POPULATION

U.S. Demographic Trends

Six main demographic trends in the U.S. are the following:

1. The population is aging with both the number and the proportion elderly increasing.

2. Immigrants, some unskilled, others highly skilled, are moving into the U.S. at a current rate of roughly one million per year.

3. Family structure and fertility patterns are changing in ways that have a major impact on the educational achievement and economic well-being of children.

4. The ethnic, racial, and socio-economic structure of the U.S. is changing, in part because of differential fertility rates and in part because of immigration.

5. The geographic location of the population is shifting south and west.

6. The absolute size of the population is increasing, but the relative size of the population, as a proportion of total world population is shrinking.

Worldwide Demographic Trends
(Lutz, W. PopNet Nr. 25, Summer 1994)

1. World population will continue to grow. By 2030, world population will increase by at least 50% and maybe even double in size. Inevitable, short-term growth is already build into the age structure of today's world population. The question is not "if" world population will grow, but rather "how large" will it become".

2. Developing countries will account for a greater share of the world population. By 2030, today's developing countries will represent betweeen 85 and 87% of the world populationthis is a very small margin of uncertainty resulting from extremely different scenarios. Under all scenarios, Africa's share of world population will increase most rapidly.

3. All populations will become older. The average age of all world regions will increase under all scenarios. The more rapid fertility declines, the faster the population ages.

World Population Projections to 2150

(from Population Division, Dept. of Economic and Social Affairs, United Nations Secretariat, New York, NY 10017; Feb. 1, 1998)

The long-range population projections presented here prepared by the United Nations Population Division, cover the period from 1950 to 2150. A total of seven projections for each of the eight major areas of the world are considered in this report. The variants are distinguished by their assumptions regarding future scenarios in total fertility rates. The range of potential demographic outcomes underscores the difficulty in focusing on any particular scenario and also highlights the critical importance of current policies and actions for the long-range future of the world population.

The seven main conclusions from these long-range population projections are:

• According to the medium-fertility scenario, which assumes fertility will stabilize at replacement levels of slightly above two children per woman, the world population will grow from 5.7 billion persons in 1995 to 9.4 billion in 2050, 10.4 billion in 2100, and 10.8 billion by 2150, and will stabilize at slightly under 11 billion persons around 2200.
• Although the high and low fertility scenarios differ by just one child per couple, half a child above and half a child below replacement fertility levels, the size of the world population in 2150 would range from 3.6 billion persons to 27.0 billion.
• If fertility rates were to stay constant at 1990-1995 levels for the next 155 years, the world in 2150 would need to support 296 billion persons.
• If all couples of the world had begun to bear children at the replacement-fertility level in 1995 (about 2 children per couple), the growth momentum of the current age structure would still result in a 67 per cent increase in the world population, to 9.5 billion by 2150.
• The future will see a continued geographical shift in the distribution of the world population as the share living in the currently more developed regions will decrease from 19 to 10 per cent between 1995 and 2150.
• Declining fertility and mortality rates will lead to dramatic population ageing. In the medium-fertility scenario, the share aged 60 years or above will increase from 10 to 31 per cent of the world population between 1995 and 2150.
• The ultimate world population size of nearly 11 billion persons, according to the medium fertility scenario of these projections, is 0.7 billion persons fewer than previously published by the United Nations in 1992, mainly due to larger-than-expected declines in fertility in many countries.

Elementary Characteristics of Populations

Information on populations is obtained either through a census or through a survey, the distinction of which is far from clear-cut. A complete convass of an area is typically thought of as a census where the intent is to enumerate every individual in the population by direct counting and further, to cross-classify by age (stage), sex and so forth. The intent of a survey is to estimate population characteristics on a sample basis.

Population Size. In concept, the notion of population size is extremely simple since it means the total number of individuals in the population.

Distribution. There are two broad spatial measures that characterize a particular distribution. These are: i. Number by spatial subdivision--statistics in this case can be given as i): percentage of the total by subdivision; or ii) a rank order from the subdivision with the highest count to the spatial unit with the lowest. Depending upon which method is used, comparisons of two census times will reveal the change in percent or the change in rank by spatial location. ii. Measures of central location--the center of a population or the mean point of the population distributed over an area is defined as the center of population gravity or of population mass. The formula for the coordinates of the population center is given by:

Structure. The structure of a population is the relative frequency of any enumerable or measurable characteristic, quality, trait, attribute or variable observed for individuals. These items could include age, sex, genetic constitution, weight, length, shape, color, biotype, birth origin and spatial distribution. Only age and sex will be covered here since they are the most common traits by which individuals in populations are decomposed. Sex ratio (SR) is the principle measure of sex composition and is usually defined as the number of males per female or:

where n_m and n_f represents the number of males and the number of females, respectively. The simplest kind of analysis of age or stage data is the frequency distribution of the total population by age or:

where f_x is the frequency of individuals aged x, n_x is the number in the population at age x and N_t is the total number in the population.

An age pyramid is often used to illustrate the age-by-sex distribution of a population. An age pyramid gives number or percentages of population in various age groups. If wide base then large proportion of births and thus rapidly growing population. If narrower base then moderately growing population. If rectangular shape then zero or negative population growth.

Population Change (in size)

If a population numbers N_t and N_t+1 at times t and t+1, respectively, then the amount of change equals

N_t+1 - N_t = Amount of Change

which is simply the difference in the population number at the two time periods. However, the rate of change is given by

Total Rate of Change

which gives the factor by which the population changed over one time period relative to the number at time t and

Fractional Rate of Change

which give the fraction by which the population changes over one time period relative to the number at time t.

Population Change (in space)

Population change occurs when migrants move from one area to another. Every move is an out-migration with respect to the area of origin and an in-migration with respect to area of destination. The balance between in-migration and out-migration is termed net migration. The sum total of migrants moving one direction or the other is termed gross in-migration or gross out-migration. The sum total of both in and out migration is termed turn over. A group of migrants having a common origin and destination is termed a migration stream. The difference between a stream and its counterstream is the net stream or net interchange between two areas. The sum of the stream and the counterstream is called the gross interchange between the two areas.

Rate of Change

All models concerned with population dynamics are concerned with population rate of change. This notion is different in an important respect from the rate of speed of a physical object like an automobile. If an insect population is 100 at the beginning of a week, and at 120 at the end of the week then by analogy with the automobile its rate would be 20 insects per week. To become a population rate this has to be divided by the population at the start of the week. Therefore the population is growing at a rate of 20/100 or .20 per week. This means every individual is increasing its number 20% or 1.2-fold per week.

The two kinds of rates are distinguished in symbols. The analogue of the physical rate x' in terms of population at times t and t + 1, N_t and N_t+1 is:

x' = N_t+1 - N_t (= amount of change)

or

N_t+1 = N_t + x'

while the demographic rate is

x = (N_t+1 - N_t)/N_t (= fraction or x-fold change)

or

N_t+1 = N_t(1-x)

Both of these relations can be expressed in terms of a short time period.

