Chapter 1 The Development Gap - Jack Rossbach:...

Chapter 1

The Development

Gap

© 2014 Pearson Education, Inc. All rights reserved. 2-2

STORIES OF CATCH-UP AND DECLINE

• The development gap emerged because some countries developed earlier than others.

• In historical perspective the “Industrial Revolution”:• The British economy began to expand and change rapidly

in the late 18th century.• The American economy and much of continental Europe

started in the 19th century. • Germany and Japan started late, but caught up very

rapidly.

• The record is not all good. Examples of rich countries that subsequently declined include China, Argentina, and the Ottoman Empire (Turkey).



Figure 1.10. Japan’s Per Capita Income as a Percentage of Levels in the United Kingdom and the United States.



Figure 1.11. German Per Capita Income as a Percentage of Levels in the United Kingdom.



• Alexander Gerschenkron: “the advantages of (economic) backwardness”. Latecomers can achieve a faster process of industrialization that would allow them to catch up to early industrializers.

• Adapt existing technologies used in richer countries

• The data on catch-up shows that the advantage does not always apply.



Economic Decline

•When we look at history, some of the currently poor countries and regions of the world were once the richest.

•China was once the richest country in the world with higher living standards than Europe until around the 15th century and higher than Japan until about the 19th century. During the 19th

and 20th century Chinese growth continually lagged and did not start growing again until recently (1980s).

•After 1453, Eastern Europe was dominated by the Ottoman Empire. But the Empire declined throughout the 19th century and eventually collapsed during WWI.

•Argentina was one of the richest countries in early 20th century, mainly due to high agricultural productivity. In 1900s Argentina income levels were 80% of the U.S. By 2000, income levels declined to about 30% of U.S.


STORIES OF CATCH-UP AND DECLINEFigure 1.12. Estimates of GDP Per Capita in China and Europe in 1990 International Dollars.


STORIES OF CATCH-UP AND DECLINEFigure 1.13. GDP Per Capita of Argentina as a Percentage of Levels in the United Kingdom and the United States.



• There are many other examples of former world powers that have declined and become poor countries and/or regions of the world today.

• To date, there are no examples of prolonged economic decline in industrialized countries. However, the period of industrialization is still short (about 250 years).

• An important question is then, why do some wealthy countries begin to decline and ultimately become poor?


FACTS ABOUT THE DEVELOPMENT GAP

•The development gap between rich and poor countries involves more than just differences in average income

Other important features of the development gap

• Differences in Poverty and Hunger

• Differences in Health such as life expectancy and child mortality

• Differences in Education opportunities

Urbanization may also play an important role in development



The Poverty Gap

•The poverty headcount ratio measures the number of the world’s population living on less than $2 a day (in a PPP basis).

•This is the measure used by the World Bank to gauge “extreme poverty.”

•According to this definition, 70% of the population in South Asia (Pakistan, India, Bangladesh, and neighbors) lives in extreme poverty.

•Likewise, nearly 70% of the population of Sub-Saharan Africa fits that definition.

•In East Asia and the Pacific, 33% of the population lives below the poverty line.

•In total, this adds up to approximately 2.53 billion people. Almost half of the world’s population lives in poverty.


FACTS ABOUT THE DEVELOPMENT GAPFigure 1.3. Poverty Headcount Ration in 2008 at Poverty Line of $2 a Day in 2005 Prices (PPP basis).



The Health Gap•There are large differences in life expectancy and infant mortality between developed and developing countries. •Life expectancy measures the number of years a newborn infant would live if health and living conditions at the time of its birth remained the same throughout its life.

•Reflects the health conditions and quality of health care

•A child born in a developed country is usually expected to live longer than a child born in a developing country.

•In general, life expectancy is highly positively correlated with income.

•There are some exceptions. Cuba (79) is an example of a poor country with high life expectancy.



Table 1.1. 2010 Life Expectancy (Years) at Birth in Regions of the World and in Selected Countries.



• The infant mortality rate measures the probability that a child will die before reaching the age of 1.

• It is computed as the number of children dying before age 1 per 1,000 live births in the same year.

• It is negatively correlated with income.

• It is highest in Sub-Saharan Africa and South Asia.

• Sierra Leone has an infant mortality rate of 134 per 1,000 live births.

• By comparison, the United States has an infant mortality rate of 6.5 per 1,000 live births.

