Follow along with the video below to see how to install our site as a web app on your home screen.
Note: This feature may not be available in some browsers.
I'm happy about that just because it means they'll continue to deflate into not being relevant which I like
@Mista
I think the Korean age pyramid is different, and it looks actually more like 1,17 than Chinese 1,5. But let me be clear I didn't "eye-balled" both pyramids, I did some counting to estimate it good enough. I will try to find my post at the Polish forum where I counted it in a simple way. (Unfortunately, I was looking for it but I couldn't find it - the search button doesn't work at this forum, idk why)
But I did it like that. I had looked at the similar Polish data (Children born that year, and Women which were at the age of 15-49) Polish official statistics showed that TFR at that time was 1,42 or 1,39 or sth like that. I did some simple maths e.g. multiplication and so on. And it showed me that Chinese women at that age have a bit more children than Polish, so the conclusion is China should have a higher TFR. Of course, it's not very accurate, but I think good enough.
You can count by real TFR formula if you can find data on how many children were born by women age 15-19 and so on. Maybe it will be 1,17 but I think it will be ~1,50.
There are some explanations, NBS are taking their statistics from the ***
How is that low TFR in 2015 possible(1,05 by a survey) even possible with that much births 15/16/17 million (recent years) and about 360m women age 15-49?
if Poland had similar to China population (I had also taken into account TFR bearing women at that time when I was counting), Poland with TFR of about 1,4 would have lower births than China with TFR 1,05.
Does an increase in births mean that TFR will definitely go up?
An increase in the number of births does not necessarily lead to an increase in TFR. Whether TFR will increase depends not only on the number of births (numerator), but also on the number of women in the childbearing age groups (denominator). Thus, even if there are more births, TFR may not increase if there are also more women in the childbearing age groups.
We observed this phenomenon in 2015-2017, where the number of Singapore Citizen births were relatively higher than the past decade’s average (for example, there were 32,353 births in 2017[1] and 33,167 births in 2016, above the decade’s average of about 32,200), yet TFR declined to 1.20 in 2016 and 1.16 in 2017 (from 1.24 in 2015). While there were more babies, the number of women entering the peak child-bearing age groups (25-39 years) had also risen. These women were born in the decade starting from 1988, and many of them are children of the Baby Boomer generation. The oldest of this cohort was just 29 years old in 2017. Compared to earlier cohorts, more of them were not yet married or had not started having children yet.
Over the years, the ASFRs have been gradually declining for those aged below 30 years, while rising slightly for those aged 30 years and over. In 1980, fertility rates were highest among females aged 25-29 years. With the delay in childbirth among females, fertility rates have become highest among females aged 30-34 years instead.
Yes, I have looked into it, and it's 15-49. I wouldn't compare it if it's different.Why not?
And why do you keep approximating China's TFR through comparison with Poland?
Look, TFR is calculated by adding up the average number of births per woman across five-year age groups (i.e. age-specific fertility rates, or ASFR). This is because a woman giving birth in her 20s can potentially continue to give birth in her 30s or 40s, unlike a woman in her 40s.
It's not just plonking in the number of births divided by the number of woman aged 15-49, or worse, approximating through another country with different culture and demographics.
Does Poland have the exact same demographic as China? Does Poland have the exact same childbearing age as China? Does Poland have the same peak child-bearing age group as China? Does the average Polish woman have exactly the same number of children as the average Chinese woman in that specific age group?
There are so many different factors at play here which cumulatively make a big difference. Eg; just a 10% difference away from a 1.4 TFR in Poland is a 0.14 difference in TFR. Your made up method is plain simplistic.
Case in point, in Singapore:
View attachment 636747
It's not that simple just by looking at the number of births or comparing with another country without the details.
I've counted in approximation.
TFR in Poland was 1,5 in 2016, here is a population pyramid
And here is Chinese population pyramid.
If you compare it with Poland TFR it is impossible that Chinese TFR was such low in 2016 and 2015.
There are some explanations, NBS are taking their statistics from the ***, the second - population born was smaller than 16,5m. Third NBS has their own definition of TFR different than the rest of the world.
Nothing wrong with a lower population. Japan is overpopulated as is so I don't think it'll be too bad.
Yes, I have looked into it, and it's 15-49. I wouldn't compare it if it's different.
I know it's not that simple but I couldn't find statistics to count it professionally so I made a short comparison to check the results if 2015 TFR 1,05 is reality. And the differences are too big in TFR.
