Why is GNI per capita rather than GDP per capita used as international measure of the state of development?

Denmark

In 2010, Denmark’s population was 5.5 million; in 2011 the GNI per capita was US$33,518 (PPP). The 2011 infant mortality rate was 3 per 1000 live births, life expectancy at birth was 79.0 years, and the HDI was 0.01, ranking 15th highest of 177 countries. The crude birth rate was 11 in 2005, with 100 percent of births occurring in medical facilities. The maternal mortality rate was 12 per 100,000 (2010); in 2000 it was 8.0. Immunization coverage in infancy in 2011 was 91 percent for polio and DTP, and declined from 99 percent in 2000 to 87 percent in 2011 for measles.

In 1803, the predecessor of the National Board of Health was established; from 1858 local boards of health began to be set up. There is a long history of decentralized health services, which have been the responsibility of local towns and municipalities since the early years of the eighteenth century.

Reforms focus on ensuring continuity of care across administrative sectors, with easy access to unified prevention, primary care, and rehabilitation services. The focus is on improved service for multiproblem situations, the disadvantaged, the chronically ill, and at-risk children. Denmark has not built any institutional accommodation since 1987 but has developed subsidized housing and extensive home care services for older people. The percentage of GDP spent on health increased from 8.1 percent in 1980 to 11.1 percent in 2010. Between 1990 and 2010, acute care beds declined from 4.1 to 2.9 per 1000 population.

9.2.1 Developing Countries

The division between developed and developing countries is a helpful simplification that can be done in different arbitrary ways. In this chapter we follow the World Bank's main criterion based on gross national income (GNI) per capita: Developing countries are those with per capita GNI below a certain nominal threshold (US$ 12,276 in 2011). These nations are usually classified into six geographical regions: East Asia and Pacific (EAP), Eastern Europe and Central Asia (ECA), Latin America and the Caribbean (LAC), Middle East and North Africa (MENA), South Asia (SA), and sub-Saharan Africa (SSA). The Appendix includes a list of all the developing countries in each region with their populations.3 The developing countries cover almost 75% of the total land area in the world and represent 85% of the total population. Table 9.1 summarizes some basic demographic and economic statistics.

Table 9.1. Population, GNI per capita and Human Development Index, 2010

Developing countries, by region

Source: Population is taken from the United Nations Demographic Yearbook. Gross National Income (GNI) per capita in international dollars adjusted for purchasing power parity (PPP), and in current US$ (Atlas method) are taken from World Development Indicators. The Human Development Index (HDI) is from the UNDP Human Development Report. GNI and HDI are unweighted averages across countries.

According to these indicators Eastern Europe and Central Asia is the most developed region in the group: per capita GNI is almost twice the mean for the developing world, and the Human Development Index (HDI) is significantly higher. Latin American and the Caribbean ranks second, and Middle East and North Africa third. Although economic growth in Asia has been remarkable in the last decades, per capita GNI and other development indicators are on average still below the mean of the developing world. South Asia is significantly less developed than East Asia and the Pacific. Sub-Saharan Africa is the poorest and least developed region of the world. The mean of the national per capita GNIs in that region is less than 50% of the developing world mean and less than 10% of the mean of the industrialized economies.

Abstract

This chapter will introduce the main geosocial differences found from the perspective of the user in the analysis of public transport service quality in a variety of territorial contexts according to the 2014 World Bank classification of the Gross National Income per capita of each nation. The differences relate to the date these studies started, the actors involved in such analyses (researchers, operators, and/or transport administrators), and the methodological approach used to obtain and process the information about user perception of service quality. Different survey and data collection techniques are explained along with the methodology used to extract the information from the survey. In some cases, these methodologies can be quite sophisticated using complex mathematical models and data mining algorithms, which are often combined in the same analysis to extract more precise information from the data. Finally, the variables the users considered to be the most important are identified for the different public transport industries, operating fields, and territorial contexts.

User Guide

The default view provided to the Data Portal visitors is of an interactive map displaying the most recent population numbers among more than 50 African countries. Users can select other views: GDP in current US dollars, GNI per capita, inflation rate, and current account balance as a percentage of GDP by scrolling down the drop-down menu on the map. However, for a deeper dive into the data, users can select from several options on the left of the page. These include a Dashboard view, which allows users to view customizable quick statistics on agricultural, financial, social, and energy topics, filtered by country and year. Users can download the individual dashboards in Excel format.

