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# **5. Where Does the Developing World Stand?**

Given the crucial importance of cognitive skills for economic development, it is telling to document how the developing countries fare in this regard. In the following, we document both the quantity of schooling and quality of education achieved by developing countries from an international perspective, and this vividly illustrates the magnitude of the task at hand.

## **_5.1 Lack of Quantity of Schooling_**

The disadvantages of less developed countries in terms of educational enrollment and attainment have been well documented and are well known. To provide an aggregate picture, Figure 5.1 presents the share of children aged 15-19 who have completed grade 9, dropped out between grades 5 and 9 or between grades 1 and 5, or never enrolled, for eight regions of developing countries.<sup>62</sup> The shares are unweighted averages of the available countries in the Demographic and Health Surveys (DHS) and similar surveys (cf. Filmer (2006)), conducted in a large number of developing countries. These household survey data are much more reliable than the administrative data on school enrollment rates traditionally used, because the administrative data available in many developing countries often overstate actual enrollment rates. Further, the self-reported data on the highest grade completed is more relevant for actual education than enrollment rates, which are affected by grade repetition and the like.

While almost all OECD countries have universal school attainment to grade 9, essentially all developing regions are far from that. In the average African country in the data, only 13% of each cohort finishes grade 9, and less than 30% in Central America and South and East Asia. Even in South America, this figure is only 43%, although on the other hand only 17% of a cohort do not complete grade 5 (which often serves as an initial indication of basic literacy and numeracy rates). In West and Central Africa, 59% of each cohort do not even complete grade 5, and 44% never enroll in school in the first place. It is notable across countries, however, that the lack of grade 5 attainment is at least as often due to dropping out of school than due to never enrolling. In any event, while the pattern of educational attainment varies greatly across countries and regions, the lack of quantitative educational attainment from universal completion of basic education – be it grade 5 or grade 9 – is immense in the majority of developing countries.

62 Grades 5 and 9 are chosen as two possible definitions of basic schooling. The age range 15-19 is chosen to balance the relevance of the data for most recent conditions against the censoring problem of some children still being in school. The basic patterns observed are the same when using estimates adjusted for the censoring (Pritchett (2004)).

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that are the same as those produced by many other firms, and thus face large amounts of competition.

# **4.4 Firm Size**

Finally we examine whether larger firms have better business practices. The causation here may go both ways: firms with better practices will sell more and be able to grow larger – consistent with the results for sales growth we show on Table 4 – in the end hiring more employees. But being larger may also allow owners to hire specialists to perform some of the functions we measure (such as record-keeping) and give the owner more time for strategic planning and marketing rather than day-to-day operations. Column 6 of Table 6 shows that larger firms do have better business practices. A firm with 1 to 4 paid workers has a 0.101 higher business practices score than a firm with no workers, and the coefficients increase with each category of firm size, so that a firm with 21 or more workers has a 0.235 (almost one s.d.) higher business practice score than a firm with no workers.

The last column of Table 6 considers all these factors together. We continue to see positive associations between better business practices and human capital, having parents who owned a business, and firm size.

# **5. Conclusions**

Micro and small enterprises are the predominant form of economic activity in low- and middleincome countries. There is broad recognition that the microenterprise sector is highly heterogeneous, with some owners drawn by opportunities to create a business and others drawn by the necessity to scrape out a living. Aspirations and education have been viewed as the main underlying sources of heterogeneity. We show that the enterprises are also differentiated by the quality of the business practices they employ, and that business practices have effects on enterprise outcomes which are independent of the effects of basic human capital.

Our index of business practices is designed to be easily implemented in closed-end field surveys and is customized to microenterprises. Most of our data are self-reported, but we show that the reports of owners are highly correlated with measures from independent auditors visiting the businesses and spending several hours asking open-ended questions about practices. Using data 19
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**Figure 1: In contrast to the fast growing countries of the past 20 years, ESA countries have lost share of the global market for merchandise**

