The Numbers Game, Part One

A frequent topic of discussion in Counterjihad circles concerns the alarming demographics of the Western democracies. Due to mass immigration from the Third World, and a much higher birth rate among the new arrivals than the original population, the native peoples of the West are in decline relative to those who are on the verge of supplanting them.

These facts are well known to demographers, but reliable statistics about how rapidly this transformation is occurring are comparatively hard to find. When it comes to certain sensitive metrics, most governments decline to compile statistics by ethnic group, and sometimes even forbid such data-gathering by law as a “racist” activity. New births are typically catalogued merely by the citizenship of the parents, rather than by ethnic origin, so that the decline in the white birth rate is masked by the overall totals, which include a large number of births to immigrant citizens or their descendants.

To these difficulties can be added the fact that much immigration, particularly of the poorest and least educated people, is illegal and undocumented. The new arrivals sneak into the country of their choice, disappear into the ghettos of their ethnic fellows, work in the black economy, and often purchase false identity documents in order to obtain state benefits. As a result, a reliable statistical snapshot of the most sensitive demographic trends is difficult to come by.

I recently read several articles about the explosion of Muslim immigration into the United Kingdom, and it started me thinking about what might be involved in evaluating the population data and projecting it into the future.

I chose Britain for my analysis for two reasons — (1) quite a bit of data is available, and (2) it’s in English. Data are also available for the United States, but the USA is more complicated to evaluate, since the greatest influx is from Mexico rather than Muslim countries. Illiterate and chauvinistic Mexicans are damaging to our nation, but the harm they cause will not become so evident or so severe until long after the Muslim colonization of Europe.

My goal is not to produce absolutely accurate demographic figures, nor to predict exactly what will happen in the decades ahead. My intention is rather to design a reasonable set of projections of what the future may hold, based on a certain set of assumptions. I’ve constructed scenarios using three sets of parameters — labeled somewhat arbitrarily as “optimistic”, “neutral”, and “pessimistic” — and followed an algorithm to discover where they lead.

Assumptions

The basis for my calculations includes certain assumptions about the populations involved. These presuppositions do not present a great degree of accuracy, but merely act as approximations for the purpose of modeling the trends.

First of all, I assume that Muslims and natives in Britain have different age distributions. I used the United States for a general age-population breakdown, based on a variety of sources, because it was easier to find the data. I chose a reasonably recent (2000) spread of age groups for the demographic base of natives, and a breakdown taken from 1880 for the Muslim immigrants. The latter seemed appropriate, because America was teeming with immigrants in the 1880s, with the demographic balance tipped heavily towards children and young adults. This seems a suitable template to use for today’s new arrivals in Britain.

A summary of the age distributions is given in the table below:

		Under 5		5-19		20-44		45-64		65 and over
1880		13.8%		34.3%		35.9%		12.6%		3.4%
2000		6.8%		20.7%		35.4%		24.6%		12.4%

The model I use begins with the year 2010. According to various sources, the current population of the UK is estimated at 62 million, of which approximately 2.2 million are Muslims. Ignoring the fact that the non-Muslim population includes Hindus, Sikhs, Jamaicans, Eastern Europeans, and other non-Muslim immigrants and their descendants, I will refer to the non-Muslim residents as “natives” for the sake of simplicity. I rounded off the number of natives to 60 million when initializing the model for the year 2010.

The most optimistic scenario assumes that the official estimate of the Muslim population in the UK — 2.2 million — is accurate. However, numerous immigrants arrive illegally in Britain every year, so the actual number may be higher. Therefore the other two scenarios assume a larger Muslim population in 2010.

Annual changes in population are derived from a combination of births, deaths, and net migration.

The number of births to existing residents depends on the average fertility rate for each woman and the total number of childbearing-age females. Unfortunately, fertility rates for distinct ethnic groups are notoriously hard to determine, given that most countries only make available the numbers born to citizens and non-citizens. Since many immigrants and their descendants are now citizens, the analyst is reduced to guessing the respective fertility rates for Muslims and natives.

The latest figures for Britain show a fertility rate of about 1.8 children per woman. Knowing the demographics of Pakistan (the source of most Muslim immigrants), the likely breakdown may be 4 to 5 per Muslim women versus 1.6 to 1.7 per native woman. Anecdotal evidence seems to confirm these approximations, so the model uses several different guesses based on them to project the three scenarios.