The Data Portal also provides three more specific data tools, including Data Analysis, Data Query, and Data by Topic. The Data Analysis tool allows users to create tables according to year, country or region, and indicators. Users can then filter this data using statistical measures of totals calculations, 80/20 analysis, and recalculating totals as percentages at the top right of the table. The data results can be downloaded in Excel. The Data Query tool is a more traditional search tool where users can search for specific data points by indicator, region or country, and year. The results data can be exported in TXT, CSV, XLS, MDB, or DBF format by selecting “Bulk Export” at the bottom of the page. The Data by Topic tool allows users to view data by topics including Millennium Development Goals, gender indicators, education, health, environmental, business, macroeconomic, and financial indicators. These topics can be viewed as an aggregate for all of Africa, or by a specific country or region. The results can be downloaded in Excel format.

6.6 Income (Gross National Income per Capita)

There were 46 high-income countries, with three, Germany, Japan, and the United States, among the 19 most populous countries.s All but 3 of the high-income countries scored 60 or above in human capital, with 23 scoring 70 or above. The 3 who scored below 60 were Barbados, Kuwait, and Saudi Arabia.

The situation was quite different for the 31 countries in the upper-middle income category as only 1 country: the Russian Federation, scored above 70 in human capital. The Russian Federation was among the 19 most populous countries. The rest of the countries in this category were fairly evenly split between earning scores of 60 to less than 70 and 50 to less than 60, with 17 in the first and 14 in the second range.

The vast majority of the 19 most populous countries were in a middle-income category, with 7 in the upper-middle income category and 8 in the lower-middle income category.

There were 35 lower-middle income countries, with just 1 country: Ukraine, scoring above 70 in human capital. Twelve scored in the 60 to less than 70 range, 16 in the 50 to less than 60 range, and 6 scored below 50.

An equal number of countries in the lower-middle income category and the lower income category were in the bottom 10 for their human capital scores.

There were 17 lower income countries, with only 1, Rwanda, scoring above 60 in human capital and only 1 country: Ethiopia, among the 19 most populous countries. The rest of the countries were evenly split between the next two ranges with eight earning scores of 50 to less than 60 and eight earning scores just below 50.

3.1 Demographic and economic differences

Most of the world's people are in developing countries, where almost all population growth occurs. The world's population, which reached 6 billion in October 1999 and 7 billion in 2011, is growing by 1.2% or 80 million a year, with 97% of the growth in developing countries.

In the past, significant demographic differences between areas prompted large-scale migration. For example, Europe had 21% of the world's almost 1 billion residents in 1800 and the Americas 4% (Table 14.3). When there were five Europeans for every American, millions of Europeans emigrated to North and South America in search of economic opportunity as well as religious and political freedom.

Table 14.3. World population by continent, 1800, 2000, 2050 (percent shares)

Source: UN (1999). The World at Six Billion, Table 2.

Will history repeat itself? Africa and Europe had roughly equal populations in 2000, but fast-growing Africa is projected to have three times more residents than shrinking Europe in 2050. If Africa remains poorer than Europe, the two continents’ diverging demographic trajectories may propel young people from overcrowded cities such as Cairo and Lagos to Berlin and Rome.

The economic differences that encourage international migration have two dimensions, one fostered by inequality between countries and the other by inequality within countries. The world's almost 200 nation states have per-capita incomes that range from less than $250 per person per year to more than $50,000, a difference that provides a significant incentive, especially for young people, to migrate for higher wages and more opportunities. Young people are most likely to move within countries and over national borders because they have the least invested in jobs and careers at home and the most time to recoup their “investment in migration” to reach the destination.

The number of migrants doubled between 1985 and 2010, a period in which nominal per-capita incomes in rich countries tripled, from $12,000 to almost $39,000. The 30 high-income countries had 1.1 billion residents in 2010, a sixth of the world's population, and their gross national income was $43 trillion, 80% of the global $62 trillion (World Bank, 2012b, pp. 392–393).4

The average per-capita income of $39,000 in high-income countries was almost 12 times the average $3300 in low- and middle-income countries. Despite rapid economic growth in many developing countries, including East Asian “Tigers” such as Korea and Singapore in the 1990s and China and India more recently, the ratio of per-capita incomes between high-income and low-income countries has widened over the past quarter century, from 44 in 1985 to 76 in 2010. The gap has also widened for middle-income countries, from 9 to 10 (Table 14.4).

