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Demand for Local Public Goods © Allen C. Goodman 2008 How Responsive are LPGs? • What are the usual suspects? • We get pretty interested in both price and income elasticities. • Presumably, as Income , Q . • Presumably, as Price , Q . • How much is it? – A little? – A lot? Let’s recall a few things from principles EY = % Q / % Y. EP = % Q / % P. Why do we care? We’d like to know (if public goods are good) whether we might naturally get more of them if incomes rose. Price elasticities Things you once learned, but you probably wanted to forget! How much does quantity demanded change if price changes? What happens to total expenditures? Suppose EP = 0. 0 = % Q / % P If % P is 10, % Q = 0, so total expenditures by 10% - that’s a lot! Price elasticities Suppose EP = -0.5. -0.5 = % Q / % P If % P is 10, % Q = -5, so total expenditures by 5% - Why? What if EP = -1.5? What happens to total expenditures? Suppose EP = -1.0. -1.0 = % Q / % P If % P is 10, % Q = -10, so total expenditures are unchanged - Why! Getting demand from median voter models • Suppose median income person is median voter. Price Trend Line YA YB>YA YC>YB Quantity C* B* tc(Yc) tb(Yb) A* tA(YA) A* B* C* Quantity YA YB YC Income Getting demand from median voter models • Suppose median income person isn’t median voter. Price tc(Yc) YA YB>YA YC>YB tb(Yb) Quantity C* A* B* tA(YA) B*A* C* Quantity YA YB YC Income Conundrum • If the first is the case, we can confidently regress median income against median expenditure and feel that we have identified the median voter. • If the second is the case, we cannot be sure. How do we examine data • Let’s look at some data on per capita state/local expenditures v. • Per capita state income CT DE DC ME MD MA NH NJ NY PA RI VT PCI 42919 31955 44731 27324 35527 38944 33922 39122 35590 30240 30434 29024 PCE 7105 6834 10804 6262 6004 6698 5132 6473 8523 5999 6474 6264 Let’s draw a picture Per Capita Expenditures 12,000 10,000 Per Capita Expenditures • What does the relationship look like? • Looks like as income expenditures . 8,000 6,000 PCE 4,000 2,000 0 0 10,000 20,000 30,000 Per capita Income 40,000 50,000 Log-log Form SUMMARY OUTPUT Dep: ln(PC Exp) Regression Statistics Multiple R 0.567371 R Square 0.32191 Adjusted R Square 0.254101 Standard Error 0.163847 Goodness Observations 12 of fit Good thing – Elasticities are easy to calculate Bad thing – 1. Elasticity is constrained to be constant 2. What do you do with 0’s? ANOVA df Regression Residual Total Intercept LN(PCI) SS MS F 1 0.127446 0.127446 4.747312 10 0.26846 0.026846 11 0.395906 Coefficients Standard Error t Stat P-value 1.650047 3.29048 0.501461 0.626901 0.685924 0.314813 2.178833 0.054353 Elasticity Linear Form SUMMARY OUTPUT Dep: Regression Statistics Multiple R 0.606519 R Square 0.367865 Adjusted R Square 0.304651 Standard Error 1228.478 Observations 12 PCE Good thing – Elasticities can vary. Bad thing – 1. Elasticity must be calculated. E = (PCE/PCE)/(PCI /PCI) ANOVA df Regression Residual Total Intercept PCI Elasticity SS 1 8782402 10 15091582 11 23873984 MS F 8782402 5.819404 1509158 E = (PCE/PCI)*(PCI /PCE) Coefficients Standard Error t Stat P-value 1252.322 2360.078 0.530627 0.607259 0.160922 0.066708 2.412344 0.036537 0.818003 E = (0.161)*(PCI /PCE) Empirical Work • Bergstrom/Goodman (no relation) – 1973 • Already kind of dated but Fisher argues that more recent stuff is similar. Bergstrom/Goodman Gen'l Expend Police Expend Parks Recreation Income 0.64 0.07 0.71 0.13 1.32 0.22 Tax share (price) -0.23 0.03 -0.25 0.05 -0.19 0.08 Population 0.84 0.03 0.80 0.06 1.17 0.11 General Literature • As income rises, quantities rise, but not by as large a percentage. Implies that expenditures rise. • As price rises, quantities fall although not by much. Also implies that expenditures may rise. Business Demand • Model is one of consumer demand but how do businesses feel? • Application 4.1 is interesting • On the one hand, businesses always seem to want lower taxes. • On the other hand, – “without additional revenues, Colorado will be left with little choice but to woefully under-fund areas such as higher education, our state highways, water resources, and vital capital construction and maintenance projects.”