• Policy interventions can make a difference in lowering child mortality. For example, Cuba has an infant mortality rate of 4.6, which is lower than that of the United States.



Figure 1.4. Infant Mortality Rates in 2010 (Per 1,000 Live Births)



The Education Gap

•Many poor countries cannot afford a good educational system, contributing to the perpetuation of the development gap.

•There have been improvements in primary school enrollment in developing economies, but many lag behind developed nations in terms of secondary school enrollment.

•Secondary school enrollment is pupils enrolled in secondary education divided by the population in the age group. (Can be greater than 100% due to over-aged or under-aged students)

•South Korea is a success story in terms of economic growth and educational attainment. Around 97% of South Koreans between the ages of 25 and 34 have achieved secondary education.



Figure 1.5. Secondary School Enrollment (Gross) in 2009, by Region



The Urbanization Gap

•Urbanization rate measures proportion of population living in urban areas (>200,000 people) as opposed to rural areas.

•Development drives urbanization as workers flow to industries and services located in cities.

•Urbanization is increasingly rapidly across the world. In 2010, the global rate exceeded 50% for the first time.

•In Africa, Ethiopia, and Rwanda urbanization rates are below 20% while Djibouti and Gabon have urbanization rates close to 90%.

•In Asia, Nepal is the least urbanized at 18.2%. South Korea, on the other hand, has an urbanization rate of 81%, higher than Japan’s 67%.

•In Latin America, Guyana is the least urbanized at 28.5%. Brazil, Argentina, and Venezuela have urbanization rates above 90%.



Figure 1.6. World Urbanization Rates, 2010



• The recent acceleration of urbanization is not necessarily due to attractive higher levels of income in urban areas. Many people living is large cities live in extreme poverty with little basic infrastructure (safe water, electricity, gas, transportation, sewage).

• Most of the world’s largest cities are in the developing world. These include: Mexico City (Mexico), Sao Paulo (Brazil), Mumbai (India), Shanghai (China), Djakarta (Indonesia), Kolkata (India) and Cairo (Egypt).

• There is a great need for public policy to address how to improve housing, infrastructure, health and education in large cities of the developing world.

• Text cites Naga City, Philippines as example on how better urban development might be accomplished



• The development gap, as measured by income, poverty, health, education and urbanization, is a “stylized fact” of the economics of development. It raises the important questions in the economics of development:

Why did some countries develop earlier than others?

• To frame development issues, we need a dynamic (over time) view of economic development:

How is the development gap is evolving over time?

• Some countries have made great progress toward closing the gap, while for others the gap has widened.

• Countries that are falling further behind rich countries usually experience economic stagnation and even decline.


Millennium Development Goals (MDGs)

The United Nations (UN) established eight MDGs in 2000

1. Eradicate extreme Poverty and Hunger

2. Reduce Child Mortality

3. Improve Maternal Health

4. Combat HIV/AIDS, malaria, and other diseases

5. Achieve Universal Primary Education

6. Promote gender equality and empower women

7. Ensure environmental sustainability

8. Develop a global partnership for development

The goals have specific targets and goals for achieving each target

• Reports are issued giving updates on progress towards goals


Examples of MGDs Targets and Progress

1.A) Halve the proportion of people with an income less than $1.25/day

• Portion of developing population in extreme poverty fell from ~50% in 1990 to 14% in 2015. 800 million people still in extreme poverty.

8.D) Deal with the debt problems of developing countries

• The debt burden of developing countries fell from 12% in 2000 to 3.1% in 2013

8.F) Make available benefits of new technologies

• Global coverage by 2G cellular network grew from 58% in 2001 to 95% in 2015. Internet use grew from 6% of world population in 2000 to 43% in 2015

Chapter 2

Poverty and Inequality


When you have completed your study of this chapter, you will be able to

1. Measure poverty across countries using different approaches and explain how poverty has evolved over time.

2. Measure income inequality within a country and between nations.

3. Explain the relationship between income inequality and economic growth across countries and over time.


INTRODUCTION

The study of poverty and inequality is at the heart of economics. Important questions for us include:

• How do we measure inequality and poverty?

• What is the difference between absolute poverty and relativepoverty?

• How has poverty evolved over time?

• What are the trends in the different regions of the world?

• How has inequality evolved on a country-by-country basis?

• What determines the gap between the rich and the poor, both within and across countries?

• Does inequality tend to increase or decrease over time?

