Todaro and Smith Economic Development Ch.2 PDF

MICHAEL P. TODARO STEPHEN C. SMITH ECONOMIC DEVELOPMENT THIRTEENTH EDITION  2 Comparative Economic Development In this chapter, we introduce the study of comparative economic development. 2.1 An Introduction The developin...

MICHAEL P. TODARO STEPHEN C. SMITH ECONOMIC DEVELOPMENT THIRTEENTH EDITION  2 Comparative Economic Development In this chapter, we introduce the study of comparative economic development. 2.1 An Introduction The developing world is generally thought of as sub-Saharan Africa, most of Asia, North Africa and the Middle East, Latin America and the Caribbean, other islands, and “transition” countries of Eastern Europe. It is contrasted with the developed, high-income Organization for Economic Cooperation and Development (OECD) world, sometimes called “the North,” although it includes Australia and New Zealand. The developing world is the subject of this text—while one of its central points is that the variation among develop- ing countries is sometimes as great as the differences between the developing and developed worlds. We often focus on groups of developing countries with distinct character- istics, such as the low-income countries or upper-middle-income countries, sub-Saharan African countries, or transition economies, depending on problems and policies addressed, as explained in this chapter. A large majority of countries have made substantial economic development progress over the last few decades. At the same time, the global economy contin- ues to present extreme contrasts. Output per worker in the United States is over eight times higher than it is in India and more than 50 times higher than in the Democratic Republic of Congo (DRC). In 2017, gross national income (GNI) per capita was $58,270 in the United States, $1,800 in India, and $460 in the DRC.1 If we think of the world as a single economy, its income would be distributed more unequally than any country. There are also enormous gaps in other measures of social welfare. Life expec- tancy is 78.7 years in the United States, 68.6 in India, and just 59.6 in the DRC. The percentage of children who are underweight is less than 2% in the United States but 36% in India and 23% in the DRC. Whereas almost all women are literate in the United States, only 63% are in India, and 67% in the DRC.2 How did such wide disparities come about? In today’s world, with so much knowledge and with the movement of people, information, and goods and ser- vices so rapid and comparatively inexpensive, how have such large gaps man- aged to persist, and for many countries even widen? Why have some developing countries made striking progress in closing these gaps, while others have made so much less? 35 36 CHAPTER 2 Comparative Economic Development In this chapter, we examine how national levels of economic development are measured so as to allow for quantitative comparisons across countries. Average income is one, but only one, of the factors defining a country’s level of economic development. This is to be expected, given the discussion of the meaning of development in Chapter 1. We examine how levels of development currently differ across regions of the world. We begin in Section 2.2 by describing how national levels of economic development are conventionally classified according to average income. We then examine the significance of making adjustments for purchasing power parity in making realistic comparisons across country standards of living. Finally, we consider the significance of some other well-known classifications of countries that are sometimes used in defining the developing and developed worlds. In Section 2.3, we go beyond income to consider indicators of average lev- els of education and health; we then introduce a widely followed composite measure, the Human Development Index, that combines all three. We find the wide range of all these indicators serves as an early warning for us not to over- generalise. Indeed, the economic differences between low-income countries in sub-Saharan Africa and South Asia and upper-middle-income countries in East Asia and Latin America can be even more profound than those between Developing countries high-income OECD and upper-middle-income developing countries. Countries primarily in Asia, In Section 2.4, we consider ten important characteristics of countries that help Africa, the Middle East, Latin America, eastern Europe, and identify economic development challenges. In each case, we find commonalities the former Soviet Union that across developing countries, but also substantial differences depending upon the are presently characterized by level of economic development they have already achieved, and other factors. low levels of living and other These differences are as essential to appreciate as are similarities. development deficits. Used in the development literature as We examine, in turn, levels of income and productivity; human capital a synonym for less developed attainments; inequality and absolute poverty; population growth rate and age countries, or collectively low structure; social fractionalisation; rural population size and rural-to-urban and middle income countries. migration; level of industrialisation; geography and natural resource endow- Human capital Productive ments; extent of financial and other markets; and quality of institutions and investments in people, such extent of external dependence. The mix and severity of challenges among these as skills, values, and health characteristics help define the constraints and policy priorities for economic resulting from expenditures on education, on-the-job train- development. ing programs, and medical After reviewing commonalities and differences among developing countries, care. and between high-income and low- and middle-income economies, in Section 2.5 we study the extent to which developing and developed countries are converg- ing in their levels of development. We examine the roots of how the world econ- omy came to be so unequal, in what has been called the “Great Divergence.” Then, we examine the extent to which countries are now converging in their levels of economic development. For deeper perspective on causes of the Great Divergence, and the slow and erratic progress of developing countries catching up toward developed coun- tries, in Section 2.6 we draw on recent scholarship on comparative economic development to further clarify how such an unequal world came about and remained so persistently unequal, and why some countries face steep chal- lenges in achieving development. We see the major role played by colonialism in shaping economic institutions that set the “rules of the economic game,” which can limit or facilitate opportunities for economic development. We examine other factors in comparative development, such as nations’ levels of  2.2 What is the Developing World? Classifying Levels of National Economic Development 37 inequality. We will come to appreciate why so many developing countries have experienced such difficulties in achieving economic development; but also will begin to see some of what can be done to overcome obstacles and encourage faster progress even among today’s least-developed countries. We also shed light on some positive factors behind recent rapid progress in a significant por- tion of the developing world. The chapter concludes with a comparative case study of Ghana and Côte d’Ivoire, which highlights the relationships between institutions, colonial lega- cies, and contemporary economic development. 2.2 What is the Developing World? Classifying Levels of National Economic Development A traditional way to define levels of economic development level is by per capita income. We begin by examining standard measures based on income dif- ferences, though we find this metric to be very incomplete (if not misleading). We then extend country comparisons to education and health; and examine in detail the best-known composite measure of all three facets, the United Nations (HDI). 