CAPÍTULO 5. “RESULTADOS Y EJEMPLOS”
5.1. S IMULADOR DEL MICROPROCESADOR Y ENVIÓ DE DATOS
I used a sample of identical twins to estimate the health returns to di¤erent levels of education. The results suggest a causal e¤ect running from education to health. Higher educational levels are found to be positively related to self-reported health but negatively related to the number of chronic conditions. In contrast, estimates based on imputed number of years of schooling showed only small associations with health in the pooled twin sample and no signi…cant association when employing twin FE methods.
My results do not provide any evidence that that the education/health gra-dient works through important lifestyle factors, such as smoking and overweight, or factors such as job risks and health insurance coverage. To the best of my knowledge, this is the …rst attempt to apply a twin-di¤erencing approach to the topic. A twin-di¤erencing approach may provide estimates that come closer to re‡ect an Average Treatment E¤ect compared to studies using educational re-forms, for instance, to identify the e¤ect of education on health. Further studies should continue to explore the mechanisms, while properly controlling for the endogeneity of education.
My results does not provide any evidence that unobserved "ability" di¤er-ences within twin pairs are biasing my within-twin-pair estimates. I investigated this by …rst estimating the correlation between average twin-pair education and average average twin-pair early life characteristics that may be correlated with
"ability" and/or time preferences, such as birthweight, early life mental and physical health, early health behaviours, and parental treatment. By compar-ing these estimates with those obtained from regressions on within-twin-pair di¤erences in education on within-twin-pair di¤erences in the same early life characteristics, I was able to get an indication of the expected "ability" bias in the regressions. The results indicated that the ability bias is less in the within-twin-pair estimates.
For self-reported health, I found that the twin FE estimates exceeded the OLS estimates. This is a bit unexpected, since it is usually assumed that the OLS estimates are upward biased and that controlling for unobserved ability will reduce the magnitude of the estimates. A similar results for the wage returns to education was obtained by Ashenfelter and Kreuger (1994).19 One interpretation is that the correlation between ability, schooling, and health is more complex than what is usually assumed. If unobserved components, such as ability, a¤ects the marginal cost of schooling, but not the marginal bene…t, a negative correlation between ability and schooling may result. For instance, the marginal cost of schooling may be higher for people with high ability, since the foregone earnings are greater. If twin di¤erencing removes unobserved ability, estimates will then increase in magnitude.
While I was able to address the issue of within-twin-pair ability bias, I was not able to account for the in‡uence of measurement errors in the reports on
1 9This result did not hold, however, when Rouse (1998) and Ashenfelter and Rouse (1998) replicated the study with larger samples, suggesting that the …nding of Ashenfelter and Kreuger (1994) was an artifact of their sample.
schooling. It should be noted, though, that ability bias give rise to an upward bias in the estimates, whereas measurement errors give rise to a downward bias.
For the purpose of this paper, it was more important to address the former problem, since knowledge is still needed as to whether education has a causal e¤ect at all on health.
In future work, I will consider a much larger sample of twins, drawn from twin registers. This will allow me to address the issue of heterogenous health returns to education with much greater precision, to adress the measurement errors problem, as well as to examine a greater range of health outcomes and health behaviours.
7 References
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8 Tables
Table 1: Descriptive statistics.
Variables Means (std. err.)
Main sample Twin sample CPS Socio-economic and demographic
Female (percent) 0.505 0.527 0.517
(.009) (.019)
Age 25-34 0.215 0.226 0.276
(.007) (.016)
Age 35-44 0.246 0.317 0.270
(.007) (.018)
Age 45-54 0.236 0.249 0.192
(.007) (.016)
Age 55-64 0.192 0.141 0.139
(.007) (.013)
Age 65-74 0.109 0.066 0.122
(.005) (.009)
White 0.880 0.934 0.848
(.006) (.010)
Married or cohabitating 0.678 0.776
-(0.008) (.015)
High school graduate 0.297 0.318 0.342
(.008) (.018)
Some college (no bachelor) 0.309 0.330 0.276
(.008) (.018)
College graduate 0.283 0.291 0.226
(.008) (.017)
Income ($1,000) 23,549 25,979
(463.724) (1001.463) Health variables
Health 0-10 scale 7.348 7.856
(.031) (.057)
Number of chronic conditions 2.569 1.982
(.049) (.086)
Smoking 0.243 0.213
(.007) (.016)
Physical activity 5.158 5.822
(.100) (.214)
Body Mass Index 26.893 26.025
(.104) (.191)
Overweight 0.495 0.490
(.009) (.019)
Work impact on health 2.590 2.612
(.023) (.048)
Work accident 0.610 0.545
(.064) (.081)
Health insurance 0.886 0.901
Table 2: Regressions on self-reported health and the number of chronic condi-tions.
