Table 5.
Estimated results for regressions using diabetes as dependent variable
| Variable | OLS | Robust Estimation |
|---|---|---|
| Obesity rate | 0.1329*** | 0.0981*** |
| Hypertension rate | 0.0279 | 0.0221* |
| Ln(GDP) | 0.0036* | 0.0023* |
| Ln(wage) | 0.0066 | 0.0051* |
| Health center density | 0.0037*** | 0.0023*** |
| Hospital density | −0.0063* | −0.0055** |
| Household size | −0.0064* | 0.0004 |
| Gender | −0.001 | −0.0005 |
| Age | 0.0022*** | 0.0013*** |
| East | 0.0064* | 0.0031* |
| Middle | 0.0008 | 0.0007 |
| North | 0.0024 | 0.0014 |
| Constant | −0.0152 | −0.0709*** |
| F (Wald) test for all variables | 24.07*** | 37.60*** |
| R square | 0.5124 | |
| Adjusted R square | 0.4911 | |
| Hausman Test for two regressions | χ2-statistic—46.22*** | |
| Skewness/Kurtosis test for Normality | χ2-statistic—18.81*** | |
| Shapiro-Wilk W test for Normality | z-statistic—8.615*** | |
| Shapiro-Francia W test for Normality | z-statistic—7.829*** | |
Note: The null hypothesis for F or Wald test is that the concerned coefficients are jointly equal to zero. The null hypothesis for normality test is the normal distribution of the model
*, **, and *** give the coefficients’ significance indicated by estimated standard errors or bootstrap standard errors at 10%, 5% and 1% level individually