notes Population Momentum

notes Population Momentum - Eco 572 Research methods in...

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Eco 572: Research methods in Demography Population Momentum Our final unit focuses on population momentum, the notion that in most of the world population would continue to grow even if fertility dropped suddenly to replacement level. I used Mata for the calculations, but I could have done them just a easily using Stata. An alternative version of the handout using only Stata is available here. Momentum in Western Asia We turn to Box 7.3 in the textbook, which uses data from Western Asia in 1995-2000 to illustrate the Preston- Guillot calculations. We start by entering the female population, the survival ratios, and the maternity function . mata: ------------------------------------------------- mata (type end to exit) ------------------------------------------- : N = (12013,11027,9856,8614,7694,6893,6135,5318,4376,3510)' : L = (4.834,4.803,4.789,4.773,4.748,4.716,4.678,4.631,4.570,4.483)' : m = (0,0,0,0.043,0.112,0.112,.058,.029,.007,0)' : nrr = sum ( L :* m) : nrr 1.70282 : end --------------------------------------------------------------------------------------------------------------------- We see that the net reproduction rate is 1.703 daughters per woman. The population of Western Asia is growing fast. What would happen if fertility dropped instantly to replacement level? One way to answer the question would be to adjust the maternity function and do the projection. Here we will consider the alternatives. The Preston-Guillot Method We first need to estimate the replacement-level maternity function, which we do by simply dividing the observed rates by the NRR. (Note that there are many other maternity functions that would work just as well, we follow tradition in assuming a proportionate decline.) We also need the mean age of the new maternity schedule. . mata: ------------------------------------------------- mata (type end to exit) ------------------------------------------- : ms = m/nrr : sum( L :* ms) 1 : a = range(0,45,5) :+ 2.5 : as = sum( a :* ms :* L) : as 26.60042753 : end --------------------------------------------------------------------------------------------------------------------- The mean age is 26.60, in agreement with the textbook. (Note that we computed just the numerator of the mean
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