1. Mills on Suburbanization © Allen C. Goodman, 2000

2. Explanations of Suburbanization “Traditional” –Increased income  Demand for land , people want to move further away. –Decreased transportation costs  Easier to travel further “Flight from Blight” –Higher minority populations –Higher crime rates –Worse public services

3. Looking at Decentralization. What do we want? Identify central and suburban areas (density gradients don’t do this). Let L c (central city land) and P (metro-politan population be exogenous, but not P c (cc population) or L s (suburban land). Account for variations in the sizes of central cities relative to urbanized areas. P c  as P  ; P c /L c  as L . It is plausible that P c  at least proportionately with simultaneous increases in P and L c. Popu-lation density in central city does not  as P . Should be fairly general.

4. Functions P c = A 1 P  1 Lc  1. Leads to: P c /P= A 1 P  1 -1 Lc  1. For employment: E c = A 2 P  2 Lc  2. We expect  > 0. Why? Z = P c /P= A 1 P  1-1 Lc  1.  Z/  P = (  1 – 1)Z/P E ZP =  1 – 1

5. We expect   1. Why? Density = Q = P c /L c = A 1 P  1 Lc  1 -1 Q/L c = (  1 - 1) Q / L c Maybe  +  > 1. This implies that a 10% increase in metro population and a 10% increase in CC area  at least a 10% increase in CC population.

6. Regressions P c = A 1 P  1 Lc  1. Take logs: ln Pc = ln A + a ln Lc + b ln P + c 1 Black + c 2 crime + c 3 income

7. What does this mean? Mills views the  and  coefficients as being in keeping with his hypotheses  0.6;  0.4;  +   1.0 – others “add little.” I don’t think he interprets things correctly. It appears that Black is entered in percents between 0 and 100. If so elasticity of P c w.r.t. is (  P c /  B)(B/P c ) = c 1 Black. For Detroit, 1980 pct. Black was  60. So the elasticity = - 0.324.

8. Implies that a 10% increase in Detroit’s % Black  3.24% decrease in central city population. Moving from 60 to 66% Black  a decrease of 40,500. Another interpretation: For Detroit in 1980: Pc = 1.25 (million);P = 4.5 Bc = 0.75 (million);B = 1.0 This implies Ps = 3.25; Bs = 0.25. What does this mean?

9. What would regression predict if the Black population percentage was the same in the Central City as in the entire metro area? Would imply 22.2% Black in both Detroit and the suburbs, or a decrease in the Detroit percentage of (60 – 22.2) = 37.8% points. dPc = c1 Pc dBlack, or = -0.0054 * 1.25 * (-37.8) = 0.25515  Increase in CC population of 255,150 or an increase of over 20%. Seems like a large change. Adding up differences across the large number of cities, would suggest decentralization of millions of people. What does this mean?