7. If a person's income is $40,000, how much do you predict that they will spend on consumption? 8. The R-squared, or coefficient of determination, from this regression is 0.844. Interpret the R-squared.
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- 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…Setting: U.S. Auto manufacturers are trying to develop a multivariate function with which to estimate the demand for their gas-electric hybrid compact cars. Here is one that Motors General developed for its Jolt: Qj = 65000 – 20Pj + 20Pf + 35Pt – 5Pb + 0.2Tc + 0.05Y + 10Mg + 0.04A Where Qj = the number of Jolts demanded per week. Pj = the price of each new Jolt (in $). Pf = the price of each new Ford gas-electric hybrid (in $). Pt = the price of each new Toyota gas-electric hybrid (in $). Pb = the price of replacement batteries for the Jolt (in $). Tc = the amount of tax credit incentive offered with the purchase of a new hybrid (in $). Y = average weekly disposable income of a typical Jolt purchaser (in $). Mg = the miles per gallon of gas rating of the Jolt (in miles per gallon). A = average weekly Jolt advertising expenditure (in $). 6 If all variables remain unchanged except that the price of the Toyota hybrid (Pt) decreases by $500, then the demand for Jolts will: 7…Is auto correlation possible in cross-sectional data? why?
- Econometrics Thomas Eisensee and David Stromberg wanted to measure how much news coverage of a foreign disaster impacted the amount of disaster relief provided by the U.S. government. They argue that the simple relationship would be biased. Let X = Minutes of News Coverage and Y= Disaster Aid. Choose a variable X2 that could bias the simple relationship. This variable should impact the amount of coverage and impact the amount of aid for reasons other than purely news coverage. Eisensee and Stromberg introduce an instrument Z = During the Olympics. Explain how Z could satisfy the relevant and exogenous criteria. Explain how you could use Z to estimate the impact of X on Y free from X2 bias. Hint: you should mention two stages.Question 2 Suppose we are interested in the effect of attending a particular school on students’ income in adulthood. Let malei be a dummy variable which is equal to 1 if student i is male. Translate the following mathematical expression into plain English E(Yi(1) − Yi(0)|malei = 1). Full explain this question and text typing work only We should answer our question within 2 hours takes more time then we will reduce Rating Dont ignore this line .Q7. Do quadretic regression to find the forcast value of quauter 9 and 10 Quarters (x) 1 2 3 4 5 6 7 8 9 10 Demand (y) 5.10 11.40 22.70 35.00 64.22 81.77 115.50 149.90
- A commercial airline is analyzing the price scale for round trip flights between New York and Pennsylvania. The sooner the c buys the ticket, the cheaper the ticket price is. The sales manager collected information for the last year on how many cust bought their tickets at each price: Ticket Price (in dollars) # of Customers (in thousands) 5 15 23 27 20 89 125 135 150 178 198 10 What is the coefficient of correlation between the ticket price and the number of customers purchasing at that price? Answer:Sally Sells Sea Shells by the Sea Shore and collects all sales dataNow she is curious to find out what the elasticity of demand is for her shells Assume they are all the same type and quantity She scatter plots the data and finds there is a linear relationship that looks ripe for a regression estimation of the price response function for her shells The slope of her regression line is 61. Currently, her average daily price is 11.74 and she sells 95 quantity at that priceCalculate the point elasticity of demand for her sea shellsnot use ai please
- Please no written by hand and no emage Your company, which specializes in running shoes for men who are growing increasingly follicly-challenged (BalderDash®), has the following demand function: Q = a + bP + cM + dR where Q is the quantity demanded of BalderDash’s most popular shoes, P is the price of that product, M is consumer income, and R is the price of a related product. The regression results are: Adjusted R Square 0.7796 Independent Variables Coefficients Standard Error t Stat P-value Intercept 21,055.04 1428.27 14.74 8.1E-16 P -83.912 19.079 -4.398 0.000 M 0.0266 0.013 2.064 0.047 R -16.6 10.664 -1.556 0.129 Discuss whether you think these regression results will generate good sales estimates for BalderDash. Now assume that the income is $69,100, the price of the related good is $39, and BalderDash chooses to set the price of its product at $54. b. What is the estimated number of units sold given the data above? (round to nearest unit; no decimals) c.…K Period Demand 1 8 where y = Demand and x = Period. What is your estimate of the demand in period 7? Estimated demand in period 7 is 2 11 3 10 4 12 y = 7.93 + 0.83 x, 5 10 The least-squares regression equation that shows the best relationship between demand and period is (round your responses to two decimal places): 6 14 (round your response to two decimal places).Please answer a b and c