Variables Main Pooled FE Main Pooled FE
Self-reported health Number of chronic conditions
Age -0.038** -0.051 0.100*** 0.090*
(0.018) (0.036) (0.028) (0.052)
Age squared 0.000** 0.001* -0.001** -0.001
(0.000) (0.000) (0.000) (0.001)
Female 0.024 0.119 0.567*** 0.695***
(0.063) (0.115) (0.098) (0.168)
White -0.149 -0.588** 0.043 -0.661**
(0.096) (0.230) (0.151) (0.335)
Married/Part. 0.007 0.038 0.075 -0.090 -0.132 -0.275 (0.071) (0.144) (0.198) (0.112) (0.210) (0.261) Income 0.003*** 0.002** 0.003** -0.003*** -0.002 -0.002
(0.001) (0.001) (0.002) (0.001) (0.002) (0.002) High school 0.480*** 0.569** 1.043** -0.784*** -1.703*** -1.480***
(0.114) (0.254) (0.422) (0.180) (0.370) (0.556) Some college 0.382*** 0.658** 1.242*** -0.745*** -2.055*** -1.203**
(0.114) (0.255) (0.440) (0.180) (0.372) (0.579) College degree 0.590*** 0.904*** 1.221** -1.203*** -2.005*** -0.941
(0.118) (0.260) (0.507) (0.186) (0.379) (0.667) Constant 7.672*** 8.340*** 6.476*** 0.313 1.917 3.508***
(0.422) (0.874) (0.435) (0.664) (1.274) (0.572)
n 2877 642 624 2886 641 622
Table 3: Regressions on smoking.
Variables Pooled FE Pooled FE
Smoking Smoking at 16
Age 0.009 -0.005
(0.010) (0.012)
Age squared -0.000 0.000
(0.000) (0.000)
Female 0.032 -0.135***
(0.031) (0.040)
White 0.060 0.165**
(0.063) (0.080)
Married/Part. -0.055 0.051 -0.052 -0.045 (0.039) (0.043) (0.050) (0.056)
Income -0.001* -0.000 0.001 -0.000
(0.000) (0.000) (0.000) (0.000) High school -0.183*** -0.070 -0.077 0.010
(0.069) (0.098) (0.088) (0.126) Some college -0.185*** -0.047 -0.121 -0.173
(0.070) (0.101) (0.088) (0.131) College degree -0.357*** -0.167 -0.226** -0.023
(0.071) (0.116) (0.090) (0.150) Constant 0.325 0.270*** 0.728** 0.603***
(0.238) (0.100) (0.303) (0.130)
n 642 690 638 686
Table 4: Regressions on physical activity, BMI, and overweight.
Variables Pooled FE Pooled FE Pooled FE
Physical activity BMI Overweight
Age -0.140 0.189* 0.018
(0.123) (0.114) (0.012)
Age squared 0.001 -0.002 -0.000
(0.001) (0.001) (0.000)
Female 0.773* -1.526*** -0.230***
(0.401) (0.371) (0.039)
White 1.053 -1.663** -0.128
(0.796) (0.744) (0.078)
Married/Part. 0.438 -0.228 -0.230 -0.083 0.009 -0.019
(0.499) (0.743) (0.464) (0.405) (0.049) (0.056)
Income 0.006 0.007 -0.004 -0.001 -0.000 -0.000
(0.004) (0.006) (0.004) (0.003) (0.000) (0.000)
High school 1.427 3.049* -1.607* 0.751 -0.156* -0.003
(0.880) (1.574) (0.825) (0.839) (0.087) (0.127) Some college 1.827** 3.369** -2.266*** 0.027 -0.160* -0.009 (0.884) (1.642) (0.829) (0.881) (0.087) (0.132) College degree 2.198** 3.314* -3.160*** 0.019 -0.200** 0.050
(0.899) (1.890) (0.840) (1.018) (0.089) (0.151) Constant 9.252*** 5.909*** 26.406*** 25.757*** 0.510* 0.519***
(3.030) (1.623) (2.814) (0.871) (0.298) (0.131)
n 639 646 618 625 642 690
Table 5: Regressions on occupational hazards.