<!-- Start of picture text --> Average share of world m erchandise exports (% of US$ current)<br>Average HP 16 Average ESA<br>0 .04%<br>1 .2%<br>Average High Perform ing 16 0 .04%<br>1 .0% 0 .03%<br>0 .8% 0 .03%<br>0 .02%<br>0 .6%<br>0 .02%<br>0 .4%<br>0 .01%<br>0 .2% Average ESA<br>0 .01%<br>0 .0% 0 .00%<br>Source: Bank staff calculations, based on data from IMF W orld Economic Outlook, Ethiopia and Eritrea counted as one country<br>19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02 20 04<br><!-- End of picture text --> Figure 2 shows a similar story for exports of services. The average ESA country has had a very low and declining share of the global market for services. This is in contrast to the fast growing countries, which have, on average, almost tripled their share of the world market over the past 25 years. Hence, the challenge for ESA and other ACP countries is to provide a trade policy climate in which to attain the sustained increases in exports of both goods and services and rising global market shares that have driven growth in the high performing countries.

These figures also suggest a lack of effectiveness of current and previous agreements with the EU in supporting sustained growth of exports or in dealing with the constraints that have undermined the share of ESA countries in the world market. In other words, this weak performance occurred despite preferential access to the EU and other markets. Preferences alone have not helped to strongly integrate ESA into the global economy. With decreasing margins of preference due to continued multilateral liberalization, they are even less likely to help in achieving this objective in the future.

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account. For example, it would be a mistake to consider countries with low stock-market capitalization as financially backward if, for instance, they allocate a large amount of credit to private enterprises through the banking.

Using the methodology outlined in the previous section, two indices are presented to measure the degree of a country’s financial development. They were constructed in a way such that comparisons over time and across countries are possible. Each index consists of indicators that quantify different aspects of the performance of the financial system.” The first index is closely linked to the development of the banking sector. The second is related to stock markets. In order to obtain information about long-term financial development from the following financial indicators, it is important to focus on their long-run trends. Their temporary fluctuations, which may be rather large, are mostly determined by the business cycle and one-time events, such as the privatization of public enterprises.”'

# 1. Banking sector development

- The-first element to consider in assessing the development of the banking sector is the depth of a nation’s financial system relative to the size of its economy. This can be measured by quasi-liquid liabilities of the financial system relative to GDP, that is, (M3-M1)/GDP.” Currency and highly liquid demand deposits (M1) are excluded because they are rather volatile and do not represent longterm investments in financial intermediaries. Another element to consider is the participation of private institutions in providing credit. This is important because private institutions have clearer incentives to . mobilize savings toward profitable projects, exert corporate control, and facilitate risk diversification. To proxy for the participation of private institutions in the provision of credit, this paper uses the ratio

2° Detailed data for the period 1985-95 on these and all other indicators presented in the paper are given in the appendix. 21 Of course, the decomposition of any economic variable into its permanent and transitory components is far from trivial. No formal decomposition technique is used in this paper.

*2 The end-of-year nominal quasi-liquid liabilities is deflated by the end-of-year CPI, and nominal GDP is deflated by the yearly average CPI. This deflation is an important correction to the usual practice of taking the ratio of end-of-year liquid liabilities to nominal GDP, practice that renders an artificially high ratio for- high inflation countries/periods. In this document, the same deflation procedure is used when dealing with ratios of any end-of-year stock measure (for example, a monetary or capital market aggregate) to a flow measure (for example, GDP).

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and then continuing outlay on maintenance, expansion, and improvement.<sup>30</sup> This does not seem practically feasible until urban GDP has crossed a certain threshold and is on an upward trend.<sup>31</sup> In the balance of the paper we will examine the empirical links between income growth and health and also between infrastructure spending, education and urban health to suggest why the GDP growth, infrastructure-led, and education supported approach is key to a strategy for improving urban health and sustaining the gains achieved.

# **_III. Selected Empirical Studies on Health and Growth_**

The correlation between health and wealth has long been documented in the literature on public health and development economics. In the words of Nobel Laureate Amartya Sen, health is among the basic capabilities that gives value to human life (Sachs 2001) and has been hailed as the foundation of development. However, empirical research on the relationship between income and health has been plagued by the endogeneity. While good health can be considered as a part of human capital with a beneficial effect on growth, wealthy individuals can also consume many healthenhancing goods and services to improve their health (Lopez-Casasnovas, Rivera, and Currais 2005b).