• Is inequality good, bad, or neutral for economic growth?


POVERTY MEASUREMENTS AND COMPARISONS International organizations, governments, and non-governmental organizations (NGOs) have worked to fight poverty.

Measuring Poverty

• Poverty measurements are usually based on survey data. A survey is a sampling of data based on questionnaires asked to a representative subset of a population.

• Local poverty assessments usually ask people in local communities to identify who, among them, are poor.

• Calorie counting determines the minimal local cost of 2,000 calories worth of food per day which becomes the level of income below which people are considered poor.

• Calorie counting fails to account for nutrition, food preferences, availability of diverse food choices, and eating habits.


POVERTY MEASUREMENTS AND COMPARISONS

• A traditional definition of the poverty line is the income required to purchase 2,000 calories of food, based on the food basket typically purchased by local households.

• The poverty headcount indicates the number of people (Q) in the population (N) earning below the poverty line. This is a measure of absolute poverty.

• The poverty headcount ratio is a proportion of the population below the poverty line (H = Q/N). This is known as relative poverty.

• The poverty line should be adjusted year to year for inflation and other factors, but this can be difficult.

• The poverty line does not reflect the degree of poverty. For example, a family with income 1% percent below the poverty line is counted the same as a family 50% below.


POVERTY MEASUREMENTS AND COMPARISONS Poverty Gap

• The poverty gap takes into account the degree of poverty, or the distance from the poverty line. It is computed by multiplying the poverty headcount by the average distance from the poverty line:

• The average poverty gap, APG = H*((z - yq) / z)

where z is poverty line and yq is avg income of those below z

• Table 2.1 provides two examples where H = 50%:A: Average income of people below the poverty line is $0.65

APG = 50%(1 – 0.65)/1 = 17.5%B: Average income of people below the poverty line is $0.35

APG = 50%(1 – 0.35)/1 = 32.5.5%Country B’s poverty is more serious

• Unfortunately, detailed data on income distribution of individuals or households is often unavailable.


POVERTY MEASUREMENTS AND COMPARISONSTable 2.1. An Example of the Poverty Headcount Ratio and the Average Poverty Gap.


POVERTY MEASUREMENTS AND COMPARISONSTable 2.1. An Example of the Poverty Headcount Ratio and the Average Poverty Gap.

𝑦𝑦𝑞𝑞𝐴𝐴 =10 × .25 + 0

2 + 10 × . 50 + .252 + 40 × .75 + .25

2 + 40 × 1.00 + .752

10 + 10 + 40 + 40= 0.65


POVERTY MEASUREMENTS AND COMPARISONSTable 2.2. The Poverty Headcount Ratio and the Average Poverty Gap for Selected Countries.


POVERTY MEASUREMENTS AND COMPARISONS• One dollar a day: Using the work of Chen and Ravallion, the World

Bank established an international extreme poverty line of $1 per day. (Updated to $1.25 per day to account for inflation.)

• They used existing household consumption surveys and PPP rates to compile most accurate and internationally comparable poverty estimates across countries and across time.

• Data is found in the annual World Development Report and are used for the Millennium Development Goals (MDG), global targets established at the 2000 Millennium Summit.

• Table 2.3: There has been a large reduction in absolute (number of persons) and relative poverty (proportion of persons living in poverty), especially in East Asia.

• Absolute poverty has increased in South Asia, sub-Saharan Africa and Europe and Central Asia.

• Transition from socialism resulted in -- hopefully temporary increases -- in relative poverty in Europe and Central Asia.


POVERTY MEASUREMENTS AND COMPARISONSTable 2.3. The Poverty Headcount and Headcount Ratio Based on $1.25 a Day.


MEASUREMENT AND COMPARISONS OF INEQUALITY

Measuring Income Inequality In general, we measure the income distribution within countries.

• Divide population of a country into quantile groups: quartiles (4 groups), quintiles (5 groups), or deciles (10 groups).

• The quantile ratio is the average income in the highest quantile over the average income in the lowest quantile. Provides no information about people in the middle range of the income distribution.

• The Lorenz curve plots the cumulative share of income held by the different quantiles of the population (Figure 2.1).

• A completely equal distribution should match the diagonal perfectly while a completely unequal distribution should resemble a backward L-shape.



Figure 2.1. The Lorenz Curve.


MEASUREMENT AND COMPARISONS OF INEQUALITYFigure 2.2. Lorenz Curve with Extremely Equal and Unequal Income Distribution.



