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- For tax purposes, “gross income” is all the money a person receives in a given year from any source. But income taxes are levied on “taxable income” rather than gross income. The difference between the two is the result of many exemptions and deductions. To see how they work, suppose you made $50,000 last year in wages, earned $10,000 from investments, and were given $5,000 as a gift by your grandmother. Also assume that you are a single parent with one small child living with you. a. What is your gross income? b. Gifts of up to $14,000 per year from any person are not counted as taxable income. Also, the “personal exemption” allows you to reduce your taxable income by $4,050 for each member of your household. Given these exemptions, what is your taxable income? c. Next, assume you paid $700 in interest on your student loans last year, put $2,000 into a health savings account (HSA), and deposited $4,000 into an individual retirement account (IRA). These expenditures are all tax exempt,…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?Assume that driving skill, S, varies throughout the population. Automobile insurers classify drivers into two categories: “Good” and “Bad”. Good drivers are those people who have driving skills above a threshold level of driving skill, S*. Bad drivers, on the other hand, have driving skills that fall below the threshold level, S*. Good drivers pay lower rates than Bad drivers. Additionally, assume that it’s common knowledge that Welsh are more skillful drivers than Scots, such that a higher proportion of the Welsh population has driving skills above S* than the Scottish population. Also assume that there is a law that prohibits insurers from learning a person’s driving skill. Suppose that drivers can decide to use a new device that will send credible real time driving data to their insurance company (e.g., speed, stopping distance, driving times, etc.) that allows insurers to correctly classify a driver as having skill greater than or less than S*. Which group would be most likely to…
- Assume that driving skill, S, varies throughout the population. Automobile insurers classify drivers into two categories: “Good” and “Bad”. Good drivers are those people who have driving skills above a threshold level of driving skill, S*. Bad drivers, on the other hand, have driving skills that fall below the threshold level, S*. Good drivers pay lower rates than Bad drivers. Additionally, assume that it’s common knowledge that Welsh are more skillful drivers than Scots, such that a higher proportion of the Welsh population has driving skills above S* than the Scottish population. Also assume that there is a law that prohibits insurers from learning a person’s driving skill. Suppose that drivers can decide to use a new device that will send credible real time driving data to their insurance company (e.g., speed, stopping distance, driving times, etc.) that allows insurers to correctly classify a driver as having skill greater than or less than S*. Who is most likely to employ these…If Ford produced $80 million worth of cars in 2020 in the United States but sold only $55 million worth of cars. US GDP in 2020 will include million worth of cars. O $55 O $80 $45 O $135Consider 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.
- 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;…Revenue at a major smartphone manufacturer was $1.3 billion for the 9 months ending March 2 up 86 percent over revenues for the same period last year. Management attributes the increase in revenues to a 10o percent increase in shipments. Despite a 32 percent drop in the average blended selling price of its line of phones. Given the information, is it surprising that the company's revenue increased when it decreased the average selling price of its phones?QUESTION 3 What was the approximate level of GDP production in the United States in 2015? Oa. $18 trillion O b. $1.8 trillion O c. $180 billion O d. $1,800 million Oe. $18 billion
- 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.…part a b and c solved 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?…AD has estimated the following demand relationship for its product over the last four years, using monthly observations: ln Qt = 4.932- 1.238 ln Pt + 1.524 ln Yt-1 + 0.4865lnQt-1(2.54) (1.38) (3.65) (2.87)R2= 0.8738where Q = sales in units, P = price in Rs., Y is income in Rs,000, and the numbers in brackets are t-statistics.a. Interpret the above model.b. Make a sales forecast if price is Rs. 9, income last month was Rs. 25,000 and sales last month were 2,981 units.c. Make a sales forecast for the following month if there is no change in price or income.d. If price is increased by 5 per cent in general terms, estimate the effect on sales, stating any assumptions.