The rates x' and x yield different results if projected into the future. A population of 100 growing by 20 persons per year would have grown by 40 at the end of 2 years and by 60 at the end of 3 years. However, a population growing at a rate of 20% per year will have grown by 44 at the end of 2 years and by 73 at the end of 3 years. This last rate is called geometric increase and the former is called arithmetic increase. The distinction between these is that an arithmetic series will have a common difference while a geometric series will have a common ratio. For example, the series 1, 4, 7, 10, 13 is arithmetic with the difference being 3 (i.e. 4- 1 = 3; 7 - 4 = 3, etc). The series 1, 3, 9, 27, 81 is geometric with a common ratio of 3 (i.e. 81/27 = 3; 27/9 = 3; etc.).

The Balancing Equation

The crude rate model is the simplest of all population models. It is based on the Balancing Equation which relates the total population this year (or month, week, day, etc.) to the total population last year. Suppose last year was the initial population at time 0 (i.e. t=0; Pop₀) then this equation is given as:

Pop₁ = Pop₀
+ births
- deaths
+ in-migrants
- out-migrants

This model partials out the relative contribution of birth, death and migration. Migration is not typically considered for purposes of simplification (closed population). Since births and deaths represent totals, these terms can be re-expressed as:

births = Pop₀(b)

deaths = Pop₀(d)

where b and d denote per capita birth and death rates, respectively. Substituting these terms into the equation yields (excluding migration terms):

Pop₁ = Pop₀ + Pop₀(b) - Pop₀(d)

= Pop₀(1 + b - d)

Note that if b - d = 0 the population at time t will equal the population at time t+1, if b > d the population will increase and if b < d the population will decrease. The population at time t=2 (i.e. Pop₂) is determined as follows:

Pop₂ = Pop₁ (1 + b - d)

= Pop₀ (1 + b - d) (1 + b - d)

= Pop₀ (1 + b - d)2

The relationship for t number of time units is:

Pop_t = Pop₀ (1 + b - d)^t

The Crude Rate Model has three assumptions: 1)Homogeneity assumption (no age structure); 2)Birth and death rates remain fixed; 3)closed population. The only major conceptual difference between the crude rate model and the models covered later is that of homogeneity. Age structure adds a more realistic and interesting dimension but does not change the notion of geometric population growth. As an example projection using the Balancing Equation use birth rate b=.03 births/person/year and death rate d=.01 deaths/person/year. Also let Pop1989=5 billion. Then

Pop1990 = Pop1989(1+b-d)

= 5 (1+.03-.01)
= 5(1.02)
= 5.1 billion

and

Pop1991 = Pop1990 (1.02)
= 5.1(1.02)
= 5.202 billion

Projecting to the year 2000 yields:

Year	Number	Amount of Change	Proportion of Change	Percent
1989	5.000	--	--	--
1990	5.100	100 million	1.02	2%
1991	5.202	102 million	1.02	2%
1992	5.306	104 million	1.02	2%
1993	5.412	106 million	1.02	2%
1994	5.520	108 million	1.02	2%
1995	5.631	111 million	1.02	2%
1996	5.743	112 million	1.02	2%
1997	5.858	115 million	1.02	2%
1998	5.975	117 million	1.02	2%
1999	6.095	120 million	1.02	2%
2000	6.217	122 million	1.02	2%

For perspective in the year 2000 there will be: 1. 122 million new people added that year; 2. 334,247 new people added each day; 3. 13,927 new people added per hour; 4. 232 new people added per minute; 5. 4 people added per second.

Stable Population Theory

Stable population theory provides the foundation for our understanding of age structured population growth. It is based on three basic assumptions:

1. Population is closed to migration

2. Fertility and mortality remain constant

3. Only one sex is studied at a time.

The main conclusions are: i)a closed population subject to the basic assumptions of fixed birth and death rates and no migration will eventually attain a constant rate of increase (intrinsic rate of increase) and a constant fraction of the total population in each age class (stable age distribution); and ii)this rate of increase and the stable age distribution are independent of initial conditions.

Age Structure

The age structure of a population is determined by three factors: i)population growth rate; ii)mortality rates; and iii)transient effects (eg. baby boom). Consider the following hypothetical population with no mortality and the birth rate is 10-fold greater with each time step:

Note here that this growing population contains a total of 111 individuals at time step #3 (i.e. 100+10+1) with 90.1% in age class #1, 9.0% in age class #2 and .9% in age class #3. Now note the situation where the population experiences a 10-fold decrease in births each time step:

Note here that this decreasing population contains a total of 111 individuals at time step #3 (i.e. 1+10+100) with 90.1% in age class #3, 9.0% in age class #2 and .9% in age class #1. The point here is that growth rate alone determined the age distribution in these two hypothetical populations.

One-Step Transitions

Pick one time frame in which at most one event can happen between two states. Suppose we divide a population into five marital states: single (S), married (M), divorced (Dv), widowed (W) and dead (D). Designate these states by circles and connect them via various pathways. We organize the various pathways and transition probabilities using what is called a "transition matrix". For example, we determine: i)the proportion of individuals that make the transition from the single state to the married state; or ii)the proportion of individuals that make the transition from the married state to the widowed state.

The comple matrix is given as
TO:_
Single	.80	.00	.00	.00	.00
Married	.19	.90	.25	.35	.00
Widowed	.00	.01	.70	.00	.00
Divorced	.00	.08	.00	.60	.00
Dead	.01	.01	.05	.05	1.00
	S	M	W	Dv	D
FROM

The significance of this is that we can now bring matrix algebra to bear on the problem of population projection.

A matrix formulation of the Lotka model is known as the Leslie Matrix. It is useful for illustrating and studying the transient properties of populations as they converge to the stable state and provides a technique of cohort-component projection. The Leslie Matrix is given as:

where the top row are the birth elements F_x, the subdiagonals p_x are the period survival elements and the vectors N_x,t and N_x,t+1 denote the numbers at age x at times t and t+1, respectively. A population is projected through time by first entering an initial number of individuals into one or more age classes and multiplying the Leslie Matrix by the age vector, N_x,t. The resulting age vector, N_x,t+1, is then substituted for the age vector N_x,t and the process repeated. This is referred to as matrix iteration. As an example, consider a population with three age classes starting with N_0,t = N_1,t = N_2,t = 1 and with Leslie matrix elements of F₀ = 0, F₁ = 5, F₂ = 2, p₀ = 0.8 and p₁ = 0.5. Two iterations be computed as follows:

3-age class Leslie Matrix

Iteration #1

Iteration #2

The results for selected time periods between 0 and 10 days are presented in Table 1. Shows: i)change in numbers, age structure and growth rate with time. Note that the growth rate of the population, , becomes damped with time as it converges to a stable state (constant).

Table 1. Results of Leslie Matrix projection of hypothetical population (=2.091)

TIME	0	1	2	3	4	5	6	7	8	9	10
N0	1	7	5	28.8	25.6	119.2	125.4	497.3	597	2089	2786
N1	1	.8	5.6	4.0	23.0	20.5	95.4	100.3	398	478	1672
N2	1	.5	.4	2.8	2.0	11.5	10.2	47.7	50	199	239
TOTAL	3	8.3	11.0	35.6	50.6	151.2	231.0	645	1045	2766	4697
	2.8	1.3	3.2	1.4	3.0	1.5	2.8	1.6	2.6	1.7

Demographic Transition Theory

Demographic transition theory describes the changes that take place in birth and death rates as a population passes from traditional to urban/industrialized. It is based on two observation:

• that fertility and mortality are high in traditional societies and low in modern societies
• that every modern society has passed from low to high rates.

