? C. Is it statistical significance at the 1 percent level of significance?
In the December, 1969, American Economic Review (pp. 886-896), Nathanial Leff reports thefollowing least squares regression results for a cross section study of the effect of age composition onsavings in 74 countries in 1964:log S/Y = 7.3439 + 0.1596 log Y/N + 0.0254 log G - 1.3520 log D1 - 0.3990 log D2 (R2= 0.57)log S/N = 8.7851 + 1.1486 log Y/N + 0.0265 log G - 1.3438 log D1 - 0.3966 log D2 (R2= 0.96)where S/Y = domestic savings ratio, S/N = per capita savings, Y/N = per capita income, D1 = percentage ofthe population under 15, D2 = percentage of the population over 64, and G = growth rate of per capitaincome. Are these results correct? Explain..
4- The manager of Collins Import Autos believes the number of cars sold in a day(Q) depends on two factors: (1) the number of hours the dealership is open (H) and (2) the number of salespersons working that day (S ). After collecting data for two months (53 days), the manager estimates the following log-linear model: Q = aHbSc ----- a. Explain how to transform this log-linear model into a linear form that can be estimated using multiple regression analysis. b. How do you interpret coefficients b and c? If the dealership increases the number of salespersons by 20 percent, what will be the percentage increase in daily sales? c. Test the overall model for statistical significance at the 5 percent significance level.
s EconomicsQ&A LibraryEach term (3 months) the current group of economics students completed a questionnaire as to how much they would spend on new purchases compared to how much they would save/pay off bills, if they suddenly and unexpectedly received a check for $1,000. The average MPC is shown in the table below. Month in which student poll was taken Average of students’ responses as MPC March 0.41 June 0.30 September 0.22 December 0.56 What do these MPC’s imply about the students’ thinking over the course of the year? (Enter response here.) What is likely happening in the economy during the same period of time? Each term (3 months) the current group of economics students completed a questionnaire as to how much they would spend on new purchases compared to how much they would save/pay off bills, if they suddenly and unexpectedly received a check for $1,000. The average MPC is shown in the table below. Month in which student poll was taken Average of students’…