Assume Demand equation of a product as = 70 -10 P + 4Pr + 50 I Where Q = Quantity of the product demanded, P = Price of the product (in $), Pr = Price of the related product (in $) and = Per capita income (in '000) State the key steps for analyzing the above demand equation and calculate the regression results. Tell the key steps to analyze above demand %3D
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- kad 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 + 0.4865ln qt-1 (2.54) (1.38) (3.65) (2.87) r 2= 0.8738 where 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.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.Given the following data X (consumers of teff) or popn 3 6 8 1 13 13 14 Y ( teff consumption) 8 6 10 12 12 14 20 year 2013 2014 2015 2016 2017 2018 2019 Estimate the regression equation, Y= a+bX, Where Y denotes demand for teff while X is consumers of teff (population) By assuming demand for teff is only affected by its consumers, find the amount demand for teff in the year 2022 if the populations (consumers of teff) are about 18 people? (Hint: use the least square method, parameter a and b can be estimated by solving the two linear equations) SY= na+ bSX SXY=aSX +b Where n is number of years. For example, Estimate the sales for 2012, 2015 and fit a linear regression equation and draw a trend line.ar X Sales (Y) XY X2 year X Sales (Y) XY X2 2002 1 22734 22734 1 2003 2 24731 49462 4 2004 3 31489 94467 9 2005 4 44685 178740 16 2006 5 55319…
- The ATV Company produces a specialty cement used in the construction of roads. ATV is a price-setting firm and estimates the demand for its cement using a demand function in the linear form: Q = f (P, M, PR) where Qc = demand for cement/month (in yards) Pc = the price of cement per yard, M = country’s tax revenues per capita, and PR = the price of asphalt per yard. The manager of ATV obtained the following results in her attempt to estimate the demand for cement in the succeeding months. The results are presented below: DEPENDENT VARIABLE Qc R- SQUARE F-RATIO P-VALUE ON F OBSERVATIONS 64 0.8093 84.872 0.0001 VARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 8.20 4.01 2.04 0.0461 PC -3.54…The ATV Company produces a specialty cement used in the construction of roads. ATV is a price-setting firm and estimates the demand for its cement using a demand function in the linear form: Q = f (P, M, PR) where Qc = demand for cement/month (in yards) Pc = the price of cement per yard, M = country’s tax revenues per capita, and PR = the price of asphalt per yard. The manager of ATV obtained the following results in her attempt to estimate the demand for cement in the succeeding months. The results are presented below: DEPENDENT VARIABLE Qc R- SQUARE F-RATIO P-VALUE ON F OBSERVATIONS 64 0.8093 84.872 0.0001 VARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 8.20 4.01 2.04 0.0461 PC -3.54…The ATV Company produces a specialty cement used in the construction of roads. ATV is a price-setting firm and estimates the demand for its cement using a demand function in the linear form: Q = f( P, M, PR) where Qc = demand for cement/month (in yards) Pc = the price of cement per yard, M = country’s tax revenues per capita, and PR = the price of asphalt per yard. The manager of ATV obtained the following results in her attempt to estimate the demand for cement in the succeeding months. The results are presented below: DEPENDENT VARIABLE Qc R- SQUARE F-RATIO P-VALUE ON F OBSERVATIONS 64 0.8093 84.872 0.0001 VARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 8.20 4.01 2.04 0.0461 PC -3.54…
- The ATV Company produces a specialty cement used in the construction of roads. ATV is a price-setting firm and estimates the demand for its cement using a demand function in the linear form: Q = f( P, M, PR) where Qc = demand for cement/month (in yards) Pc = the price of cement per yard, M = country’s tax revenues per capita, and PR = the price of asphalt per yard. The manager of ATV obtained the following results in her attempt to estimate the demand for cement in the succeeding months. The results are presented below: DEPENDENT VARIABLE Qc R- SQUARE F-RATIO P-VALUE ON F OBSERVATIONS 64 0.8093 84.872 0.0001 VARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT 8.20 4.01 2.04 0.0461 PC -3.54…Even though insignificant explanatory variables can raise the adjusted R2 of a demand function, one should not interpret their effects on the regression when ..................What is Heteroscedastic? And is there a way to fix data in case of heteroscedasticity presence ?
- An economic research centre has published data on GDP and Demand for refrigerators as given below:Year 2011 2012 2013 2014 2015 2016 2017GDP (billion) 20 22 25 27 30 33 35Refrigerator 50 60 80 80 90 100 120(a) Estimate regression equation R= a+by, where R= No of refrigerator sold and Y= GDP.Forecast demand for refrigerator in the year 2018 and 2019. The research centre has projected GDP for 2018 and 2019 at Rs. 38 billion and Rs. 40 billion respectively.26) Consider the following regression line: i= -7.29 + 1.93 x YearsEducation. You are told that the t-statistic on the slope coefficient was 24.125. What is the standard error of the slope coefficient? (assume 5% level of significance) A. -0.08 B. 0.30 C. 1.64 D. 0.08We know that discrimination exists. It influences wages, but also many other dimensions over the life cycle which affect wages indirectly. I run OLS regression with variables wage, age, female and degree. The dependent variable is log(wage) and we replace the variables female and degree with the interaction term. However, discrimination is not included among the observed regressors. Given that omitting confounding variables from regression model can bias the coefficient estimates, omitting discrimination would lead to biased results. Could you please help me provide an example of how unobserved gender discrimination can affect my OLS estimates. [Hint: think about ways in which discrimination can invalidate OLS assumptions.].