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A paper on the prediction of urban population size
Understanding the potential pattern of future population level is very important for forecasting and planning the changing age structure, resources and medical care needs, as well as the environment and economic situation. The future fertility model is the key input to estimate the future population size, but there are huge uncertainties and differences in the estimation and prediction methods around it, which leads to significant differences in global population prediction. In many countries, the changing population size and age structure may have a far-reaching impact on economy, society and geopolitics.

Recently, SteinEmilVollset and others of the University of Washington published an online article entitled "Fertility rate, mortality rate, migration and population scenarios in 20 195 to 20 100 195 countries and regions: Africa struggles for the global disease burden". The study found that the global population is expected to reach 97.5% in 2064. Asia and Central and Eastern Europe will become the regions with the fastest population decline, and the population of 23 countries and regions such as China, Japanese, Korean and Italian will be reduced by half.

2 100 the top five national reference forecasts are India, Nigeria, China, the United States and Pakistan. The results also show that by 2 100, the age structure in many parts of the world is changing, with 2.37 billion individuals over 65 years old and17 billion individuals under 20 years old. It is predicted that by 2035, China will become the largest economy.

In a word, the research results show that the continuous trend of women's education level and contraceptive methods will accelerate the decline of fertility rate and slow down the population growth. If the total fertility rate remains below 2. 1, many countries, including Japan, India and South Korea, will have economic, social, environmental and geopolitical consequences. In the next few years, while maintaining and enhancing women's reproductive health, it will be very important to choose policies that adapt to the sustained low fertility rate.

Population forecasting is an important planning and risk management tool for governments, enterprises, non-governmental organizations and individuals. The government needs short-term and medium-term plans to estimate the demand for schools, hospitals and other public services; Help to provide long-term benefits for infrastructure investment; Planning the necessary skills and knowledge for the future workforce; Invest wisely in health research and development resources. The government needs long-term population growth to understand the potential environmental, military, geopolitical and other risks and implement prevention or mitigation strategies. For enterprises engaged in long-term return investment, population prediction is equally important. Similarly, individuals may be deeply worried about the future population: will there be enough workers paying taxes to support the pensions and medical benefits of retirees? Will population change enhance global and national security and stability, or will it make society more unstable?

Since the 1950' s, the main provider of world population forecasts has been the Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat, which now makes forecasts every five years. Since 1950, great changes have taken place in the forecasting method of UNPD. In 20 10, UNPD used a new statistical method to predict the fertility rate, and in 20 12, it used a new statistical method to predict the mortality rate. The methods of these important components are now based on statistical models suitable for past data. The latest prediction of UNPD only takes time as the decisive factor to determine the future trajectory of fertility and mortality.

It seems that the global population forecast mainly depends on two key issues: the rate of fertility decline in sub-Saharan Africa, and what will happen when the fertility falls to countries with a total fertility rate below 2. 1. The Wittgenstein Center's reference population scenario assumes that by 2200, low-fertility countries will slowly converge to TFR of 1.75. UNPD applies a model to some selected low-fertility countries, where the fertility rate has reached replacement level. This leads to a model that predicts that the fertility rate tends to 1.75.

The post-transition fertility rate refers to the fertility rate of countries and regions that have experienced what demographers call population transition. From high mortality and high fertility to low mortality and low fertility. In a society where the fertility rate is below replacement level, the challenge of modeling TFR is caused by the low level TFR fluctuation. However, this variable model is largely due to the fact that TFR is a measurement of a hypothetical cohort of women aged 15, who have accepted the fertility rate observed at a specific age today and have no mortality.

In this study, the limitations of these previous prediction work have been solved. In this study, a statistical model was established to understand the relationship between the complete cohort fertility rate at the age of 50 and the fertility rate at a specific age, education level and contraceptive demand, and the proportion of women of childbearing age who used modern contraceptive methods to meet contraceptive needs. Finally, an uncertain statistical model is developed. Until 2 100, the net mobility is uncertain. Because each model has independent driving factors, this study explored alternatives related to the educational level and the changing speed of contraceptive demand. This study tracks the potential economic and geopolitical consequences of demographic changes in this century.

It is found that the global population is expected to reach the peak of 9.73 billion in 2064 and drop to 8.79 billion in 2 100. Asia and Central and Eastern Europe will become the regions with the fastest population decline, and the population of 23 countries and regions such as China, Japanese, Korean and Italian will be reduced by half.

2 100 the top five national reference forecasts are India, Nigeria, China, the United States and Pakistan. The results also show that by 2 100, the age structure in many parts of the world is changing, with 2.37 billion individuals over 65 years old and17 billion individuals under 20 years old. It is predicted that by 2035, China will become the largest economy.

In a word, the research results show that the continuous trend of women's education level and contraceptive methods will accelerate the decline of fertility rate and slow down the population growth. If the TFR exchange rate remains below 2. 1, many countries, including Japan, India and South Korea, will face economic, social, environmental and geopolitical consequences. In the next few years, while maintaining and enhancing women's reproductive health, it will be very important to choose policies that adapt to the sustained low fertility rate.

Finally, write a summary

The global population is likely to peak at the end of this century. In view of the fact that the overall trend of TFR predicted by this study will be lower than 1.5, once the global population begins to decline, I am afraid it will continue relentlessly. With the decline of the world's total population, some countries will maintain their population through free immigration policies and social policies, which are more supportive of women's work and achieve the required family size. These countries may have a larger overall GDP than other countries, and have various economic, social and geopolitical benefits brought by a stable working-age population. The analysis of this study shows that the future of population structure is not always static for any country or region. The policies pursued by countries today can change the trajectory of fertility, death and migration.

Original source:

SteinEmilVollset,EmilyGoren,Chun-WeiYuan,etal。 Fertility rate, mortality rate, migration and population in 95 countries and regions from 20 17 to 2 100: a forecast analysis of global disease research. Lancet vol.3 96no.10258p1285 _1306 Release date: July 2020 14.