There are three states:

• Balanced Stage--high potential for growth when both birth and death are high
• Transitional Stage--rapid growth when death rates fall but birth rates continue at high level
• New Balanced Stage--both birth and death rates are low with potential for a dwindling population.

Fundamental Properties of Populations

• Age Structure Transience. If two populations, one which had fixed birth and death rates and the other which had these rates changing, were to begin with a narrow age distribution, say a single female, each would undergo a sequence of demographic changes. As current births reached maturity a new surge of births would "echo" the initial female's production of offspring, and this process would continue. In populations with fixed schedules, these echoes would be periodic and distinct initially but they would eventually become damped. In populations with unfixed schedules the surges may or may not be distinct or periodic depending upon the specific features of the changing schedules and, by definition, would never become stable. The main point is this--variation in age structure and growth rate will exist in both populations. A population growing with fixed schedules not yet converged to a stable state may produce patterns which are virtually indistinguishable over a short period from those produced by a population subject to changing schedules.
• Independence of Initial Conditions. The more remote a past age distribution becomes its form makes less and less difference to the shape of the current age distribution. The same factors that cause the transient effects of an initial age distribution to disappear from the stable population will operate for any time path of fecundity and mortality rate. After a suitably long period, the effect of an initial age distribution is swamped by the cumulative effect of the time pattern of vital rates. In short, the age distribution of any closed population is entirely determined by the mortality and fecundity rates of recent history. Hence given any observed age structure, it is impossible to determine either the initial population's size or its age structure.
• Fertility and Mortality. Fertility differences usually have a far greater impact on current age distributions than do mortality differences. This is because the role of fertility in shaping age distributions is simpler than mortality by the fact that the differences in fertility operate in a single direction. In contrast, mortality differences have only second order effects on age distributions. That is, a change in mortality tends to change all cohorts, implying a small effect of mortality on the immediate age distribution. When mortality changes in a gradual and monotonic fashion, the age distribution tends to adapt continuously and closely to current mortality conditions. Thus the age structure tends to differ very little from that which would have resulted from the existence of the indefinite past of current mortality conditions.
• Population Momentum. Like physical objects that have a tendency to continue moving once in motion, increasing populations have a tendency to continue growing. This is referred to in demography as population momentum. It is the extent to which a population continues to change in size after it adopts replacement-level rates of mortality and fertility. The momentum of a population can be regarded as the opposite of the intrinsic rate of increase which indicates the growth rate implicit in a set of vital schedules and independent of initial age structure. In contrast, population momentum describes the growth potential due to age structure alone.

CURRENT ISSUES IN POPULATION

The Overpopulation Crisis

Malthus (London economist) originated concept that food supply increases in arithmetic progression while population increases geometrically. Published "Population: The First Essay" in 1798.What brings end to growth? Only two things--fertility and mortality. Little progress toward fertility control and no thought of increasing mortality. But mortality is increased through misery and starvation. Thus get dismal theorem:

• Dismal Theorem (after Boulding, 1988)--if the only ultimate check on the growth of population is misery, then the population will grow until it is miserable enough to stop growth.
• Utterly Dismal Theorem--any technical improvement can only relieve misery for a while, for as long as misery is the only check on population the improvement will enable population to grow, and will soon merely enable more people to live in misery than before.

Crucial principle is that there must be some limit to the number of mankind and that growth of population, at no matter how slow a rate, must eventually bring the number to this limit. If present population were to grow at 2% per year then in 750 years the whole surface of the earth sould be covered with a solid mass of people and in 8,000 years the whole known universe 2,000 light years in radius would be solid humanity. Same argument that if start with single pair of breeding house flies in March would cover earth to depth of 12 feet by September.

Population Policy in the Developing World (from Bongaarts, J. 1994 Science 263, 771)

We are currently adding around one billion people to the globe per decade or 100 million per year. This is equivalent to adding all of the people in California, New York Texas and Florida combined. The vast majority of the growth is in the developing world, particularly in Africa, Asia and Latin America. It is impossible to understand the world today without understanding demographics--poverty, welfare, pollution, military and so forth all involve age structure, growth rate and migration.

The concerns were expressed by Malthus 200 yrs ago when he stated in his famous "First Essay" (1798) that "...the power of population is indefinately greater than the power in the earth to produce subsistence for man."

Three broad policy options for slowing population expansion:

1. Reduce unwanted pregnancies by strengthening family planning programs. Unmet need for contraception due to: i)lack of knowledge; ii)limited access to services; iii)side effects/inconvenence; iv)disapproval of husband/family; and v)cost. The consequences of the unmet need is that bear more children.

2. Reduce demand for large families through investment in human development. Advocate methods that reduce desire for births through social and economic policies. The general objective is to change the cost-benefits of child rearing from quantity to quality of child (i.e. education, status of women, child mortality).

3. Address population momentum. The tendency of population size to increase for some time after fertility has reached a level consistent with long-range population stability. Two ways to reduce: i)reduce fertility to below replacement level (leave some women with one birth); and ii)raise average age of child bearing.

How Many People Can Live on Earth?

(From Joel Cohen, May 7, 1994; PAA Meetings in Miami, FL)

Questions about how many people:

• What average level of well being?
• What distribution of material, food, etc?
• What technology?
• What domestic and international political system?
• What family structure and configuration?
• What physical and chemical environment?
• What variability of stability?
• What risk or robustness?
• How long support N number of people? 100, 500, 1000 yrs?
• Eat insects, rice, rodents, etc.?

Table 1. Demographic traits of major regions of the world--1984 and 2000.

	1984		2000
Region	Number (X 1000)	Percent of World	Number (X 1000)	Percent of World	Growth Factor	Percent Growth
Africa	536,589	11.3%	877,061	14.3%	1.63	63%
Latin America	397,138	8.3	549,971	9.0	1.38	38
North America	261,190	5.5	298,006	4.9	1.14	14
East Asia	1,238,640	26.0	1,470,036	24.0	1.19	19
South Asia	1,538,745	32.3	2,073,657	33.9	1.35	35
Europe	490,259	10.3	510,197	8.3	1.04	4
Oceana	24,458	.5	30,410	.5	1.24	24
USSR	276,066	5.8	313,940	5.1	1.14	14
	4,763,085	100.0	6,123,278	100.0

Note that the developed regions (North America and Europe) constituted 15.8% of world population in 1984 but will constitute only 13.2% in the year 2000. There are currently 1.2 billion people in China and 800 million in India. Thus around one out of three people in the world are either East Indian or Chinese. In the year 2000 nearly 60% of the world population will be in East and South Asia and nearly 87% of the population will in developing countries.

Aging Societies

"Longevity is not an end in itself. We need a reason to get up each morning." (Helen Caro quoted in NY Times Magazine3/3/96)

The elderly as a concept is an inadequate generalization that obscures the heterogeneous nature of a population group that spans more than 40 years of life. The elderly are at least as diverse as younger age groups in terms of personal and social resources, health, living arrangements and intergration into social life.

