Economic Impact of Fertility Rates Below Replacement

Posted on February 18, 2014 by climatechangefork

The golden rule of free enterprise economy seems to be that everything that contributes to economic growth is good, while anything that detracts from the same is bad. The rationale behind this is that as the population grows, the economy has to accommodate the growing population in order to maintain or improve the standard of living. I have argued against this reasoning before, especially as it relates to long-term planetary sustainability (see Economic Growth and Problems With My Sourdough Bread blog Feb. 11, 2013 and the series of blogs surrounding it). The previous argument was based on the idea that continuous economic growth inevitably comes at the expense of the deterioration of the physical environment, with climate change as one of the major impacts. The argument there was that for the long term (again, my standard is 1000 years) with stabilized population, the only justified economic growth is for homogenizing the economic structure to ensure that everybody can afford a decent living.

This perspective agrees with the recent quote from Dilama Rousseff, the President of Brazil, in an email correspondence with Nicholas Lemann of the New Yorker: “The main aim of economic development must always be the improvement of living conditions,” she told him. “You cannot separate the two concepts.”

The conclusion I reached in my most recent discussion was that in order to be successful going forward, we must learn to shift the paradigm of the holy grail of economics from growth to stability. Here I would like to shift the focus to economic consequences of decrease in population that results from fertility rates consistently below replacement. Since, as I have mentioned in a number of recent blogs, more than half of the world’s developing countries and the majority of its developed countries currently live with below replacement fertility rates, the economic consequences need not be deduced from long term extrapolations. They should start to be visible now – indeed, we are already starting to see some of the impacts.

The issue recently gained some attention due to some comments made by Larry Summers in a short speech that he gave at a research IMF conference to honor Stanley Fischer (President Obama’s recent nomination to serve as Vice Chairman of the US Federal Reserve Bank). A key paragraph is given below:

It is a central pillar of both classical models and Keynesian models that stabilization policy is all about fluctuations – fluctuations around a given mean – and that the achievable goal and therefore the proper objective of macroeconomic policy is to have less volatility.  I wonder if a set of older and much more radical ideas that I have to say were pretty firmly rejected in 14.462, Stan, a set of older ideas that went under the phrase secular stagnation, are not profoundly important in understanding Japan’s experience in the 1990s, and may not be without relevance to America’s experience today.

The term “secular stagnation” is reintroduced here from its original use in the mid 1950s. The stagnation itself and the responsible driving forces are still controversial, but the demographic shift is a very likely contributor.

One important reason for the recent discussions rests on an apparent anomaly in the statistics of the recovery from the last recession. The unemployment rate is shrinking quickly, but this actually corresponds less to the addition of new jobs, and more to the increasing number of people leaving the workforce. If people are leaving the workforce because they don’t believe that they will be able to find work, it indicates an unhealthy economy that needs to be fixed. If, however people leave the workforce because they choose or are forced to retire because they have reached the retirement age, it’s a different issue. The baby boomers (born after the 2nd World War) are now starting to reach the retirement age and the economy needs to accommodate them. This is a demographic transition that is coming about because of changes that took place in the demographic pyramid caused by events that took place more than two generations ago.

The relative weight of the demographic changes compared to cyclical job availability, is a controversial issue, loaded with political arguments across the political spectrum. The dynamics (and the politics) hold similarities to the debate about climate change: i.e. whether the causes are anthropogenic (caused by humans) or “natural.” It is much more likely the two components both play important roles; attempts to differentiate between the two show up periodically across this blog.

A related discussion (and political debate) has now opened around the new healthcare law in the US (Obamacare). It has recently been projected that the law will lower the labor force by more than two million toward the end of the decade (people will not need to go to work simply to guarantee health insurance). Opponents of the law immediately started trying to brand the law as a job killing legislation. Supporters, meanwhile, have maintained that the law allows people the freedom to choose whether and how much they want to work.

A recent piece in the Economist (January 4th – 10th 2014) describes an interesting dynamic with a new building site in Battersea, London. The site is being built as a retirement village. Its 112 flats are available only to buyers over 65. It will include restaurants, gym, a swimming pool and a care home. It describes the background:

Britain’s population is ageing fast. The number of people older than 85 is expected to double by 2030. Yet Britain’s elderly are badly served by the housing market. Although 71% of people over the age of 65 own their homes outright, lots still live in large family houses, paying dearly to heat empty bedrooms and struggling with too-large gardens, broken boilers and council tax bills.

It’s bad for the old people and contributes to Britain’s housing shortage:

According to data from the English Housing Survey, roughly 49% of owner-occupied homes have at least two more bedrooms than the government deems necessary. Among those who rent—either privately or from the state—the figure is just 13%. Neal Hudson, an analyst at Savills, a big estate agent, estimates that there are almost 1.2m inefficiently used homes in London and the south-east alone.

Demographic changes have major impacts on everything that we do. We need to learn how to accommodate those changes. If our population is shrinking, with older generations outnumbering those that must care for them, it is imperative that we learn how to manage and redistribute essential goods and services. This goes double for when we take into account climate change and the resources that will be available in the times to come.

Posted in Climate Change | Tagged , , , , , , , , , , , , , , , , , , , , | 1 Comment

Attempts to Reverse Negative Impacts of Fertility Rates That Have Crossed Below Replacement

Posted on February 11, 2014 by climatechangefork

As Jim mentioned in his guest blog (January 14, 2014):

Half of the countries worldwide now have sub-replacement fertility. The downside to this trend is shrinking labor forces – a factor which has led some governments to try to reverse the course and increase fertility. Romania banned abortion, and fertility briefly increased – until illegal sources of abortion appeared to meet demand.  Other countries like France and Germany in the 1930s provided families with generous incentives ranging from free childcare to cash payments for additional children, but these actions did not produce substantially higher fertility. The relaxation of China’s one-child policy may result in higher fertility, but the effects will not be known for several years.

There have been several attempts to reverse these negative impacts, specifically with regards to the shrinking labor forces.

Abortion: As the figure below shows, there is no correlation between the legal grounds on which abortions are permitted globally and the demographic concern about crossing the replacement fertility rates. While abortions on request are permitted in most developed countries, this is not the case in most developing countries. Public debates and demonstrations about abortion are almost always front page news. These often correlate with individual religious beliefs, arguments about the sanctity of life, and women’s safety and autonomy over their own bodies. Spain is going through such a debate right now, and fertility rates and population growth play no part in the argument.

Abortion Legal Grounds by Level of Development - UN

Money: About eight years ago I visited Russia, one of the countries with the most serious fertility declines below replacement. Vladimir Putin was a new president at the time and he had promised Russian women $5,000 for every new baby that they gave birth to. I asked my young Russian guides if they planned to go along with this and “produce” some babies – apparently it was the patriotic thing to do. Without exception, they laughed and said that if Putin were to promise them an apartment, then they would think about it.

Incentives to attract and keep women in the work force: As we saw in the previous blog, this is clearly working and is a major factor to account for the lack of clear correlation between the decline in fertility rates and changes in the size of the work force. The relative number of women does not increase beyond their demographic ratio. The recent effort on this score can be found in South Korea:

South Korea will adopt a name-and-shame policy, publicly identifying companies with low female employment levels, as President Park Geun Hye targets 1.65 million extra jobs for women.

Policy steps will include increased subsidies for parents on childcare leave and preferential treatment for “family-friendly” companies seeking government contracts, six ministries said in a joint statement today.