# **Income to Health**

In order to sidestep the problem of endogeneity in conducting such tests, some researchers have relied on instrumental variable approach and natural experiments to isolate the independent effect of income or economic growth on health.<sup>32</sup> Using terms-of-

> 30 Improved access to sanitation and better hygiene practices have a larger impact on health than improvement in the quality of drinking water.  This is because most diarrheal diseases are transmitted from person to person through poor hygiene, contaminated food and the improper disposal of excrete (Cairncross and Valdmanis 2006; World Bank 2003).  For a household of five, the minimum consumption requirement of water is about 50 liters per capita per day for maintaining basic hygiene, while 100 liters will represent modest usage (Foster and Yepes 2006).  Europeans use on average 200 liters per day and Americans, more than 400 liters per day (UNDP 2006).

> 31 In a decentralized fiscal system, this also depends on the development of local financing options.  See Cutler and Miller (2005) for an assessment based on past U.S. experience.

> 32 Causation runs both ways and omitted variable biases such as technologies, differences in health sector institutions, and specific interventions remain sources of bias and error, especially for cross-country analysis (Acemoglu and Johnson 2006). Using detailed data on mortality in seven European countries, Janssen, Kunst, and Mackenbach (2006) find that GDP levels prevailing at specific ages effect the

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unique database which has information on all new work contracts issued to Filipino workers over the 1992 to 2009 period, including information on the destination country and contracted wage.

The Philippines provides an excellent setting to examine how migration responds to shocks at destination. It was the first country to implement temporary overseas contract work on a wide scale, and Filipinos now migrate in large numbers to a very diverse set of countries, which have experienced substantial heterogeneity in macroeconomic conditions over the period of our data. In 2007, 1.7 million Filipinos were working outside of the Philippines in 181 countries, with overseas contract work the primary channel of emigration.

Using these data, we estimate how the number of contract workers and the wages they are paid respond to economic shocks in destination countries. We find a strong and significant positive relationship between migrant numbers and GDP fluctuations at destination, with the point estimate suggesting migrant quantities respond more than one-for-one to proportional GDP changes. In contrast, we find that the wages migrants are paid has no large or statistically significant relationship with GDP changes at destination. This pattern is consistent with the existence of binding minimum wages that lead to migrant labor supply exceeding labor demand at the contracted wages. This occurs for both low- and high-skilled workers, suggesting the distortion comes not just from national minimum wages in destination countries, but also from restrictions on the wages that migrants of higher skill levels can be paid. For example, the United States H1B program that many IT professionals and foreign professors use to work in the United States requires that employers pay the “prevailing wage” obtained from a salary survey, as do a number of other immigration categories in the U.S.; Australia requires employers to pay their overseas workers the market salary rate and on top of this, specifies a threshold (currently A$49,330) that skilled migrants must make;<sup>1</sup> and the Philippines’ bilateral labor contracts require workers to be paid the prevailing wage for their positions in the destination countries. As a result, the same market imperfection that enables workers to so dramatically increase their incomes by working abroad shifts all the burden of adjustment to demand shocks onto quantities rather than wages.

> 1 See http://www.immi.gov.au/skilled/temporary-skilled-migration-threshold.htm (accessed October 18, 2011).

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**Table 5 Definition and source of variables for exploratory regression analyses.**