Aging trends in U.S. population (from Rice and Feldman 1983):

1. Rapid Growth of Aged. Since 1960 the population aged 65 and over has grown more than twice as fast as the younger population. The elderly increased from 16.7 million in 1960 to 25.9 million in 1980--a 55 percent increase; for the population under age 65, the increase was only 24 percent. The elderly have also increased as a proportion of the population, from 9.1 percent in 1960 to 11.1 percent twenty years later. The number of the very elderly is growing even more rapidly. In the same time span, those aged 75 to 84 rose 65 percent while the 85 years and over group rose 174 percent.

   

2. Increase in Chronic Disease. As more people live longer, chronic diseases, most commonly conditions of middle and old age, have emerged as major causes of death and disability. There are now many more persons suffering from conditions that are managed or controlled rather than cured. These conditions cause afflictions for decades, impairing ability to function and requiring much medical care. Because these conditions are often of long duration, they create burdens for the individual and for society. Approximately 32 million persons, 15 percent of the noninstitutionalized population, report limitations of activity due to chronic diseases in 1979 (National Center for Health Statistics 1981a.. The number suffering limitation of activity increases with age, rising from 7.3 percent of the total under 45 years to 24.1 percent at ages 45 to 64 years, and 46 percent at age 65 and over (see graph).
   

3. Nursing Homes. Only a small proportion--5 percent--of the elderly are in nursing homes, but 22 percent of the very old (85 years and over) are in nursing homes. As expected, nursing home residents are older and more dependent than the noninstitutional elderly. Nursing home residents' median age, in 1977, was 81 years, and 35 percent were 85 years and older. In general, these elderly residents of nursing homes suffer from multiple chronic conditions and functional impairments. Almost one third (32 percent. are senile, 35 percent have heart trouble, and 15 percent have diabetes). Orthopedic problems due to a variety of disease conditions are common; 37 percent are bedfast or chairfast and 26 percent are incontinent.

4. Increase Use of Medical Care of Elderly. Medical care utilization patterns among the elderly reflect their poorer health status. They visit physicians, and use hospital and nursing homes considerably more frequently than the younger population, and the use rates rise significantly for the very old (Kovar 1977). In 1981 the elderly comprised 11 percent of the noninstitutionalized population and consumed 29.8 percent of the hospital short-stay days of care (National Center for Health Statistics 1982b..

   

5. Increase of Medical Cost. Although the elderly comprised 10.9 percent of the population in 1978, 29.4 percent of the health care dollar is spent for their care. Persons aged 65 and over spent $2,026 per capita for health care--7 times the $286 per capita spending for persons under age 19, and 2 1/2 times the $764 per capita expenditure for persons aged 19 to 64 (Fisher 1980).
   

6. Population Aging. The aging of the population is a worldwide phenomenon among industrialized nations and the age structure of the population is a consequence of the demographic history of the country. In 1980, for example, 6.4 percent of East Germany's population was aged 75 and over due to its wartime losses, postwar population shifts, and low birthrates in subsequent years; the proportion is estimated to decline to 5.8 by the year 2000 (Table 1). By comparison, 4.4 percent of the United States population was in this older age group in 1980 and the United Nations estimates an increase to 5.5 percent in 2000, a significantly lower proportion than projected in this paper. The United Nations projection assumes that mortality rates in the older age groups will decline extremely slowly during the next two decades.

Retirement and Social Security

Social security was set up in 1935 was a trust fund. Fifty years ago there were 42 workers for every beneficiary wheras now there are only 3.2 workers for every beneficiary and in 2010 there will be only 2.9. Furthermore, the government has increased payoffs. A worker who retired in 1980 got back his contribution in less than three years. "Social Security paid off nicely for the generation that set it up" (like the originators of a chain letter). Government officials say they have enough money today to meet Social Security's commitments until 2036. There are several steps that could be taken to sustain Social Security (Atlantic Monthly, June, 1995, p53): i)starting in 10 years the minimum age for receiving Social Security payments should be raised to 70. The 10-year delay would give future retirees time to plan. When Social Security was enacted, life expectancy in the U.S. was 61.7 years; now expectancy has increased to 76.3 years and it is time for the law to reflect this demographic change. Of the 43 million people who received monthly Social Security benefits in December 1993, 27% were under age 65 and 58% were women; ii)the rate of growth of Social Security payments should be gently slowed. It is the rate of increase that has helped to put the Social Security trust fund on the road to insolvency; and iii)a 2 percent increase in the contribution rate would probably make the Social Security program (old age and survivors benefits) solvent for the period lasting through 2070.

According to researchers, the average retiree lives on five income streams (from Worth Magazine, December/January 1995):

1. Government assistance (42%). When Social Security was launched in the mid-1930s more than 40 contributors supported each recipient. A lot has changed since. then including longivity and expansion of Social Seurity to include more benefits and recipients. By 1993 there were just three contributors to pay for each recipient. Both baby boomers and baby busters cannot receive as much as their parents did for as long as they did.

2. Personal wealth (20%). Today's retirees got their own money from investments and real estate. In both cases, luck and the postwar boom were vital. Between the ages of 20 and 30 their incomes increased over 500% in real terms whereas Boomers had just a 34% increase over this period. In addition, postwar housing came cheap and the government helped with college. Boomer's parents had children early and hit their peak earning years after the kids were grown.

3. Pension income (20%). Almost all the private pension money received by today's retirees comes from plans in which an imployer or union guarantees a set income and benefits for each retiree. This is changing in two ways: i)these plans are starting to break their promises; and ii)such plans are getting out of vogue anyway. Workers now must match or supplement the contributions of employers to pensions. Pension incomes will certainly decline for boomers.

4. Other sources (3%). Current retirees may be the richest elderly generation in U.S. history, but they are not rich enough. The average net worth of boomer's parents is around $300,000. The average boomer has three siblings. Besides, much of the average estate will be eatern up by rising health care costs for oldsters who live longer than previous generations.

5. . Wage earnings (15%). The top three sources of retirement income--government, personal wealth and pensions--are headed downward. That leaves a big gap to be closed by wages. Thus in the future there will be only two options: i)work long (retire later); or ii)live on less.

Percent of Population 65 and over Fig. 1. The world's 20 oldest countries in 1992

SUGGESTED READING

Bongaarts, J. 1994. Population policy options in the developing world. Science 263:771-776.

Cohen, J. E. 1995. Population growth and earth's human carrying capacity. Science 269:341-346.

Connelly, M. and P. Kennedy. 1994. Must it be the rest against the West? Atlantic Monthly, December, 61-91.

Fogel, R. W. 1994. Economic growth, population theory, and physiology: the bearing of long-term processes on the making of economic policy. American Economic Review 84:369-395.

Graubard, S. R. 1986. The Aging Society. Daedalus 115:1-400.

Keyfitz, Nathan. 1984. The population of China. Scientific American 250(2):38-47.

Keyfitz, Nathan. 1989. The growing human population. Scientific American Sept. 1989.