With an aging population threatening to undermine South Korea’s economic growth, Park, the nation’s first woman president, has pledged to lift the female employment rate to 61.9 percent, from 53.5 percent, before her term ends in 2018. Cho Yoon Sun, the minister for gender equality, is working with the family-run industrial groups called chaebol to try to end male-dominated employment practices.

Incentives to keep older people in the workforce: I am nine years past the upper limit of the age of the “working population.” I keep working because I have the choice. I like my work, I am in reasonably good health, and by any available standard I do as a good job now as I did when I was younger. For most positions in the US, an employer could not fire me for being old, without facing a lawsuit for age discrimination. Many older workers don’t have this choice. They would love to retire, but they cannot do so because of economic concerns. The pension obligations of many public employers and some private employers are deteriorating to such a degree that they are incapable of paying those already owed, much less those who have yet to retire. Perhaps in part due to that, the age definition of “working population” is drifting upward. This drift, similar to the limits on female participation in the work force, is self-limiting by biology. Life expectancies are not increasing at the same rate as our ability to be healthier and stay longer in the workforce.

In the long term (again, I will use 1000 years as my yardstick) these trend will not stabilize the negative impacts of a steadily declining population.

There is one “remedy” that might do the trick by changing the equation for stabilization: replacing humans with robots, where applicable.

Robotics: Let’s examine two other paragraphs from Jim’s guest blog:

Barring massive migration to extra-terrestrial planets, global population growth will continue to be determined by the difference between births and deaths.  If there are more births than deaths, the population will grow. If there are more deaths than births, the population will shrink. It’s as simple as that.

Let’s look at deaths first: Death rates have been declining for more than a century, even taking into account the overall aging of the population and the ongoing HIV epidemic. Purposefully containing population growth by increasing deaths would require us to resort to the apocalyptic factors of war, pestilence and starvation; strategies which few would advocate.

These two paragraphs are indeed as true as they seem. The times in which we purposefully “adjusted” global populations on a massive scale through deaths using wars and epidemics as tools, are hopefully long past, not to return. I am obviously excluding possibilities of collective insanities such nuclear Armageddon. But technology and innovation offer other options that work to achieve the same objective. Our moral code objects to the use of death to control population, but it doesn’t object to the destruction of machines to control the workforce.

As I have mentioned repeatedly, at the time that I was born the world population was around 2 billion, a number which has increased to 7 billion during my lifetime (as of October 2011). I have also mentioned that if we allow the population to shrink back to around two billion, the population pyramids (January 21, 2014 blog) will drastically change, reducing the number of working age adults that are available to support the rest of us. Can we – instead of stabilizing the population – stabilize the “working hands,” while letting the overall population shrink? It seems that not only is such a solution feasible, but we are already (inadvertently) making great “progress” with such a scenario.

The figure below shows the estimated worldwide shipment in industrial robots (in thousands). In 2011 sales of industrial robots reached 166,000 units, an increase of 38% compared to 2010. The shipments are estimated to exceed 200,000 by 2015. Presently, the largest purchaser is the automotive industry.

http://www.21stcentech.com/wp-content/uploads/2012/09/Growth-of-Industrial-Robots.jpg

This number doesn’t include domestic robots or those that are being used in the service industry, but it reflects a clear trend toward their increased participation in the workforce.

The increasing participation of robots in the workforce, along with their growing ability to replace humans in many tasks, has often been labeled as the Second Industrial Revolution. Once or twice in some academic meetings, I have also heard the term “Third Industrial Revolution,” which limits the second one to the introduction of computerized gadgets. Whatever your preference, once we use the trend in the same context as the original Industrial Revolution, we have to include Luddites in the discussion. “The Luddites,” according to Wikipedia, “were 19th-century English textile artisans who protested against newly developed labour-saving machinery from 1811 to 1817.” In each case, the advents of these technological breakthroughs have been met by some with strong disapproval. Since this happened following the use of machines to replace workers – both in the 21st century and the 19th century predecessor, it seems fair to use the same term to describe the like-minded groups. In any case, our economy will require a new paradigm in order to assuage any current or future Luddites. It is key to emphasize that what we need robots for now is not so much to replace human workers as supplement them. We have a large job ahead of us: using a shrinking percentage of working age people to care for the growing percentage of older generations, and some of it might be easier if we can delegate certain tasks to machines.

Posted in Climate Change | Tagged , , , , , , , , , , , , , , , , , , , , | 1 Comment

Stabilization

Posted on February 4, 2014 by climatechangefork

My latest series of blogs has focused on long term population growth; one of the main aspects has been an attempt to understand the United Nations’ medium projection and the reasoning behind its very large margin of error (December 24, 2013 blog).

Here are the two key paragraphs that I quoted from the original report:

Future population size is sensitive to small but sustained deviations of fertility from replacement level. Thus, the low scenario results in a declining population that reaches 3.2 billion in 2150 and the high scenario leads to a growing population that rises to 24.8 billion by 2150.

The long-range projections prepared by the United Nations Population Division include several scenarios for population growth for the world and its major areas over the period 1995-2150.The medium scenario assumes that fertility in all major areas stabilizes at replacement level around 2050; the low scenario assumes that fertility is half a child lower than in the medium scenario; and the high scenario assumes that fertility is half a child higher than in the medium scenario. The constant scenario maintains fertility constant during 1995-2150 at the level estimated for 1990 – 1995, and the instant-replacement scenario makes fertility drop instantly to replacement level in 1995 and remain at that level thereafter.

Mathematically, based on achieving long-term replacement fertility rates, these projections are very easy to compute. The main question raised was how to get there. Jim Foreit in his January 14, 2014 guest blog concluded that:

A sub-replacement fertility world seems inevitable, with fewer productive adults supporting larger numbers of the elderly. What this will mean for human welfare will depend on both the future productivity of working adults and living the expected living standards for their parents.

I see an obvious conflict in the two statements and an unanswered question of how we can achieve a stable global population in the long term (which I have somewhat arbitrarily defined as 1000 years). In my last blog I explored the populations in countries that have already crossed the fertility replacement rate. For some of the reasons that I mentioned there, I couldn’t get a satisfactory answer. It seems that we need more time to observe the trends. Since it seems I cannot get answers on the ground, I will try instead to use simple mathematical models and simple examples. That’s what physicists usually do. I will start first with the math:

We need to explore two modes of growth: exponential growth and logistic growth. A good pictorial presentation of these two modes of growth, as related to population growth, is given in the graph below:

exponential and logistic population growthThe term dN/dt on the left-hand side of both curves represents the rate of population growth over time; d  represents change, N represents population and t represents the time. The horizontal axis represents the time in units of passing generations. The exponential growth grows unabated because the growing number of kids each have their own kids. This is represented by the fact that the growth rate is proportional to the population.  The logistic curve reaches stabilization at the arbitrary population of K = 1500. The equation is identical to the exponential growth with an additional term on the right that is responsible for the saturation. This term represents negative feedback: “when the result of a process influences the operation of the process itself in such a way as to reduce changes” and the system becomes self regulating. The simplest example – and probably the most familiar – that we often use for regulating a physical system, is the thermostat. It regulates the temperature of an enclosure by measuring the actual temperature and switching on or off the heating or cooling system or regulating the flow of the heating element. I was looking for a “populationstat,” with the planet as my enclosure. The stabilization doesn’t have to be as smooth as the one showed in the logistic curve above. I can live with bumps. I can also live with reasonable limits on my ability to stabilize the system but I cannot (or we cannot) live with unbounded systems. We have found out that we know how to switch population growth off (“development is the best contraceptive” :() but I have no idea how to switch it on again. Jim Foreit says that we will have to learn how to live with this. In the next few blogs I will try to explore some alternative options.

