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ps4sol - Department of Economics University of California...

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1 Department of Economics Spring 2006 University of California Prof. Woroch Economics 140 Problem Set 4 Due: Thursday, March 23, 2:00 PM (before lecture) 1. Data on beer consumption habits of 500 men and women were collect over the course of a single year. The results are found in the Excel spreadsheet called: beer.xls . It contains data on five variables for each survey respondent: qbeer = number of (12oz. equivalent) cans/bottles of beer purchased during the year pbeer = average price of a can/bottle of beer at nearest convenience store pcola = average price of a can/bottle of cola at nearest convenience store income = annual income of the individual male = dummy variable equal to 1 if male and 0 if female a) Begin by describing relevant microeconomic theory that would generate testable hypotheses relating the beer consumption and these other variables. For simplicity assume that the supply of beer is perfectly inelastic, thus our model of the beer market would look something like: The downward slope of the demand curve implies that the price of beer and the quantity consumed are negatively correlated …usually. (This relationship is complicated significantly if supply is not perfectly inelastic, but we will talk more about that once we get to chapter 10.) Microeconomic theory tells us that (1) besides own price, demand is dependent on prices of substitutes (e.g., soda, wine) and complements (e.g., pretzels, pizza, football games) and on consumer’s income, (2) the effect of an own price change is a combination of a “substitution effect” and an “income effect.” As long as the income effect is not too negative, demand curve will slope down in own price. The sensitivity of demand to price is measured by “price elasticity” which is the % change in demand for a 1% increase in price. As income and male increase we would expect the demand curve to shift right as beer is probably a normal good and we know that males have more of a taste for it than females. Consequently we would expect both income and male to be positively correlated with the amount of beer consumed. (This is difficult to see in the graph as it appears quantity is constant, but if the supply curve is not perfectly inelastic or we control for the price of beer, then the correlation could be positive.) It is not obvious that cola is a substitute for beer, but if Q P
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