Malthus, Thomas Robert. 1798. Population: The First Essay. Reprinted by Ann Arbor Paperbacks, The University of Michigan Press.

Table 1. Demographic indicators by country or area in the world, major areas and regions (from United Nations, 1984. The World Population Situation in 1983 (Department of International Economic and Social Affairs, Population Studies, No. 85).

			Population (thousands)		Annual Growth Rate			Age Distribution			Crude Rates (per 1000) GRR		e0	% urban
Country or Area			1984	2000	1950-55	1980-85	1995-2000	0-14	15-64	65+	Births	Deaths	1980-85	1980-85	1980
World total			4,763,085	6,123,278	1.8	1.7	1.5	35.6	58.6	5.7	27.3	10.6	1.73	58.9	40.9
More developed regions			1,165,789	1,272,194	1.3	0.6	0.5	23.0	65.6	11.4	15.5	9.5	0.96	73.1	71.0
Less developed regions			3,597,297	4,851,083	2.1	2.0	1.8	40.0	56.2	3.8	31.2	11.0	2.00	56.6	30.6
A.	Africa		536,589	877,061	2.1	3.0	3.1	45.2	61.7	3.1	46.4	16.5	3.16	49.7	28.5
	1.	Eastern Africa	155,447	266,238	2.2	3.2	3.4	46.8	50.6	2.6	49.1	17.0	3.35	48.8	16.0
		Burundi	4,503	6,951	1.7	2.7	2.7	43.4	53.4	3.3	47.6	20.9	3.17	44.0	2.4
		Comoros	443	715	2.3	3.0	2.8	45.8	51.3	2.8	46.3	15.9	3.10	50.0	10.5
		Ethiopia	35,420	58,407	2.0	2.6	3.1	45.5	51.9	2.6	49.2	21.5	3.30	42.9	14.2
		Kenya	19,761	38,534	2.9	4.1	4.1	52.2	45.9	1.9	55.1	14.0	4.00	52.9	13.9
		Madagascar	9,731	15,552	1.8	2.8	3.0	43.4	53.2	3.4	44.4	16.5	3.00	49.6	18.5
		Malawi	6,788	11,669	1.9	3.2	3.4	47.7	50.1	2.2	52.1	19.9	3.45	45.0	34.7
		Mauritius	1,031	1,298	2.9	1.9	1.2	34.1	62.9	3.0	25.5	6.0	1.35	66.7	52.5
		Mozambique	13,693	21,779	1.2	3.0	2.9	44.3	52.4	3.3	44.1	16.5	3.00	49.4	7.5
		Reunion	555	685	3.1	1.4	1.2	35.0	61.3	3.7	20.5	6.5	1.10	66.4	54.9
		Rwanda	5,903	10,565	2.3	3.5	3.7	48.2	49.2	2.6	51.1	16.6	3.60	49.5	4.0
		Somalia	5,423	7,079	1.6	3.7	2.5	43.2	53.3	3.5	46.5	21.3	3.00	42.9	30.3
		Uganda	15,150	26,774	3.1	3.5	3.5	48.0	49.4	2.5	49.9	14.7	3.40	52.0	11.9
		United Republic of Tanania	21,710	39,129	2.2	3.5	3.7	48.4	49.3	2.3	50.4	15.3	3.50	51.0	11.2
		Zambia	6,445	11,237	2.4	3.3	3.5	46.9	50.4	2.6	48.1	15.1	3.33	51.3	38.8
		Zimbabwe	8,461	15,132	4.0	3.5	3.6	47.2	50.0	2.7	47.2	12.3	3.25	55.7	23.1
	2.	Middle Africa	60,723	95,693	1.8	2.7	2.9	43.6	53.2	3.2	44.9	18.1	2.97	47.2	33.6
		Angola	8,540	13,234	1.4	2.5	2.8	44.2	52.9	3.0	47.3	22.2	3.15	42.0	19.2
		Central African Republic	2,508	3,736	1.2	2.3	2.6	41.5	54.6	3.9	44.7	21.8	2.90	43.0	40.9
		Chad	4,901	7,304	1.3	2.3	2.6	41.9	54.5	3.6	44.2	21.4	2.90	43.0	17.7
		Congo	1,695	2,646	1.7	2.6	2.9	43.2	53.5	3.3	44.5	18.6	2.95	46.5	37.5
		Equatorial Guinea	383	559	1.1	2.2	2.4	40.7	55.1	4.2	42.5	21.0	2.79	44.0	55.4
		Gabon	1,146	1,611	0.6	1.6	2.4	34.0	59.9	6.1	34.6	18.1	2.30	49.0	18.3f
		United Republic of Cameroon	9,371	14,045	1.9	2.4	2.6	41.9	54.3	3.8	43.6	19.2	2.85	46.0	34.3
		Zaire	32,084	52,410	2.2	2.9	3.1	44.8	52.3	2.9	45.2	15.8	3.00	50.0	39.2
		Tunisia	7,042	9,725	1.8	2.4	1.7	42.0	53.7	4.3	34.1	10.1	2.40	60.6	51.4
	3.	Northern Africa	121,386	185,671	2.2	2.9	2.4	43.2	53.0	3.8	41.9	12.9	2.93	55.9	44.6
		Algeria	21,272	35,194	2.1	3.3	2.9	46.6	49.4	3.9	45.1	12.3	3.40	57.8	61.7
		Egypt	45,657	65,200	2.4	2.5	2.0	39.5	55.9	4.5	38.4	12.5	2.55	57.3	46.1
		Libyan Arab Jamahiriya	3,471	6,072	1.8	3.8	3.3	46.7	51.1	2.2	45.6	10.9	3.50	57.9	52.5
		Morocco	22,848	36,325	2.5	3.3	2.6	46.0	50.9	3.1	44.0	11.5	3.14	57.9	41.0
		Sudan	20,945	32,926	2.0	2.9	2.7	44.9	52.4	2.7	45.9	17.4	3.22	47.7	24.4
	4.	Southern Africa	36,246	54,456	1.7	2.5	2.5	41.7	54.3	4.0	39.6	14.2	2.57	53.0	46.8
		Botswana	1,042	1,865	2.1	3.5	3.7	49.7	48.4	2.0	50.0	12.7	3.20	54.5	26.2
		Lesotho	1,481	2,251	1.6	2.5	2.6	42.0	54.5	3.6	41.7	16.4	2.85	49.3	4.6
		Namibia	1,507	2,382	2.0	2.8	2.9	44.0	52.8	3.2	45.1	17.3	3.00	48.2	34.0
		South Africa	31,586	46,918	1.7	2.5	2.4	41.3	54.7	4.1	38.7	13.9	2.50	53.5	50.8
		Swaziland	630	1,041	1.9	3.0	3.2	45.4	51.6	3.0	47.5	17.2	3.20	48.6	8.8
