Griffith Feeney

How Long Do We Live

Period life expectancy is calculated from age-specific death rates using life table methods that are among the oldest and most widely employed tools of demography. These methods are rarely questioned, much less criticized. Yet changing age patterns of adult mortality in countries with high life expectancy provide a basis for questioning the conventional use of life tables. This article argues that when the mean age at death is rising, period life expectancy at birth as conventionally calculated overestimates life expectancy. Estimates of this upward bias, ranging from 1.6 years for the United States and Sweden to 3.3 years for Japan for 1980-95, are presented. A similar bias in the opposite direction occurs when mean age at death is falling. These biases can also distort trends in life expectancy as conventionally calculated and may affect projected future trends in period life expectation, particularly in the short run. Copyright 2002 by The Population Council, Inc..

Estimating mean lifetime

The life expectancy implied by current age-specific mortality rates is calculated with life table methods that are among the oldest and most fundamental tools of demography. We demonstrate that these conventional estimates of period life expectancy are affected by an undesirable “tempo effect.” The tempo effect is positive when the mean age at death is rising and negative when the mean is declining. Estimates of the effect for females in three countries with high and rising life expectancy range from 1.6 yr in the U.S. and Sweden to 2.4 yr in France for the period 1980–1995.

Recent Fertility Dynamics in China: Results from the 1987 One Percent Population Survey

There has been considerable speculation about the effects of Chinas economic reforms on recent trends in fertility. This article uses data from a 1987 survey the 1st detailed national-level data since the 1982 census and 1/1000 survey to analyze recent fertility change. The total fertility rate shows no overall trend since the late 1970s fluctuating around 2.4 children per woman. Sharp fluctuations in age distribution and marriage patterns render the crude birth rate an unreliable indicator. Parity progression ratios suggest that the overall trend has been toward slightly increasing numbers of 1-child families. Implications for policy and programs are discussed as are possible reasons for the halt of fertility decline at current levels. (authors)

Increments to life and mortality tempo

This paper introduces and develops the idea of “increments to life.” Increments to life are roughly analogous to forces of mortality: they are quantities specified for each age and time by a mathematical function of two variables that may be used to describe, analyze and model changing length of life in populations. The rationale is three-fold. First, I wanted a general mathematical representation of Bongaart’s “life extension” pill (Bongaarts and Feeney 2003) allowing for continuous variation in age and time. This is accomplished in sections 3-5, to which sections 1-2 are preliminaries. It turned out to be a good deal more difficult than I expected, partly on account of the mathematics, but mostly because it requires thinking in very unaccustomed ways. Second, I wanted a means of assessing the robustness of the Bongaarts-Feeney mortality tempo adjustment formula (Bongaarts and Feeney 2003) against variations in increments to life by age. Section 6 shows how the increments to life mathematics accomplishes this with an application to the Swedish data used in Bongaarts and Feeney (2003). In this application, at least, the Bongaarts-Feeney adjustment is robust. Third, I hoped by formulating age-variable increments to life to avoid the slight awkwardness of working with conditional rather than unconditional survival functions. This third aim has not been accomplished, but this appears to be because it was unreasonable to begin with. While it is possible to conceptualize length of life as completely described by an age-varying increments to life function, this is not consistent with the Bongaarts-Feeney mortality tempo adjustment. What seems to be needed, rather, is a model that incorporates two fundamentally different kinds of changes in mortality and length of life, one based on the familiar force of mortality function, the other based on the increments to life function. Section 7 considers heuristically what such models might look like.

Afterthoughts on the mortality tempo effect

The preceding chapters in this volume provide a broad ranging and stimulating analysis of our claim that conventional estimates of period life expectancy may be distorted by a mortality tempo effect. Much new insight into the process of mortality change and its measurement has been gained, but there is no clear consensus on the existence, nature and size of the tempo effect. Views from different contributors range widely from strongly supportive to dismissive.

Comment: on the uncertainty of population projections.

Population projections for 50 to 100 years are highly uncertain. 160 years from now the world population is projected to be between 10 and 11 billion thus the chances are 2:3 that the population will be between 5 and 22 billion. This means that there is a 1:3 chance that it will be either higher than 22 or lower than 5 billion. This set of events can be seen in 2 ways. Longterm population projections can be seen as irrelevant because of their poor chances. Yet this fact makes them relevant because it shows their uncertainty conflicts with widely held convictions about world population. The whole idea of rapid population growth is based on the mathematical principle of exponential growth. When it is the only method of calculating population growth it does clearly show that population will quickly become absolutely huge. But real life population growth is not exponential on a worldwide scale and certainty not in all local areas. Even today with some countries experiencing overpopulation other populations are shrinking. The reason is that with all things involving human behavior there are variables. In this case the population growth rate is not exponential but rather variable. It is true that many countrys demographic profiles indicate that they will continue to experience rapid population growth but there are others where this is not the case. Infant mortality is a biological measure that indicates that the world is in fact not overpopulated. Because infant mortality is at its lowest level in all of human history lowest by a large margin the world can be seen as clearly not overpopulated.