Search Results for « Population growth »

An important issue in the study of cities is defining a metropolitan area, because different definitions affect conclusions regarding the statistical distribution of urban activity. A commonly employed method of defining a metropolitan area is the Metropolitan Statistical Areas (MSAs), based on rules attempting to capture the notion of city as a functional economic region, and it is performed by using experience. The construction of MSAs is a time-consuming process and is typically done only for a subset (a few hundreds) of the most highly populated cities. Here, we introduce a method to designate metropolitan areas, denoted "City Clustering Algorithm" (CCA). The CCA is based on spatial distributions of the population at a fine geographic scale, defining a city beyond the scope of its administrative boundaries. We use the CCA to examine Gibrat's law of proportional growth, which postulates that the mean and standard deviation of the growth rate of cities are constant, independent of city size. We find that the mean growth rate of a cluster by utilizing the CCA exhibits deviations from Gibrat's law, and that the standard deviation decreases as a power law with respect to the city size. The CCA allows for the study of the underlying process leading to these deviations, which are shown to arise from the existence of long-range spatial correlations in population growth. These results have sociopolitical implications, for example, for the location of new economic development in cities of varied size.

Projections of population size, growth rates, and age distribution, although extending to distant horizons, shape policies today for the economy, environment, and government programs such as public pensions and health care. The projections can lead to costly policy adjustments, which in turn can cause political and economic turmoil. The United Nations projects global population to grow from about 7 billion today to 9.3 billion in 2050 and 10.1 billion in 2100, while the Old Age Dependency Ratio doubles by 2050 and triples by 2100. How are such population projections made, and how certain can we be about the trends they foresee?

Abstract If age-specific birth rates drop immediately to the level of bare replacement the ultimate stationary number of a population will be given by (9): multiplied by the present number, where b is the birth rate, r the rate of increase, the expectation of life, and R0 the Net Reproduction Rate, all before the drop in fertility, and μ the mean age of childbearing afterwards. This expression is derived in the first place for females on the stable assumption; extension to both sexes is provided, and comparison with real populations shows the numerical error to be small where fertility has not yet started to drop. The result (9) tells how the lower limit of the ultimate population depends on parameters of the existing population, and for values typical of underdeveloped countries works out to about 1. 6. If a delay of 15 years occurs before the drop of the birth rate to replacement the population will multiply by over 2. 5 before attaining stationarity. The ultimate population actually reached will be higher insofar as death rates continue to improve. If stability cannot be assumed the ultimate stationary population is provided by the more general expression (7), which is still easier to calculate than a detailed projection.

If a population is growing in a randomly varying environment, such that the finite rate of increase per generation is a random variable with no serial autocorrelation, the logarithm of population size at any time t is normally distributed. Even though the expectation of population size may grow infinitely large with time, the probability of extinction may approach unity, owing to the difference between the geometric and arithmetic mean growth rates.

The world and most regions and countries are experiencing unprecedentedly rapid demographic change. The most obvious example of this change is the huge expansion of human numbers: four billion have been added since 1950. Projections for the next half century expect a highly divergent world, with stagnation or potential decline in parts of the developed world and continued rapid growth in the least developed regions. Other demographic processes are also undergoing extraordinary change: women's fertility has dropped rapidly and life expectancy has risen to new highs. Past trends in fertility and mortality have led to very young populations in high fertility countries in the developing world and to increasingly older populations in the developed world. Contemporary societies are now at very different stages of their demographic transitions. This paper summarizes key trends in population size, fertility and mortality, and age structures during these transitions. The focus is on the century from 1950 to 2050, which covers the period of most rapid global demographic transformation.

Demographers are often interested in the environmental impacts of population growth. I examine the impact of growth specifically on air quality in California. In recent decades, California has suffered from notoriously polluted air and has experienced rapid population growth. Despite the population growth, air quality actually has improved since the early 1980s due to aggressive regulatory efforts. Using data for 56 counties, I analyze the contribution of population growth to trends in atmospheric emissions of five regulated pollutants from 1980 to 1990, controlling for trends in per capita income and regulatory efforts. The analysis is disaggregated by source of emissions and demonstrates that population growth is strongly associated with some sources of emissions but not with others. Thus, the overall impact of population growth depends upon the composition of production and consumption activities in each county. I also explore whether the trend in number of households predicts better than the trend in number of persons, and whether the impact of population growth depends upon the age structure or source of growth (immigration or domestic increase). Generally, these alternative specifications of population do not improve the models of atmospheric emissions.

Do populations grow as countries become richer? In this study we estimate the effects on population growth of shocks to national income that are plausibly exogenous and unlikely to be driven by technological change. For a panel of over 139 countries spanning the period 1960–2007, we interact changes in international oil prices with countries’ average net-export shares of oil in GDP. Controlling for country and time fixed effects, we find that this measure of oil price induced income growth is positively associated with population growth. The IV estimates indicate that a 1 percentage point increase in GDP per capita growth over a 10-year period increases countries’ population growth by around 0.1 percentage points. Furthermore, we find that this population effect results from both a positive effect on fertility and a negative effect on infant and child mortality.

BACKGROUND: Protected areas are the first, and often only, line of defense in efforts to conserve biodiversity. They might be detrimental or beneficial to rural communities depending on how they alter economic opportunities and access to natural resources. As such, protected areas may attract or repel human settlement. Disproportionate increases in population growth near protected area boundaries may threaten their ability to conserve biodiversity. METHODOLOGY/PRINCIPAL FINDINGS: Using decadal population datasets, we analyze population growth across 45 countries and 304 protected areas. We find no evidence for population growth near protected areas to be greater than growth of rural areas in the same country. Furthermore, we argue that what growth does occur near protected areas likely results from a general expansion of nearby population centers. CONCLUSIONS/SIGNIFICANCE: Our results contradict those from a recent study by Wittemyer et al., who claim overwhelming evidence for increased human population growth near protected areas. To understand the disagreement, we re-analyzed the protected areas in Wittemyer et al.'s paper. Their results are simply artifacts of mixing two incompatible datasets. Protected areas may experience unusual population pressures near their edges; indeed, individual case studies provide examples. There is no evidence, however, of a general pattern of disproportionate population growth near protected areas.

The role of population growth in the process of industrialization is studied in a general equilibrium model. It provides a formal presentation of Rostow’s insight of the role of a leading sector in industrialization. Population growth may lead to a shortage of food and a breakdown of the industrialization process. However, population growth may benefit the manufacturing sector in the adoption of increasing returns to scale technologies. Elasticity of demand for agricultural goods plays an important role in determining whether an improvement of agricultural technology or an increase of population is beneficial to the manufacturing sector. A comparison of China and Britain before the Industrial Revolution shows that research and development are necessary for sustained growth. Achieving industrialization independently requires a combination of a sufficiently large market size from the demand side and a sufficiently large supply of technologies from the supply side. (JELO14, E10, N10, Q01)