Table 14.4. Global migrants and per-capita income gaps, 1975–2005

The 1990 migrant stock was raised from 120 million to 154 million, largely to reflect the break-up of the USSR.

2005 data are gross national income.

Sources: UN Population Division and World Bank Development Indicators; 1975 income data are 1976.

The fact that an average person can increase his or her income by 10 times or more by crossing a national border is a powerful incentive to migrate, especially for a young person beginning to work. Labor force projections suggest that almost all labor force growth will be in developing countries, while labor forces in high-income countries will shrink. In 2010, for example, the 613 million workers in more developed countries were almost 20% of the global labor force of 3.3 billion. By 2020, the labor force of high-income countries is expected to shrink to 603 million, while the labor force of developing countries is expected to expand by about 400 million to 3 billion (Table 14.5). If employers in rich countries do not adopt labor-saving innovations, as in agriculture, their demand for workers may induce more south–north labor migration.

Table 14.5. World, DC, LDC economically active population (EAP) 1980–2020 (thousands)

Source: ILO Laborsta, <http://laborsta.ilo.org/>.

In lower-income countries, half or more of workers are employed in agriculture, a sector that is often taxed despite the fact that farmers and farm workers usually have below-average incomes (Taylor and Martin, 2001). There are many ways to tax farmers in developing countries with limited banking systems, including selling them needed inputs such as seed and fertilizer via monopoly firms that charge high prices, or having only one buyer for the commodities they produce that pays below-market prices. Taxes are the difference between the higher price that farmers pay for inputs and the lower world price or the difference between the higher world price for the commodities they produce and the lower farm price. Taxes that keep farm incomes below nonfarm incomes encourage rural–urban migration, which is one reason why the urban share of the world's population surpassed 50% for the first time in 2008.

Industrial countries had “Great Migrations” off the land after World War II that provided workers for expanding factories and accelerated urbanization. Similar Great Migrations are underway today in countries from China to Mexico. This rural–urban migration has three implications for international migration. First, many ex-farmers and farm workers accept 3-D (dirty, dangerous, difficult) jobs, whether inside their countries, as with rural–urban migrants in China, or abroad, as with Mexicans who fill jobs ranging from farm worker to gardener to kitchen helper. Second, rural–urban migrants make physical as well as cultural transitions when they move from villages to cities, and some find that this transition from village to city is as easy abroad as at it would be at home, especially if friends and relatives are already abroad. Third, rural–urban migrants within a country usually get closer to the country's exits, since labor recruiters who arrange foreign jobs are usually in the cities with government agencies that issue passports and have airports that can transport workers abroad.

1.2 From GDP to National Income

The link between aggregate measures of production and income is established by the fact that the incomes generated by production are all paid out of value added. As operating profits are the residual amount remaining after all the other incomes have been paid, the sum of all the incomes generated by production, including operating profits, must be identical with value added. At the level of the economy, the sum of the incomes generated by production is described as Gross Domestic Income, or GDI, which is equal in value with Gross Domestic Product by definition.

Gross National Income, or GNI, is derived from GDI by adding the incomes received by residents from foreigners and deducting the incomes paid to foreigners. (Unfortunately, GNI has traditionally been described as Gross National Product, or GNP, although it is an income rather than a production concept.) Net National Income is obtained by deducting depreciation from GNI. It is often described simply as National Income.

The numerical identity between GDP and GDI means that they can be estimated from two quite different sets of data, namely income or production data. Because income data are often incomplete and unreliable, most countries place more reliance on GDP measured from the production side using data on inputs and outputs collected in industrial inquiries. There is also a third approach that uses expenditures on final outputs, namely household and government consumption, capital formation, and exports less imports. Estimates from the production, income, and expenditure sides provide checks on each other. In practice, there are usually significant statistical discrepancies between them that may be reduced by adjusting the data, but many countries find it impossible to eliminate statistical discrepancies altogether and are obliged to publish them.

2.2 National Accounts

The balance of payments is part of the National Accounts system, which registers economic activity based on a standardized accounting system between nations. We will now see how transactions with the rest of the world relate to the main domestic macroeconomic aggregates, through the national accounts.

