Impact Of Population Growth On Economic Development – This is Population Growth and Economic Development, Chapter 19.2 of Principles of Macroeconomics (version 2.0). For details on this (including licensing) click here.

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Impact Of Population Growth On Economic Development

Impact Of Population Growth On Economic Development

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Pdf) The Impact Of Population Growth On Economic Development In Pakistan

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Effects Of Slower Economic Growth

It’s easy to see why some are concerned when it comes to population growth rates in developing countries. If we look at the world’s low-income countries, we see that the population of more than 2 billion is growing at a rate that doubles every 31 years. How to handle large numbers of people? The following statement captures the essence of the widely expressed concern:

“At the end of each day there are two hundred thousand more mouths in the world than the day before; a million and a half more at the end of each week; An additional eighty million at the end of each year. … Mankind, now doubling its numbers every thirty-five years, is lurking in its own creation; Economists call it the ‘Malthusian trap,’ after the man who most clearly expressed our biological problem: population growth outstrips the food supply.” Philip Appleman, ed., Thomas Robert Malthus: An Essay on Population Policy – Text, Sources, and Background, Review (New York: Norton, 1976), xi.

But what about such a statement? If the rate of world population growth continues at the same rate as it has for the past 50 years, there is little chance that economic growth will raise the average standard of living. But population growth rates are not constant; It is influenced by other economic forces. This chapter begins with a discussion of the relationship between population growth and income growth, then explains the sources of population growth in low-income countries, and concludes with a discussion of the Malthusian caveat suggested in the quote above.

Impact Of Population Growth On Economic Development

At the simplest level, the relationship between population growth and per capita income growth is obvious. Ultimately, per capita income equals total income divided by population. The growth rate of per capita income is equal to the difference between the income growth rate and the population growth rate. For example, annual real GDP growth in Kenya from 1975 to 2005 was 3.3 percent. The growth rate of its population during this period was 3.2%, so the growth rate of GDP per capita was only 0.1%. A lower population growth rate combined with the same rate of GDP growth would have given Kenya a very impressive growth in per capita income. The implication is that if developing countries want to increase their per capita GDP growth rate relative to developed countries, they must control population growth.

Population Development As A Driver Of Coastal Risk: Current Trends And Future Pathways

Figure 19.2, Population and Income Growth, 1975-2005. Plots population growth rates against per capita GDP growth rates from 1975 to 2005 in over 100 developing countries. We don’t see simple relationships. Many countries are experiencing rapid population growth and negative changes in GDP per capita. But others saw relatively rapid population growth but rapid growth in GDP per capita. Clearly, achieving an increase in per capita income requires more than slowing population growth. But there is the problem posed at the beginning of this chapter: Can the world continue to support a population that is growing exponentially, that is, doubling at regular intervals?

A scatterplot of population growth rates against per capita GNP growth rates in various developing countries over the period 1975–2005 shows no systematic relationship between population growth rates and income.

. It proved to be one of the most enduring works of its time. Malthus’ basic argument was that population growth would inevitably face diminishing returns.

Low returns mean that adding more labor to a given land increases productivity, but less and less. Ultimately, Malthus concluded that the increase in food production would be too small to support the increase in the number of people consuming that food. As population continued to grow uncontrollably, the number of people eventually exceeded the Earth’s ability to produce enough food. There will be an inevitable Malthusian trap, the point at which the world can no longer meet the population’s food needs, and hunger will become the main drag on population growth. , the point at which the world can no longer meet the food demands of population and hunger becomes a major inhibitor of population growth.

Development Economics Definition And Types Explained

The Malthus Trap is shown in Figure 19.3 The Malthus Trap. The total amount of food required can be determined by multiplying the population at any given time by the amount of food required for the survival of one person. As the population grows exponentially, the demand for food increases faster and faster, the curve labeled “food demand” shows. According to Malthus, the food produced increases by a constant amount in each period; Its increase is shown by the upward sloping straight line labeled “industrial food”. The food required eventually exceeds the food produced and the Malthus trap is reached just in time

If the population grows at a constant exponential rate, the amount of food needed will increase exponentially. But Malthus believed that food production could only increase by a fixed amount in each period. Given these two different growth processes, food requirements eventually catch up with food production. In the Malthusian trap shown here at T, people reach a subsistence level of food production.

What happens in the Malthus trap? It is clear that there is not enough food to support population growth driven by the “food demand” curve. Instead, people starve and population begins to grow exponentially, which is inhibited by the “produced food” curve. Hunger becomes the controlling force of people; People live on the edge of life. For Malthus, man’s long-term destiny was a standard of living that was insufficient for survival. As he put it, “The appearance has a melancholy.”

Impact Of Population Growth On Economic Development

Fortunately, Malthus’s predictions did not match the experience of Western societies in the 19th and 20th centuries. The weakness of his argument is that he does not take into account the increase in productivity that can be achieved by expanding the use of physical capital and new technologies in agriculture. The amount of capital per worker in the form of machinery, improved seeds, irrigation and fertilizers increased, while the supply of labor increased. Agricultural productivity in the United States has increased rapidly over the past two centuries, in contrast to the decline in productivity expected by Malthus. Labor productivity continued to grow. Population Growth, Income Distribution, And Economic Development: Theory, Methodology, And Empirical Results (population Economics): 9783642785733: Heerink, Nico: Books

Malthus was also wrong about the relationship between population growth and income. He believed that any increase in income would contribute to population growth. But the law of demand tells us that the opposite is also possible: higher incomes reduce population growth. The primary cost of having children is the opportunity cost of the time parents spend raising them—higher income increases this opportunity cost. Higher incomes increase the cost of having children and reduce the number of children people want, thus slowing population growth.

Panel (a) of Figure 19.4, Income Levels and Population Growth, shows fertility rates in low-, middle-, and high-income countries over the period 2000–2005. As incomes rise we see birth rates fall. Fewer births mean slower population growth. In panel (b), we see that over the past 30 years, population growth rates have been much lower in high-income countries than in middle- and low-income countries.

Panel (a) shows the 2000–2005 period in low-income countries. The total fertility rate (births per woman) was higher than in high-income countries. In panel (b), we find that it is significantly higher in low-income countries

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