Death rates are somewhat easier to estimate. Life expectancy is now about 77 years in the West, and we can assume that those immigrants who become established here avail themselves of the generous welfare benefits and advanced medical care on offer, and thus enjoy a longevity comparable to that of the natives. There will be some variations — for example, Muslim immigrants have a higher incidence of serious congenital disorders, and are also more prone to violence, so this may increase the death rate in certain age groups.

On the other hand, the natives probably drink more heavily and may be more prone to drug addiction, so trends in the opposite direction could also be at work. All in all, however, 77 seems a suitable life expectancy, and will be used in the model.

This means that 1/77 of the population dies each year, on average. However, the death rate obviously varies across age groups, and I have used an actuarial model that contains a modest spike in the lowest ages to represent infant mortality, and then is more or less flat until after age 45, when it rises to its maximum at 77. Once again, this is by no means accurate, but will serve to produce an instructive model.

Other annual changes to the population come from immigration and emigration. According to the latest estimates, more than 600,000 immigrants enter the UK every year. Figures for emigration vary, but seem to indicate that about 180,000 to 200,000 British citizens leave the country permanently every year. Both of these rates have been increasing over the past decade.

The big question here is how many of the immigrants are Muslims, and how many of the emigrant citizens are natives. One would assume that a large portion of the immigrants are Muslims: 50% seems a reasonable approximation. And it seems likely that most of the emigrants would be native Britons, escaping the conditions created in part by the massive influx of immigrants.

My scenarios employ a fairly cautious range of parameters for migration: between 250,000 and 350,000 Muslim immigrants every year, and 100,000 to 200,000 annual native emigrants.

Utilizing the above assumptions, I have devised three scenarios employing the following parameters to model future trends:

	Natives					Muslims
Scenario	Pop.		Fert.		Migrate	Pop.		Fert.		Migrate
Optimistic	60 mln		1.9		-100k	2.2 mln		3.5		250k
Neutral	60 mln		1.6		-150k	2.6 mln		4.5		300k
Pessimistic	60 mln		1.3		-200k	3.0 mln		5.5		350k

The “pessimistic” scenario can get even more pessimistic: the fertility rate among white Britons could trend more towards an Italian or Japanese scenario, and drop to 1.2 or 1.1. Immigration has been increasing every year, as has emigration of the natives — both sets of numbers could increase further than I have assumed in any of the scenarios.

Even so, this is a good set of assumptions for a beginner’s analysis.

Two additional assumptions:

1.		Women have a 28-year “breeding shelf-life”, which runs from ages 15 to 42. Within this range, a woman is considered equally likely to give birth, based on the assumed aggregate fertility rate. This model obviously not completely accurate, since women between 20 and 30 are more likely to give birth than younger or older women, and a fair number of births are to women outside the given age range. However, the method is close enough to be useful in calculating the birth rate and providing the number of “breeders”.
2.		Migrants (both immigrants and emigrants) are distributed according to the age-proportions of the existing population. This, too, is less than completely accurate, since younger people are more likely to migrate than the elderly. But it will serve our purposes for statistical modeling.

Now comes the algorithm for calculating the demographic changes.

Methodology

I am no demographer, and my skill with statistical techniques has lain unused for forty years. As a result, the method described below relies simply on common sense and a reasonable competence in computer programming.

Using the assumptions about the age distribution for the ethnic groups as described above, the starting population for each run of the model is allocated to an array with 77 elements, one for each year of the age groups. Like everything else in the model, this is a compromise, since many people live well beyond the average life expectancy. However, to make the programming easier, I simply kill everyone off on their 78th birthday and distribute the rest of the deaths through the population array according to the actuarial schema.

At the beginning of each year, the program calculates the number of “breeders” using the assumptions outlined above, taking half of the number in each appropriate age group to be the number of women. The number of births is calculated based on these numbers.

At that point each of array elements 2 through 77 is pulled from the previous element, after being adjusted for deaths and migration, thus making everyone a year older. The number of births is added to element 1 in the population array, and then the process starts over at the beginning of the following year.

To populate the tables of results, at the end of each year two additional numbers are calculated:

1.		Voters: The total of the numbers in array elements 18 and above. This is significant for evaluation of future electoral trends.
2.		Dangerous: This is the total of young men between 15 and 30. It is calculated by adding up the appropriate array elements and dividing by two. The assumption is that these young men are more likely to be “warriors”. Most street fighters and terrorists will be in this age group. Hence they are labeled dangerous.