Posted in Climate Change | Tagged , , , , , , , , , , , , , , | 2 Comments

Crossing the Fertility Replacement Rate – the Last 20 Years

Posted on January 28, 2014 by climatechangefork

As I have shown in previous blogs, long-term (I use 1000 years as the “magic” number – see the December 17, 2013 blog) exponential growth (or decline) cannot continue unabated without serious consequences. Lately, I have emphasized this concept mainly with regards to population growth, but these arguments apply equally to economic growth. As long as we are stuck here, the planet will eventually impose its own limits. Over the last 60 years we have learned how to collectively reduce fertility rates, thereby controlling population growth rates. While fertility rates and growth rates are now declining almost everywhere, regardless of a country’s wealth, we have not seen them stabilize around replacement rates.

In his fabulous guest blog (January 14, 2014) Jim Foreit, wrote that “half of the countries worldwide now have sub-replacement fertility” and that “the downside to this trend is shrinking labor forces.” After mentioning some sporadic efforts to reverse this trend, he concluded his blog with the suggestion that, “A sub-replacement fertility world seems inevitable, with fewer productive adults supporting larger numbers of elderly.”

In this blog I’d like to examine some specific cases, using data from the World-Bank database from the last 20 years. Based on the population pyramids I showed in my last blog, one should expect a time delay between the reduction in fertility and the expected reduction in population growth, which determines the distribution of the workforce

The tables below show some of the countries whose fertility rates have dropped the furthest below replacement rate (2011). We see that they are not restricted to rich countries. I have selected 5 countries for a more detailed longitudinal (study of changes over time) analysis.

Total Fertility Rates (TFR) Below Replacement (2011)

Country TFR Country TFR
Armenia 1.7 Hungary 1.2
Albania 1.7 Italy 1.4
Austria 1.4 Japan 1.4
Belarus 1.5 South Korea 1.2
Bosnia-Herzegovina 1.3 Latvia 1.3
Canada 1.6 Lebanon 1.5
China 1.7 Macedonia 1.4
Croatia 1.5 Moldova 1.5
Cuba 1.5 Romania 1.3
Czech Republic 1.4 Serbia 1.4
Estonia 1.5 Slovakia 1.5
Germany 1.4 Spain 1.4
Greece 1.4 Thailand 1.4

World TFR (2011) – 2.5

 

China

  1995 2000 2005 2010
TFR 1.7 1.5 1.6 1.7
Population(Millions) 1200 1260 1300 1340
Population Growth (%) 1.1 0.8 0.6 0.5
GDP/Capita ($2005) 778 1,122 1,731 2,869
GDP/Capita Growth (%) 9.7 7.5 10.6 9.9
Age Dependence Ratio* 53 48 39 36
Share of Women Employed** 39 ——- ——- ——-
Total Labor Force (% population) 56.4 57.5 58.4 57.8

 

Japan

  1995 2000 2005 2010
TFR 1.4 1.4 1.3 1.4
Population(Millions) 125 127 128 127
Population Growth (%) 0.4 0.2 0.0 -0.1
GDP/Capita ($2005) 32,438 33,957 35,781 36,473
GDP/Capita Growth (%) 1.6 2.1 1.3 4.7
Age Dependence Ratio* 44 47 51 57
Share of Women Employed** 39 40 41 43
Total Labor Force (% population 53.5 53.2 52.0 52.3

 

Thailand

  1995 2000 2005 2010
TFR 1.9 1.7 1.5 1.4
Population(Millions) 59 62.3 65.6 67.4
Population Growth (%) 0.8 1.2 0.7 0.2
GDP/Capita($2005) 2,280 2,206 2,690 3,164
GDP/Capita Growth (%) 8.3 3.5 3.9 7.6
Age Dependence Ratio* 49 44 43 39
Share of Women Employed** 41 44 45 45
Total Labor Force (% of population) 53.7 55.2 56.9 57.6

 

Spain

  1995 2000 2005 2010
TFR 1.2 1.2 1.3 1.4
Population(Millions) 39.4 40.2 43.3 46
Population Growth (%) 0.2 0.8 1.6 0.4
GDP/Capita ($2005) 19,997 23,921 26,056 25,596
GDP/Capita Growth (%) 2.5 4.2 1.9 -0.6
Age Dependence Ratio* 47 46 45 47
Share of Women Employed** 36 39 42 47
Total Labor Force (% of population) 42.1 45.0 48.5 50.4

 

Italy

  1995 2000 2005 2010
TFR 1.2 1.3 1.3 1.4
Population(Millions) 56.8 56.9 58.6 60.5
Population Growth (%) 0.0 0.0 0.7 0.2
GDP/Capita ($2005) 26,464 29,872 30,479 29,163
GDP/Capita Growth (%) 2.9 3.6 0.2 1.2
Age Dependence Ratio* 46 48 51 52
Share of Women Employed** 37 40 43 44
Total Labor Force (% of population) 40.1 40.9 42.1 41.5

* Age dependency ratio is the ratio of dependents—(people older than 64 or younger than 15) –to the working-age population–those ages 15-64.

** Share of women employed in non-agricultural sector as % of total non-agricultural sector.

Among these selected countries, in spite of the fact that these countries have crossed the replacement fertility rate for almost a full generation, this has only translated to negative population growth very recently in one country (Spain). The rest are still growing (including zero growth), albeit at a very slow pace. The only consistent trend, not surprisingly, can be seen in China. The situation in China is somewhat unique and I will try to analyze it in more detail in one of the future blogs. The time period that these tables cover includes the recent global-wide recession. The data for labor force availability (% of population) show an actual increase except for Japan, which shows a small decrease. The age dependency ratio (ratio of the non-working population ages to the working population ages) is sharply decreasing in China and Thailand, increasing in Japan and Italy, and staying approximately constant in Spain. The share of women employed is increasing in four of the countries (data were not available for China). All the data show that the impact of crossing the fertility replacement rate has yet to crystallize into a decipherable trend – in spite of the passing of almost a generation.

Obviously, the empirical evidence of the impacts of crossing the replacement fertility rates is not yet available. However, over the relatively long period of time that we are discussing, it should be clear that we cannot let exponential decline go unchecked.

The next blog will focus on some of the science involved in trying to stabilize the system.

Posted in Climate Change | Tagged , , , , , , , , , , , , , , , , | 2 Comments

Crossing the Fertility Replacement Rates – Background

Posted on January 21, 2014 by climatechangefork

One of the fascinating things in trying to do what I do, be that teaching, writing or lecturing, is to try to anticipate long term future trends, given the ever changing present. Sometimes the present gets my full attention, and sometimes I choose to ignore it in favor of developments that might become important factors in our future. The last few weeks are no exception. We were freezing over here with the Polar Vortex; meanwhile, the best tennis players in the world have been competing in 2014’s first big tennis tournament – the Australian Open. The temperature in Melbourne reached 1110F (~ 440C). The players, the ball boys/girls and the spectators were very unhappy, but the tournament management was, for a time, dismissing the complaints. The Chief Medical Officer of the tournament was quoted as saying, “We’ve evolved in the high plains of Africa chasing antelope for eight hours under these conditions.”