Gini Coefficient

• From the Lorenz curve we can construct the Gini coefficient, a numerical representation of income inequality. It is defined as twice the area between the diagonal and the Lorenz curve.

• In the case of perfect income equality, the Gini coefficient would equal 0. In the case of complete income inequality, the Gini coefficient would equal 1.

• Thus, G = 1 - 2S. Where S is the area under the Lorenz curve. The ratio is between 0 and 1, and therefore can also be represented as percentages.



Figure 2.3. The Lorenz Curve and the Gini Coefficient.


INEQUALITY MEASUREMENT AND COMPARISONS

• Across regions, Latin America, Africa, and China have relatively high income inequality.

• In Latin America in particular, the decile ratio is 2 to 3 times higher than everywhere else.

• Among developed nations, the United States has a relatively unequal income distribution with a Gini coefficient of 40.8. The average for developed OECD countries is around 35.



Figure 2.4. Income Inequality in Selected Countries.


INEQUALITY MEASUREMENT AND COMPARISONS

Table 2.4. Income Inequality in Different Regions of the World (1995-2006).


ECONOMIC DETERMINANTS OF INEQUALITY

Education and Income InequalityThe variance in access to education across countries is a possible determinant of income inequality.

• People in societies where access to education is limited will tend to acquire less skills and, thus, earn lower wages.

• Uneducated people also tend to be excluded from groups in society that are powerful enough to demand from their government.

• Data on the relationship between income inequality and education is indicative, but not conclusive.

• Africa, for example, has both high income inequality and low literacy rates. South Asia, on the other hand, has low income inequality but literacy rates are even lower than in Africa.

• Also, the direction of causality is not clear. Income inequality may lead to educational inequality, or vice versa.



Table 2.5. Education and Income Inequality.



• Land Ownership and Income Inequality• Another possible determinant of income inequality is the

historical access to property ownership. • The distribution of land ownership is particularly important in

developing countries, where a bigger share of the population depends on agricultural production for subsistence.

• It is clear from the data (Figure 2.5) that income inequality and land inequality are positively correlated (i.e., inequality of land wealth leads to inequality of income).

• Latin America is also extremely inequitable in terms of land ownership, while South Asia has more equitable distribution.



Figure 2.5. Income and Land Inequality.


INEQUALITY, GROWTH, AND DEVELOPMENT

• Is inequality good or bad for economic growth?

• How does income inequality affect economic growth?

• What is the direction of causality?

• How has income inequality evolved historically?

The Kuznets Hypothesis

• Over the course of development, income inequality follows a U-curve relationship. Inequality first increases but then decreases.

• At initial stages, only small parts of society benefit, but income eventually “trickles down” to the rest of society.

• One process that generates U effect is the shift from agriculture to industry.

• However, there is little evidence to support this hypothesis in both cross-sectional and panel studies.


INEQUALITY, GROWTH AND DEVELOPMENT

Figure 2.6. The Kuznets Curve.


INEQUALITY, GROWTH AND DEVELOPMENTIncome Inequality and Economic Growth• The data show a negative correlation between long-term

growth rates of GDP per capita and the Gini coefficient. • In recent decades, Latin America has experienced both high

income inequality and poor economic growth. • Asia, on the other hand, has relatively equitable distribution

and high rates of growth.

Some possible theoretical explanations include:• Credit market imperfections: people in countries with a more

equal income distribution will have access to more credit. • Political economy: high inequality builds pressure for

redistribution of income, possibly leading to high taxation of the rich.


INEQUALITY, GROWTH AND DEVELOPMENTFigure 2.7. Income Inequality and Economic Growth.



Inequality over Time• Income inequality seems to have been increasing within countries in

the past few decades. • It has increased in Central and Eastern Europe and in China as a

result of the transition from socialism to capitalism. • It has increased in the United States and many Western European

countries.

Alternatively, we can look at world-wide income distribution.Income inequality seems to be decreasing across countries as living standards increase in developing economies. • Xavier Sala-i-Martin finds evidence that the Gini coefficients across

countries have declined since around the 1980s. • A possible explanation is the recent economic performance of China

and India. As these countries develop, hundreds of millions of people have been pulled out of poverty.



Figure 2.8. The Evolution of the World GiniCoefficient.



Figure 2.9. Evolution of the World GiniCoefficient (1970-200), Excluding Various Countries.

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