Residential Mobility, Heterogeneous Neighborhood effects and Educational Attainment of Blacks and Whites Li Gan Texas A&M University and NBER Yingning Wang Texas A&M University June 21, 2008

Introduction Wage difference (blacks & whites) Education difference Different returns to education Different neighborhoods But, returns to education converges over last twenty years So, it is our objectives

Evidence Social experiments Gautreaux Program Suburb mover youth do better on several educational measures. (Rosenbaum,J.1992,1995) Placement assignment were not entirely random (Kling and Votruba 2001 ) Moving to Opportunity (MTO) Difference in welfare participation, employment and child test score between control group and treatment group is less (Ladd 1997; Hanratty 1998; Katz 2001; Ludwig 2001)

Contribution Identified heterogeneous neighborhood effects on educational attainment Significant neighborhood effects for people whose location choice is endogenous to education Crime rate has negative effects on educational attainment Neighborhood educational level has positive effects on individuals’ educational attainment Moving will attenuate the original location’s neighborhood effects Insignificant neighborhood effects for people whose location choice is exogenous to education

Outlines Literature Review Data Empirical Strategies Simulation Conclusion

Literature Review Neighborhood effects and educational attainment Crane (1991), Datcher (1982) Lillard (1993) Duncan (1994, 1997), Ginther, Haveman, Wolfe (2000) Subject to selection bias Neighborhood effects identification Ioannides and Zabel (Journal of Urban Economics,2007 ) Neighborhood effects on housing demand Housing demand and location choice as joint decision

This paper Assumes moving and educational attainment as joint a decision Assumes heterogeneity in endogeneity of moving: Endogenous moving: moving for education Exogenous moving: moving for reasons unrelated with education.

Data Educational attainment data: the extra schooling years after compulsory education Individual level data County level data The proportion of population with high school degree only Mortality data (by county and race and gender) Crime rate Other county level data Residential mobility data Move dummy(1, if moved in 1979 and 1982,otherwise 0)

Empirical Strategy Schooling year choice Exogenous effects Endogenous effects correlated effects

Empirical Strategy Residential mobility choice ( Ioannides and Zanella 2007 ) IV: the means of adjacent counties which do not include the county where households reside.

Empirical Strategy Joint decisions Schooling choice Moving choice Correlation

Identification Problem caused by: Problem solved by: Unobservable characteristics correlated with endogenous and exogenous neighborhood effects: Problem solved by: IV(1): the county mean of selection correction terms Selection introduced by: uncorrelated with Selection terms uncorrelated with IV(2): residential segregation indexes

Heterogeneity Education functions for two types: Type is determined by: “Type” is not observable, so:

Empirical Strategy Compared with Heckman model Heckman equation (without type) Extra terms

Table 1: Rivers and Vuong procedures: the second stage results for moving equation  coefficient standard error residual family below poverty at origin 0.004** 0.00 residual family below poverty at destination -0.001 residual unemployment at origin 0.007* residual unemployment at destination 0.003 (0.01) residual high school percent at origin 0.004*** residual high school percent at destination -0.002 residual crime at origin 0.000 residual crime at destination -0.000** residual dissimilarity at origin -6.107 (4.36) residual dissimilarity at destination 14.392** (5.67) residual black percent at origin -0.003*** residual black percent at destination 0.001 residual mortality rate at origin 0.010* residual mortality rate at destination -0.005

external mortality rate for the young at origin 0.0211 0.0266 Variables Coef.   Std. Err. external mortality rate for the young at origin 0.0211 0.0266 the number of families below poverty at origin 0.0025 0.0099 unemployment rate at origin 0.0174 ** 0.0079 the percent population who finish high school at origin -0.0221 0.0331 black percent at origin -0.0003 0.0239 crime rate at the destination 0.0004 0.0009 Dissimilarity index at destination -3.6897 11.5482 mum's education -0.0033 0.0683 dad's education 0.0417 0.0299 family size -0.0825 0.0326 age 0.1188 0.4788 age squared 0.0001 0.0143 black 2.9120 8.1445 male -1.3067 1.2854 living in urban or not 0.1197 0.5287 per cap income at origin 0.0021 0.0015 crime rate at the origin 0.0007 Dissimilarity index at origin -1.5741 1.0133 the percent population who finish high school at destination 0.0167 0.0245 per cap income at destination -0.0019 0.0014 unemployment rate at destination -0.0267 0.0284 the number of families below poverty at destination 0.0003 0.0096 external mortality rate for the young at destination -0.0023 0.0040 black percent at destination 0.0209

