1. You’ve been hired by “Indo,” the new Indonesian automobile manufacturer, to build a model of U.S. car prices in order to help the company undercut U.S. prices. Allowing Friedmaniac zeal to overwhelm any patriotic urges, you build the following model of the price of 35 different American-made 2016 U.S. sedans (standard errors in parentheses): (Pi is a symbol but I couldn’t make it truly. Pi has a cap up of it) Model A: Pi = 9.0 0.28Wi 1.2Ti 5.8Ci 0.19Li (0.07) (0.4) (2.9) (0.20) (R is a symbol but I couldn’t make it truly. R has a line up of it) R2 = .92 Where: Pi = the list price of the ith car (thousands of dollars) Wi = the weight of the ith car (hundreds of pounds) Ti = a dummy equal to 1 if the ith car has an automatic transmission, 0 otherwise Ci = a dummy equal to 1 if the ith car has cruise control, 0 otherwise Li = the size of the engine of the ith car (in liters) Your firm’s pricing expert hypothesizes positive signs for all the slope coefficients in Model A. Test her expectations at the 5-percent level. What econometric problems appear to exist in Model A? 

In particular, does the size of the coefficient of C cause any concern? Why? What could be the problem? You decide to test the possibility that L is an irrelevant variable by dropping it and rerunning the equation, obtaining the following Model T equation. Which model do you prefer? Why? (Hint: Be sure to use our four specification criteria.) Model T: P = 24 0.29 Wi 1.2 Ti 5.9 Ci (0.07) (0.30) (2.9) (R is a symbol but I couldn’t make it truly. R has a line up of it) R2 = .93 

2. For each of the following situations, determine the sign (and, if possible, comment on the likely size) of the expected bias introduces by omitting a variable: 

a. In an equation fort he demand for peanut butter, the impact on the coefficient of disposable income of omitting the price of peanut butter variable. (Hint: Start by hypothesizing signs.) 

b. In an earnings equation for workers, the impact on the coefficient of experience of omitting the variable for a ge. 

c. In a production function for airplanes, the impact on the coefficient of labor of omitting the capital variable. 

d. In an equation for daily attendance at outdoor concerts, the impact on the coefficient of the weekend dummy variable (1 = weekend) of omitting a variable that measures the probability of precipitation at concert time.