2.2.1 Conventional Comparisons of Average National Income Probably the best-known system for income comparisons is used by the largest multilateral development bank, the World Bank Group. (The World Bank is World Bank An organisa- examined in detail in Chapter 13, Box 13.2.) In the World Bank’s classification tion known as an “interna- tional financial institution” system, briefly introduced in Chapter 1, 216 economies with a population of at that provides development least 30,000 are ranked by their levels of GNI per capita. These economies are funds to developing countries then classified as low-income countries (LICs), lower-middle-income countries in the form of interest-bearing (LMCs), upper middle-income countries (UMCs), high-income OECD coun- loans, grants, and technical assistance. tries, and other high-income countries (HICs). The cutoffs are updated each year to adjust for inflation and other factors. For the 2018–19 period, the LICs Low-income countries (LICs) were defined as having a per capita GNI of $996 or less; LMCs have incomes In the World Bank classifi- cation, countries with a GNI between $996 and $3,895; upper-middle-income countries have incomes between per capita of less than $996 $3,896 and $12,055; and HICs have incomes above $12,055.3 in 2018. With a number of important exceptions, when defined by income level the Lower-middle-income developing countries are widely considered those with low-, lower-middle, or countries (LMCs) In the upper-middle incomes, distinctions introduced in Chapter 1. These countries are World Bank classification, grouped by their geographic region in Table 2.1, making them easier to identify countries with a GNI per cap- ita incomes between $994 and on the map in Figure 2.1. $3,895 in 2018. Each year, when the latest income data become available, the classifications Upper middle-income coun- are updated; some countries grow enough to move up a category, or, less often, tries (UMCs) In the World a country’s income falls enough to move down to a lower category. Over the Bank classification, countries last quarter century, countries as a whole have steadily moved from low to LMC with a GNI per capita between $3,896 and $12,055 in 2018. income levels, so that by 2018 there were 34 countries classified as LICs; there were 47 LMCs and 56 UMCs. There were 81 HICs with at least $12,056 per High-income countries person, ranging from small European microstates such as Andorra and Liech- (HICs) In the World Bank classification, countries with a tenstein to large countries including the US and UK, and recent entrants, such GNI per capita above $12,055 as Panama, which joined the HIC group in 2018. Comparisons of incomes for in 2018. 38 CHAPTER 2 Comparative Economic Development TABLE 2.1 Classification of Economies by Country Code, Region, and Income, 2018 Country Code Class Country Code Class Country Code Class East Asia and the Pacific Costa Rica CRI UMC Comoros*‡ COM LIC American Samoa‡ ASM UMC Cuba‡ CUB UMC Congo, Dem. Rep.* COD LIC Cambodia* KHM LMC Dominica‡ DMA UMC Congo, Rep. COG LMC China CHN UMC Dominican Republic‡ DOM UMC Côte d’Ivoire CIV LMC Fiji‡ FJI UMC Ecuador ECU UMC Equatorial Guinea GNQ UMC Indonesia IDN LMC El Salvador SLV LMC Eritrea* ERI LIC Kiribati*‡ KIR LMC Grenada‡ GRD UMC Ethiopia*† ETH LIC (North) Korea, Dem. PRK LIC Guatemala GTM UMC Gabon GAB UMC People’s Rep Guyana‡ GUY UMC Gambia, The* GMB LIC Lao PDR*† LAO LMC Haiti*‡ HTI LIC Ghana GHA LMC Malaysia MYS UMC Honduras HND LMC Guinea* GIN LIC Marshall Islands‡ MHL UMC Jamaica‡ JAM UMC Guinea-Bissau*‡ GNB LIC Micronesia, Fed. FSM LMC Mexico MEX UMC Kenya KEN LMC Sts.‡ Nicaragua NIC LMC Lesotho*† LSO LMC Mongolia† MNG LMC Paraguay† PRY UMC Liberia* LBR LIC Myanmar* MMR LMC Peru PER UMC Madagascar* MDG LIC Nauru NRU UMC St. Lucia‡ LCA UMC Malawi*† MWI LIC Papua New Guinea PNG LMC St. Vincent and the VCT UMC Mali*† MLI LIC Philippines PHL LMC Grenadines‡ Mauritania* MRT LMC Samoa‡ WSM UMC Suriname‡ SUR UMC Mauritius‡ MUS UMC Solomon Islands*‡ SLB LMC Venezuela, RB VEN UMC Mozambique* MOZ LIC Thailand THA UMC Namibia NAM UMC Timor-Leste*‡ TLS LMC Middle East and North Africa Niger*† NER LIC Tonga‡ TON UMC Algeria DZA UMC Nigeria NGA LMC Tuvalu* TUV UMC Djibouti* DJI LMC Rwanda*† RWA LIC Vanuatu*‡ VUT LMC Egypt, Arab Rep. EGY LMC Sao Tome and STP LMC Vietnam VNM LMC Iran, Islamic Rep. IRN UMC Principe*‡ Iraq IRQ UMC Senegal* SEN LIC Europe and Central Asia Jordan JOR UMC Sierra Leone* SLE LIC Albania ALB UMC Lebanon LBN UMC Somalia* SOM LIC Armenia† ARM UMC Libya LBY UMC South Africa ZAP UMC Azerbaijan† AZE UMC Morocco MAR LMC South Sudan* SSD LIC Belarus BLR UMC Syrian Arab Republic SYR LIC Sudan* SDN LLC Bosnia and BIH UMC Tunisia TUN LMC Swaziland† SWZ LMC Herzegovina West Bank and Gaza PSE LMC Tanzania* TZA LIC Bulgaria BGR UMC Yemen, Rep.* YEM LIC Togo* TGO LIC Georgia GEO LMC Uganda*† UGA LIC Kazakhstan† KAZ UMC South Asia Afghanistan*† AFG LIC Zambia*† ZMB LMC Kosovo XKX LMC Zimbabwe† ZWE LIC Kyrgyz Republic† KGZ LMC Bangladesh* BGD LMC Macedonia, FYR† MKD UMC Bhutan*† BTN LMC High-Income OECD Countries Moldova† MDA LMC India IND LMC Australia AUS Montenegro MNE UMC Maldives‡ MDV UMC Austria AUT Romania ROU UMC Nepal*† NPL LIC Belgium BEL Russian Federation RUS UMC Pakistan PAK LMC Canada CAN Serbia SRB UMC Sri Lanka LKA LMC Chile CHL Tajikistant† TJK LICSub-Saharan Africa Czech Republic CZE Turkey TUR UMCAngola* AGO LMC Denmark DNK Turkmenistan† TKM UMCBenin* BEN LIC Estonia EST Ukraine UKR LMCBotswana† BWA UMC Finland FIN Uzbekistan† UZB LMCBurkina Faso*† BFA LIC France FRA Burundi*† BDI LIC Germany DEU Latin America and the Caribbean Cabo Verde‡ CPV LMC Greece GRC Belize‡ BLZ UMC Cameroon CMR LMC Hungary HUN Bollvia† BOL LMC Central African CAF LIC Iceland ISL Brazil BRA UMC Republic*† Ireland IRL Colombia COL UMC Chad*† TCD LIC Israel ISR  2.2 What is the Developing World? Classifying Levels of National Economic Development 39 TABLE 2.1 Classification of Economies by Country Code, Region, and Income, 2018 ( Continued ) Country Code Class Country Code Class Country Code Class Japan JPN Barbados‡ BRB New Caledonia‡ NCL Korea, Rep. KOR Bermuda BMU Northern Mariana MNP Latvia LVA British Virgin Islands VGB Islands‡ Luxembourg LUX Brunei Darussalam BRN Oman OMN Netherlands NLD Cayman Islands CYM Palau‡ PLW New Zealand NZL Channel Islands CHI Panama PAN Norway NOR Croatia HRV Puerto Rico‡ PRI Poland POL Curacao CUW Qatar QAT Portugal PRT Cyprus CYP San Marino SMR Slovak Republic SVK Faroe Islands FRO Saudi Arabia SAU Slovenia SVN French Polynesia‡ PYF Seychelles‡ SYC Spain ESP Gibraltar GIB Singapore‡ SGP Sweden SWE Greenland GRL Sint Maarten (Dutch SXM Switzerland CHE Guam‡ GUM part) United Kingdom GBR Hong Kong SAR, HKG St.Kitts and Nevist‡ KNA United States US China St. Martin (French MAF Isle of Man IMN part) Other High-Income Economies Italy ITA Taiwan, China TWN Andorra AND Trinidad and To TTO Antigua and Barbuda‡ ATG Kuwait KWT Liechtenstein LIE bago‡ Argentina ARG Turks and Caicos TCA Aruba‡ ABW Lithuania LTU Macao SAR, China MAC Islands Bahamas, The‡ BHS United Arab Emirates ARE Bahrain‡ BHR Malta MLT Monaco MCO Uruguay URI Virgin Islands (US) VIR * least-developed countries † landlocked developing countries ‡ small island developing countries Source: Data from World Bank, World Development Indicators, 2018 several countries are shown graphically in Figure 2.2. The wide range of numbers shows that a simple grouping of the “more-developed” and “less-developed” worlds by incomes is inadequate for many purposes. Note that a significant number of the countries grouped as “other high-income economies” in Table 2.1 again are sometimes considered devel- oping countries, such as when this is the official position of their governments. Moreover, high-income countries that have one or two highly developed export sectors but in which significant parts of the population remain relatively uned- ucated or in poor health, or social development is viewed as low for the coun- try’s income level, may be viewed as still developing. Examples may include oil exporters such as Saudi Arabia. Upper-income economies also include some tourism-dependent islands with lingering development problems, which now face daunting climate change adaptation challenges, such as some Caribbean countries. A country may be viewed as still developing if it has passed the