Before running the “real” data through the model, I tested it with a fertility rate of 2.1 — widely considered the “replacement rate” for modern populations — and a migration rate of zero. I ran it for five hundred years, and the population fluctuated through several cycles for a century or so before settling into a sine wave around the baseline of the original population. So, in that sense, the model works.

The results for the three scenarios are below, in tabular form. Each scenario is played out until 2050, with the numbers displayed every five years. First comes the optimistic scenario, with the totals for natives and Muslims, then the neutral, then the pessimistic. All population numbers are given in thousands:

Scenario: Optimistic					Group: Natives
Year		Population		Breeders		Voters		Dangerous
2010		60,000		12,294		43,794		6,720
2015		57,446		12,018		41,823		6,542
2020		55,763		11,745		40,630		6,458
2025		54,449		11,809		39,992		6,576
2030		53,291		11,498		39,453		6,416
2035		52,304		11,194		38,713		6,252
2040		51,363		10,968		38,018		5,800
2045		50,337		10,747		37,263		5,710
2050		49,204		10,427		36,423		5,614

Scenario: Optimistic					Group: Muslims
Year		Population		Breeders		Voters		Dangerous
2010		2,200		505		1,366		343
2015		3,722		848		2,293		577
2020		5,405		1,214		3,308		848
2025		7,261		1,672		4,445		1,133
2030		9,309		2,141		5,707		1,416
2035		11,574		2,659		7,054		1,738
2040		14,065		3,200		8,537		2,051
2045		16,784		3,805		10,168		2,441
2050		19,751		4,475		11,951		2,876

Scenario: Neutral					Group: Natives
Year		Population		Breeders		Voters		Dangerous
2010		60,000		12,294		43,757		6,714
2015		56,563		11,967		41,605		6,509
2020		54,035		11,644		40,237		6,397
2025		51,893		11,595		39,426		6,364
2030		49,875		10,931		38,349		5,874
2035		47,972		10,285		36,845		5,392
2040		46,060		9,722		35,407		4,682
2045		44,004		9,141		33,899		4,544
2050		41,776		8,434		32,253		4,362

Scenario: Neutral					Group: Muslims
Year		Population		Breeders		Voters		Dangerous
2010		2,600		597		1,617		406
2015		4,556		1,008		2,726		686
2020		6,774		1,446		3,941		1,010
2025		9,283		2,004		5,303		1,373
2030		12,142		2,636		6,881		1,790
2035		15,424		3,362		8,662		2,289
2040		19,176		4,159		10,679		2,813
2045		23,447		5,096		12,970		3,438
2050		28,327		6,192		15,588		4,170

Scenario: Pessimistic					Group: Natives
Year		Population		Breeders		Voters		Dangerous
2010		60,000		12,294		43,719		6,709
2015		55,681		11,916		41,387		6,475
2020		52,317		11,543		39,843		6,336
2025		49,361		11,382		38,860		6,151
2030		46,519		10,365		37,245		5,334
2035		43,773		9,382		34,983		4,538
2040		41,000		8,488		32,812		3,580
2045		38,061		7,569		30,574		3,417
2050		34,928		6,515		28,179		3,187

Scenario: Pessimistic					Group: Muslims
Year		Population		Breeders		Voters		Dangerous
2010		3,000		688		1,868		470
2015		5,431		1,168		3,159		795
2020		8,251		1,678		4,574		1,173
2025		11,504		2,339		6,160		1,619
2030		15,319		3,157		8,075		2,195
2035		19,853		4,125		10,344		2,907
2040		25,213		5,226		12,973		3,693
2045		31,532		6,572		16,039		4,618
2050		39,037		8,218		19,679		5,746

To highlight some of the salient points from the above data, I calculated each Muslim population number as a percentage of the total population in each category. Within these I designated a “point of no return” and a “critical point” for three categories: population, voters, and dangerous young men.

Fifty percent is the “point of no return” for any of these categories, the point past which Islamization is guaranteed and cannot be reversed except through foreign intervention. These numbers are highlighted in red.

However, the critical point in each category will be reached long before the fifty percent mark. For the entire population, I took the example of India as a baseline: at thirteen percent, it suffers from relentless jihad attacks, with deadly terrorist incidents occurring nearly every day.