Both ends of the temperature scale were blamed on climate change, with the deep freeze of the Polar Vortex to be used as the “absolute proof” that we are not experiencing global warming but instead we are going through global cooling. This stream of thought seems to come up no matter how many times scientists assert that a single weather event on either scale can never be used as a proof for or against anthropogenic (human influenced) climate change. Since I already wrote about the extreme temperature and the abundance of fires in Australia (January 14, 2013 blog) I decided that this time, I would skip the discussion of the present, and instead continue to focus on the future and population.

Jim Foreit’s wonderful guest blog last week (January 14, 2014) summarized the great success over the last 60 years in reducing both fertility rates and the growth in global population, but it ended with a less cheerful note about trying to reach a stable population over the long term. His blog ends with the following two paragraphs:

Half of the countries worldwide now have sub-replacement fertility. The downside to this trend is shrinking labor forces – a factor which has led some governments to try to reverse the course and increase fertility. Romania banned abortion, and fertility briefly increased – until illegal sources of abortion appeared to meet demand.  Other countries like France and Germany in the 1930s provided families with generous incentives ranging from free childcare to cash payments for additional children, but these actions did not produce substantially higher fertility. The relaxation of China’s one-child policy may result in higher fertility, but the effects will not be known for several years.

A sub-replacement fertility world seems inevitable, with fewer productive adults supporting larger numbers of the elderly. What this will mean for human welfare will depend on both the future productivity of working adults and living the expected living standards for their parents.

I have decided to focus the next few blogs on the consequences and possible remedies to a relatively recent phenomenon: the decline of the fertility rate to below replacement rate (we call this “crossing” the fertility replacement rates), which leads to shrinking future global populations. Since, as I have mentioned before, the world population was around 2 billion when I was born, and the world was more or less functioning (remember, this was 3 months before the start of World War II), the question remaining is what issues would be associated with a shrinking world population. The UN scenario of a global population stabilizing around fertility replacement rates is not a bad scenario. The question is how we get there. The past 60 years have taught us how to move toward those numbers from high fertility rates – mainly though economic development and the use of modern contraceptives. As Jim clearly points out, we have no idea how to stabilize once global fertility has crossed below these rates.

It is not too difficult to visualize what will happen if population continues to grow. My estimation for such a scenario was that in few hundred years, with present constant population growth the world would reach the present density of Mumbai, India. This would include populating the presently completely unpopulated areas such as Antarctica and the Sahara desert.

Global Decline in Fertility 1950-2010 This graph, which I also used in a previous post (January 2, 2014), was originally presented in the special Science Magazine issue that was dedicated to the global population crossing the mark of 7 billion people in October 2011. It shows a sharp decline of the global fertility rate. The fertility rate in the developing countries declined from around 6 children per woman to around 3 in 2010, while that in the developed countries changed from under 3 to below 2. The fertility rate didn’t stabilize anywhere near replacement. In some countries it went as low as 1.3 – 1.4, well below replacement. As a result, the population of these countries is shrinking quickly.

As Jim mentioned, the fertility rates in about half of the world’s countries are below replacement rates. Some of these countries are well below these rates, and not all of them are rich countries. In a future blog I will show in some detail the demographic changes that took place in some of the most populous countries that crossed the barrier of replacement rates.

The key changes can be examined in terms of the two graphs below:

Age Distribution Pyramids 2010Ratio of Working Age Adults to Older 2010 2050

These two graphs were taken from the same 2011 Science Magazine that I mentioned before. They help give insight into Jim’s last two sentences. The first one shows what are referred to as population pyramids of developed and developing countries. These pyramids directly describe the relative numbers of the various age groups in 5-year intervals, illustrating the changes in the distribution of age groups with changing fertility rates. The second graph demonstrates one of the most direct consequences of the changes shown in the pyramids; the customary definition of working age populations includes those from 15 – 64 years old. In 2010, the highest ratio of working age adults to older adults was 17, while in the more developed countries it was down to 4, with a projected decline to 2 by mid century.

When a country or a world crosses the fertility replacement rate, it means that fewer babies are born, and with the death of the parents, the population should decrease (this is true for the global accounting but doesn’t include immigration and emigration in national accounting). As a direct result, fewer babies grow up to be part of the working age population. If at the same time, the number of older people that leave the work force grows, there are fewer working-age adults to support them. However, the process of growing up into the work force takes time: approximately one generation. In addition, other demographic transitions took effect during the last 60 years. Of these, the two most important transitions, as they closely correlate with economic development, are the much broader participation of women and the increased participation of those aged 65+ in the work force. Both transitions blur the declining ratio of working adults per non-working older adults.

In the next blog I will describe the specific cases of a few countries that have significantly crossed the fertility replacement rate. In the following blogs I will try to go into some details to fill the gaps in the UN predictions and try to outline what we need to do to get there.

Posted in Climate Change | Tagged , , , , , , , , , , , , , , , , , , , , | Leave a comment

Jim Foreit Guest Blog: How Does Population Decline?

Posted on January 14, 2014 by climatechangefork

In the last few posts, I have discussed the global population (both current and future), as it relates to both economic input and contribution to climate change. I promised to ask a friend who specializes in demographics for his comments. I am very thankful that – fortunately for all of us – he said yes. What follows is his explanation of the various factors that contribute to the rise or fall of population.

How Does Population Decline?
By Jim Foreit

The Climate Change Fork blogs of December 24, 2013 and January 2, 2014 asked why the prospects for world population growth varied so widely – from today’s population of some 7 billion people to the possibility of anywhere between 3.2 and 24.8 billion in 2150. Making predictions more than 50 years out is risky.  In this blog, I will discuss the determinants of that growth and limit the discussion to the year 2050, when world population is predicted to grow to roughly 8 – 10 billion.[i]

Barring massive migration to extra-terrestrial planets, global population growth will continue to be determined by the difference between births and deaths.  If there are more births than deaths, the population will grow. If there are more deaths than births, the population will shrink. It’s as simple as that.

Let’s look at deaths first: Death rates have been declining for more than a century, even taking into account the overall aging of the population and the ongoing HIV epidemic. Purposefully containing population growth by increasing deaths would require us to resort to the apocalyptic factors of war, pestilence and starvation; strategies which few would advocate.

Therefore, world population growth can be slowed or reversed only by reducing births, or as demographers refer to it, fertility. Since only women are capable of giving birth, we can focus our calculations on that one gender. It is inevitable that some children will die before adulthood, so to compensate for these losses, every woman must have an average of 2.1 children in her lifetime (this is called the total fertility rate or TFR), in order to replace herself and her partner. At these replacement fertility rates, population levels eventually stabilize. This will not happen overnight because there are many more potential mothers (girls under the age of 15) today than there are adult women, and if they all have 2.1 births, the population will continue to grow for another generation. If TFR drops below 2.1, the population will eventually shrink; this was the motivation behind China’s one child policy. Currently, TFR ranges from about five children in Sub-Saharan Africa to less than two in North America, Europe, China, and Japan. Global TFR was approximately 4.9 in 1950 and approximately 2.6 in 2010.