high-income line but is widely viewed as susceptible to an income decline, such as due to financial and debt instability. An example is Argentina, whose income finally crossed the line from UMC to HIC in 2017, only to experience a sharp downturn in 2018–2019, and find itself on the verge of a financial crisis.4 Even a few of the high-income OECD member countries such as Portugal were classified as developing countries until comparatively recently.5 Nevertheless, low- and middle-income countries are concentrated in sub-Saharan Africa, North Africa and the Middle East, Asia (except Japan and, 40 CHAPTER 2 Comparative Economic Development FIGURE 2.1 Nations of the World, Classified by GNI Per Capita 2.2 What is the Developing World? Classifying Levels of National Economic Development 41 42 CHAPTER 2 Comparative Economic Development FIGURE 2.2 Income Comparisons for Selected Countries, 2017 Congo, Dem. Rep. Ethiopia Haiti Kenya Bangladesh Pakistan Côte d’Ivoire India Country Ghana Egypt, Arab Rep. Indonesia Dominican Republic Brazil Mexico China United Kingdom Canada United States 0 10,000 20,000 30,000 40,000 50,000 60,000 Annual gross national income per capita (2018 US $) Source: World Development Indicators more recently South Korea and perhaps a few other high-income economies), Latin America and the Caribbean, and among “transition” countries of Eastern Europe and Central Asia. Thinking of this as the developing world remains a useful gen- eralisation for some purposes—always taking care not to overgeneralise! In con- trast, the developed world constituting the core of the high-income OECD largely comprises the countries of Western Europe, North America, Japan, Australia, and New Zealand. (A handful of nations including South Korea and Singapore may be regarded as having recently joined the “club” of developed countries.) On the other hand, if income is to be used as an index of economic devel- opment level, for some purposes it can be helpful to designate an additional category of “very high-income” countries, which would represent an income standard providing an approximate guide to economies that have mastered a majority of frontier technologies and skills and are advanced in productivity in Sector A subset (part) of an most sectors. A “very high-income” line of approximately $40,000 per capita economy, with four usages may be considered for this purpose. Although inherently imprecise, the higher in economic development: technology (modern and line would, in many more cases, better proxy for the key non-income dimen- traditional sectors); activity sions of development available at a given point in time.6 Even so, here too there (industry or product sectors); would be several notable exceptions, particularly among economies that are pre- trade (export sector); and dominantly oil- and other resource-based, as people in even some of these very sphere (private and public sectors) high-income countries often lack in important capabilities.7 This is one of the reasons why, ultimately, there is no alternative to relying on other non-income Very high-income country indicators, whether single-dimensional such as years of healthy life, or multidi- An informal category for a per mensional incorporating at least health and education along with wealth. capita income standard indic- ative of economies that master In 2017, the total national income of all the nations of the world was valued at frontier technologies, skills more than US $78 trillion, of which over $50 trillion originated in the high-income and productivity at a point in countries, with the rest originating in low- and middle-income countries. time, such as $40,000 in 2018. High-income countries received nearly two-thirds of world income, despite having only about one-sixth of world population.8 In 2017, by this measure, Norway had more than 262 times the per capita income of Burundi, and more than 41 times that of India. Per capita GNI comparisons of real living standards between high-income  2.2 What is the Developing World? Classifying Levels of National Economic Development 43 and low-income countries like those shown in Figure 2.2 are, however, exaggerated by the use of official foreign-exchange rates to convert national currency values into US dollars. For a clearer picture of comparative living standards, adjustments using Purchasing Power Parity are often used, which we turn to next. 2.2.2 Adjusting for Purchasing Power Parity In accordance with the World Bank’s income-based country classification scheme, GNI per capita, the most common measure of the overall level of economic activity, is often used as a summary index of the relative economic well-being of people in different nations. It is calculated as the total domestic and foreign value added claimed by a country’s residents without making deductions for Value added The portion depreciation (or wearing out) of the domestic capital stock. Gross domestic of a product’s final value that is added at each stage of product (GDP) measures the total value for final use of output produced by an production. economy, by both residents and nonresidents. Thus, GNI comprises GDP plus the difference between the income residents receive from abroad for factor ser- Depreciation (or wearing vices (labour and capital) less payments made to nonresidents who contribute out) The wearing out of equipment, buildings, infra- to the domestic economy. Where there is a large nonresident population playing structure, and other forms of a major role in the domestic economy (such as foreign corporations), these dif- capital, reflected in write-offs ferences can be significant (see Chapter 13). to the value of the capital Per capita GNI comparisons between developed and less-developed coun- stock. tries like those shown in Figure 2.2 do not measure the relative domestic pur- Capital stock The total chasing power of different currencies. To address this problem, researchers have amount of physical goods tried to compare relative GNIs and GDPs by using Purchasing Power Parity existing at a particular time that have been produced for (PPP) instead of exchange rates as conversion factors. PPP is calculated using use in the production of other a common set of international prices for all goods and services. An intuitive goods and services. although imprecise way to think about Purchasing Power Parity is the number of units of a foreign country’s currency required to purchase the quantity of Gross domestic product (GDP) The total final out- goods and services in the local developing country market as $1 would buy put of goods and services in the United States (in locations with an average cost of living). In practice, produced by the country’s adjustments are made for differing relative prices across countries so that living economy, within the country’s standards may be measured more accurately.9 territory, by residents and nonresidents, regardless of its Generally, prices of nontraded services are much lower in developing coun- allocation between domestic tries because wages are so much lower. Clearly, if domestic prices are lower, PPP and foreign claims measures of GNI per capita will be higher than estimates using foreign exchange Purchasing power parity rates as the conversion factor. For example, India’s 2017 GNI per capita was only (PPP) Calculation of GNI about 3.1% of that of the United States using the exchange-rate conversion, but using a common set of inter- was 11.7% when estimated by the PPP method of conversion.10 The amount is national prices for all goods calculated on average prices in the country—for example, typically lower than and services, to provide more accurate comparisons of liv- a high-cost coastal city, but higher than an area where the cost of living is unu- ing standards. sually low for the country. Income gaps between developed and developing nations tend to be less when PPP is used. The most important reason is that real wages are lower in developing countries, which makes the price of (low-skill) services cheaper in real terms. There are other limitations of GNI (including PPP) calculations as measures of economic performance and welfare, including the lack of accounting for