Table 3: Heckman regression for movers and non-movers coefficient SE crime rate -0.0001** 0.00 0.000 high school Percent 0.026 (0.05) -0.056 (0.10) mortality rate 0.001 -0.001 AFQT 0.044*** 0.050*** (0.01) religion frequency 0.118*** (0.03) 0.054 (0.09) mother went to college or not 0.612*** (0.12) 1.330*** (0.47) family size -0.025 -0.072 rank among siblings -0.071 (0.08) 0.225 (0.18) poverty status -0.160 (0.14) 0.616* (0.37) times of light illegal -0.023*** -0.026* times of heavy illegal -0.079*** -0.009 (0.06) safe feeling about school 0.088 0.355* lived with parent until 18 0.170 0.264 (0.36) employment in education institution 0.012** 0.005 per cap income 0.000* -0.000 black percent 0.005*** unemployment 0.020** -0.012 (0.02) inverse mills ratio 0.139* (0.07) 0.096 (0.15) constant -2.079 (2.64) 2.252 (5.19)

Table 4: Estimation results with heterogeneity of Endogenous type Exogenous type endogeneity of moving  coefficient. SE constant -54.196*** (15.14) 2.060 (3.82) mortality rate 0.003 (0.01) -0.001 0.00 interaction mortality rate & move 0.015 0.002 high school percent 0.949*** (0.27) -0.036 (0.07) interaction high school percent & move -0.255*** (0.10) 0.005 (0.02) crime rate -0.001** -0.000 interaction crime rate & move 0.001* poverty status -1.081* (0.61) -0.038 (0.16) family size 0.042 (0.24) -0.003 (0.04) rank among siblings -1.353** (0.60) -0.069 (0.14) religion frequency 0.412 (0.25) 0.081 (0.05) times of light illegal behaviors -0.066*** -0.029*** times of heavy illegal behaviors -0.129* mother went to college or not -2.012** (0.83) 0.791*** employment in educational institution 0.118*** lived with parents until age 18 or not 4.163*** (1.29) 0.217 (0.17) safe feeling about school 0.707** (0.28) 0.094 (0.06) per capital income 0.003*** 0.000 black percent 0.035*** unemployment 0.085** 0.013 AFQT 0.042*** ζ 0.978* (0.53) 0.014 (0.08)

Table 5: Type determination estimation   Coefficient SE constant -38.770** (17.42) rank among siblings -1.084** (0.48) religion frequency 0.247** (0.12) times of light illegal -0.080*** (0.02) lived with parents until age 18 or not 3.005*** (0.73) black -1.563** (0.67) mother went to college or not -1.082*** (0.40) male -0.661* (0.35) oldest sibling's highest grade -0.255*** (0.09) age 5.976** (2.38) AFQT -0.061*** age squared -0.181** (0.07)

Empirical results schooling years Type Mean Std. Dev. Exogenous type   schooling years Type Mean Std. Dev. Exogenous type 5.8428571 2.8316826 Endogenous type 4.2092534 2.3331385 Total 4.3212537 2.4047805

