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## Life expectancy at birth versus GDP per capita (PPP)Graphs
/ Images, Econometrics / EconomicsThe data for this graph is available from the Index Mundi website. The data is from 2003. The graph shows that life expectancy at birth, increases at a decreasing rate with respect to The main reason for this non-linear relationship is because people consume both needs and wants. People consume needs in order to survive. Once a person’s needs are satisfied, they could then spend the rest of their money on non-necessities. If everyone’s needs are satisfied, then any increase in GDP per capita isn't the only thing that affects life expectancy. Government intervention can also affect it. A nation could be rich, but if its government ignores the plight of the poor, it could lower the life expectancy. Some poor nations have high life expectancies because their governments’ strongly prioritise needs over wants. Another reason for the wide variation in the life expectancies for countries with low The relationship between life expectancy and The following is R output for a regression model that was fitted to the data: > fit=lm(LifeExpectancyAtBirth~I(1/(GDPpcPPP+1200))+GDPpcPPP+LElt40) > summary(fit) Call: lm(formula = LifeExpectancyAtBirth ~ I(1/(GDPpcPPP + 1200)) + GDPpcPPP + LElt40) Residuals: Min 1Q Median 3Q Max -27.9828 -2.5941 0.3209 3.0735 22.6424 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 7.549e+01 1.513e+00 49.884 <2e-16 *** I(1/(GDPpcPPP + 1200)) -4.827e+04 4.376e+03 -11.032 <2e-16 *** GDPpcPPP 1.401e-04 6.537e-05 2.143 0.0335 * LElt40 -2.319e+01 2.200e+00 -10.540 <2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 6.316 on 176 degrees of freedom Multiple R-squared: 0.7591, Adjusted R-squared: 0.7549 F-statistic: 184.8 on 3 and 176 DF, p-value: < 2.2e-16 The above output won’t make much sense to a layperson. The regression output shows that the following equation was estimated (for countries with life expectancy of at least 40) where y is the life expectancy at birthx is The regression model includes: - An intercept
- A hyperbolic term
- A linear term
- A dummy variable with a 1 for countries with a life expectancy less than 40; 0 otherwise. There were only nine countries with life expectancy less than 40.
The estimated equation can be added to the graph: To comment on this or other blog posts, join the Statistical Consultants Ltd Facebook page or Google+ page. Suggestions for blog posts are welcome. |

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