environmental losses to the prevalence of nonmonetary transactions, distributional concerns, and other capabilities.11 Table 2.2 provides a comparison of exchange-rate and PPP GNI per capita for 30 countries, ten each from Africa, Asia, and Latin America, plus Canada, the United Kingdom and the United States (along with averages for three income levels). In 44 CHAPTER 2 Comparative Economic Development the first column of Table 2.2, incomes are measured at market or official exchange rates and suggest that income of a person in the United States is 127 times that of a person in the DRC. But this is unbelievable, as many services cost much less in the DRC than in the United States. The PPP rates give a better sense of the amount of goods and services that could be bought evaluated at US prices and suggest that real US incomes are closer to 69 times that of the DRC—still a level of inequality that stretches the imagination. Overall, the average real (PPP) income per capita in high-income countries is more than 22 times that in low-income countries and more than four times higher than in middle-income countries. The simple division of the world into developed and developing countries is sometimes useful for analytical purposes. Many development models apply TABLE 2.2 Comparison of Per Capita GNI in Selected Developing Countries, Canada, the United Kingdom, and the United States, Using Official Exchange-Rate and Purchasing Power Parity Conversions, 2017 GNI Per Capita (US $) Country Exchange Rate Purchising Power Parity Bangladesh 1470 4040 Bolivia 3130 7340 Botswana 6730 16420 Brazil 8600 15200 Cambodia 1230 3750 Canada 42870 46070 Chile 13610 23570 China 8690 16760 Colombia 5890 14090 Congo, Dem. Rep. 460 870 Costa Rica 11120 16200 Côte d’lvoire 1580 3820 Dominican Republic 6630 15290 Egypt, Arab Rep. 3010 11360 Ghana 1880 4280 Guatemala 4060 8000 Haiti 760 1830 India 1800 6980 Indonesia 3540 11900 Kenya 1460 3250 Korea, Rep. 28380 38340 Mexico 8610 17840 Niger 360 990 Nigeria 2100 5700 Pakistan 1580 5830 Peru 5960 12880 Philippines 3660 10050 Senegal 1240 3360 Thailand 5950 17040 Uganda 600 1820 United Kingdom 40530 42560 United States 58270 60200 Vietnam 2160 6450 Low income 775 2127 Middle income 4942 11993 High income 40142 47575 Source: World Bank World Development Indicators  2.2 What is the Developing World? Classifying Levels of National Economic Development 45 across a wide range of developing country income levels. However, we empha- sise again that the wide income ranges among low- and middle-income countries serve as an early warning not to overgeneralise. 2.2.3 Other Common Country Classifications As mentioned in Chapter 1, there are a few other often-used official international designations. The G7 and G20. Two country groupings of geopolitical significance are the group of seven largest developed economies (G7); and an expanded group of 20 (G20) countries that also includes the large middle-income countries. The role and activities of these groups will be discussed in Chapters 12–14.12 Least-developed countries. This is a widely used United Nations (UN) desig- nation that included 47 countries as of the end of 2018; 33 are in Africa, 9 in Asia, 4 in (Pacific) Oceana, plus Haiti. For inclusion, a country has to meet each of three criteria: low income, low human capital (health and educa- tion), and high economic vulnerability. In 2019 just over one billion people lived in these countries. Initially, to be included, GNI per capita had to be less than US $1,026; countries can “graduate” after GNI reaches $1,230. As conditions are improving in most countries—even if slowly and unevenly in many cases—the “least-developed” list is getting shorter. Botswana, Cabo Verde, Equatorial Guinea, Maldives, and Samoa have graduated, and are not included in the list. Angola, Bhutan, Kiribati, São Tomé and Príncipe, Sol- omon Islands, and Vanuatu are in the UN process of official “graduation.” We will refer to this group of countries later in the text.13 Landlocked and small island countries. Two additional special UN classifica- tions are also noteworthy: the landlocked developing countries (LLDCs, of which there are 30, with 15 of them in Africa); and the small island develop- ing states (SIDS, of which there are 38).14 Heavily indebted poor countries (HIPCs). This is another official classification, which from the early 2000s has received special consideration for assistance programmes according to international agreements. As of 2019 there are 39 HIPC countries.15 (The problems of debt and development are addressed in detail in Chapter 13.) Newly industrialising countries (NICs). This is an informal term that was used to refer to economies at an early stage of export-led manufacture growth. For example, the NIC label was widely applied to South Korea and Taiwan, and subsequently to Thailand and Indonesia, from the 1970s to 1980s. The term may be applied today to a country such as Vietnam. We do not use NIC as a systematic term in this text, although it is used in the press. Emerging market. This is a more informal and less stably defined country label widely used in the financial press. The term was originally coined at the Inter- national Finance Corporation (IFC), the private sector arm of the World Bank Group; but it remains an unofficial designation. The IFC introduced the term to bring to mind a sense of progress, to avoid the then-standard term “Third World” that investors, at least in the view of the IFC, seemed to associate with stagnation. Investors sometimes use the term “frontier markets” to refer to countries they consider at a lower (riskier) level than emerging markets. In 46 CHAPTER 2 Comparative Economic Development this text we rarely use these terms for three reasons. First, an emerging mar- ket is widely used in the financial press to suggest the presence of active stock and bond markets; although financial deepening is important and helpful under the right conditions, it is only one aspect of economic development. Second, referring to nations as markets may lead to an under-emphasis on critical nonmarket priorities in development including education, health, and nutrition. Third, usage varies, and there is no established or generally accepted designation of which markets should be labelled as emerging, and which remaining on the “frontier,” yet to emerge. Different rating agencies and investment groups classify countries differently; and countries may be moved depending upon year-to-year financial news. For example, in 2018 Argentina was demoted by some banks from emerging to frontier status in the wake of financial turbulence (see the case study at the end of Chapter 3). Human development level. The United Nations Development Programme (UNDP) classifies countries according to their level of human development, including health and education attainments, as low, medium, high, and very high. We examine the UNDP Human Development Indexes in detail in the next section. 2.3 Comparing Countries by Health and Education, and the Human Development Index To measure the average level of economic development, it is necessary to go beyond average incomes to evaluate a nation’s average health and educational attainments, which reflect core capabilities. 2.3.1 Comparing Health and Education Levels Table 2.3 shows three basic indicators of average health—life expectancy at birth, the under-5 mortality rate, and the prevalence of undernourishment; and two indicators of average education—the gross enrolment ratio for secondary school, and the per cent of the population with at least some secondary education. (Each country’s region and income grouping can be found in Table 2.1.) Life expec- tancy is the average number of years that newborn children would live if sub- jected to the mortality risks prevailing for their cohort at the time of their birth. Undernourishment means consuming too little food to maintain normal levels of activity; it is what is often called the problem of hunger. Gross enrolment in sec- ondary school can be greater than 100%, because it includes students who have taken longer to graduate or returned to school later. Table 2.3 also presents the health indicators for the low-, lower-middle-, upper-middle-, and high-income country groups. Table 2.3 shows averages from 33 illustrative countries across regions.16 In addition to big differences across the major income classifications, low-income countries and middle income countries are very diverse groups with greatly differing development challenges. 