The main aggregate of national accounts is the Gross Domestic Product (GDP), which measures everything that is produced within the country’s borders.8 However, not all that is produced within the country belongs to the residents of that country. Consider, for example, the profit generated by a factory belonging to a multinational corporation. Production is done by means of a production factor, the capital, whose owners do not reside in the country. Therefore, the profit does not belong to the residents of that country. The Gross National Income (GNI), in turn, registers the value of all goods and services produced by production factors resident in the country. The difference between the two aggregates, GDP and GNI, corresponds to the net payment of income of the factors used in production but that are not residents in the country. As we saw in Section 2.1.1, the payment of income between residents and nonresidents is registered in the primary income account of the current account. Defining PI as the primary income balance, we have that:

(2.1)GNI−GDP =PI

If the primary income balance is negative, that is, if the country makes net income payments, then the GDP is greater than the GNI.

The goods and services available for use in a country correspond to the sum of GDP (Y) and the import of goods and services (M). These goods and services can be used for private consumption (C), investment9 (I), government consumption (G), or to be exported (X). This accounting can be represented by the equation:

Y+M=C+I+G+X

which can be rewritten as:

(2.2)Y=C+I+G+TB

where TB is the trade balance, which is the balance of the goods and services account. Adding the primary income balance to both sides of Eq. (2.2) and using Eq. (2.1), we have that:

(2.3)Y+PI︸GNI=C+ I+G+TB+PI

Finally, adding the secondary income balance to both sides, we get:

GNI+SI ︸GrossNationalDisposableIncome=C+I +G+TB+PI+SI︸Current Account

which we represent by:

(2.4)Yd=C+I+G+CA

where Yd is the Gross National Disposable Income, defined as the GNI plus the secondary income balance. We have seen that secondary income includes items such as, for example, international aid or remittances by immigrants to their families. These incomes should therefore be added to what is available for consumption in the country. CA represents the current-account balance, which is, by definition, the sum of trade balance with the primary and secondary income balances: CA=TB+PI+SI.

Equation (2.4) represents the basic identity of national accounts. The left side of the equation is the total disposable income of domestic residents and the right side represents the uses for this income, which can be private consumption, investment, government consumption, or transactions with the rest of the world. We can write it as:

(2.5)Yd ︸Income−(C+I+G)︸ Expenditures=CA

which shows that when the current-account balance is positive, income is greater than expenditures in a country. In this case, the country can lend to the rest of the world. When the current-account balance is negative, the national income is less than expenditures and the country borrows from the rest of the world.

Another way to interpret Eq. (2.4) is by identifying private savings (Sp) and government savings (Sg) in the equation. To do this, we add and subtract taxes (T) on the left side of Eq. (2.5), thus obtaining:

(2.6)(Yd−T−C)+(T−G)−I=CA,SP+Sg−I=CA.

According to the equation, a deficit in current account means that investment in the country is greater than savings. The equation also shows that a reduction of the account deficit has as a counterpart an increase in savings and/or a reduction in investment (Box 2.2).

Box 2.2

The Chinese Exchange Rate

During the 2000s, China was accused of maintaining its currency depreciated, generating trade surpluses and, consequently, very high current-account surpluses. Using Eq. (2.6), it becomes clear that the essence of the problem was an excess of savings in the economy: the over-depreciated currency was, actually, the result of high savings. According to what we will see in Chapter 5, the exchange rate is associated with the current account in such a way that the current-account surplus has as its counterpart a more depreciated currency. However, there is no way to alter the exchange rate by brute force to solve the problem. It is necessary to change the incentives for investment and savings for the economy to come to save less and invest more. Consequently, the surplus in current account will reduce and bring about a more appreciated exchange rate.

It is important to emphasize that Eq. (2.6) is an accounting identity: it is true regardless of ideologies or viewpoints regarding how the economy functions. It defines the relation between economic variables, but does not indicate the causality between them. To know, for instance, what the impact will be of an increase in production on the current account or what type of economic policy to use to affect the current-account balance, one must understand the way the economy works, what the motivations are for the economic agents, and how the variables relate to each other.

What is the impact of economic shocks on the current account? Take, for example, a country that has a positive income shock, such as the discovery and exploitation of a new oil reserve. If the story were to end with this increase in GDP, Eq. (2.6) would tell us that there would be an increase in savings and, therefore, an increase in current-account balance. However, it is expected that, along with the increased income, the economic agents would decide to consume more. If all the additional income is consumed, there would be no change in the level of savings and the current-account balance would remain unaltered. Or rather, if it is known that more oil reserves will be exploited in the future, the population may decide to consume even more because they believe they will be even richer in the future, causing savings to fall along with the current-account balance. We can therefore see that the effects of a shock or a change in the economy depend on the reaction of the economic agents. Economic models try to represent individual incentives in order to capture the causalities among the variables. In Chapter 4, we will present a model that explains how variables such as the income level or international interest rates affect the current account, taking into consideration the behavior of individuals in response to changes in the economy.