Variables Pooled FE Pooled FE
Job a¤ects health Number of work accidents
Age -0.004 0.028
(0.036) (0.061)
Age squared -0.000 -0.000
(0.000) (0.001)
Female -0.195** -0.335**
(0.098) (0.169)
White -0.279 0.365
(0.203) (0.347)
Married/Part. -0.131 -0.053 0.087 0.538 (0.121) (0.201) (0.207) (0.385)
Income 0.000 0.001 -0.002 0.000
(0.001) (0.002) (0.002) (0.003)
High school -0.193 0.144 -0.134 -0.447
(0.237) (0.509) (0.407) (0.974)
Some college -0.359 -0.107 0.277 0.201
(0.237) (0.507) (0.406) (0.971) College degree -0.305 0.010 -0.124 -0.981
(0.237) (0.560) (0.406) (1.073)
Constant 3.748*** 2.561*** 0.222 0.468
(0.805) (0.510) (1.385) (0.974)
n 499 481 498 482
Table 6: Regressions on health insurance.
Variables Pooled FE
Health insurance
Age 0.003
(0.007) Age squared -0.000
(0.000)
Female 0.003
(0.023)
White 0.057
(0.046)
Married/Part. 0.053* -0.011 (0.029) (0.044)
Income 0.089* 0.000
(0.052) (0.000) Health insur.
High school 0.133** -0.014 (0.052) (0.095) Some college 0.179*** -0.119
(0.053) (0.098) College degree 0.001** -0.036
(0.000) (0.112) Constant 0.538*** 0.925***
(0.176) (0.096)
n 638 614
Table 7: Pooled twin sample and twin FE of the health returns to education by parents’education.
Variables Pooled FE Pooled FE
Self-reported health Chronic conditions
High school 1.911** 1.251*** -1.768 -1.289**
(0.741) (0.441) (1.086) (0.581)
Some college 1.699** 1.244*** -0.904 -0.985
(0.744) (0.459) (1.090) (0.604)
College degree 1.711** 1.250** -1.341 -0.933
(0.747) (0.514) (1.095) (0.677) High school * parents’educ -0.882* -0.382** -0.076 0.093
(0.497) (0.174) (0.729) (0.229) Some college * parents’educ -0.702 -0.134 -0.737 0.059
(0.487) (0.127) (0.714) (0.168) College degree * parents’educ -0.600 -0.174 -0.470 0.227
(0.481) (0.108) (0.706) (0.143)
Parent’s educ 0.605 0.508
(0.468) (0.686)
n 609 294 608
Table 8: Di¤erences within twin pairs in early life.
Variables Parents emphasized Twins shared Twins shared di¤erences between same classroom playmates
the twins
Always 1.5% 35.4% 53.1%
Most of the time 6.2% 21.8% 36.6%
Some of the time 6.8% 28.6% 8.6%
Never 85.5% 14.2% 1.8%
Table 9: Correlation of education and other characteristics between twin pairs and within twin pairs.
Variables Correlation between average Correlation between within-twin-pair twin-pair education and average di¤erences in education and
twin-pair characteristics within-twin-pair characteristics
Education Education
Birthweight 0.0001 0.0001
Phys. health at 16 0.0572 0.068
Ment. health at 16 0.0404 0.0446
Mother: time and attention 0.1568** 0.0049
Father: time and attention -0.0860 0.0641
Mother: ove and a¤ection -0.0543 0.0201
Father: love and a¤ection -0.0038 0.1056**
Mother: strictness about rules -0.0076 0.0521
Father: strictness about rules 0.1081* -.0044
Mother: harsch when punishing 0.0369 0.0256
Father: harsch when punishing 0.1120* 0.0106
Mother: relationship rating -0.0036 -0.0445
Father: relationship rating -0.0268 -0.0075
Mother: expectations -0.2266*** -0.0128
Father: expectations -0.0778 -0.0044
Mother: physical abuse 0.1269** 0.0446
Father: physical abuse 0.2015*** 0.0275