2.3.2 Introducing the Human Development Index The most widely used measure of the comparative status of socioeconomic development is presented by the United Nations Development Programme (UNDP) in its annual series of Human Development Reports. The centrepiece  2.3 Comparing Countries by Health and Education, and the Human Development Index 47 TABLE 2.3 Commonality and Diversity: Some Basic Indicators of Health and Education Gross Enrolment Population Mortality Ratio: Secondary with at least Life expectancy rate, under-5 Prevalence of (% of secondary some secondary at birth total (per 1,000 live undernourishment school-age education (% age (years) births) (% of population) population) 25 and other) Country 2017 2018 2016 2012–2017 2006–2017 Bangladesh 72 30.2 15.2 69 45.5 Bolivia 71 26.8 17.3 86 58.2 Botswana 69 36.5 26.4 - 89.2 Brazil 75 14.4 2.5 100 60 Cambodia 69 28 17.2 - 21.3 Canada 82 5 2.5 113 100 Chile 80 7.2 2.9 100 80.6 China 76 8.6 8.7 95 77.4 Colombia 77 14.2 5.6 98 50.2 Congo, Dem. Rep. 60 88.1 - 46 50.7 Costa Rica 80 8.8 4.7 126 52.9 Côte d’Ivoire 57 80.9 19.6 46 26.1 Dominican Republic 74 28.8 9.9 77 56.6 Egypt, Arab Rep. 72 21.2 4.4 86 64.5 Ghana 63 47.9 5.9 60 62.1 Guatemala 74 26.2 15 64 37.8 Haiti 63 64.8 49 - 33.2 India 69 36.6 14.9 75 51.6 Indonesia 71 25 8.6 86 48.8 Kenya 66 41.1 27.4 - 34.6 Korea, Rep. 83 3.2 2.5 100 95.6 Mexico 75 12.7 3.7 97 59.3 Niger 62 83.7 14.1 24 6.6 Nigeria 54 119.9 11.5 56 - Pakistan 67 69.3 20.6 46 37.3 Peru 76 14.3 9.7 98 62.2 Philippines 71 28.4 13.5 88 73.2 Senegal 67 43.6 12 48 17.1 Thailand 77 9.1 7.8 121 44.8 Uganda 63 46.4 39.7 - 31.7 United Kingdom 81 4.3 2.5 125 82.9 United States 79 6.5 2.5 97 95.3 Vietnam 75 20.7 9.4 - 69.4 Low income 63 68.1 68.1 Lower middle 68 49.1 49.1 income Upper middle 76 12.6 12.6 income High income 81 5 5 Source for health indicators: WDI. Source for education indicators: UNDP. of these reports, which were initiated in 1990, is the construction and refinement of its informative Human Development Index (HDI). This section examines the Human Development Index New HDI, initiated in 2010. (The well-known and still sometimes informally (HDI) An index measuring national socioeconomic devel- used traditional HDI—the UNDP centrepiece from 1990–2009—is examined in opment, based on combining detail in Appendix 2.1.) Box 2.1 summarises “Differences Between the Current measures of education, health, Human Development Index and the Traditional HDI” comparing its properties and adjusted real income per to those of its predecessor. The current HDI formulation ranks each country on capita. 48 CHAPTER 2 Comparative Economic Development a scale of 0 (lowest human development) to 1 (highest human development) based on three goals or end products of development: a long and healthy life as measured by life expectancy at birth; knowledge as measured by a combination of average schooling attained by adults and expected years of schooling for school-age children; and a decent standard of living as measured by real per capita gross domestic income adjusted for the differing Purchasing Power Par- ity of each country’s currency to reflect cost of living and for the assumption of Diminishing marginal diminishing marginal utility of income. utility The concept that the There are two steps in calculating the New HDI: first, creating the three subjective value of additional consumption (income) lessens “dimension indices”; and second, aggregating the resulting indices to produce as total consumption becomes the overall New Human Development Index (NHDI). We will go through the higher. steps, illustrating them with 2014 data for Costa Rica. After defining the relevant minimum and maximum values (or lower and upper “goalposts”), each dimension index is calculated as a ratio that basically is given by the per cent of the distance above the minimum to the maximum levels that a country has attained. Actual Value - Minimum Value Dimension Index = (2.1) Maximum Value - Minimum Value The health (or “long and healthy life”) dimension of the New HDI is calculated with a life-expectancy-at-birth index. We illustrate with the case of Costa Rica in 2014. The “goalposts” for life expectancy took a minimum value of 20 years and a maximum value of 85 years. No country has had a life expectancy of less than 20, at least since before the 20th century; a life expectancy of 85 is close to the highest of any country at present (for example, life expectancy in Japan is 84). This resulting index for the health (life expectancy) dimension, for the case of Costa Rica was: Life Expectancy Index = (79.93 - 20)/(85 - 20) = 0.922 (2.2) The education (“knowledge”) component of the HDI is calculated with a combi- nation of the average years of schooling for adults and expected years of school- ing for a school-age child now entering school. As explained by the UNDP, the education indicators are normalised using a minimum value of 0, because societies “can subsist without formal education.” The maximum value was set to 15 years for average schooling because this was viewed as attainable by some countries in the medium term. For Costa Rica in the 2014 index, the average years of schooling among adults was 8.37 years; so the mean years of schooling sub-index was calculated as: (8.37 - 0)/(15 - 0) = 0.558 (2.3) We can think of this as indicating that Costa Rica was about 56% of the way to a global long-term goal for average education. In considering expected future education for any country, the highest value (cap, or “goalpost”) is given as 18 years (which we may think of as approxi- mately corresponding to attaining a master’s degree in most countries). For Costa Rica, the expected number of years of schooling for a child entering school was estimated at 13.5 years. The expected years of schooling sub-index was then calculated as: (13.5 - 0)/(18.0 - 0) = 0.750 (2.4)  2.3 Comparing Countries by Health and Education, and the Human Development Index 49 The education index was then calculated as a simple arithmetic of the two sub-indexes.17 In the Costa Rica example, the combined education index was given by: [0.558 + 0.750]/2 = 0.654 (2.5) The standard of living (income) component is calculated using purchasing power-adjusted per-capita GNI. The natural log of income is used to represent the idea of diminishing marginal utility of income; indeed the UNDP currently assumes an upper goalpost of $75,000 per capita, based on their interpretation of the evidence that “there is virtually no gain in human development and well-being from annual income beyond $75,000.”18 For Costa Rica, the income index therefore is (where ln stands for the nat- ural log): ln(13,011.7) - ln(100)]/[ln(75,000) - ln(100)] = 0.735 (2.6) The UNDP then uses a geometric mean to construct the overall index, rather than an arithmetic mean (as had been done before 2010). The use of a geometric mean in computing the New HDI is very important. When using an arithmetic mean (adding up the component indexes and dividing by 3) in the HDI, the effect is to assume perfect substitutability across income, health, and education. For exam- ple, a higher value of the education index could compensate, one for one, for a lower value of the health index. In contrast, use of a geometric mean ensures that poor performance in any dimension directly affects the overall index.19 As the UNDP puts it, the new calculation “captures how well rounded a country’s performance is across the three dimensions.” Moreover, the UNDP argues “that it is hard to compare these different dimensions of well-being and that we should not let changes in any of them go unnoticed.” Thus by allowing for imperfect substitutability, the UNDP proposes that a geometric mean is the preferred way to construct the index.20 So, in the New HDI, instead of adding up the health, education, and income indexes and dividing by three, the HDI is calculated with the geometric mean, which is applied in the Costa Rica case as follows: HDI = H1/3E1/3I1/3 = 3 2(0.922*0.654*0.735) = 0.763 (2.7) where H stands for the health index; E stands for the education index; and I stands for the income index. This is equivalent to taking the cube root of the product of these three indexes. Table 2.4 shows the 2016 values of the HDI for a set of 31 countries. Using these indicators and applying the formula to data for all 187 countries for which data are available, in 2018 the HDI classified countries in four groups: low human development (0.0 to 0.549), medium human development (0.550 to 0.699), high human development (0.700 to 0.799), and very high human devel- opment (0.80 to 1.0). 