TABLE 1.
The impact of age structure on COVID-19 total cases in April 2020.
| Independent variables | GLM1,2 | GMM3,4,5 | Quantile (25)6,7,8 |
| Median age | 7.91 (1.13) [6.98] {0.00} | 6.80 (1.40) [4.84] {0.00} | 0.35 (0.26) [1.34] {0.18} |
| Quantile (50)6,7,8 | |||
| 1.60 (0.28) [5.66] {0.00} | |||
| Quantile (75)6,7,8 | |||
| 5.88 (0.98) [5.98] {0.00} | |||
| Aged-65_older | 27.40 (3.19) [8.58] {0.00} | 2 3.46 (3.70) [6.32] {0.00} | 2.41 (1.14) [2.11] {0.03} |
| Quantile (50)6,7,8 | |||
| 8.97 (1.39) [6.40] {0.00} | |||
| Quantile (75)6,7,8 | |||
| 24.51 (4.96) [4.93] {0.00} | |||
| Aged-70_older | 43.17 (4.85) [8.89] {0.00} | 37.47 (5.71) [6.56] {0.00} | 3.73 (1.79) [2.08] {0.03} |
| Quantile (50)6,7,8 | |||
| 15.42 (2.19) [7.01] {0.00} | |||
| Quantile (75)6,7,8 | |||
| 42.66 (5.66) [7.53] {0.00} |
1By Newton-Raphson-Marquardt steps. 2The coefficient covariance is computed using observed Hessian. 3Estimation weighting matrix: HAC (Bartlett kernel, Newey-West fixed bandwidth = 5.0000). 4Standard errors and covariance are computed following the estimation weighting matrix. 5Instrument specification: total-cases-per-million (−1). 6Sparsity methods: Kernel (Epanechnikov) using residuals. 7Bandwidth methods: Hall-Sheather. 8Estimation successfully identifies the unique optimal solution. () shows standard errors, and {} denotes probability values.