Table 3.
Two Stage Least Squares Regressions Stratified by Income.a
| Two Stage Least Squares | Low-Income Counties | Middle-Income Counties | High-Income Counties | |||
|---|---|---|---|---|---|---|
| β0 | λ | β0 | λ | β0 | λ | |
| (SE) | (SE) | (SE) | (SE) | (SE) | (SE) | |
| Infant deaths PC | 0.0251b | −1.5971c | 0.0009 | −0.8420b | 0.0077 | −0.1788 |
| (0.0106) | (0.5581) | (0.0093) | (0.3255) | (0.0062) | (0.3651) | |
| Early deaths PC | 0.0366 | −0.1818 | 0.0218 | −0.3758 | 0.0211 | −0.6339 |
| (0.0267) | (0.5693) | (0.0171) | (0.2585) | (0.0234) | (0.3816) | |
| Heart disease deaths PC | −0.0205 | 0.1109 | 0.0764b | −0.3458c | 0.0986 | −0.2931 |
| (0.0730) | (0.3146) | (0.0365) | (0.1226) | (0.0683) | (0.3066) | |
| Cancer deaths PC | −0.0011 | 0.6634 | 0.0421 | −0.5703c | −0.0181 | 0.1301 |
| (0.0503) | (0.4039) | (0.0502) | (0.1481) | (0.0429) | (0.5442) | |
| Diabetes deaths PC | 0.0159 | −0.6951d | 0.0044 | 0.0415 | 0.0031 | −0.5459d |
| (0.0143) | (0.3703) | (0.0167) | (0.2949) | (0.0114) | (0.3097) | |
| Asthma deaths PC | 0.0043 | −0.1377 | −0.0031 | −1.6468d | 0.0026 | −1.3495b |
| (0.0026) | (0.1842) | (0.0031) | (0.9494) | (0.0030) | (0.5834) | |
| Cancer PC | 0.0452 | 0.8303d | −0.0119 | −0.4864d | 0.0954d | −0.7930 |
| (0.0721) | (0.4249) | (0.0271) | (0.2887) | (0.0568) | (0.5328) | |
| Heart disease PC | 0.2215 | 0.3233d | 0.4989c | −0.1204 | 0.0880 | 0.2569 |
| (0.1982) | (0.1772) | (0.1584) | (0.1661) | (0.1588) | (0.3983) | |
| Diabetes PC | 0.0014 | −0.3853 | 0.0255 | −0.2392 | −0.0162 | −0.1510 |
| (0.0396) | (0.2741) | (0.0337) | (0.2483) | (0.0365) | (0.2619) | |
| Asthma PC | 0.0201 | 0.5048 | 0.0281 | 0.1193 | 0.0181 | 0.3274 |
| (0.0627) | (0.4818) | (0.0232) | (0.2171) | (0.0365) | (0.4777) | |
Abbreviations: FE, fixed effect; GGIA, general grant-in-aid; SE, standard error.
aThe data used in this analysis come from Georgia’s 159 counties from 2000 to 2011 (N = 159, T = 12). This represents a sample size of 1908 county-years. Standard errors, clustered by county, are in parentheses. Income per capita, number of medical doctors per 1000, age and racial/ethnic distributions, and unemployment rates are included in each model. The impact of an extra US$1000 GGIA PC on health outcomes is estimated, and dollar figures are adjusted for inflation and expressed in constant 2009 dollars. All specifications in this table include county and year fixed effects as well as lagged values of public health spending. For full results, see http://www2.gsu.edu/˜ecojhm/public_health.html.
bStatistical significance at the 5% level.
cStatistical significance at the 1% level.
dStatistical significance at the 10% level.