2.3.3 Human Development Index Ranking: How Does it Differ from Income Rankings? One reason for the importance of the HDI is that income predicts rather weakly how countries will perform on education and health, and on the HDI in par- ticular. For example, countries such as Botswana, China, Egypt, Chad, Turkey, 50 CHAPTER 2 Comparative Economic Development TABLE 2.4 2018 Human Development Index and its Components for Selected Countries Expected GNI Per Life Mean Years of Capita Rank HDI Expectancy Years of Schooling GNI per Minus HDI Country Rank at Birth Schooling (of children) Capita HDI Value Rank Canada 12 82.5 13.3 16.4 43,433 0.926 10 United States 13 79.5 13.4 16.5 54,941 0.924 -2 United Kingdom 14 81.7 12.9 17.4 39,116 0.922 13 South Korea 22 82.4 12.1 16.5 35,945 0.903 8 United Arab 34 77.4 10.8 13.6 67,805 0.863 - 27 Emirates Chile 44 79.7 10.3 16.4 21,910 0.843 13 Russian 49 71.2 12.0 15.5 24,233 0.816 3 Federation Costa Rica 63 80.0 8.8 15.4 14,636 0.794 15 Turkey 64 76.0 8.0 15.2 24,804 0.791 - 14 Cuba 73 79.9 11.8 14.0 7,524 0.777 43 Mexico 74 77.3 8.6 14.1 16,944 0.774 -6 Sri Lanka 76 75.5 10.9 13.9 11,326 0.770 19 Brazil 79 75.7 7.8 15.4 13,755 0.759 2 China 86 76.4 7.8 13.8 15,270 0.752 -9 Botswana 101 67.6 9.3 12.6 15,534 0.717 - 26 Gabon 110 66.5 8.2 12.8 16,431 0.702 - 40 South Africa 113 63.4 10.1 13.3 11,923 0.699 - 23 Egypt 115 71.7 7.2 13.1 10,355 0.696 - 15 Guatemala 127 73.7 6.5 10.8 7,278 0.650 -8 India 130 68.8 6.4 12.3 6,353 0.640 -5 Bangladesh 136 72.8 5.8 11.4 3,677 0.608 9 Ghana 140 63.0 7.1 11.6 4,096 0.592 3 Equitorial Guinea 141 57.9 5.5 9.3 19,513 0.591 - 80 Kenya 142 67.3 6.5 12.1 2,961 0.590 16 Pakistan 150 66.6 5.2 8.6 5,311 0.562 - 14 Papua New 153 65.7 4.6 10.0 3,403 0.544 -3 Guinea Madagascar 161 66.3 6.1 10.6 1,358 0.519 20 Côte d’lvoire 170 54.1 5.2 9.0 3,481 0.492 - 22 Burkina Faso 183 60.8 1.5 8.5 1,650 0.423 -7 Chad 186 53.2 2.3 8.0 1,750 0.404 - 15 Niger 189 60.4 2.0 5.4 906 0.354 -2 Source: United Nations Development Program Guatemala, South Africa, Gabon, Côte d’Ivoire, Equatorial Guinea, Pakistan, and the United Arab Emirates perform more poorly on the HDI than would be predicted from their income level, while the reverse is true of Chile, Bangladesh, Cuba, Sri Lanka, Kenya, and Madagascar. Finally, Brazil, Ghana, Papua New Guinea, and Niger are among those that currently perform on the HDI just about as predicted by their income levels. For example, Cuba and Guyana are very close in real income per person, but Cuba ranks 73rd on the New HDI (43 points above where predicted by its income level) and Guyana ranks 125th (8 below where predicted by income). Per capita income is 44% higher in Pakistan than Bangladesh, but Bangladesh ranks 136th, nine places higher than predicted by income, while Pakistan ranks 150th, 14 places below; see the case study at the end of Chapter 1 for a detailed examination of diverging development in these two countries. Some additional comparative exam- ples are provided in Table 2.5.  2.3 Comparing Countries by Health and Education, and the Human Development Index 51 TABLE 2.5 HDI for Countries with Similar Income Levels Gross National GNI per Life Expected income capita rank HDI value expectancy years of Average years (GNI) per minus HDI (2015) at birth schooling of schooling capita rank Country GDP Per Capita Near PPP $1000 158-Madagascar 0.512 65.5 10.3 6.1 1,320 25 166-Togo 0.487 60.2 12.0 4.7 1,262 18 170-Malawi 0.476 63.9 10.8 4.4 1,073 16 183-Guinea 0.414 59.2 8.8 2.6 1,058 4 187-Niger 0.353 61.9 5.4 1.7 889 1 Country GDP Per Capita Near PPP $3500 139-Bangladesh 0.579 72.0 10.2 5.2 3,341 8 139-Zambia 0.579 60.8 12.5 6.9 3,464 7 157-Mauritania 0.513 63.2 8.5 4.3 3,527 - 12 160-Lesotho 0.497 50.1 10.7 6.1 3,319 - 12 165-Sudan 0.490 63.7 7.2 3.5 3,846 - 22 Country GDP Per Capita Near PPP $7500 68-Cuba 0.775 79.6 13.9 11.8 7,455 48 84-Urkaine 0.743 71.1 15.3 11.3 8,189 28 103-Belize 0.706 70.1 12.8 10.5 7,375 14 117-El Salvador 0.680 73.3 13.2 6.5 7,732 -3 148-Eswatini 0.541 48.9 11.4 6.8 7,522 -33 (Swaziland) Country GDP Per Capita Near PPP $10,000 73-Sri Lanka 0.766 75.0 14.0 10.9 10,789 21 86-Jorda 0.741 74.2 13.1 10.1 10,111 15 111-Egypt 0.691 71.3 13.1 7.1 10,064 -7 113-Indonesia 0.689 69.1 12.9 7.9 10,053 -8 125-Namibia 0.640 65.1 11.7 6.7 9,770 - 18 Country GDP Per Capita Near PPP $20,000 54-Uruguay 0.795 77.4 15.5 8.6 19,148 8 60-Panama 0.788 77.8 13.0 9.9 19,470 0 109-Gabon 0.697 64.9 12.6 8.1 19,044 - 46 135-Equatorial 0.592 57.9 9.2 5.5 21,517 - 79 Guinea Data Source: 2016 Human Development Report 2016, Table 1, Pages 198-201 (New York: United Nations Development Program), 2015 data. 2.3.4 Human Development Index: Alternative Formulations While the differences across countries remain stark, it is also important to keep in mind how much progress has been made. Most developing countries expe- rienced dramatic improvements in human development in the quarter century since the HDI was introduced, reflected in increases in HDI levels. Figure 2.3 shows this progress, presenting the average trends in HDI by region. The UNDP now also offers the Inequality-Adjusted Human Development Index (IHDI), which imposes a penalty on the HDI that increases as inequality 52 CHAPTER 2 Comparative Economic Development FIGURE 2.3 Improvements in Human Development Since 1990, by Region Human development classification (Human Development Index value) Very high (0.800 or greater) High (0.700– 0.799) Medium (0.550– 0.699) Low (less than 0.550) 1990 1995 2000 2005 2010 2015 Europe & Central Asia East Asia & the Pacific Latin America & the South Asia Caribbean Sub-Saharan Africa Arab States Source: Human Development Report Office, UNDP – Human Development Report, 2016, p. 27 across people becomes greater, and the Gender Inequality Index (GII). The UNDP also features an important and highly influential innovation, the Mul- tidimensional Poverty Index (MPI), which is examined in detail in Chapter 5. Clearly, the HDI has made a major contribution to improving our under- standing of what constitutes development, which countries are succeeding (as reflected by rises in their NHDI over time), and how different groups and regions within countries are faring. By combining social and economic data, the NHDI allows nations to take a broader measure of their development performance, both relatively and absolutely. In these ways, it focuses attention on the vital importance of improvements in health and education, rather than a potentially excessive focus on income alone. There are some significant criticisms of the NDHI. For example, broadly, by adding some non-income indicators, but omitting others, it could lead to attention shifting from areas such as legal rights to education and health, or income. Thus some areas could receive even less attention than they would have otherwise. A specific criticism that has been raised is that expected educational attainment is difficult to forecast, particularly in low- and lower-middle-income countries, and could lead to an overly optimistic view, resulting in too little attention to education quality improvements. However, the fact remains that the HDI, when used in conjunction with other economic measures of development,  2.3 Comparing Countries by Health and Education, and the Human Development Index 53 BOX 2.1 Development Policy: Differences Between the Current Human Development Index and the Traditional HDI I n 2010, the UNDP introduced its (New) Human Development Index (NHDI), which had notable changes from its traditional HDI; the new version has ambiguous: it is a UN forecast subject to uncer- tainty, not an achievement (in the framework of the capabilities approach). clear strengths, but also a few potential drawbacks: 4. The two previous components of the education 1. Possibly the most consequential change is that index, literacy and enrolment, were correspond- the NHDI is computed with a geometric mean ingly dropped. In contrast to expected attain- rather than a simple arithmetic mean, as exam- ment, literacy is clearly an achievement, and ined previously in the text. even enrolment is at least a modest achievement. 