<br><h3> Chapter One </h3> <b>Economic Growth and Economic Development: The Questions <p> <p> 1.1 Cross-Country Income Differences</b> <p> There are very large differences in income per capita and output per worker across countries today. Countries at the top of the world income distribution are more than 30 times as rich as those at the bottom. For example, in 2000, gross domestic product (GDP; or income) per capita in the United States was more than $34,000. In contrast, income per capita is much lower in many other countries: about $8,000 in Mexico, about $4,000 in China, just over $2,500 in India, only about $1,000 in Nigeria, and much, much lower in some other sub-Saharan African countries, such as Chad, Ethiopia, and Mali. These numbers are all in 2000 U.S. dollars and are adjusted for purchasing power parity (PPP) to allow for differences in relative prices of different goods across countries. The cross-country income gap is considerably larger when there is no PPP adjustment. For example, without the PPP adjustment, GDP per capita in India and China relative to the United States in 2000 would be lower by a factor of four or so. <p> Figure 1.1 provides a first look at these differences. It plots estimates of the distribution of PPP-adjusted GDP per capita across the available set of countries in 1960, 1980, and 2000. A number of features are worth noting. First, the 1960 density shows that 15 years after the end of World War II, most countries had income per capita less than $1,500 (in 2000 U.S. dollars); the mode of the distribution is around $1,250. The rightward shift of the distributions for 1980 and 2000 shows the growth of average income per capita for the next 40 years. In 2000, the mode is slightly above $3,000, but now there is another concentration of countries between $20,000 and $30,000. The density estimate for the year 2000 shows the considerable inequality in income per capita today. <p> The spreading out of the distribution in Figure 1.1 is partly because of the increase in average incomes. It may therefore be more informative to look at the logarithm (log) of income per capita. It is more natural to look at the log of variables, such as income per capita, that grow over time, especially when growth is approximately proportional, as suggested by Figure 1.8 below. This is for the simple reason that when <i>x (t)</i> grows at a proportional rate, log <i>x (t)</i> grows linearly, and if <i>x</i><sub>1</sub> <i>(t)</i> and <i>x</i><sub>2</sub> (t) both grow by the same proportional amount, log <i>x</i><sub>1</sub> <i>(t)</i> – log <i>x</i><sub>2</sub> (t) remains constant, while <i>x</i><sub>1</sub> <i>(t)</i> – <i>x</i><sub>2</sub> <i>(t)</i> increases. <p> Figure 1.2 shows a similar pattern, but now the spreading is more limited, because the absolute gap between rich and poor countries has increased considerably between 1960 and 2000, while the proportional gap has increased much less. Nevertheless, it can be seen that the 2000 density for log GDP per capita is still more spread out than the 1960 density. In particular, both figures show that there has been a considerable increase in the density of relatively rich countries, while many countries still remain quite poor. This last pattern is sometimes referred to as the "stratification phenomenon," corresponding to the fact that some of the middle-income countries of the 1960s have joined the ranks of relatively high-income countries, while others have maintained their middle-income status or even experienced relative impoverishment. <p> Figures 1.1 and 1.2 demonstrate that there is somewhat greater inequality among nations today than in 1960. An equally relevant concept might be inequality among individuals in the world economy. Figures 1.1 and 1.2 are not directly informative on this, since they treat each country identically regardless of the size of its population. An alternative is presented in Figure 1.3, which shows the population-weighted distribution. In this case, countries such as China, India, the United States, and Russia receive greater weight because they have larger populations. The picture that emerges in this case is quite different. In fact, the 2000 distribution looks less spread out, with a thinner left tail than the 1960 distribution. This reflects the fact that in 1960 China and India were among the poorest nations in the world, whereas their relatively rapid growth in the 1990s puts them into the middle-poor category by 2000. Chinese and Indian growth has therefore created a powerful force for relative equalization of income per capita among the inhabitants of the globe. <p> Figures 1.1, 1.2, and 1.3 look at the distribution of GDP per capita. While this measure is relevant for the welfare of the population, much of growth theory focuses on the productive capacity of countries. Theory is therefore easier to map to data when we look at output (GDP) per worker. Moreover, key sources of difference in economic performance across countries are national policies and institutions. So for the purpose of understanding the sources of differences in income and growth across countries (as opposed to assessing welfare questions), the unweighted distribution is more relevant than the population-weighted distribution. Consequently, Figure 1.4 looks at the unweighted distribution of countries according to (PPP-adjusted) GDP per worker. "Workers" here refers to the total economically active population (according to the definition of the International Labour Organization). Figure 1.4 is very similar to Figure 1.2, and if anything, it shows a greater concentration of countries in the relatively rich tail by 2000, with the poor tail remaining more or less the same as in Figure 1.2. <p> Overall, Figures 1.1–1.4 document two important facts: first, there