What drives fertility? At its root, fertility is biology: women may or may not get pregnant, and once pregnant they may or may not take that pregnancy to term. There are three principal factors or behaviors under a woman’s control that determine whether or not she gets pregnant, and one main factor that determines whether pregnancies result in a live birth. These are called proximate determinants of fertility. Socio-economic factors that influence population growth do so by acting on the proximate determinants and are called distal determinants of fertility.

The Proximate Determinants of Fertility [ii]

If she does not die in childbirth or from other causes, the average woman will have 35 years in which she can bear children – from menarche (roughly age 15, although this number has recently been seen to be declining) to menopause (roughly age 49). The earlier she has her first child, and the more rapidly she gets pregnant again, the more children she will have in her lifetime. She can delay her first birth by delaying sexual activity (traditionally by postponing marriage), and/or by using contraception; she can delay subsequent pregnancies by breastfeeding her previous child (exclusive breastfeeding suppresses ovulation by 6 months on average) and/or by using contraception. If an unwanted pregnancy occurs, she can terminate it with an abortion.

At the population level, these are the four proximate determinants of fertility: percentage of women 15-49 married or sexually active, percentage of women using contraception (and the type of contraception used, as some methods are more effective at preventing pregnancy than others), average length of breastfeeding, and the abortion rate. The transition from high to low fertility has occurred by delaying the first birth and replacing “natural” constraints like breastfeeding (which has actually declined) with the more effective constraints of modern contraception and abortion.

Distal Determinants of Fertility

History clearly shows that urbanization, declining infant mortality rates, and increases in women’s education and employment are associated with sustained fertility decline. Why? These distal determinants must be mediated by their impacts on one or more of the proximate determinants – that is, marriage, breastfeeding, contraception and/or abortion. Often they interact synergistically for greater effect.

Let’s begin with female education. In many cultures, school attendance is seen as incompatible with marriage, so keeping girls in school raises the marriageable age and shortens the total time possible for childbearing. In high-fertility settings in sub-Saharan Africa, a one-year increase in age at marriage may be associated with a TFR decline of one birth or more.

However, the single most important factor in fertility change is change in demand for children – that is, how many children a woman or couple wants to have. In economic terms, as the cost of children increases, the demand for children decreases.[iii] Here’s why:

In traditional rural agricultural settings, children begin working at an early age: they contribute to family income and support their parents in old age. Hence, value flows from children to parents, and fertility is high. High levels of infant mortality contribute to parents’ desire for large numbers of children to ensure that at least a few survive into adulthood; as infant mortality declines, fewer children are needed, so the desired number of children declines. This, however, does not immediately translate to a smaller population. In the short term, without increased use of contraception and/or abortion, fertility remains high and population growth rates accelerate. Mortality almost always declines before fertility, so when no contraception is available, it is very difficult to achieve desired family size. In developing countries, ideal family sizes are lower than attained fertility.

With migration to cities, children contribute less to family income. To succeed in an urban environment, families pay more for their children’s food, clothing, education and health care, and income now flows from parents to children. Thus, urbanization leads to lower desired family size, and to the extent that methods and services are available, women can act on their fertility desires and prevent/delay pregnancy through contraception or terminate an unplanned pregnancy through abortion. Urbanization also increases women’s educational and employment opportunities, encouraging them to postpone marriage as we saw above, as well as to use contraception so that they can work outside the home and contribute to family income. In fact, the more women’s income grows, the greater the cost of taking time off to raise children. This often translates into greater use of contraception and abortion and lower fertility. When I lived in Korea in 1978, a piano was seen as the ultimate family status symbol, and it was said that middle class families in Seoul were foregoing having a third child in order to instead buy a piano for the first two!

The table below illustrates the distal determinants between a country in the early stage of development – Nigeria, a country in a middle stage of development – India, and a fully developed country – the United States.  In the US, fertility differences across the factors are extremely low, so only contraceptive prevalence (the percent of women of fertile age using contraceptives, or CPR) TFR, and infant mortality are shown.

Factor Nigeria  2008 India 2005-6 USA 2010
TFR CPR TFR CPR TFR CPR
National level TFR/CPR 5.7 9.7 2.6 48.5 1.9 77
Urban 4.7 16.7 2.1 55.8   –   –
Rural 6.3 6.5 3.0 45   –   –
Highest Wealth Quintile 4.0 22.3 1.8 58   –   –
Lowest Wealth Quintile 7.1 2.5 3.9 34.6   –   –
Women W/No Education 7.3 2.6 3.6 45.7   –   –
Women W/Secondary and above Education 4.2 18.9 2.1 50.3   –   –
National level Infant Mortality 91 57 6

Although TFR is much higher in Nigeria than in India, and CPR is much higher in India than in Nigeria, the same pattern of lower fertility in urban areas, among the better educated and wealthier is evident in both countries.

Manipulating Fertility Decline: Can We Speed Up the Process?

The population-development debate is as old as Malthus (1798). Margaret Sanger organized the first World Population Conference in 1927. The UN took up the baton decades later, holding conferences in 1954, 1965, 1974, 1984 and 1994.[iv] Debate at the conferences centered on the need for family planning. Some argued that development was sufficient (“development is the best contraceptive”) to drive down fertility because populations would adopt fertility control without the need for organized programs. Others argued that development had to be accompanied by strong family planning policies and programs. While academics argued, countries and development donors took action: family planning programs were launched in India in the 1950’s, in East Asia (Korea, Taiwan, Thailand and Indonesia) between 1960 and 1970, in Latin America in the late 1970’s and 1980s, and sub-Saharan Africa in the 1990s.

Do family planning programs work? The answer is it depends. Results are mixed, but by most accounts, Bangladesh’ s family planning program is the world’s success story in this matter, and demonstrates that such programs can be highly effective despite considerable odds.

“During the early 1970s, American officials termed newly-independent Bangladesh a ‘basket case’… [and] demographers contributed to the dismal prognosis by using Bangladesh as an example of a society that was unlikely to initiate a transition from higher to lower fertility in the foreseeable future… Even optimists doubted that Bangladeshis would accept family planning on a large scale.”[v]

In an environment of little or no socio-economic development, but with concerted government support and enormous donor funding that provided information and contraceptive methods down to women’s doorsteps, contraceptive use quintupled in 20 years, from less than 10% of married women in 1970 to over 49% in 1990, and fertility fell by half (from 6.3 TFR to 3.3)[vi]. This success came at a cost– over $800 million per year in today’s dollars, largely from international donors.

Coercion can also result in rapid fertility decline. China initiated its one child policy in 1979, enforced by fines, forced abortion and sterilization.TFR fell from 3 in 1978 to 1.6 in 2012. Since few other countries have the desire (or the ability) to coerce their populations into low fertility, strong family planning programs seem the best option for speeding up fertility decline.

Manipulating Fertility Decline: How Low Can We Go?

Half of the countries worldwide now have sub-replacement fertility.[vii] The downside to this trend is shrinking labor forces – a factor which has led some governments to try to reverse the course and increase fertility. Romania banned abortion, and fertility briefly increased – until illegal sources of abortion appeared to meet demand.  Other countries like France and Germany in the 1930s provided families with generous incentives ranging from free childcare to cash payments for additional children, but these actions did not produce substantially higher fertility. The relaxation of China’s one-child policy may result in higher fertility, but the effects will not be known for several years.