2. GNI per capita replaces GDP per capita. This is However, literacy has always been badly and too an unambiguous improvement: GNI reflects infrequently measured and is inevitably defined what citizens can do with income they receive, more modestly in a less-developed country. And whereas that is not true of value added in goods enrolment is no guarantee that a grade will be and services produced in a country, which may completed or for that matter that anything is go to someone outside it; while income earned learned or that students (or teachers) even attend. abroad benefits some of the nation’s citizens. As 5. The upper goalposts (maximum values) in each trade and remittance flows have expanded rap- dimension were increased to the observed max- idly, this distinction has become increasingly imum rather than given a predefined cutoff. In important. some ways, this returned the index to its origi- 3. The education index was completely revamped. nal design, which was criticised for inadequately Two new components were used: average actual recognising small gains by countries starting at educational attainment of the whole popu- very low levels. But since 2014, the index has lation, and expected attainment of today’s returned to the use of fixed upper goalposts. children. Each has implications. Use of actual attainment—average years of schooling—as an 6. The “lower goalpost” (maximum value) for indicator is unambiguously an improvement. income has been reduced. This was based Although it is only a rough guide to what is on updated estimates for the historic low for actually learned—on average, a year of school- recorded income for any country.a ing in Mali provides students with much less 7. A minor difference is that rather than using the than a year of schooling in Norway—credible common logarithm (log) to reflect diminish- and comparable data on quality across coun- ing marginal benefit of income, the NHDI now tries are not available. Expected educational uses the natural log (ln). This reflects a more attainment, the other new component, is more usual construction of economic indices. a It is possible that low income is supplemented by tapping into savings (broadly defined), which would reflect the unsustainable nature of such a low income. greatly increases our understanding of which countries are experiencing devel- opment and which are not. And by modifying a country’s overall HDI to reflect income distribution, gender, regional, and ethnic differentials, as presented in recent Human Development Reports, we are now able to identify not only whether a country is developing but also whether various significant groups within that country are participating in that development.21 54 CHAPTER 2 Comparative Economic Development 2.4 Key Similarities and Differences Among Developing Countries Ten features help to define key similarities and differences among developing countries, and the mix and severity of the economic development challenges facing any one country. For each feature, we also discover that behind the aver- ages are very substantial differences that are essential to appreciate and take into account in development policy. These ten features of similarities and differences are: 1. Levels of income and productivity 2. Human capital attainments 3. Inequality and absolute poverty 4. Population growth and age structure 5. Rural population and rural-to-urban migration 6. Social fractionalisation 7. Level of industrialisation and manufactured exports 8. Geography and natural resource endowments 9. Extent of financial and other markets 10. Quality of institutions and external dependence Clearly, the scope of comparative economic development goes far beyond income differences; this is to be expected, given the discussion of the meaning of development in Chapter 1. All of these features play a role in setting the devel- opment constraints and policy priorities of a developing nation. We address each in turn. 2.4.1 Levels of Income and Productivity As we noted at the outset of the chapter, there is a vast gulf in productivity between advanced economies such as the United States and the developing nations, but also a very wide range among middle- and low-income developing countries, such as India and the DRC. (Economic development in India is considered in detail in the end-of-chapter case study for Chapter 5.) The lower average levels but wide ranges of income in developing areas are seen in Table 2.2 (earlier in this chapter). Although resulting from a number of deeper causes, the wide disparity in income across countries largely corresponds to the large gaps in output per worker between developing and developed countries.22 At very low income levels, a vicious circle may set in whereby low income leads to low investment in education and health as well as plant and equipment and infrastructure, which in turn leads to low productivity and economic stagnation. (This type of inferior equilibrium, sometimes referred to as a poverty trap, is discussed in Chapter 4.) However, it is important to stress that there are ways to escape from low income—which much of the world is doing—as you will see throughout this text. Further, the low-income, least-developed countries are themselves a very diverse group with differing development challenges.  2.4 Key Similarities and Differences Among Developing Countries 55 Some star performers among now high-income economies, such as South Korea and Taiwan, were a few decades ago among the poorest countries in the world. Some middle-income countries are relatively stagnant, but others are grow- ing rapidly—China most spectacularly, and India more recently (as considered in detail in the case studies at the end of Chapters 4 and 5, respectively). Indeed, income growth rates have varied greatly in different developing regions and coun- tries, with rapid growth in East Asia, slow or in some cases even no growth in sub-Saharan Africa, and intermediate levels of growth in other regions. Problems of igniting and then sustaining economic growth are examined in Chapters 3 and 4. One common misperception is that low incomes result from a country being too small to be self-sufficient (or, in what was previously a more common misperception, too large to overcome economic inertia). However, as seen in Table 2.6 there is no necessary correlation between country size in population or area and economic development (although each may have different advantages and disadvantages that can offset each other).23 The 12 most populous countries include representatives of all four cate- gories: low-, lower-middle-, upper-middle-, and high-income countries (see Table 2.6). The 12 least-populous on the list include primarily lower-middle- and upper-middle-income countries, if high-income microstates are excluded.24 2.4.2 Human Capital Attainments Human capital—including health, education, and skills—is vital to economic growth, as well as a key aspect of human development. There has been dramatic progress in health and education in most developing countries over the past quar- ter century. Despite this, there remain great disparities in human capital around the world, as we saw when considering the components of the Human Development Index. Compared with developed countries, many developing nations, particu- larly the least-developed countries, have lagged in their average levels of nutrition, health (as measured, for example, by life expectancy or undernourishment), and education (measured by literacy). By these measures, the