|**Variable name**|**Definition**|**Source**|
|---|---|---|
|**Per capita calorie**supply<br>(kcal/capita/day)|Estimates of per capita food supplies available for human consumption during the reference period in terms<br>of quantity, caloric value, protein and fat content (2020). Calorie supplies are reported in kilocalories (1<br>calorie = 4.19 kJ. Availability does not imply actual consumption due to intervening factors such as food<br>waste, and likely exceeds values from dietary intake surveys|FAOSTAT|
|**MDD-W**|% of women who consumed at least five out of ten predefined food groups, 2021|Gallup World Poll (2021) /<br>Food systems dashboard;|
|**MDD**(6-23 months)|Percentage of children 6–23 months of age who consumed foods and beverages from**at least five** **out of**<br>**eight**defined food groups during the previous day. Various years, 2014-2019 (1 observation from 2011, 1<br>from 2008 and 1 from 2006)|UNICEF|
|**NCD-Protect**score among adults ≥<br>15|NCD-Protect scores are on a scale of 0 to 9; higher scores indicate greater protection against<br>noncommunicable diseases. Data are for individuals ≥15 years of age from the 2021 Gallup World Poll for<br>2022|World Gallup Poll<br>(GDQP) / Food systems<br>dashboard|
|**NCD-Risk**score among adults ≥ 15|NCD-Risk scores are on a scale of 0 to 9; higher scores indicate greater risk for noncommunicable diseases.<br>Data are for individuals ≥15 years of age from the 2021 Gallup World Poll for 2022|World Gallup Poll<br>(GDQP) / Food systems<br>dashboard|
|Prevalence of**overweight & obesity**<br>among women (20 - 49 years) %|Percentage of women 20–49 years of age with a BMI greater than or equal to 25 kg/m2 in 2016|UNICEF Global Database<br>(based on NCD-RisC)|
|Prevalence of**underweight**among<br>women (20 - 49 years) %|Percentage of women 20–49 years of age with a BMI less than 18.5 kg/m2 in 2016|UNICEF Global Database<br>(based on NCD-RisC)|
|Adult**diabetes**prevalence|Proportion of adults aged 18+ years with diabetes. Diabetes is defined as having a fasting glucose of 7.0<br>mmol/L or higher, being on medication for raised blood glucose, or having a past diagnosis of diabetes. Data<br>for 2014, except 1 country 2003, 1 country 2005, 2 countries 2010, 1 country 2012.|NCD-RisC / Food systems<br>dashboard|
|Adult**raised blood pressure**<br>prevalence|Percent of adult population (18+ years) with systolic blood pressure ≥ 140 mmHg or diastolic blood pressure<br>≥ 90 mmHg in 2015|NCD-RisC / Food systems<br>dashboard|
|**Gini**coefficient|Index of inequality, 0=perfect equality, 100=perfect inequality, latest year available (ranges by country from<br>2010 to 2021)|World Bank|
|**Region**= AFRO (omitted dummy)|Benin, Burkina Faso, Cameroon, Chad, Gabon, Ghana, Kenya, Malawi, Mali, Mozambique, Niger, Nigeria,<br>Senegal, Sierra Leone, Tunisia, Uganda, United Republic of Tanzania, Zimbabwe|World Health<br>Organization|
|**Region** =AMRO|Bolivia, Chile, Colombia, Ecuador, Honduras, Mexico, Nicaragua, USA,||

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income countries. In high-income countries, mutual fund assets expanded from 10 to 24 percent of GDP between 1992 and 1998, while in middle-income countries they grew from 4 to 8 percent in the first half of the 1990s but then fell back to 4 percent by 1998. All types of mutual funds grew between 1992 and 1998 in high-income countries, but in middle-income ones equity and bond funds exhibited little net growth.

**Chart 1- Mutual Funds Net Assets in high and middle-income countries (% of GDP)**

<!-- Start of picture text --> Total Net Assets / GDP Equity Funds Net Assets / GDP<br>24-12 -<br>L.14 -- 4-<br>4 4 0 * *<br>92 93 94 95 96 97 98 92 93 94 95 96 97 98<br>Years Yearn<br>ab5. l Total + -Deeloped a -- DelIoping [ 2. | Total + Dereloped -f-- - Daieloping<br>ae - Bond Funds , Net Assets GDP a a 2 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Money . . ............ Market Funds Net Assets L<br>7 -- --------- - -. GDP<br>co ~~2.5 - -<br>a22<br>3 ~~~~11.--------------<br>92 93 94 95 96 97 98 92 93 94 95 96 97 98<br>Yearn<br>Years<br>- Total -o De%eloped - -Dewlopin t Total --- Devwloped _-lW- De%oaoping<br><!-- End of picture text -->

The last result is explained by the declines experienced by some East Asian countries (Korea and Malaysia) as well as Israel and Mexico. In contrast, most Latin American countries as well -as Arab and Eastern European countries achieved high growth rates, but starting from low or nonexistent bases. Most high-income countries registered high growth rates.

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