Simulation

Repetition Variable True value Type(1) Heckman-Mover(2) Heckman-Non_mover(3) (2)/(1) (3)/(1) Bias% 300 gamma1_nonmover Type 1 0.60 -0.0607 -0.3667 6.0364 gamma1_mover 0.36 0.0724 0.4325 5.9706 beta11 -0.12 0.3479 2.0468 2.0475 5.8825 5.8844 b0 0.50 0.1350 -0.2737 -0.2609 -2.0277 -1.9330 gamma2_nonmover Type 2 0.26 0.2603 0.4614 0.0000 1.7729 gamma2_mover -0.0808 -0.1405 1.7386 beta21 -0.50 -0.1527 -0.2688 -0.2686 1.7607 1.7596 b1 0.30 -0.0427 0.2105 0.2318 -4.9270 -5.4259 theta   -0.1691 0.8307 2.1682 500 -0.0502 -0.3678 7.3208 0.0584 0.4326 7.4073 0.3126 2.0472 2.0479 6.5495 6.5516 0.1266 -0.2718 -0.2722 -2.1473 -2.1503 0.2534 0.4589 1.8109 -0.0776 1.8092 -0.1481 -0.2687 -0.2685 1.8136 1.8125 -0.0358 0.2136 0.2130 -5.9664 -5.9482 -0.1664 0.8440 2.2102

Repetition Variable True value Type(1) Heckman-Mover(2) Heckman-Non_mover(3) (2)/(1) (3)/(1) Bias% 800 gamma1_nonmover Type 1 0.60 -0.0557 -0.3665 0.0000 6.5782 gamma11_mover 0.36 0.0628 0.4321 6.8863 beta11 -0.12 0.3214 2.0473 2.0476 6.3694 6.3704 b0 0.50 0.1249 -0.2679 -0.2588 -2.1458 -2.0729 gamma2_nonmover Type 2 0.26 0.2555 0.4620 1.8084 gamma21_mover -0.0780 -0.1407 1.8050 beta21 -0.50 -0.1489 -0.2687 -0.2686 1.8048 1.8042 b1 0.30 -0.0271 0.2201 0.2353 -8.1209 -8.6802 theta   -0.1658 0.8488 2.2105 1000 -0.0568 -0.3667 6.4524 0.0642 0.4305 6.7092 0.3300 2.0482 2.0477 6.2061 6.2045 0.1304 -0.2527 -0.2590 -1.9381 -1.9861 0.2588 0.4615 1.7834 -0.0786 -0.1417 1.8020 -0.1506 -0.2684 1.7820 1.7828 -0.0298 0.2454 0.2350 -8.2411 -7.8909 -0.1676 0.8454 2.1873

size Variable True Value Type Bias (1) Movers Bias (2) Non-movers Bias (3) (2)/(1) (3)/(1) 10000 gamma1_nonmovers 0.6 Type 1 -0.84 -0.37 0.44 gamma1_mover 0.36 0.29 0.43 1.50 beta11 -0.12 -1.88 2.05 2.06 -1.09 -1.10 constant 0.5 -0.15 -0.24 -0.33 1.54 2.14 gamma2_nonmovers 0.26 Type 2 -0.03 -17.12 gamma2_mover 0.05 -0.14 -3.04 beta21 -0.5 0.02 -0.27 -11.96 -11.87 0.3 -4.05 0.27 0.12 -0.07 theta   -0.06 2.39 6.34 50000 -0.02 -0.36 24.00 0.01 73.25 -63.95 -63.81 -0.22 -4.90 -4.01 0.13 0.47 3.67 4.14 -0.94 0.22 0.30 10.66 14.67 -0.09 1.51 3.91 100000 5.45 9.36 0.38 5.33 5.32 0.15 -0.26 -0.25 -1.75 -1.72 0.46 1.79 -0.08 1.80 1.77 -0.04 0.24 0.25 -5.67 -5.87 -0.17 0.85 2.20

Conclusion Heterogeneity of endogeneity leads to heterogeneous neighborhood effects Moving will attenuate neighborhood effects.