One must remember that any economic model must obey the rules of the economy, among them the accounting identities of national accounts and balance of payments. In the next section, we will take a step in that direction by analyzing the conditions for equilibrium in balance of payments and the sustainability of current-account deficits. In this process, we will present some simplifying assumptions in order to study the topic. We will not develop an economic model, so to speak, since we will not analyze the behavior of individuals. We will only take the first step: simplify to better understand.

The EU Cohesion Grants

A major grant program very much in the spirit of LeGrand's principle of fiscal equalization is the European cohesion grants, which constitute about 35% of the European Union's budget. A primary motivating factor in the formation of the European Union was to reduce fiscal disparities throughout the member nations, a goal the European Union refers to as convergence. The cohesion grants are the principal means to this end. They are targeted to regions within countries whose per capita gross national income is substantially below the overall EU average (less than 90% of the average under one of the grant programs, and less than 75% of the average under two other grant programs that distribute the majority of the funds). The grants have a number of goals, but over 60% of the total grant funds are specifically to support convergence. The main difference from the LeGrand prescription is that the cohesion grants are project grants, not unconditional grants. They are targeted to projects such as infrastructure investment, business investments, and job training in the poorer regions. Grant recipients propose specific projects and are expected to pay part of the costs.3

4.5.3 Indicator of Standard of Living

The third HDI component, standard of living, was measured by real Gross Domestic Product (GDP)af per capita in Purchasing Power Parity Dollars (PPP$)ag between 1990 and 2010. It was replaced with Gross National Income (GNI)ah per capita in constant PPP$.ai Many limitations of the GDP were pointed out over the years—starting with the limitations inherent in its own construction by excluding those goods and services not traded in markets, ignoring household productive activities such as taking care of own children, housekeeping, and food production for own consumption. Such activities are omnipresent and universally important, especially in developing countries. GDP includes all effects of economic activities, but ignore the costs of activities such as those that cause pollution.

The GNI per capita replaced the GDP per capita in the HDI in 2010. In a globalized world, differences can be large between the income of a country’s residents (GNI) and its domestic production (GDP). Some of resident earnings are sent abroad, some residents receive international remittances and some countries receive sizeable aid flows. In other words, GNI expresses the income accrued to residents of a country, including some international flows, and excluding income generated in the country but repatriated abroad. Thus, GNI is a more accurate measure of a country’s residents’ ability to instrumentally use income to expand capabilities. For example, because of large remittances from abroad, GNI in the Philippines greatly exceeds GDP (for about 10% in 2019). In Ireland's case, GDP is actually larger than GNI because of repatriation of profits by companies resident in Ireland and repayments on the foreign elements of Ireland’s national debt.

The 2009 Report by the Commission on the Measurement of Economic Performance and Social Progressaj mentions that “Income flows are an important gauge for the standard of living, but in the end it is consumption and consumption possibilities over time that matter.” The Report then recommends using income or consumption rather than production; moreover, the Report suggests the use of wealth to take into account the temporal dimension. Income misses the various dimensions of wealth including financial and real wealth and natural wealth, which is central to evaluating sustainability. Foster (2013) entertained the idea of using one flow variable to indicate what is available for transformation into capabilities and to generate standard of living now, and one stock variable to indicate what is saved and transferred to the next generation.

The Commission also recommended that instead of using the averages of income, consumption, and wealth, it might be more insightful to use the medians as measures that pertain better to the “typical” individual or household than the mean (which may be distorted by extreme values at either end of the distribution). However, in practice, moving from means to medians may be difficult given that medians require microdata from household income surveys, whereas macroeconomic measures from the national accounts are based on a range of different macroeconomic sources and may not pertain to the same population. Many of the important properties of means, as well as the theories developed around the concepts such as welfare standards, may not translate directly to the median-based measures.

The standard of living dimension was settled for GNI per capita to account for income generated in the country plus some income received from abroad minus some sent abroad. Data on household income or consumption are neither readily available nor harmonized.