A sub-replacement fertility world seems inevitable, with fewer productive adults supporting larger numbers of the elderly. What this will mean for human welfare will depend on both the future productivity of working adults and living the expected living standards for their parents.

 

James Foreit, Dr. PH has worked in family planning program research and evaluation for over thirty-five years, and lived in developing countries for eighteen years. He is the author of books, manuals and journal articles that relate to family planning, HIV/AIDS, and maternal and child health. Dr. Foreit retired as a Senior Associate of the Population Council, New York in 2012. He currently consults and teaches courses in operations research techniques and scientific writing.

 [i] United Nations, Department of Economics and Social Affairs, Population Division. 2013. World Population Prospects the 2012 Revision, Key Findings and Advanced Tables.

[ii] John Bongaarts and Robert G. Potter, Fertility, Biology, and Behavior, an Analysis of the Proximate Determinants, Academic Press, 1983, is the basic work on the proximate determinants.

[iii] Becker, G. S. and Lewis, H.G. 1973. On the Interaction Between the Quantity and Quality of Children, Journal of Political Economy, 81, S279 – S288.

[v] A. Larson and S.N. Mitra (1992). Family Planning in Bangladesh: an unlikely success story. International Family Planning Perspectives, 18, 123-129.

[vi] In recent years, Bangladesh has benefited from large-scale female employment in the garment industry and continued family planning support. In 2011, CPR had risen to 61% and TFR was near replacement at 2.3.

Posted in Climate Change | Tagged , , , , , , , , , , , , , , , , , , , , , , , , | 3 Comments

Why Do We Care About Inequality?

Posted on January 7, 2014 by climatechangefork

Happy New Year!

My last blog ended with a quote from Karan Singh, a former minister of population in India, who said, “Development is the best contraceptive.” This was supported by data which shows that fertility rates and population growth tend to decrease as the GDP/person and the overall educational levels increase. Of course, poverty is not restricted to developing countries; rich countries have their own populations of poor people. However, statistics such as fertility rates and population growth reflect the decisions of individuals, and therefore do not always reflect the projected country averages. We measure individual poverty levels in all countries by looking at income distribution and the degree of inequality associated with such distributions.

I am starting to write this post on Friday, January 3. It’s bitter cold outside and we have just come through the major snow storm that hit a significant part of the country. I live and work in NYC and my school, like most others in the City, is closed because of the weather.

In November, we elected Bill de Blasio to be our 109th mayor, and he was sworn in on Wednesday (January 1, 2014) to start his term. His winning election campaign promised to “take dead aim at the Tale of Two Cities,” and “leave no New Yorker behind.” During de Blasio’s inauguration, the Rev. Frederick Lucas was quoted as saying, “Let the plantation called New York City be the city of God, a city set upon the hill, a light shining in darkness.” When our new mayor speaks of “two cities,” he is referring to the widening gap between the rich and poor within New York. His call for action struck a chord with voters that translated to a majority of roughly 75% against his Republican opponent in the November election.

When my French cousin heard about these results, I got a sarcastic congratulatory email on having finally elected a “commie” to lead us. I very patiently explained to him that de Blasio is not a “commie,” but that the widening gap between rich and poor is a real issue that needs to be addressed. On the off chance he was not convinced, I suggested that his mother, a longtime member of the left in French politics, might be tempted now to move to NYC. I got an immediate response from her, informing me that she doesn’t want to give up her job in a French company and she is happy where she is. Oh well, it was worth a try 🙂 .

The expanding gap between rich and poor is not only NYC issue; it is a global issue. A recent Gallup report quantifies the issue in the table below:

Income InequalityWhen I discuss this in class in the context of climate change (see the November 26 and December 3, 2012 blogs), the most common reaction from students is: “So what? What does this have to do with climate change anyway?”

Here is one appropriate response, as given in Bjorn Lomborg’s recent op-ed in the New York Times with the following emphasis:

PRAGUE — THERE’S a lot of hand-wringing about our warming planet, but billions of people face a more immediate problem: They are desperately poor, and many cook and heat their homes using open fires or leaky stoves that burn dirty fuels like wood, dung, crop waste and coal.

About 3.5 million of them die prematurely each year as a result of breathing the polluted air inside their homes — about 200,000 more than the number who die prematurely each year from breathing polluted air outside, according to a study by the World Health Organization. There’s no question that burning fossil fuels is leading to a warmer climate and that addressing this problem is important. But doing so is a question of timing and priority.

There are many problems that repeatedly stand in the way of such necessary change. Among these are the ongoing conflicts between developed and developing countries that impede any global agreement to confront climate change, an issue that once again came to light at the recent POP 19 meeting in Warsaw, Poland.

Paul Krugman examines a different aspect of inequality in his recent op-ed column in the New York Times, in which he argues that inequality is a serious impediment for economic growth:

The best argument for putting inequality on the back burner is the depressed state of the economy. Isn’t it more important to restore economic growth than to worry about how the gains from growth are distributed?

Well, no. First of all, even if you look only at the direct impact of rising inequality on middle-class Americans, it is indeed a very big deal. Beyond that, inequality probably played an important role in creating our economic mess, and has played a crucial role in our failure to clean it up. Start with the numbers. On average, Americans remain a lot poorer today than they were before the economic crisis. For the bottom 90 percent of families, this impoverishment reflects both a shrinking economic pie and a declining share of that pie. Which mattered more? The answer, amazingly, is that they’re more or less comparable — that is, inequality is rising so fast that over the past six years it has been as big a drag on ordinary American incomes as poor economic performance, even though those years include the worst economic slump since the 1930s.

The reduction of poverty on any scale can bring about many positive changes in infrastructure, such as better health care, education and a pension system. As a result, such a change in economic situation is probably the best way to reduce fertility; unfortunately, this cannot entirely ensure the stability of future populations at replacement rate. A fertility rate below the replacement rate presents its own challenges that I will try to explore in the coming blogs.

Posted in Climate Change | Tagged , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Poverty and Population

Posted on January 2, 2014 by climatechangefork

Happy New Year!

My last two blogs raised the issue of a timeline for “absolute” sustainability; one that would give us enough time to move any remnants of the human population to another planet in case we are “successful” in destroying our own. For me, the trivial event of this year’s coincidental timing of Thanksgiving and Hanukkah (an event that was dubbed “Thanksgivukkah”) was the trigger for my thoughts on the matter. In the last blog, I started to illustrate this timeline with projections of global population growth. This is an important starting point because almost every other impact that we can influence strongly depends on population. The objective here, as throughout this blog in general, is to try to provide workable options for present actions.

Instead of just playing with numbers, I thought that it might be useful to put the timeline in terms of visible markers that can serve as incentives for the actions we are advocating. I chose to use the event in which the total global population density equals that of the current most populous mega city (Mumbai – India) to illustrate the dire nature of an exponential population increase. For the opposite occurrence, I described a population decline to 10% of present world values. I selected these markers thinking (perhaps naively) that nobody alive wants to live in a world characterized by either of these two situations, so people might be more open to accepting some corrective actions to avoid such occurrences.

The emphasis on population control to prevent environmental meltdown is a controversial topic with very long history – one that I will probably touch on in some future blogs. The modern version can be traced to Thomas Malthus (1766 – 1834) and to the concept of Malthusian Trap, as summarized in the Wikipedia excerpt below:

It was Thomas Malthus who first made the argument that in “every age and in every state” that population increases are limited by the means of subsistence, and that when the means of subsistence increases, population will also increase, and that the population increase will be limited by “misery and vice.” This pessimistic view on the impossibility of real progress was first made [4] in 1798, ironically, just as the industrial revolution was getting underway.