And in the end, I was right that the NBS survey shows different data than official statistics of births given by China at the end of the year.
The year 2015 - NBS survey TFR 1,05 - Children born by survey 11,31m
The year 2015 - TFR 1,54 - if counted by official Chinese year-end statistics of births 16,55m.
So mine estimations of 1,50-1,55 are pretty good, and it looks like the children born in Poland and China are almost by the same age groups of women.
I knew the flaws, but I didn't have any other way to compare TFR and I wanted to check it. Because when I looked at Chinese live births at 16,55m or later almost 18m and looked at Poland it was strange to me that Chinese TFR is only 1,05.Well, if you insist on comparing with Poland despite me explaining the flaws of your premise, then show me mathematically how.
[URL='https://www.ncbi.nlm.nih.gov/pubmed/?term=Wang%20M%5BAuthor%5D&cauthor=true&cauthor_uid=30976710']Mengqiao Wang[/URL] said:There has long existed the controversial debate on the precise value of TFR in China. The most-recent TFR in China was reported as 1.62 by the World Bank (2016) and 1.60 by the United Nations (2011–2015), all significantly higher than the NBS level of 1.05 calculated for 2015 and 1.08 forecasted for 2016. The most critical argument against the raw TFRs calculated from age-specific CFRs was that the NBS sample surveys underreported births due to various potential reasons [28, 29, 30], e.g. respondents' unwillingness to report new births in fear of financial penalty, or difficulty to track the migrating groups. Assuming the surveys as simple random samples of the whole population, inference of annual births from the fertility and demography datasets indeed displayed a systematic underestimation compared to annual live births aggregate-reported by the NHFPC (Fig. 16A). The differences were 2–5.2 million in counts and 12%–32% in proportion from 2003 to 2015, and in 2016, the gap became bigger as the termination of “one-child” policy was not factored into the predictive model. Using the underestimation proportion in annual births as weights of adjustment, adjusted TFRs displayed a systematic lift of 0.2–0.5 compared to raw TFRs (Fig. 16B). Once adjusted, TFRs were in the range of 1.6–1.8 during 2003–2010, and since then dropped to 1.45–1.55, matching the levels reported by the World Bank and the United Nations. Interestingly, adjusted TFR forecasted for 2016–2018 displayed a spike to 1.65 in 2016 but the temporary rise immediately reversed to a sequential decrease since 2017, arguing against the claim that terminating the “one-child” policy but keeping a “two-child” limit was sufficient in restoring replacement-level fertility.
A third parameter of the completed fertility rates longitudinally track a cohort of representative women up to the end of their fertility life, and sum age-specific CFRs of this defined cohort to reveal fertility at the materialized level. However, the requirement of longitudinal surveys on a single cohort made the task very challenging, especially in large and under-developed countries like China. To overcome the difficulty, this study used data from a large national survey in place of a cohort for displaying the number of children women have had by their ages. China Family Panel Studies (CFPS) is a comprehensive and nationally representative longitudinal social survey at the individual, family, and community levels, launched with baseline survey in 2010 and first follow-up survey in 2012 [31]. With a conservative quality-control standard of matching the sex and age of children in both 2010 and 2012 surveys, a total of over forty thousand respondents were analyzed for age-specific “pseudo” completed fertility in 2012 (Fig. 16C) [32]. For the birth-completed group (age 50+, born between 1935 and 1962), those born before 1953 displayed sequential drop in the average number of children from 3.61 to 2.19, all of which were above the replacement level of 2.1, but those born between 1954 and 1962 displayed largely stable level of 1.85–2.03, all below 2.1. Therefore, assuming 15–49 as fertility years, the fertile-active group had since 1969 shifted from replacement level to sub-replacement level, and by 2003 (those born in 1953 turning 50), there was no longer any fertile-active group with completed fertility rates over 2.1. Meanwhile, for the birth-active group (age of 15–49, born between 1963 and 1997), the “pseudo” completed fertility rates were still growing, but did not appear able to surpass a threshold of 1.90. Notably, people born in 1965 turned 15 in 1980 (when “one-child” policy officially started), and became the first wave under full fertility regulation; the group had on average 1.87 children as of 2012 (with 2 more years of fertility available), and this level likely stood as the upper threshold for all following generations. People born in 1977 turned 35 in 2012, and assuming all 1st births happen by the age of 35 and considering the limit of one birth per couple, their completed level of 1.47 would theoretically no longer rise beyond 2012, and thus presumably mark the true upper threshold of fertility in the “one-child” era.
