Category Archives: population forecasts

Global Population in 2100

Probabilistic and Bayesian methods suggest global population will reach about 11 billion by 2100. Stabilization, zero population growth, or population declines are not likely to occur in this century.

These projections come from an article in Foresight, which styles itself the International Journal of Applied Forecasting.

Here’s an exhibit from the article (“The United Nations Probabilistic Population Projections: An Introduction to Demographic Forecasting with Uncertainty”). If you can read through the haze in the reproduction, I found some interesting stuff (click to enlarge). Africa, for example, significantly approaches Asia in population – both with more than 4 billion persons. China is projected to still have more people than India, and the population of Nigeria will be just short of one billion.


The projections are constructed with a cohort component projection method, which projects populations by sex and and five-year age groups based on possible future trajectories of fertility, mortality, and migration.

Traditionally, the UN produced deterministic population projections and point forecasts, supplemented with ranges based on scenarios.

In 2014, however, the United Nations issued its first probabilistic population projections that attempt to quantify the uncertainty of the forecasts.

In the probabilistic method, uncertainty is captured by building a large sample of future trajectories for population size and other demographic metrics. Median outcomes then are used for point forecasts.

A key aspect the methodology is predicting fertility rates by county.

There are three phases to fertility, high fertility Phase I, a phrase involving a steep decline, down to the Phase III – the post-fertility transition.


Most developed countries are in phase III. All countries have completed Phase I.

The article explains, more clearly than I have found heretofore, how probabilistic projections and Bayesian methods can be combined in population forecasting. Really one of the best, short treatments of the topic I have found.

Links – February 2015

I buy into the “hedgehog/fox” story, when it comes to forecasting. So you have to be dedicated to the numbers, but still cast a wide net. Here are some fun stories, relevant facts, positive developments, and concerns – first Links post for 2015.

Cool Facts and Projections

How the world’s population has changed – we all need to keep track of this, 9.6 billion souls by 2050, Nigeria’s population outstrips US.


What does the world eat for breakfast?

Follow a Real New York Taxi’s Daily Slog 30 Days, 30 random cabbie journeys based on actual location data

Information Technology

Could Microsoft’s HoloLens Be The Real Deal?


I’ll Be Back: The Return of Artificial Intelligence



Why tomorrow’s technology needs a regulatory revolution Fascinating article. References genome sequencing and frontier biotech, such as,

Jennifer Doudna, for instance, is at the forefront of one of the most exciting biomedical advances in living memory: engineering the genomes not of plants, but of people. Her cheap and easy Crispr technology holds out the promise that anybody with a gene defect could get that problem fixed, on an individual, bespoke basis. No more one-size-fits all disease cures: everything can now be personalized. The dystopian potential here, of course, is obvious: while Doudna’s name isn’t Frankenstein, you can be sure that if and when her science gains widespread adoption, the parallels will be hammered home ad nauseam.

Doudna is particularly interesting because she doesn’t dismiss fearmongers as anti-science trolls. While she has a certain amount of control over what her own labs do, her scientific breakthrough is in the public domain, now, and already more than 700 papers have been published in the past two years on various aspects of genome engineering. In one high-profile example, a team of researchers found a way of using Doudna’s breakthrough to efficiently and predictably cause lung cancer in mice.

There is more on Doudna’ Innovative Genomics Initiative here, but the initially linked article on the need for regulatory breakthrough goes on to make some interesting observations about Uber and Airbnb, both of which have thrived by ignoring regulations in various cities, or even flagrantly breaking the law.


Is China Preparing for Currency War? Provocative header for Bloomberg piece with some real nuggets, such as,

Any significant drop in the yuan would prompt Japan to unleash another quantitative-easing blitz. The same goes for South Korea, whose exports are already hurting. Singapore might feel compelled to expand upon last week’s move to weaken its dollar. Before long, officials in Bangkok, Hanoi, Jakarta, Manila, Taipei and even Latin America might act to protect their economies’ competitiveness…

There’s obvious danger in so many economies engaging in this race to the bottom. It will create unprecedented levels of volatility in markets and set in motion flows of hot money that overwhelm developing economies, inflating asset bubbles and pushing down bond rates irrationally low. Consider that Germany’s 10-year debt yields briefly fell below Japan’s (they’re both now in the 0.35 percent to 0.36 percent range). In a world in which the Bank of Japan, the European Central Bank and the Federal Reserve are running competing QE programs, the task of pricing risk can get mighty fuzzy.

Early Look: Deflation Clouds Loom Over China’s Economy

The [Chinese] consumer-price index, a main gauge of inflation, likely rose only 0.9% from a year earlier, according to a median forecast of 13 economists surveyed by the Wall Street Journal

China’s Air Pollution: The Tipping Point


Energy and Renewables

Good News About How America Uses Energy A lot more solar and renewables, increasing energy efficiency – all probably contributors to the Saudi move to push oil prices back to historic lows, wean consumers from green energy and conservation.