	5.	Western Africa	162,787	275,002	2.1	3.1	3.3	46.6	50.7	2.7	49.3	18.5	3.38	46.8	22.2
		Benin	3,890	6,381	0.7	2.9	3.2	45.8	51.2	3.0	51.0	22.5	3.45	42.5	31.3
		Cape Verde	317	382	2.7	1.4	1.0	35.4	61.1	3.5	23.9	10.3	1.30	57.0	6.3
		Gambia	630	898	1.1	1.9	2.3	42.1	54.9	3.1	48.4	29.0	3.15	35.0	19.2
		Ghana	13,044	21,923	4.8	3.2	3.2	46.3	50.9	2.8	47.0	14.6	3.20	52.0	36.6
		Guinea	5,301	7,935	1.0	2.3	2.6	42.9	54.2	2.9	46.8	23.5	3.05	40.2	19.8
		Guinea-Bissau	875	1241	0.6	1.9	2.3	40.1	55.6	4.3	40.7	21.7	2.65	43.0	16.8
		Ivory Coast	9,474	15,581	1.2	3.4	3.0	44.6	52.4	2.9	46.0	18.0	3.30	47.0	36.7
		Liberia	2,123	3,564	1.9	3.2	3.3	45.6	51.3	3.1	48.7	17.2	3.40	49.0	34.6
		Mali	7,825	12,363	1.7	2.8	2.8	45.9	51.4	2.8	50.2	22.4	3.30	42.0	19.7
		Mauritania	1,832	2,999	2.0	2.9	3.1	45.7	51.5	2.8	50.1	20.9	3.40	44.0	35.7
		Niger	5,940	9,560	1.0	2.8	3.2	45.9	50.3	3.8	51.0	22.9	3.50	42.5	12.5
		Nigeria	92,037	161,930	2.4	3.3	3.6	48.1	49.5	2.4	50.4	17.1	3.50	48.5	19.5
		Senegal	6,352	10,036	1.9	2.7	2.9	44.5	52.6	2.9	47.7	21.2	3.20	43.3	25.1
		Sierra Leone	3,536	4,868	1.1	1.8	2.1	40.9	56.1	3.0	47.4	29.7	3.02	34.0	25.9
		Togo	2,838	4,599	1.2	2.9	3.1	44.2	52.7	3.2	45.4	16.9	3.00	48.7	18.0
		Upper Volta	6,768	10,542	1.4	2.3	2.8	44.1	53.1	2.8	47.8	22.2	3.20	42.0	9.5
B.	Latin America		397 138	549 971	2.7	2.3	1.9	39.4	56.3	4.3	31.8	8.2	2.01	64.1	65.5
	6.	Caribbean	31,364	40,833	1.8	1.5	1.6	37.2	57.3	5.5	27.1	8.4	1.64	64.0	52.5
		Barbados	262	307	1.5	0.8	1.0	29.5	61.2	9.3	19.9	8.6	1.10	71.6	40.6
		Cuba	9,966	11,718	1.9	0.6	1.0	31.3	61.4	7.3	16.9	6.4	0.96	73.4	65.4
		Dominican
		Republic	6,101	8,407	2.7	2.3	1.7	43.9	53.2	2.9	33.1	8.0	2.04	62.6	54.5
		Guadeloupe	319	338	2.3	0.1	0.5	35.8	57.5	6.7	19.5	7.3	1.25	70.4	45.0
		Haiti	6,419	9,860	1.7	2.5	2.7	43.6	52.9	3.6	41.3	14.2	2.80	52.7	24.9
		Jamaica	2,290	2,849	1.9	1.4	1.3	40.6	53.6	5.8	28.3	6.7	1.65	70.3	41.6
		Martinique	312	338	2.1	0.0	0.7	33.6	59.1	7.3	18.8	7.6	1.15	70.9	69.2
		Puerto Rico	3,404	4,212	0.3	1.5	1.2	31.6	60.5	7.9	22.4	6.9	1.28	73.9	81.0
		Trinidad and Tobago	1,105	1,321	2.5	0.9	1.0	34.2	60.8	4.9	24.6	6.2	1.40	70.1	23.5
		Windward Island	418	525	2.0	1.2	1.4	41.2	54.3	4.5	30.4	6.2	1.75	69.1	0.0
		Other Caribbean	769	958	1.8	1.3	1.3	34.8	60.0	5.2	24.8	6.1	1.40	70.6	61.9
	7.	Middle America	102,811	149,557	2.9	2.7	2.1	44.6	61.9	3.4	35.1	7.4	2.32	65.0	60.9
		Costa Rica	2,534	3,596	3.5	2.6	1.9	38.5	58.0	3.6	30.5	4.2	1.71	73.0	42.1
		El Salvador	5,388	8,708	2.7	2.9	2.9	45.2	51.4	3.4	40.2	8.1	2.71	64.8	41.1
		Guatemala	8,165	12,739	2.9	2.9	2.7	44.1	53.1	2.9	38.4	9.3	2.52	60.7	38.9
		Honduras	4,232	6,978	3.2	3.4	3.2	47.8	49.4	2.7	43.9	10.1	3.17	59.9	36.0
		Mexico	77,040	109,180	2.9	2.6	1.9	44.7	51.8	3.6	33.9	7.1	2.25	65.7	67.0
		Nicaragua	3,162	5,261	3.0	3.3	3.0	47.4	50.1	2.4	44.2	9.7	2.90	59.8	52.6
		Panama	2,134	2,893	2.5	2.2	1.7	40.5	55.4	4.1	28.0	5.4	1.69	71.0	52.7
	8.	Temperate South
		America	44,964	55,496	1.9	1.5	1.2	30.5	61.9	7.6	24.3	8.6	1.57	69.0	79.9
		Argentina	30,094	37,197	2.0	1.6	1.2	30.0	61.8	8.2	24.6	8.7	1.66	69.7	78.9
		Chile	11,878	14,934	2.0	1.7	1.3	32.5	62.0	5.5	24.8	7.7	1.42	67.0	81.1
		Uruguay	2,990	3,364	1.2	0.7	0.7	27.1	62.5	10.4	19.5	10.2	1.35	70.3	84.5
	9.	Tropical South
		America	217,999	304,085	3.0	2.4	1.9	39.2	57.0	3.8	32.4	8.5	2.01	62.9	66.6
		Bolivia	6,200	9,724	2.1	2.7	2.9	43.5	53.3	3.3	44.0	15.9	3.05	50.7	32.9
		Brazil	132,648	179,487	3.2	2.2	1.7	37.7	58.2	4.0	30.6	8.4	1.86	63.4	67.5
		Colombia	28,110	37,999	2.9	2.1	1.7	39.4	57.1	3.5	31.0	7.7	1.92	63.6	70.2
		Ecuador	9,090	14,596	2.8	3.1	2.8	44.4	52.0	3.5	40.6	8.9	2.93	62.6	44.6
		Guyana	936	1,196	2.8	2.0	1.3	39.4	56.8	3.7	28.5	5.9	1.59	68.2	22.3
		Paraguay	3,576	5,405	2.7	3.0	2.3	42.7	53.9	3.4	36.0	7.2	2.37	65.1	39.4
		Peru	19,197	27,952	2.6	2.6	2.1	41.8	54.6	3.6	36.7	10.7	2.44	58.6	68.7
		Suriname	352	423	3.0	0.1	1.6	46.4	49.1	4.5	29.5	6.1	2.00	69.4	49.4