upper-middle-income countries are significantly closer to the upper-income countries than to the TABLE 2.6 The 12 Most- and Least-Populated Countries and Their Per Capita Income, 2017 Population GNI Per Population GNI Per Most Populous (millions) Capita (US $) Least Populous (thousands) Capita (US $) 1. China 1386 8690 1. Tuvalu 11 4970 2. India 1339 1800 2. Nauru 14 10220 3. United States 326 58270 3. Palau 22 12700 4. Indonesia 264 3540 4. Marshall Islands 53 4840 5. Brazil 209 8600 5. St. Kitts and Nevis 55 16240 6. Pakistan 197 1580 6. Dominica 74 6590 7. Nigeria 191 2100 7. Seychelles 96 14170 8. Bangladesh 165 1470 8. Antigua and Barbuda 102 13810 9. Russian Federation 144 9230 9. Micronesia 106 3620 10. Mexico 129 8610 10. Grenada 108 9180 11. Japan 127 38550 11. Tonga 108 4010 12. Ethiopia 105 740 12. St. Vincent and the 110 7390 Grenadines Source: World Bank World Development Indicators 56 CHAPTER 2 Comparative Economic Development FIGURE 2.4 Under-5 Mortality Rates, 1990 and 2017 200 1990 160 2017 Deaths per 1,000 live births 120 80 40 0 Low Lower-middle Upper-middle High income income income income Source: World Development Indicators lower-income countries. The under-5 mortality rate is about 15 times higher in low-income countries than in high-income countries; but enormous gains have been made across the income spectrum since 1990, as shown in Figure 2.4. Table 2.7 shows primary school enrolment rates (percentage of students of primary age enrolled in school) and the primary pupil-to-teacher ratios for the four country income groups. Enrolments have strongly improved in recent years, especially for primary school. However, student attendance and com- pletion, along with attainment of basic skills such as functional literacy, remain problems. The problem is moving from getting children into school to providing a quality education once they arrive. The pupil-to-teacher ratio is often used as an indicator of school quality, suggesting that the regions of South Asia and sub-Saharan Africa, and the low-income countries broadly, have a considerable distance to go. Indeed, teacher absenteeism from the classroom—ranging from taking long breaks while children are alone in the classroom to “teacher truancy” in which teachers simply stay away from the school—remains a serious problem in South Asia and sub-Saharan Africa (see Chapter 8). TABLE 2.7 Primary School Enrolment and Pupil–Teacher Ratios, 2017 Net Primary School Primary Region or Group Enrolment (%) Pupil–Teacher Ratio Income Group Low 79 39 Lower middle 88 29 Upper middle 95 19 High 97 14 Region East Asia & Pacific 96 17 Europe & Central Asia 96 15 Latin America & Caribbean 93 21 Middle East & North Africa 93 21 South Asia 90 35 Sub-Saharan Africa 78 38 Source: World Development Indicators  2.4 Key Similarities and Differences Among Developing Countries 57 Upper-middle-income countries—and in some cases lower-middle-income countries, are much closer to the high-income, developed countries in health and education standards than they are to the lowest-income, least-developed coun- tries. Although health conditions in East Asia are generally good, sub-Saharan Africa continues to be plagued by problems of malnourishment, malaria, tuber- culosis, AIDS, and the neglected tropical diseases (see Chapter 8). Despite sub- stantial progress, South Asia continues to have relatively high levels of illiteracy, low schooling attainment, and undernourishment. 2.4.3 Inequality and Absolute Poverty Poverty and inequality are two of the subjects of Chapter 5. Very high levels of inequality—extremes in the relative incomes of higher- and lower-income citizens—are also found in many low-income and particularly middle-income countries, partly because Latin American countries historically tend to be both middle-income and highly unequal. Several African countries, including Sierra Leone, Lesotho, and South Africa, and Equatorial Guinea, also have among the highest levels of inequality in the world. Inequality is particularly high in many resource-rich developing countries, notably in the Middle East and sub-Saharan Africa. Indeed, in many of these cases, inequality is substantially higher than in most developed countries (where inequality has in many cases been rising in recent decades). Inequality varies greatly among developing countries, with generally much lower, though typically rising, inequality in Asia. Corresponding to their low average-income levels, a large majority of the extreme poor live in the low-income countries of sub-Saharan Africa and the lower-middle-income countries of South Asia. Extreme poverty is due in part to low human capital but also to social and political exclusion and other dep- rivations. Great progress has already been made in reducing the fraction of the developing world’s population living on less than $1.90 per day and raising the incomes of those still below that level, far more so than had been predicted prior to this century. However, with a billion people still extremely deprived, much remains to be done, as we examine in detail in Chapter 5. Development economists use the concept of absolute poverty to represent Absolute poverty The a specific minimum level of income needed to satisfy the basic physical needs situation of being unable or only barely able to meet the of food, clothing, and shelter in order to ensure continued survival. A problem, subsistence essentials of food, however, arises when one recognises that these minimum subsistence levels will clothing, shelter, and basic vary from country to country and region to region, reflecting different physio- health care. logical as well as social and economic requirements. Economists have therefore tended to make conservative estimates of world poverty in order to avoid unin- tended exaggeration of the problem. The number living on less than $1.90 per day fell from about 1.9 billion (about 42%) in 1981 to about 750 million (about 10%) by 2017, despite the increase in the world’s population of 3 billion people during that period. However, about 46% of the world’s population still lived on less than $5.50 per day.25 Extreme poverty represents great human misery, and so redressing it is a top priority of international development. Development economists have also increasingly focused on ways in which poverty and inequality can lead to slower growth. That is, not only do absolute poverty and extreme inequality result from distorted growth, but they can also cause it. This relationship, along with measurements of inequality and poverty 58 CHAPTER 2 Comparative Economic Development and strategies to address these problems, is examined in depth in Chapter 5. The “last mile” in ending poverty will be difficult, as those still trapped are often liv- ing in particularly difficult conditions such as ongoing conflict. Because of their central importance in development, poverty reduction strategies are considered throughout the text. 2.4.4 Population Growth and Age Structure Population and development is the subject of Chapter 6. Global population has skyrocketed since the beginning of the industrial era, from just under 1 billion in 1800 to 1.65 billion in 1900 and to over 6 billion by 2000. World population topped 7.6 billion by 2018. In 2018, the global rate of population growth was about 1.1%. Rapid population growth began in Europe and other developed countries. But in recent decades, most population growth has been centered in low-income and, to some extent, middle-income, countries. Compared with Crude birth rate The number developed countries, which often have crude birth rates near or even below of children born alive each replacement (zero population growth) levels, low-income developing countries year per 1,000 population (often shortened to birth rate). typically still have high crude birth rates. Population growth rates are determined by the difference between the birth rate and the death rate (net of migration). Population dynamics varies widely among regions. Populations of some developing countries, particularly in Africa, continue to grow rapidly. From 2000 through to 2017, population in sub-Saharan Africa grew at 2.7% per year, the same growth rate as for lo