For voters, I set the critical point at ten percent. Since Muslims tend to vote in a bloc, when the number of Muslim voters reaches ten percent, they will be able to swing the result of any election, guaranteeing a dhimmi government, no matter the party. It may be that the current political establishment in Britain has already realized what lies ahead, given that all three of the major parties have abased themselves to the “Islamic community” in recent elections.

For dangerous young men, the critical point is reached at fifteen percent. Once again, Muslims tend to act cohesively as a single group when confronting non-Muslims, who are usually fragmented and prone to factional disputes — Lebanon is a case in point. Muslim youths are more likely to be violent than young white men, so fifteen percent seems a reasonable guess as to when Muslim fighters will control the streets.

Critical points are marked in blue in the numbers below:

Scenario: Optimistic
Year		Population		Breeders		Voters		Dangerous
2010		3.5%		3.9%		3.0%		4.9%
2015		6.1%		6.6%		5.2%		8.1%
2020		8.8%		9.4%		7.5%		11.6%
2025		11.8%		12.4%		10.0%		14.7%
2030		14.9%		15.7%		12.6%		18.1%
2035		18.1%		19.2%		15.4%		21.8%
2040		21.5%		22.6%		18.3%		26.1%
2045		25.0%		26.1%		21.4%		29.9%
2050		28.6%		30.0%		24.7%		33.9%

Scenario: Neutral
Year		Population		Breeders		Voters		Dangerous
2010		4.2%		4.6%		3.6%		5.7%
2015		7.5%		7.8%		6.1%		9.5%
2020		11.1%		11.0%		8.9%		13.6%
2025		15.2%		14.7%		11.9%		17.7%
2030		19.6%		19.4%		15.2%		23.4%
2035		24.3%		24.6%		19.0%		29.8%
2040		29.4%		30.0%		23.2%		37.5%
2045		34.8%		35.8%		27.7%		43.1%
2050		40.4%		42.3%		32.6%		48.9%

Scenario: Pessimistic
Year		Population		Breeders		Voters		Dangerous
2010		4.8%		5.3%		4.1%		6.5%
2015		8.9%		8.9%		7.1%		10.9%
2020		13.6%		12.7%		10.3%		15.6%
2025		18.9%		17.0%		13.7%		20.8%
2030		24.8%		23.3%		17.8%		29.2%
2035		31.2%		30.5%		22.8%		39.0%
2040		38.1%		38.1%		28.3%		50.8%
2045		45.3%		46.5%		34.4%		57.5%
2050		52.8%		55.8%		41.1%		64.3%

You’ll notice that the point of no return doesn’t appear in these figures except in the pessimistic scenario: for the dangerous it arrives in 2040, and for the population as whole in 2050.

However, the critical point arrives surprising early, even in the optimistic scenario — 2025 for voters, and 2030 for dangerous youths and the population at large. In the pessimistic scenario, Britons will face the debilitating effects of Islamization in less than ten years.

Notice that the percentage of Muslim voters rises much more slowly than for the other categories of interest. This is because of the preponderance of older people in the native population — the Baby Boomer pig takes a long time to move through the Islamized python.

For those who find graphs helpful, the same information is expressed below in graphic form, for the pessimistic scenario only. The critical points are marked as blue discs on the relevant data series:








Conclusions

All three scenarios demonstrate that trouble is coming to the UK quite soon, even in the most optimistic scenario. In a generation or less Britain will see the kind of fiscal deterioration, civil unrest, and sectarian violence that one normally associates with countries such as Bosnia and Lebanon.

The fact that the natives will retain their voting majority for another forty years is not enough to prevent catastrophe, unless they begin voting as a bloc, and relatively soon. The main political parties are already thoroughly dhimmified, and this tendency can only be expected to intensify as the Muslim portion of the electorate grows.

The most salient numbers involve the proportion of warrior-age men, and those figures are also the most alarming of all. Control of the streets will not depend on a huge preponderance of violent young thugs, but rather on the much-dismissed “tiny minority” of bloodthirsty zealots.

However, for more than a few years out this model is not an accurate predictor of what is to come. Although it is not, strictly speaking, a linear projection — the algorithm contains feedback loops that prevent linearity — it depends on factors which are assumed not to change: life expectancy, fertility, and migration levels. If one or more of these factors changes, then all bets are off.

I’ll discuss this and more impressionistic ideas in the second part of this essay.