More recent statistical evidence contradicts these observations. A good opportunity to present the global picture up front came about two years ago, when the global population passed the 7 billion marker (as I have mentioned in previous references to this marker, the global population at the time of my birth was around 2 billion people). To mark this important event (the 7 billion marker, not my birth :)), Science Magazine came out with a full issue that was dedicated to the event (Science, volume 333, 29 July 2011).

Here are some of the global charts that appear in this issue:

Global Decline in FertilityPopulation Growth RateFertility and Education

The Malthusian Trap was converted into the Demographic-economic paradox. The fertility rate is defined as the average number of children that would be born to a woman over her lifetime. The first figure above shows that this number has been decreasing over the last 60 years, both for developed and developing countries. The value for developing countries is decreasing from a high value – it now stands at around 3, while that of developed countries is also decreasing – but from a considerably lower value – and now stands at below 2. The number 2 is an important marker; in principle, it represents a replacement value for the two parents. Any number above two will drive the population higher and any number below two will lower the population. In real life many women will never reach childbearing age (one of the main reasons for that is infant mortality). The replacement value in developed countries is now estimated to be 2.1 and in developing countries it is estimated at 2.5. So, presently, the population growth in developed countries is negative while the population of developing countries is growing. The balance is shown in the second figure, which illustrates a population that is still growing, but at a considerably slower rate.

The last two figures show some of the most important driving forces that are causing the fertility rate to fall: decrease in poverty and increase in education, especially among woman. The correlation is so strong that Wikipedia (in the Demographic-economic paradox site– cited above) quotes Karan Singh, a former minister of population in India, as having said, “Development is the best contraceptive.”

In the previous blog, I quoted a United Nations report that projects the long-term population increase will stabilize around the year 2050 to replacement fertility and stay as such over the long term with the population between 8 – 9 billion people. The question that I did not find an answer to is how to reach such stability.

There are many professional experts that specialize in demographics (the study of statistics of population). I am not one of them. I have contacted a friend that qualifies and I hope that he will contribute a guest blog that addresses the issue.

Posted in Climate Change | Tagged , , , , , , , , , , , , , | 1 Comment

Future Populations

Posted on December 24, 2013 by climatechangefork

Last week’s blog established various time targets for the existence of our civilization and thus tried to establish an absolute level of sustainability. Granted, some of the targets I provided were rather trivial, like the desire to see another “Thanksgivukkah,” (an event where Thanksgiving coincides with Hanukkah). Such event could take place in as little as 60 years if we don’t care about the specific candle (which night of Hanukkah) or as long as 70,000 years if we are fussy about the candle. On the other hand, on a more serious note, we can give ourselves about 1,000 years to develop propulsion technology capable of moving people outside the solar system, while we identify a suitable, unspoiled, environment that can sustain us. As we will see shortly, the exact numbers are not very important here; the element we need to focus on right now is independent of our talks about the differences between a few hundred or a few thousand years. The most direct parameter that we can analyze for compatibility is the population.

Most population projections are based on the United Nation Population Division’s estimates. I went to Wikipedia to get a summary, and I hit on the following relevant paragraph:

Current UN projections show a continued increase in population in the near future (but a steady decline in the population growth rate), with the global population expected to reach between 8.3 and 10.9 billion by 2050.[11][12] UN Population Division estimates for the year 2150 range between 3.2 and 24.8 billion;[13] mathematical modeling supports the lower estimate.[14] Some analysts have questioned the sustainability of further world population growth, highlighting the growing pressures on the environment, global food supplies, and energy resources.[15][16][17]

Projections for 2150, the very shortest end of our need for the definition of absolute sustainability, range between 3.2 and 24.8 billion people. I thought that this must have been a typo, because this kind of range is not much different from the “small” range of 0 – infinity, and you really don’t need any professional input for that kind of an estimate.

Well, I went to the source (“Long-Range Population Projections” Proceedings of the United Nations Technical Working Group on Long-Range Population Projections (New York: United Nations: Department of Economic and Social Affairs). 2003. Retrieved July 3, 2010. ) for the following paragraph:

Future population size is sensitive to small but sustained deviations of fertility from replacement level. Thus, the low scenario results in a declining population that reaches 3.2 billion in 2150 and the high scenario leads to a growing population that rises to 24.8 billion by 2150.

Well, it’s not a typo, but it involves a bit of trivial math. Here is the methodology:

The long-range projections prepared by the United Nations Population Division include several scenarios for population growth for the world and its major areas over the period 1995-2150.The medium scenario assumes that fertility in all major areas stabilizes at replacement level around 2050; the low scenario assumes that fertility is half a child lower than in the medium scenario; and the high scenario assumes that fertility is half a child higher than in the medium scenario. The constant scenario maintains fertility constant during 1995-2150 at the level estimated for 1990 – 1995, and the instant-replacement scenario makes fertility drop instantly to replacement level in 1995 and remain at that level thereafter.

One cannot plan for a fertility rate to be equal to replacement rate. Fertility rate is a global statistical value of a collective behavior that is based on decision making by individuals. A government or the world cannot declare a policy of replacement value. The replacement value of the current global fertility rate is now 2.1 children per woman in the developed world and about 2.5 children per woman in the developing world. About two years ago, we passed a landmark when the global population crossed the 7 billion mark. When I was born the world population was around 2 billion. In my lifetime I have welcomed around 5 billion new neighbors, and I am still kicking. It is true that the fertility rate almost everywhere is in sharp decline since the end of World War II; as a direct result, the population growth rate has been decreasing since that period. This does not mean stabilization at replacement with constant population.

To stabilize the population we need to work on it. In the next blog I will start to explore what needs to be done with particular emphasis on factors such as poverty, education and availability of birth control options.

The present world population is 7.1 billion people with a 2.1% (this is a typo – see Aisha’s comment and my response – the current population growth rate is 1,12%-values are going to be corrected accordingly) growth rate and shrinking. Within a business as usual scenario (continuing present rates of growth) the doubling time for the present population would be Td = 69/1.12 = 62 years (this is a simple formula that derives from the mathematics of exponential growth).

How long will it take, given a business as usual scenario, for population growth everywhere to reach the density of the most densely populated city in the world?

The city that holds that title today is Mumbai (India), which boasts a shocking 29,650 people/km2. In the US, the equivalent is Los Angeles (ranked 90th globally), with 2,750 people/km2. Our total global land area comes out to 130 million km2 (without Antarctica), or 148.94 million km2 if we count Antarctica.

“Simple” exponential growth math shows that with the present rate of growth, it will take 571 years for the global population to grow to be as dense as Mumbai is today. That calculation provides for fully populated areas, at the same density as Mumbai today, everywhere – including Antarctica, the Sahara and Gobi deserts and other virgin areas throughout the world. If this prospect doesn’t sink in, a “short” trip to Mumbai might serve to convince. If we allow for some land dedicated to food production and recreation, the time period to reach such densities shrinks.

