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Are Ghettos Good or Bad? Cutler, Glaeser, QJE (1997) © Allen C. Goodman 2000.

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Presentation on theme: "Are Ghettos Good or Bad? Cutler, Glaeser, QJE (1997) © Allen C. Goodman 2000."— Presentation transcript:

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2 Are Ghettos Good or Bad? Cutler, Glaeser, QJE (1997) © Allen C. Goodman 2000

3 Ghettos Typically defined by race or ethnicity. Good, or bad? Costs –May increase transportation costs to jobs. –May make information regarding jobs, housing more difficult to acquire. –Public sector, loosely defined. If there are neighborhood specific public goods, ghettos may limit access.

4 Benefits of Ghettos Are there benefits? –Eliminate segregation by income. Poor are exposed to the rich. –Promotes the development and specialization of professional and entrepreneurial skills. –May put people closer to public benefits.Eliminate segregation by income. Poor are exposed to the rich.

5 How can we model? Assume two races A, and B. Assume two skill levels H, and L. Leads to four categories, AH, AL, BH, BL. Two neighborhoods, N1, N2. Workers of all types can move freely among neighborhoods (subject to a discrimination cost D that is imposed on B for living in N1). Earnings (or success, more generally) are related to one’s own type, and to the proportion of high skill types in the neighborhood.

6 Some math Earnings for low skilled workers in community k (1 or 2): –E L = W(Q k AH + Q k BH ) –E H =  W(Q k AH + Q k BH ),  > 1. Q T BH + Q T BL < 1. Assume Q T BH = Q T BL = 0.4 Q T AH + Q T BH < 1. Assume Q T AH = 0.5; Q T AL = 0.7

7 Finally, housing Finally, housing. There is 1 unit of housing in each neighborhood. In N2 housing is free, costs 0. In N1 housing has cost C. The price of housing will adjust to equate utility in each neighborhood.

8 Will yield total integration Highly skilled will have same utility in each neighborhood. Suppose D = 0

9 Segregation by skill Suppose that D>0. The high skilled people want to live where other skilled people live, so: U A H =  W(Q T AH + Q T BH ) – C. U B H =  W(Q T AH + Q T BH ) – C – D. Why? But there aren’t enough of them, so the price of housing would be free. Both low skilled A and low skilled B would like to move in, but the low skilled A are willing to pay more, since they don’t have to pay a discrimination fee. They would earn W(0) in N2. They would be willing to pay: C = W(Q T AH + Q T BH ) – W(0). This will be the price of housing in N1.

10 Segregation by skill (2) What does this mean? U A H =  W(Q T AH + Q T BH ) – C. U B H =  W(Q T AH + Q T BH ) – C – D. U A L = W(Q T AH + Q T BH ) – C = W(0) U B L = W(0). BH want to live in N1 as long as: U B (N1) > U B (N2)  W(Q T AH + Q T BH ) – C – D > W(0) (  -1)W(Q T AH + Q T BH ) – W(0) > D. Discuss

11 Segregation by Race Again, we solve to make AL types indifferent between neighborhoods. Remember, price of housing in N2 = 0. C = W(Q T AH ) - W(Q T BH ). Q T AH + Q 1 AL = = of the AL live in N2 as do all of the BH and the BL. What does this mean? U A H =  W(Q T AH ) – C. U B H =  W(Q T BH ). U A L = W(Q T AH ) – C = W(Q T BH ) U B L = W(Q T BH ).

12 In this model... BL always prefer segregation by race to segregation by skill because they have more skilled agents around them. BH may gain or lose in moving from segregation by race to segregation by skill. They pick up more wages through the skill, but lose through discrimination. –Gain =  W(Q T AH + Q T BH ) – C – D -  W(Q T BH ). –Since C = W(Q T AH + Q T BH ) – W(0). –Gain = (  - 1)W(Q T AH + Q T BH ) + W(0) – D -  W(Q T BH ).

13 So, Discrimination acts against minorities as a whole, With free mobility, a mechanism exists that makes living in the ghetto no worse than living in the non-ghetto area. With mobility (particularly in the last 30 years), it can be very difficult to determine whether people in different parts of city are worse off. However, comparing people across cities, one might find differences attributable to discrimination.

14 Test They look at outcomes on an individual level: Outcome = X  +  1 segregation +  2 segregation * black +  Focus on coefficient  2. Segregation measures (1990) mean =0.586 min =0.206 max = Detroit is near the maximum.

15 Results Table 3 through the end. Present many examples. First column Table 4. Outcome = X  +  1 segregation +  2 segregation * black HS Grad = X  segregation segregation * black A rise in segregation (1 s.d.)  *0.126 or a 3.8% decrease in probability that year old black will have graduated from HS. This is roughly 15% of national black drop-out rate.

16 Conclusions Blacks are significantly worse off in segregated communities than in non-segregated communities. Causality appears to run from ghettos to “failure” (their term), rather than reverse. None of the variables explains large portions of the differences.


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