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

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The Impact Of Population Growth On Economic Development

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Economic Development Depends Upon Substantial

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Can We Have Prosperity Without Growth?

It’s easy to see why some people have become alarmist when it comes to population growth rates in developing countries. Looking at the world’s low-income countries, they see a population of more than 2 billion growing at a rate that suggests it is doubling every 31 years. How will we cope with so many more people? The following statement captures the essence of a widely expressed concern:

“At the end of each day, the world now has over two hundred thousand more mouths to feed than it had the day before; at the end of each week another million and a half; at the end of each year an additional eighty million. … Mankind, now doubling its numbers every thirty-five years, has fallen into an ambush of its own making; Economists call it the “Malthusian trap,” after the man who most starkly stated our biological predicament: population growth tends to outstrip food supplies.” Phillip Appleman, ed., Thomas Robert Malthus: An Essay on the Population Principle – Text , Sources and Background, Criticism (New York: Norton, 1976), xi.

But what are we to say about such a statement? Of course, if the world’s population continues to grow at the rate it has for the past 50 years, it is less likely that economic growth will translate into an improvement in the average standard of living. But the rate of population growth is not constant; it is influenced by other economic forces. This section begins with a discussion of the relationship between population growth and income growth, then moves on to explain the sources of population growth in low-income countries, and concludes with a discussion of the Malthusian caveat suggested in the quote above.

At a simplified level, the relationship between population growth and per capita income growth is clear. After all, per capita income equals total income divided by population. The growth rate of per capita income is approximately equal to the difference between the growth rate of income and the growth rate of population. Kenya’s annual real GDP growth rate from 1975 to 2005, for example, was 3.3%. Its population growth rate during that period was 3.2%, leaving a GDP per capita growth rate of just 0.1%. A slower rate of population growth, coupled with the same rate of GDP growth, would leave Kenya with more impressive gains 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 limit population growth.

Ripple Effects: Population And Coastal Regions

Figure 19.2 “Population and Income Growth, 1975–2005” plots population growth rates versus per capita GDP growth rates from 1975 to 2005 for more than 100 developing countries. We don’t see a simple relationship. Many countries have experienced both rapid population growth and negative changes in real GDP per capita. Still, others had relatively rapid population growth and yet had rapid increases in GDP per capita. Clearly, there is more to achieving an increase in per capita income than simply slowing population growth. But the challenge posed at the beginning of this section remains: Can the world continue to feed a population that is growing exponentially—that is, doubling at fixed intervals?

Scatterplot of population growth rates versus per capita GDP growth rates for various developing countries for the period 1975–2005. suggests that there is no systematic relationship between population rates and income growth.

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

Diminishing returns imply that adding more labor to a fixed amount of land increases output, but by decreasing amounts. Ultimately, Malthus concluded, the increase in food production would be too small to sustain the increased number of human beings consuming that production. As the population continued to grow unchecked, the number of people would eventually outstrip the country’s ability to produce enough food. There would be an inevitable Malthusian trap where the world is no longer able to meet the population’s food needs, and starvation becomes the primary brake on population growth. , the point at which the world is no longer able to meet the population’s food needs, and hunger becomes the primary brake on population growth.

Pdf) The Impact Of Population Growth On Economic Growth And Development In Nigeria: An Econometric Analysis

The Malthusian trap is illustrated in Figure 19.3 “The Malthusian Trap”. The total amount of food needed can be determined by multiplying the population in any period by the amount of food needed to sustain one person in life. Since the population is growing exponentially, food requirements are increasing at an ever-increasing rate, as shown by the curve labeled “Food Needed”. Produced food, according to Malthus, increases by a constant amount each period; its increase is shown by an upward straight line labeled “Produced Food”. Food needed eventually exceeds food produced, and the Malthusian trap is reached over time

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

What happens in the Malthusian trap? Clearly, there is not enough food to support the population growth implied by the “food required” curve. Instead, people starve, and the population begins to grow arithmetically, under the control of the “manufactured food” curve. Hunger becomes a limiting force for the population; the population lives on the edge of existence. For Malthus, the long-term fate of human beings was a standard of living barely sufficient to sustain them. As he put it, “the view has a melancholic tinge.”

Fortunately, Malthus’ predictions do not match the experience of Western societies in the 19th and 20th centuries. One of the weaknesses of his argument is that he fails to take into account the gains in production that could be achieved through the increased use of physical capital and new technologies in agriculture. Increases in the amount of capital per worker in the form of machinery, improved seeds, irrigation and fertilization allowed for a huge increase in agricultural production at the same time as the supply of labor increased. Agricultural productivity has risen rapidly in the United States over the past two centuries, exactly the opposite of the productivity decline expected by Malthus. Productivity continued to rise.

Limitations Of The Demographic Transition Model (dtm)

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

Panel (a) of Figure 19.4 “Income Levels and Population Growth” shows the birth rates of low-, middle-, and high-income countries for the period 2000–2005. We see that the higher the income level, the lower the birth rate. Fewer births lead to slower population growth. In panel (b), we see that high-income countries have had much slower rates of population growth than middle- and low-income countries over the past 30 years.

Panel (a) shows that low-income countries had much higher total fertility rates (births per woman) during the period 2000–2005. rather than high-income countries. In panel (b), we see that low-income countries had much higher

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