is great inequality in income per capita and income per worker across countries as shown by the highly dispersed distributions. Second, there is a slight but noticeable increase in inequality across nations (though not necessarily across individuals in the world economy). <p> <p> <b>1.2 Income and Welfare</b> <p> Should we care about cross-country income differences? The answer is definitely yes. High income levels reflect high standards of living. Economic growth sometimes increases pollution or may raise individual aspirations, so that the same bundle of consumption may no longer satisfy an individual. But at the end of the day, when one compares an advanced, rich country with a less-developed one, there are striking differences in the quality of life, standards of living, and health. <p> Figures 1.5 and 1.6 give a glimpse of these differences and depict the relationship between income per capita in 2000 and consumption per capita and life expectancy at birth in the same year. Consumption data also come from the Penn World tables, while data on life expectancy at birth are available from the World Bank Development Indicators. <p> These figures document that income per capita differences are strongly associated with differences in consumption and in health as measured by life expectancy. Recall also that these numbers refer to PPP-adjusted quantities; thus differences in consumption do not (at least in principle) reflect the differences in costs for the same bundle of consumption goods in different countries. The PPP adjustment corrects for these differences and attempts to measure the variation in real consumption. Thus the richest countries are not only producing more than 30 times as much as the poorest countries, but are also consuming 30 times as much. Similarly, cross-country differences in health are quite remarkable; while life expectancy at birth is as high as 80 in the richest countries, it is only between 40 and 50 in many sub-Saharan African nations. These gaps represent huge welfare differences. <p> Understanding why some countries are so rich while some others are so poor is one of the most important, perhaps <i>the</i> most important, challenges facing social science. It is important both because these income differences have major welfare consequences and because a study of these striking differences will shed light on how the economies of different nations function and how they sometimes fail to function. <p> The emphasis on income differences across countries implies neither that income per capita can be used as a "sufficient statistic" for the welfare of the average citizen nor that it is the only feature that we should care about. As discussed in detail later, the efficiency properties of the market economy (such as the celebrated First Welfare Theorem or Adam Smith's invisible hand) do not imply that there is no conflict among individuals or groups in society. Economic growth is generally good for welfare but it often creates winners and losers. Joseph Schumpeter's famous notion of creative destruction emphasizes precisely this aspect of economic growth; productive relationships, firms, and sometimes individual livelihoods will be destroyed by the process of economic growth, because growth is brought about by the introduction of new technologies and creation of new firms, replacing existing firms and technologies. This process creates a natural social tension, even in a growing society. Another source of social tension related to growth (and development) is that, as emphasized by Simon Kuznets and discussed in detail in Part VII, growth and development are often accompanied by sweeping structural transformations, which can also destroy certain established relationships and create yet other winners and losers in the process. One of the important questions of political economy, which is discussed in the last part of the book, concerns how institutions and policies can be arranged so that those who lose out from the process of economic growth can be compensated or prevented from blocking economic progress via other means. <p> A stark illustration of the fact that growth does not always mean an improvement in the living standards of all or even most citizens in a society comes from South Africa under apartheid. Available data (from gold mining wages) suggest that from the beginning of the twentieth century until the fall of the apartheid regime, GDP per capita grew considerably, but the real wages of black South Africans, who make up the majority of the population, likely fell during this period. This of course does not imply that economic growth in South Africa was not beneficial. South Africa is still one of the richest countries in sub-Saharan Africa. Nevertheless, this observation alerts us to other aspects of the economy and also underlines the potential conflicts inherent in the growth process. Similarly, most existing evidence suggests that during the early phases of the British industrial revolution, which started the process of modern economic growth, the living standards of the majority of the workers may have fallen or at best remained stagnant. This pattern of potential divergence between GDP per capita and the economic fortunes of large numbers of individuals and society is not only interesting in and of itself, but it may also inform us about why certain segments of the society may be in favor of policies and institutions that do not encourage growth. <p> <p> <b>1.3 Economic Growth and Income Differences</b> <p> How can one country be more than 30 times richer than another? The answer lies in differences in growth rates. Take two countries, A and B, with the same initial level of income at some date. Imagine that country A has 0% growth per capita, so its income per capita remains