		Venezuela	17,819	27,207	3.8	3.3	2.3	42.2	55.1	2.8	35.2	5.6	2.11	67.8	83.3
C.	Northern America		261,190	298,006	1.8	0.9	0.7	22.6	66.3	11.1	16.0	9.0	0.90	74.3	75.6
		Canada	25,289	29,393	2.7	1.2	0.8	23.2	67.9	8.9	16.2	7.3	0.88	74.5	76.8
		United States of America	235,764	268,443	1.7	0.9	0.7	22.5	66.2	111.3	16.0	9.2	0.90	74.2	75.5
D.	East Asia		1,238,640	1,470,036	2.0	1.1	1.1	35.5	59.5	5.1	18.2	6.8	1.12	68.0	32.5
	11.	China	1,051,551	1,255,656	2.2	1.2	1.2	36.9	58.4	4.7	18.5	6.8	1.14	67.4	25.5
	12.	Japan	119,492	127,683	1.4	0.6	0.4	23.6	67.4	9.0	12.4	6.7	0.83	76.6	78.2
	13.	Other East Asia	67,597	86,697	0.6	1.8	1.4	34.9	61.1	4.0	23.8	6.6	1.42	66.7	59.5
		Hong Kong	5,498	6,894	4.6	2.1	1.0	25.5	68.0	6.5	17.9	5.9	1.00	73.9	91.5
		Korea	59,939	76,742	0.3	1.7	1.4	35.5	60.6	3.8	24.1	6.7	1.43	66.3	56.7
		Korea, Democratic People's Republic of	19,630	27,256	-1.4	2.3	1.8	40.0	56.3	3.7	30.5	7.4	1.95	64.6	59.7
		Korea, Republic of	40,309	49,485	1.0	1.4	1.1	33.4	62.7	3.9	21.0	6.3	1.20	67.5	55.3
		Mongolia	1,851	2,673	1.9	2.7	2.0	43.0	53.8	3.2	33.8	7.2	2.35	64.6	50.6
E.	South Asia		1,538,745	2,073,657	2.0	2.2	1.7	40.8	55.9	3.3	34.9	12.9	2.27	53.6	24.7
	14.	Eastern
		South Asia	393,082	519,707	2.0	2.1	1.6	40.7	56.0	3.3	31.7	10.9	2.01	56.8	22.8
		Burma	38,513	55,186	1.7	2.5	2.0	41.3	55.0	3.7	37.9	12.7	2.60	55.0	27.5
		Democratic
		Kampuchea	7,149	9,918	2.2	2.9	1.4	32.9	64.6	2.5	45.5	19.6	2.50	43.4	14.7
		East Timor	638	876	1.3	2.5	1.5	34.2	63.4	2.4	48.0	23.0	2.85	39.9	14.1
		Indonesia	162,167	204,486	1.7	1.8	1.3	41.0	55.6	3.3	30.7	13.0	1.90	52.5	19.8
		Lao People's Democratic Republic	4,315	6,213	2.1	2.5	2.1	43.4	53.7	2.9	40.6	15.5	2.85	49.7	12.8
		Malaysia	15,204	20,615	2.5	2.3	1.6	39.1	57.2	3.7	29.2	6.4	1.80	66.9	29.8
		Philippines	53,395	74,810	3.0	2.5	1.8	40.6	56.6	2.9	32.3	6.9	2.05	64.5	36.9
		Singapore	2,540	2,976	4.9	1.3	0.7	27.1	68.2	4.7	18.0	5.3	0.84	72.2	73.3
		Thailand	50,584	66,115	2.7	2.1	1.6	40.2	56.6	3.1	28.6	7.7	1.75	62.7	14.6
		Viet Nam	58,307	78,129	1.7	2.0	1.7	41.7	54.6	3.6	31.2	10.1	2.10	58.8	19.8
	15.	Middle South
		Asia	1,036,011	1,385,652	1.9	2.2	1.6	40.7	56.1	3.2	35.8	13.9	2.33	51.8	22.4
		Afghanistan	14,292	24,180	1.6	0.0	2.2	44.2	53.3	2.4	49.6	27.3	3.35	37.0	16.8
		Bangladesh	98,464	145,800	1.6	2.7	2.2	46.2	50.4	3.4	44.8	17.5	3.00	47.8	11.2
		Bhutan	1,388	1,893	1.6	2.0	1.8	40.4	56.4	3.2	38.4	18.1	2.70	45.9	4.0
		India	746,742	961,531	1.9	2.0	1.3	39.2	57.6	3.2	33.2	13.3	2.15	52.5	22.1
		Iran, Islamic Republic of	43,799	65,549	3.7	3.0	2.2	44.2	52.4	3.4	40.5	10.4	2.75	60.2	49.1
		Nepal	16,107	23,048	1.2	2.3	2.2	43.5	53.5	3.0	41.7	18.4	3.05	45.9	4.8
		Pakistan	98,971	142,554	2.1	3.1	2.2	45.0	52.1	2.8	42.6	15.2	2.85	50.0	28.1
		Sir Lanki	16,076	20,843	2.6	2.0	1.4	36.9	59.0	4.2	27.0	6.7	1.65	67.5	26.6
	16.
		Western South Asia	109,651	168,2998	2.7	2.9	2.5	41.6	54.4	4.0	37.8	10.1	2.67	60.6	54.0
		Arab Countries	55,964	93,695	2.4	3.4	3.0	45.2	51.8	3.0	43.8	11.3	3.27	58.4	56.5
		Bahrain	414	688	2.9	4.3	2.6	34.7	63.3	2.1	32.3	5.3	2.26	68.2	70.3
		Democratic Yemen	2,066	3,309	1.8	2.7	2.9	46.1	51.3	2.7	47.6	18.8	3.35	46.5	36.9
		Iraq	15,158	24,926	2.7	3.4	2.9	46.8	50.7	2.6	44.9	10.7	3.25	59.0	70.9
		Jordan	3,375	6,400	3.1	3.7	4.0	49.4	47.5	3.1	44.9	8.4	3.60	64.2	62.5
		Kuwait	1,703	2,969	5.4	5.3	2.8	42.6	55.9	1.4	36.8	3.5	3.00	71.2	87.1
		Lebanon	2,644	3,617	2.2	-0.0	1.9	40.1	54.5	5.4	29.3	8.8	1.85	65.0	75.5
		Oman	1,181	1,909	1.9	4.5	2.8	44.0	53.4	2.6
		Qatar	2,91	469	6.7	4.0	2.7	32.6	65.1	2.2	30.1	4.6	3.30	70.6	82.9
		Saudi Arabia	10,824	18,864	2.3	3.9	3.2	43.3	53.9	2.8	43.0	12.1	3.45	56.0	64.9
		Syrian Arab Republic	10,189	18,102	2.5	3.7	3.3	47.5	49.3	3.2	46.5	7.2	3.50	67.0	51.3
		United Arab Emirates	1,255	1,916	2.5	5.8	1.9	29.0	69.0	2.0	27.0	4.0	2.90	70.6	53.3
		Yemen	6,386	9,859	1.8	2.4	2.8	45.8	51.0	3.3	48.5	21.6	3.30	44.0	10.2