Nuclear will die. Solar will live Companion piece to the above. Noah Smith curates Noahpinion, one of the best and quirkiest economics blogs out there. Here’s Smith on the reason nuclear is toast (in his opinion) –

There are three basic reasons conventional nuclear is dead: cost, safety risk, and obsolescence risk. These factors all interact.            

First, cost. Unlike solar, which can be installed in small or large batches, a nuclear plant requires an absolutely huge investment. A single nuclear plant can cost on the order of $10 billion U.S. That is a big chunk of change to plunk down on one plant. Only very large companies, like General Electric or Hitachi, can afford to make that kind of investment, and it often relies on huge loans from governments or from giant megabanks. Where solar is being installed by nimble, gritty entrepreneurs, nuclear is still forced to follow the gigantic corporatist model of the 1950s.

Second, safety risk. In 1945, the U.S. military used nuclear weapons to destroy Hiroshima and Nagasaki, but a decade later, these were thriving, bustling cities again. Contrast that with Fukushima, site of the 2011 Japanese nuclear meltdown, where whole towns are still abandoned. Or look at Chernobyl, almost three decades after its meltdown. It will be many decades before anyone lives in those places again. Nuclear accidents are very rare, but they are also very catastrophic – if one happens, you lose an entire geographical region to human habitation.

Finally, there is the risk of obsolescence. Uranium fission is a mature technology – its costs are not going to change much in the future. Alternatives, like solar, are young technologies – the continued staggering drops in the cost of solar prove it. So if you plunk down $10 billion to build a nuclear plant, thinking that solar is too expensive to compete, the situation can easily reverse in a couple of years, before you’ve recouped your massive fixed costs.

Owners of the wind Greenpeace blog post on Denmark’s extraordinary and successful embrace of wind power.

What’s driving the price of oil down? Econbrowser is always a good read on energy topics, and this post is no exception. Demand factors tend to be downplayed in favor of stories about Saudi production quotas.

Demographic Change Videos – Aging and Declining Population

Hi gang. It’s Video Friday again, and I have several videos on aging and the implications of population decline, which may occur in Germany, Japan, and elsewhere.

Perspective on Germany

 What will Japan look like in 20 years? – Noriko Tsuya

 Ukraine Population Decline

 Russia Population Decline


Population Forecasts, 2020 and 2030

The United Nations population division produces widely-cited forecasts with country detail on a number of key metrics, such as age structure and median age.

The latest update (2012 revision) estimates 2010 base population at 6.9 billion persons, projecting global population at 7.7 billion and 8.4 billion in 2020 and 2030, respectively, in a medium fertility scenario.

The low fertility scenario projects 7.5 billion persons for 2020 and approximately 8.0 billion for 2030.

So, bottom line, global population is unlikely to peak during this forecast period to 2030, although it is likely to decline, under all fertility scenarios, for key players in the global economy – such as Japan and Germany.

Population decline is even possible, according to the 2012 revision, in a low fertility scenario for China, although not with higher birth rates, as indicated in the following chart.


Some rudimentary data analytics shows the importance of the estimate of median age in a country for its projected population growth in the 2012 revision.

For example, here is a scatter diagram of the median age within a country (horizontal or x-axis) and the percentage increase or decrease 2010-2030 in the medium fertility scenario of the UN projections. Thus, just to clarify, a 60 percent “percentage growth” on the vertical axis means 2030 population is 60 percent larger than the estimated base year 2010 population.


Note that a polynomial regression fits this scatter of points with a relatively high R2. This indicates that the median age is negatively related to the projected population change for a country in this period with drop-offs in the earliest and oldest median ages in the population of countries.

Thus, in the first chart, Chinese growth includes the possibility of a decline over this period, and India’s does not. This is related to the fact that the median age of China in 2010 is estimated at 34.6 years, while the median age in 2010 in India is estimated at 25.5 years of age.

China and India, of course, are the world’s two most populous countries.

Here are some other interesting charts from the UN projections.

Russia, Japan, and Germany


The comparison for these countries is between the high fertility and low fertility scenarios. The middle fertility scenario lies pretty squarely between these curves for each nation.

Indonesia, Brazil, and Nigeria


Nigeria has the highest population growth rates for any larger country for this period, again because its 2010 median age is listed as around 18 years of age.

Accuracy of UN Population Forecasts

The accuracy of UN population forecasts has improved over the past several decades, with improved estimates of base population (See for example. Data quality and accuracy of UN Population Projections, 1950-1995). Needless to say forecasts for industrially developed counties usually have been better than for nations in the developing world.

Changes in migration account for significant errors in national population forecasts, as when a large contingent, some legal, some side-stepping legal immigration channels, came from Mexico and other Spanish-speaking areas “South of the Border,” changing birth patterns in the US from the early 1990’s to the years after 2000. In fact, during the early 1990’s, Census was predicting peak population for the US might occur as early as 2025. This idea went by the wayside, however, as younger, more fertile Hispanic families took their place in the country.

Current UN forecasts indicate US population should increase in the medium fertility scenario from 312 million to 338 million and 363 million, respectively, by 2020 and 2030.