constant, while country B grows at 2% per capita. In 200 years' time country B will be more than 52 times richer than country A. This calculation suggests that the United States might be considerably richer than Nigeria because it has grown steadily over an extended period of time, while Nigeria has not. We will see that there is a lot of truth to this simple calculation. In fact, even in the historically brief postwar era, there are tremendous differences in growth rates across countries. These differences are shown in Figure 1.7 for the postwar era, which plots the density of growth rates across countries in 1960, 1980, and 2000. The growth rate in 1960 refers to the (geometric) average of the growth rate between 1950 and 1969, the growth rate in 1980 refers to the average growth rate between 1970 and 1989, and 2000 refers to the average between 1990 and 2000 (in all cases subject to data availability). Figure 1.7 shows that in each time interval, there is considerable variability in growth rates; the cross-country distribution stretches from negative rates to average rates as high as 10% per year. It also shows that average growth in the world was more rapid in the 1950s and 1960s than in the subsequent decades. <p> Figure 1.8 provides another look at these patterns by plotting log GDP per capita for a number of countries between 1960 and 2000 (in this case, I plot GDP per capita instead of GDP per worker because of the availability of data and to make the figures more comparable to the historical figures below). At the top of the figure, U.S. and U.K. GDP per capita increase at a steady pace, with a slightly faster growth in the United States, so that the log (or proportional) gap between the two countries is larger in 2000 than it is in 1960. Spain starts much poorer than the United States and the United Kingdom in 1960 but grows very rapidly between 1960 and the mid-1970s, thus closing the gap between itself and the latter two countries. The three countries that show the most rapid growth in this figure are Singapore, South Korea, and Botswana. Singapore starts much poorer than the United Kingdom and Spain in 1960 but grows rapidly, and by the mid-1990s it has become richer than both. South Korea has a similar trajectory, though it starts out poorer than Singapore and grows slightly less rapidly, so that by the end of the sample it is still a little poorer than Spain. The other country that has grown very rapidly is the "African success story" Botswana, which was extremely poor at the beginning of the sample. Its rapid growth, especially after 1970, has taken Botswana to the ranks of the middle-income countries by 2000. <p> The two Latin American countries in this picture, Brazil and Guatemala, illustrate the often-discussed Latin American economic malaise of the postwar era. Brazil starts out richer than South Korea and Botswana and has a relatively rapid growth rate between 1960 and 1980. But it experiences stagnation from 1980 on, so that by the end of the sample South Korea and Botswana have become richer than Brazil. Guatemala's experience is similar but even more bleak. Contrary to Brazil, there is little growth in Guatemala between 1960 and 1980 and no growth between 1980 and 2000. <p> Finally, Nigeria and India start out at similar levels of income per capita as Botswana but experience little growth until the 1980s. Starting in 1980, the Indian economy experiences relatively rapid growth, though this has not been sufficient for its income per capita to catch up with the other nations in the figure. Finally, Nigeria, in a pattern that is unfortunately all too familiar in sub-Saharan Africa, experiences a contraction of its GDP per capita, so that in 2000 it is in fact poorer than it was in 1960. <p> The patterns shown in Figure 1.8 are what we would like to understand and explain. Why is the United States richer in 1960 than other nations and able to grow at a steady pace thereafter? How did Singapore, South Korea, and Botswana manage to grow at a relatively rapid pace for 40 years? Why did Spain grow relatively rapidly for about 20 years but then slow down? Why did Brazil and Guatemala stagnate during the 1980s? What is responsible for the disastrous growth performance of Nigeria? <p> <p> <b>1.4 Origins of Today's Income Differences and World Economic Growth</b> <p> The growth rate differences shown in Figures 1.7 and 1.8 are interesting in their own right and could also be, in principle, responsible for the large differences in income per capita we observe today. But are they? The answer is largely no. Figure 1.8 shows that in 1960 there was already a very large gap between the United States on the one hand and India and Nigeria on the other. <p> This pattern can be seen more easily in Figure 1.9, which plots log GDP per worker in 2000 versus log GDP per capita in 1960 (in both cases relative to the U.S. value) superimposed over the 45° line. Most observations are around the 45° line, indicating that the relative ranking of countries has changed little between 1960 and 2000. Thus the origins of the very large income differences across nations are not to be found in the postwar era. There are striking growth differences during the postwar era, but the evidence presented so far suggests that world income distribution has been more or less stable, with a slight tendency toward becoming more unequal. <p> <i>(Continues...)</i> <p> <!-- copyright notice --> <br></pre> <blockquote><hr noshade size='1'><font size='-2'> Excerpted from <b>INTRODUCTION TO MODERN ECONOMIC GROWTH</b> by <b>DARON ACEMOGLU</b> Copyright © 2009 by Princeton University Press. Excerpted by permission of PRINCETON UNIVERSITY PRESS. All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.<br>Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.