Let’s go to the other extreme. Poland, Ukraine, South Korea and Belarus are all countries with populations greater than 20 million, but they have among the smallest fertility rates: around 1.2 births/woman (as of 2009). Their recent population growth rates (in %) are as follows: Ukraine is -0.76, Belarus -0.5 and Russia -0.51. These numbers include immigration and emigration. Let us now explore the extreme case of the world adapting to the reproductive statistics of these countries and in turn, reducing population growth to -0.5%/year. In such a scenario, it would only take about 460 years for the global population to shrink to 10% of its current number.

In the next blogs, I will explore the possible consequences of such a dramatic reduction. There is no mechanism that I am aware of that would allow the population to stabilize itself with a constant replacement rate.

Posted in Climate Change | Tagged , , , , , , , , , , , | 2 Comments

Hanukkah, Thanksgiving and the Drake Equation

Posted on December 17, 2013 by climatechangefork

I recently finished celebrating Thanksgiving and Hanukkah with my family; enjoying the wonderful meal, lighting the 2nd Hanukkah candle and thanking God both in English and Hebrew. Following this, we also prepared to celebrate the end of the semester, and got ready to welcome Christmas, the New Year, and our wedding anniversary. What a busy time!!

The emergence of Thanksgiving on the same date as the start of Hanukkah was another occasion to commemorate. The media was full of coverage for the event, reminding us that the next time the two events coincide will be in about 70,000 years. An example of such coverage is given below:

It’s a once in more than 70,000-year event: The first day of Hanukkah this year coincides with Thanksgiving. As a result, Jews everywhere are gearing up for “Thanksgivukkah,” a mashup of Thanksgiving and the Jewish festival of lights. This lineup of the first day of Hanukkah with Thanksgiving is incredibly rare.

“That’s not going to happen again for thousands and thousands of years. No one knows exactly how long, because the calendars aren’t going up that high,” said Jason Miller, a rabbi in Michigan who blogs at rabbijason.com. “It’s something like 70,000 years,” assuming of course that America, the Jews and the human race are still around at that time.

Well, digging a bit deeper into this issue reveals that the emphasis should be on the first day of Hanukkah. Hanukkah is celebrated for eight days, and the name “Thanksgivukkah,” could be applied to the coincidental timing of any of Hanukkah’s days with Thanksgiving. A more detailed data set is given below:

Thanksgiving Dates Chanukah Dates
11/29/1888 Kislev 25, 5649—2 candles that night
11/30/1899 Kislev 29, 5660—5 candles
11/28/1918 Kislev 24, 5679—1 candle
11/29/1945 (Texas only) Kislev 24, 5706—1 candle
11/29/1956 (Texas only) Kislev 24, 5717—1 candle
11/28/2013 (you are here now) Kislev 25, 5774—2 candles
11/27/2070 (theoretically) Kislev 24, 5831—1 candle
11/28/2165 (theoretically) Kislev 24, 5926—1 candle

This is an entirely different estimate in terms of timing. I was alive for the previous two events (Texas Only), even though, at the time I knew nothing about Thanksgiving. The next one, meanwhile, coincides with my definition of “now” in the title of my book, where “now” refers to the projected lifespan of my grandchildren, and indicates the likely stretch of the global impact of climate change. The different spelling for Hanukkah in the two entries is not unusual for words that have been transliterated from other languages.

The fluctuations in the timing of the holidays are rooted in the two different calendars by which their respective communities (US and Jewish) determine the dates, as well as the continuous adjustments by said communities to make sure that these holidays fall approximately in their appropriate seasons. Thanksgiving, for example, is celebrated on the last Thursday in November (or the fourth Thursday in November), and is dictated by the Gregorian calendar. Hanukkah is based on the lunar-based Hebrew calendar.

In terms of future coincidental timing – while I will not live to see any of them, my grandchildren have decent statistical chances of seeing the next one (it won’t be the same, but 1st candle will have to do).

What caught my eye is that the desire to see the coincidental timing can serve as an inspirational target for at least some of us. In this sense, Thanksgivukkah might become an essential part of Astrobiology: “the study of the origin, evolution, distribution, and future of life in the universe: extraterrestrial life and life on Earth.” The search for places that are suitable for extraterrestrial life is a fascinating topic to study – not just for the intellectual curiosity that is involved, but also as an existential challenge, or plan B, in case we help to make our planet unlivable. Recently, Stephen Hawking addressed the issue:

TORONTO – Stephen Hawking says the colonization of outer space is key to the revival of humankind, predicting it will be difficult for the world’s inhabitants “to avoid disaster in the next hundred years.”

In 2009, James Cameron found such a place on a planet named Pandora that circles our nearest neighbor, a pair of stars named Alpha Centauri A and B. Alpha Centauri are real stars. The distance from earth to these stars is 4.4 Light Years (LY) or 25 trillion miles (42 trillion km).

Recently it was discovered that there is a real planet that orbits Alpha Centauri B that is very similar to Earth in terms of mass, but given its surface temperature of about 12000C, it is not a habitable planet. Could James Cameron have filmed Avatar on site? Not likely. The present record space speed by a satellite belongs to Helios 2, which orbits the Sun. With the help of the sun’s gravity, Helios 2 was able to attain a speed of 241,000km/hr. Voyager 1 attained the fastest solar escape velocity at 62,120km/hr. If we take the present fastest man-made space vehicle to be around 200,000km/hr, the time that it would have taken James Cameron to reach Pandora would have been 20,000 years. There is a continuous effort to develop better space propulsion systems, but an average schedule for reaching the “practical” space speed necessary to be able to move people around is still estimated at 1,000 years. The effort to actually find a suitable home for extraterrestrial (or our own) life got a serious boost with the advent of NASA’s Kepler mission.

The effort to find extraterrestrial life goes way back. In the 1950s and 60s, when we didn’t have today’s technology, we had an abundance of UFO sightings (Unidentified Flying Objects). I have discussed some of the consequences in previous blogs (January 28 and February 4) in terms of the Fermi Paradox and the Physics of Sustainability.

In Early 1961, a young Astrophysicist, Frank Drake, organized a small conference to address the issue of trying to detect extraterrestrial intelligence. The story goes that he went to the blackboard and scribbled an equation. Since then, the equation has become almost as popular as E = mC2. Every course that even mentions the issue of extraterrestrial life starts with the equation. A sample on a t-shirt is shown below

==

A more readable form, including an explanation of each of the terms follows:

N = the number of civilizations in our galaxy with which radio-communication might be possible

R* = the average rate of star formation in our galaxy

fp = the fraction of those stars that have planets

ne = the average number of planets that can potentially support life per star that has planets

fl = the fraction of planets that could support life that actually develop life at some point

fi = the fraction of planets with life that actually go on to develop intelligent life (civilizations)

fc = the fraction of civilizations that develop a technology that releases detectable signs of their existence into space

L = the length of time for which such civilizations release detectable signals into space[8].

There is obviously a large uncertainty in most of the terms. The most interesting term for our use is L. Since we are the only advanced technological civilization that we are aware of, the best place to start our estimates of the lifetime of such society is here on earth. Such an estimate is not some astronomical constant that we just have to find a smart way to measure. The value depends on our collective actions. This will be true for any advanced civilization.

This is not just a speculative exercise that physicists can design to confuse everybody else. It provides a timeline to govern our activities and thus explore what I have defined before (February 4 blog) as an absolute scale of sustainability.

In the next few blogs I will try to use that timeline to work out some of the details, starting with the requirements for population growth (or limitation therein).

Posted in Climate Change | Tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , | 3 Comments