		Non-Arab Countries	53,686	74,602	2.9	2.3	1.8	38.0	57.0	5.0	31.7	8.8	2.10	63.8	51.5
		Cyprus	659	759	1.4	1.1	0.8	24.3	65.4	10.3	19.7	8.2	1.12	74.3	45.6
		Israel	4,216	5,376	6.6	2.1	1.3	33.2	58.4	8.4	23.6	6.8	1.50	74.0	90.5
		Turkey	48,811	68,466	2.7	2.3	1.9	38.6	56.7	4.6	32.5	9.0	2.17	63.0	48.2
F.	Europe		490,259	510,197	0.8	0.3	0.2	22.3	64.7	13.0	14.0	10.9	0.93	72.9	70.4
	17.	Eastern Europe	112,285	120,393	1.0	0.6	0.4	23.5	64.6	11.9	16.4	10.9	1.05	71.5	59.3
		Bulgaria	9,184	9,685	0.7	0.5	0.3	22.2	65.8	12.0	15.4	10.7	1.09	72.4	4.0
		Czechoslovakia	15,575	16,679	1.1	0.4	0.5	24.0	63.3	12.7	16.1	12.0	1.07	71.3	63.0
		German Democratic Republics	16,647	16,459	-0.5	-0.1	-0.0	19.5	64.2	16.3	12.5	13.9	0.80	72.4	77.3
		Hungary	10,772	10,816	1.0	0.1	0.1	21.5	65.0	13.5	14.4	13.1	1.00	70.6	65.6
		Poland	37,216	41,222	1.9	0.9	0.6	24.1	65.9	10.0	18.5	9.1	1.09	71.8	56.6
		Romania	22,891	25,531	1.4	0.8	0.7	26.5	63.1	10.4	17.4	9.8	1.19	70.8	48.1
	18.	Northern Europe	82,054	82,929	0.4	0.1	0.0	21.4	64.1	14.6	12.8	12.0	0.887	73.7	85.1
		Denmark	5,138	5,091	0.8	0.1	-0.1	20.9	64.9	14.2	11.1	11.1	0.74	74.6	84.2
		Finland	4,861	4,947	1.1	0.4	0.0	20.1	67.9	12.0	12.7	10.2	0.78	73.4	63.1
		Iceland	240	269	2.0	1.0	0.6	27.0	63.5	9.6	17.0	6.9	0.99	76.5	88.7
		Ireland	3,553	4,228	-0.3	1.1	1.1	31.0	57.9	11.1	20.9	10.0	1.55	72.7	56.2
		Norway	4,137	4,204	1.0	0.3	0.0	22.2	63.2	14.6	12.3	10.7	0.82	75.5	52.4
		Sweden	8,286	8,071	0.7	0.0	-0.2	19.6	64.3	16.2	10.5	11.5	0.75	75.9	87.2
		United Kingdom	55,592	55,849	0.2	-0.0	0.0	21.1	64.1	14.8	12.8	12.6	0.87	73.4	91.2
	19.	Southern Europe	141,722	152,262	0.8	0.6	0.4	24.0	64.3	11.7	15.4	9.7	1.03	73.0	62.7
		Albania	2,984	4,089	2.4	2.2	1.7	37.3	57.9	4.8	27.8	5.9	1.75	70.7	36.8
		Greece	9,900	10,752	1.0	0.6	0.5	22.9	63.9	13.31	5.8	9.5	1.12	75.0	59.9
		Italy	56,644	57,635	0.6	0.2	0.0	21.8	64.7	13.5	12.8	10.8	0.88	73.6	70.3
		Malta	380	418	0.1	0.7	0.5	23.0	67.1	9.9	17.3	10.4	0.95	71.9	77.5
		Portugal	10,005	10,949	0.5	0.7	0.5	26.1	63.5	10.4	17.8	10.0	1.11	70.5	30.9
		Spain	38,700	43,217	0.8	0.8	0.6	25.9	63.2	10.9	17.0	8.9	1.17	74.0	74.1
		Yugoslavia	23,022	25,103	1.4	0.8	0.5	24.4	66.4	9.2	16.4	8.9	1.00	71.0	43.3
	20.	Western Europe	154,198	154,613	0.8	0.1	-0.0	20.4	65.4	14.2	11.7	11.3	0.77	73.9	77.5
		Austria	7,484	7,454	0.0	-0.1	-0.0	20.4	64.1	125.5	12.1	12.8	0.79	72.7	54.0
		Belgium	9,872	9,867	0.5	0.0	0.0	20.1	65.6	124.3	12.1	12.3	0.78	73.1	72.2
		France	54,453	56,588	0.8	0.3	0.2	22.2	64.0	13.7	13.8	10.7	0.89	74.1	77.5
		Germany, Republic of	61,212	59,456	0.9	-0.2	-0.2	18.6	66.3	15.0	10.2	12.0	0.69	73.3	83.7
		Luxembourg	363	356	0.6	-0.1	-0.1	19.7	66.3	14.0	10.1	12.0	0.67	72.6	76.7
		Netherlands	14,452	14,957	1.2	0.4	0.1	22.1	66.4	11.5	11.6	8.7	0.70	75.7	75.5
		Switzerland	6,309	5,871	1.2	-0.3	-0.5	18.1	67.1	14.8	8.1	10.7	0.65	75.8	58.9
G.	Oceania		24,458	30,410	2.2	1.5	1.3	29.5	62.6	7.9	21.1	8.4	1.32	67.6	74.9
	21.	Australia/New Zealand	18,781	22,368	2.3	1.2	1.0	25.9	64.8	9.3	16.1	7.8	0.96	74.1	87.4
		Australia	15,518	18,675	2.3	1.3	1.1	25.6	65.1	9.3	16.2	7.7	0.97	74.3	87.4
		New Zealand	3,263	3,693	2.3	0.8	0.7	27.1	63.6	9.3	15.6	8.1	0.90	73.4	87.4
	22.	Melanesia	4,158	6,165	1.6	2.8	2.2	42.8	54.1	3.2	40.4	12.7	2.92	55.0	27.5
		Papua New Guinea	3,601	5,292	1.6	2.7	2.2	42.4	54.3	3.2	40.4	13.6	2.92	53.3	27.3
		Other Melanesia	557	873	2.0	3.2	2.5	45.0	52.2	2.8	39.9	6.6	2.90	66.8	28.7
	23.	Micronesia/Polynesia	1,519	1,877	2.8	1.7	1.1	40.7	56.1	3.1	3.1	5.4	2.08	69.3	40.9
		Micronesia	348	437	2.7	1.7	1.3	41.1	55.6	3.3	34.9	8.5	2.43	62.7	39.1
		Polynesia	1,171	1,440	2.8	1.7	1.0	40.6	56.3	3.1	31.3	4.4	1.98	71.6	41.5
		Fiji	674	821	3.0	1.7	1.0	36.9	60.0	3.1	27.2	4.1	1.55	72.5	42.2
		Other Polynesia	498	619	2.5	1.7	1.1	45.6	61.3	3.1	36.8	4.9	2.70	70.6	40.6
H.	24.	USSR	276,066	313,940	1.7	1.0	0.7	24.3	65.6	10.0	18.8	9.0	1.15	71.3	63.2

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