Using the same regression model, . reg in_poverty age agesq female nonwhite nonw_female educ educsq if age>18 & age F 0. 0600 Residual 5700. 60627 56,546 . 100813608 R-squared 0 . 0551 Adj R-squared 0 . 0550 Total 6033. 18296 56, 553 .106681926 Root MSE 31751 in_poverty Coef. Std. Err. t P>/t| [95% Conf. Interval] age -. 0102299 . 0007482 -13.67 0.080 -. 0116963 -. 0087635 agesq . 0001037 8. 80e-06 11.79 0.080 . 0060865 . 000121 female . 0397521 . 0032806 12. 12 0. 080 033322 0461821 nonwhite . 0374338 . 8041774 8.96 0.080 . 029246 0456215 nonw_female 025706 .. 0056767 4.53 0.080 . 0145796 .0368323 educ -. 0640194 . 0016982 -2.37 0. 018 -. 0073479 -. 0606909 educsq -. 0606778 . 8000686 -9.88 0.080 -. 0008122 -. 0805433 _cons 4989025 0187705 26.58 0.080 4621122 5356928 how does age impact the propensity to be in poverty? Age only impacts the propensity to be in poverty for females. Being a year older, at young ages, increases the propensity to be in poverty, but at older ages an increase in age is associated with a decrease in the propensity to be in poverty. Being older always reduces the propensity to be in poverty, as everyone is below age 65. Being a year older, at young ages, decreases the propensity to be in poverty, but at older ages an increase in age is associated with an increase ithe propensity to be in poverty. Question 19 (10 points) m 9