Data description---County level variables Mean Std. Dev. external mortality rate for the young 94.3762 76.6254 arrest rate 0.1020 0.2638 crime rate 6398.2330 3225.0540 Dissimilarity index 0.2175 0.3355 employment rate in educational institution 76.7522 21.4983 per capital income 4789.2920 692.3637 percentage of blacks 123.9522 109.3871 unemployment rate 45.1515 15.6921 the share of adults with high school only 34.8772 5.3270 the share of adults with less than college 16.2805 3.6802 the share of adults with less than high school 32.0294 7.5176 the share of adults who are college graduates 16.8211 5.1492 mortality rate for age above 55 4185.1180 1123.1000 mortality rate of 2003 49.8973 33.1315 the number of physician per 100,000 1917.1510 1135.0760 the number of hospital beds per 100,000 6848.8160 4080.7010

Data description--Individual and family level variables Mean Std. Dev. mother goes to college or not 0.6326 0.4823 poverty status 0.2239 0.4170 family size 5.1409 1.8516 mother's highest grades 11.2771 3.0103 dad's highest grades 11.2983 3.7313 rank among siblings 1.9116 0.7936 times of light illegal behaviors 0.3581 2.3737 times of heavy illegal behaviors safe feeling about school 3.4153 0.8511 lived with parents until age 18 or not 0.6532 0.4761 schooling years 4.3601 2.4278 the oldest sibling's highest grade 11.8874 2.1376 religion frequency 3.4947 1.7024

Data description whites blacks others movers non-movers total   whites blacks others movers non-movers total age 14-18 1110 3760 355 1341 97 240 6903 age 18-22 1022 2551 389 891 163 184 5200 Total 2132 6311 744 2232 260 424 12103 Note: movers and non-movers do not have any missing values in the original county or destination.

County Characteristics Residential mobility White movers County Characteristics 1979 (before moving) 1982 (after moving) Implication % difference Percentage of urban -0.00725283 0.010288079 more urban Percentage of blacks 0.013361969 0.058768821 more blacks unemployment -0.007991609 -0.009057569 less unemployment Per capital income 0.006101481 0.013252452 higher income The number of families below the poverty level 0.002007616 -0.014294823 less poverty The number of persons below the poverty level -0.146176984 -0.160544413 Percentage of population who are high school graduates 0.017359939 0.038323764 more high school graduates Percentage of population who goes to college 0.074630843 0.140421893 more college graduates The percentage of physician per 100,000 0.024703709 0.091743303 more physician The number of hospital beds per 100,000 0.04653399 -0.010184058 less hospital beds Crime known to the police 0.02567602 0.087838154 more crime known to the police Arrest rate 0.23318226 2.043032991 higher arrest rate External mortality rate for the young age 15-34) 0.038540479 -0.020158646 less mortality for the young

County Characteristics Residential mobility Black movers County Characteristics 1979 (before moving) 1982 (after moving) Implication % difference Percentage of urban -0.024447834 0.009699186 more urban Percentage of blacks -0.071205721 -0.170556944 less blacks unemployment 0.018517275 -0.046353767 less unemployment Per capital income -0.003664408 0.017524829 higher income The number of families below the poverty level 0.010131227 -0.07740122 less poverty The number of persons below the poverty level -0.18326031 -0.215660549 Percentage of population who are high school graduates 0.02091495 0.080223176 more high school graduates Percentage of population who goes to college 0.056597133 0.165726005 more college graduates The percentage of physician per 100,000 -0.0179625 0.032924942 more physician The number of hospital beds per 100,000 0.018747151 0.111129281 more hospital beds Crime known to the police 0.013666593 0.074730846 more crime known to the police Arrest rate 0.290052959 1.595125742 more arrest rate External mortality rate for the young(age 15-34) 0.095402824 -0.030929749 less mortality for the young

Age distribution Cumulative AGE_79 Frequency Percent 14 313 16.57 15   Cumulative AGE_79 Frequency Percent 14 313 16.57 15 489 25.89 802 42.46 16 467 24.72 1269 67.18 17 400 21.18 1669 88.35 18 183 9.69 1852 98.04 19 29 1.54 1881 99.58 20 7 0.37 1888 99.95 21 1 0.05 1889 100

Moving across county statistics

Simulation Heckman Extra terms Case 1 Case 2

Simulation Case 1: homogeneous type same as Heckman model

Simulation Case 2: individual has the same behavior responds regardless of the type