BUSS 230 Midterm, Fall 2005

AMERECAN UNIViIREIETY CP ihi RUE SCHOO tUSERESS NAME: WB: SECTION: VSWER ALL QUESFIONS -- FEMA ALBGWI) tiple choi r, Which of the following is the | ictinition of MCONOKREEC profit? ness profits Minus imal Totel revenuc minus iotat explici Total revenue mmuis total ip 38 prolits id i cit cass minus Which theary of profit holds characicrized by a bigh degre = Frictional Mone Voi Risk Tipo: 3 its eur reased umes could @ rece: Roruaad wi Demand wit shill Demand wit not 7. The price ofa firm's} ia firm’s marginal revenue is greater than its mar ginal cost, then the firm should: a. Increase cutput to increase profit. b. Decrease output to increase profit. c. Keep output unchanged. d. Collect additional information before deciding what to do. Ifa firm is producing a level of output where marginal cost is equal to marginal revenue, then: a Profit is at a maxinmm if marginal cost has a negative s! and marginal revenue is horizontal. b. Profit is at a minimum if marginal cost has a nogative slope and marginal revenue is horizontal. c. Profit is at a maximum if average revenue is greater than average cost. d. Profit is at a minimum if average revenue is greater than average cost c. Profit is at a minimum if marginal cost has a positive slope and marginal revenue is horizontal. sroduct declines fram S14 to SO Asa result, the y domenuded oF i rodiict iver sos Mt The ave price clasticity of dermand for thie gocd is equal to: a. -100 b. -i0 ce, d. -O1 a - O01, firm’s product is $3.0 aii ths iv the price clasticity of demand for ineonie elasticity of demand for (he product is 2.5, the firny’» total ranped ia LG Gecieess: revenue fi Ssanie ried by s: Ome is aeconly 4 Increase in product price b. 0.5% decrease in product price. 2 1% Inciease in predict price. \ 2% decrease in product price. ; increase in product price. a OSS 9. ‘the price ciasticity of demand for a good will ; hroadly defined (eg sod is iO. The Identification Probles: would net prevent estimation ofa demand curve from price and quantity data if, over the time period sampled, the only thing that varied was: Supply of the good. vel of consumer income. s of substitutes and complements. Level of advertising expenditures Consumer tastes. Ji. The ps arbin- Watson Statistic is used to test for: a. Multicollinearily. Autocorrelation. Hetcroskedasticity. ignificance of individual parameters i1 in a regression. iificance of the overall regression. 12. One advantage of estimating a function in which all variables bave been transformed into their natural iogariihims is that: a. The cstimated coefficients measure the 1espective clasticity. Problons of autocorrelation are elintinated Problems of multicullinearity between the independent variables are eliminated. Yh oetents are casier to ds nay : Nous ta ihe above ts cuucel, 13. The followine linear trend equation was estinatcd trom atu consisting of S years of quarterly defa: Sto -25-+ TOP, adjustment fictors were estineted using the ratio-to-trend meth resulted in 0.80, 0.90, 1.10, and J 20 for quarters 1, JE, HT, and Ty, respectively. What would be ihe forecast value for the HE qnarier af the forec ast year that follows the past observations? a. S75 ). E7S.5 G18 Gg 2208 e. 2509 14. Phe rool-inesintesquate error a, Semple size. b. Devigtions from the mean in a res Moving average periods exponential smoothing, t ie rn V Orecdst Gccuracy Trae/Kalse -- 20 points. On your blue book, label eaci: of the following statements as either T (true) or F (false) and briefly justify the answer. The value of a firm under unconstrained optimization would be greater than its value under constrained optimization. Sales taxes paid by a retail firm to the government are an example of implicit costs of doing business. An individual consumer’s demand fiction 1s formulated on the assumption that the price of the good is unchanged while all other determinants of demand are allowed to vary. if price elasticity of demand increases, then the firm’s margins revenue will increase also. For normal goods, the income elasticity of demand is positive. If the quantity sold of a commodity increases following an increase in the price of the commodity, then this does mot indicate that the demand curve for the commodity slopes upward. The “Y intercept” of a linear function is equal to the value of “X” when “Y” is equal to zero. The coefficient of determination obtained in a regression estimate ' calculated as the ratic of the explained errors in the Y yarn . by ihe total cirors in tic X variable. The greater the number of periods used in calculating a “meviee average’, the more scusitive the forecast is to the most recent observation. . The weight (yw) that is used fo calculate an exponertial smoothing forecast defines the contribution of the most recent ob ation io the forecast. th. Problem: (15 points). An automobile manutacinie: produces tory. lis profits depend on the mix of cars produced end are tidicated by & profit tuncti 2 a} P= 60,0005 4 3a000/ - 12.587 .75 #7115 SF S pontts. Whal is the combmation of S and J the! profits if there are no constraints on produc d R pies a pradiictton con of 16,560. Would this affect the profit-maximizing Abe POG gsine ean here Qt= sales of cereal in time period t; Pt = unit price of cereal ($); + per capita income (in O00), Pa - price ofa related food product ($) and Y > Time. ‘The R-squave value of the regression was 0.80, and the caleulated D-W value was 1.55. a. For 5 points. Are the signs of the coefficients of the independent variables in conformity with theovctical expectations? Explain your answer. Vor 5 points. Which of the independent variables (if any) anpear to he statistically signiticant (at the 5% level) in explaining sales of cereal? Kor 5 points. What proportion of the total variation in sales is explained by the regression equation? In additien, Calculate the E- statistic, conduct an I'-test and interpret its meaning. Kor 5 points. What conclusions can be drawn from the results about the possible presence of autocorrelation? yatem (ES poms), A discount department store sells patio and lawn furniture. Salus arc seasonal, with higher sales during the spring and sununer quarter {lower sales during the fail and winter quarters. ‘1’ store develored the following Guartorly sales forecasting model csing £Y rs) _ Bales Seger ehOHY bv UU $25 + GARS bP - 278 Dict 2.25 Doe + 3.50 Bes, Where Ye: predi sales in querer} ($ million), Di Das, and $33: are dummy variables for the first (winter), second (spring), and third Gamnwr quarters, respectively. *6¢ 5 points. What can be inferred trom the regression esting about the secular trond of sales of funiture? “SS points. Forecast the sales of furniture during (te second ind fourili quaiters of 20-4, ifthe coloulaicd [ statisde eri 3 td uihe calculated coetlicient of determination ( square) cad would be your interpretation of that valuc? .3 ? t Appendix C tatistical Taules = 677 - Probabilities of Frecduia SESH RNR PORE ee RA F (ALS JOPLULTONSG TT t H sescgeeme pet compe map cininemn ne ms