Good idea ,maybe encourage immigrants like the gulf countries.Japan needs to import Pakistani Males
Women in Poland age 15-49 about 9,45m (338,1m if Poland had the same population as China)
Women in China age 15-49 about 360m
-----------
360/338,1 ~ 1,065
-----------
Population in China 2015 - 1,374B
Population in Poland 2015 38,4m
Population in China is ~ 35,78 x more than in Poland
Births in Poland 369 308 - TFR in 2015 - 1.29
Births in China official 16,55m - TFR 1.54 and NBS survey (today I found the data) 11.31m - TFR in that case 1.05
----------
Births and TFR in Poland if Poland had the populations of China and similar population of women = 369 308 * 35,78 = 13,21m TFR 1,29/1,065 = 1,21
16,55/13,21 ~ 1,253
TFR estimated if Poland had a 16,55m births and population women 15-49 the same as China 1,21 * 1,253 = 1,516
But I think mine estimation doesn't matter here, more important is the fact that the NBS survey puts the number of children born in China at 11.31m but official statistics say it was 16.55m. That's what matters here, and I think we or rather the Chinese government should clarify what's going on.
近一二十年来,各种证据一再显示中国早已经陷入超低生育率陷阱。根据国家统计局的数据,中国2010到2014年的生育率分别为1.18、1.04、1.26、1.24、1.28,平均生育率仅1.2,即使取最高值也只有1.28。但2015年11月5日国家卫计委基层指导司司长杨文庄,依然声称实际生育率介于1.5到1.6。如果说生育率确实有这么高,那意味着2015年耗资不菲的人口小普查所得出的1.05的数据就漏算了1/3的婴儿;普查机构是不是应该为这么大的漏报比例承担责任?
由于都是基于抽样,再加上各种宏观因素影响,各年生育率会有一定波动性,但不可能会相差1/3。问题并不是国家统计局抽样调查的漏报,而是计划生育部门以漏报为理由一而再、再而三地大幅调高生育率数据,严重误导决策层和民众。上个月,湖北宜昌市卫计委等部门联合发出提倡生育二孩的公开信后,我们就关注过当地的生育数据。2015年8月宜昌进行了一项大规模的生育调查;结果显示,当地2015年总和生育率仅有0.81。宜昌的调查是基于30%的育龄妇女,抽样比例是一般生育率调查的30倍,应当非常准确。
宜昌是一个地级市,包括5个县,其中还有少数民族地区,该地的城市化率还略低于全国平均水平。考虑到这些因素,如果说宜昌的生育率仅有0.81,那全国1.05的生育率并不离奇。宜昌的数据也暗示,国家统计局根据人口普查和每年抽样调查所公布的数据,并不像计划生育部门一直宣称的那样严重高估了生育率;而后者对生育率的调整则是刻意的误导。而且,2015年的数据是来自抽样比例较高的小普查,按理应该比之前的几年更准确。
由于总有部分人不婚不育,或只愿生育一两个孩子,少数家庭生育特别多孩子对维持民族繁衍至关重要。在一个正常社会中,不同家庭的生育意愿千差万别。假定意愿孩子数呈如下的分布:6、3、2、2、1、1、0,且所有家庭都能如愿,那一共7个家庭将生育15个孩子,生育率为2.14,勉强接近更替水平。而在这15个孩子中,来自三孩或六孩家庭的有9个,占总数的2/3;来自两孩家庭的孩子只有4个;而独生子女只有2个,不到总数的1/7。这也意味着,当来自三孩和三孩以上家庭的孩子非常普遍时,生育率才刚处于更替水平。
这也说明,全面二孩政策远远不够。在该政策下,上述家庭的生育数量将分别变成2、2、2、2、1、1、0,即7个家庭总共生育10个孩子,生育率仅为1.43。即当人们感觉二孩家庭孩子非常普遍时,生育率已经远低于更替水平了。
比较一下辽宁与韩国的生育政策,更能看出辽宁严惩三孩政策的荒谬。韩国面积约10万平方公里,2015年人口约4900万,出生43.87万。辽宁面积约15万平方公里,2015年人口4382多万,但仅出生25.02万人。辽宁的面积是韩国的1.5倍,人口是韩国的89.4%,但新生儿却只有韩国的57.0%。