PPT Chapter 2 Comparative economic development.pptx

Copyright © 2020, 2015 Michael P. Todaro and Stephen C. Smith
Economic Development
Thirteenth Edition
Chapter 2
Comparative economic
development

2.1 Defining the Developing World
• The World Bank ranks countries on Gross National
Income (GNI) per capita
– Low-Income Countries (LICs)
– Lower-Middle Income Countries (LMCs)
– Upper-Middle Income Countries (UMCs)
– High-income OECD countries
– Other high-income countries
– (See Table 2.1 and Figure 2.1)

2.2 Basic Indicators of Development:
Real Income, Health, and Education
• Gross National Income (GNI)
• Gross Domestic Product (GDP)
• PPP method instead of exchange rates as conversion
factors (see Table 2.2)

Table 2.1
Classification of Economies by Country Code, Region, and Income, 2018
Source: Data from World Bank, World Development Indicators, 2018

Table 2.1
Classification of Economies by Country Code, Region, and Income, 2018
(Continued)
Source: Data from World Bank, World Development Indicators, 2018

Figure 2.1
Nations of the World, Classified by GNI Per Capita

Figure 2.2
Income Comparisons for Selected Countries, 2017
Source: World Development Indicators

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
Source: World Bank World Development Indicators

Source for health indicators: WDI. Source for education indicators: UNDP.
Table 2.3
Commonality and Diversity: Some Basic Indicators of Health and Education

2.3 Holistic Measures of Living Levels and
Capabilities
• Income is one indicator, but needs to be supplement with others
• Health e.g. Life Expectancy
• Education
• Other indicators are considered in various indices
• The New Human Development Index (NHDI), or simply “HDI”
• Introduced by UNDP in November 2010
• NHDI as an attempt to create and use holistic measure of living
levels; takes into account income, health, and education
• NHDI can be calculated for groups and regions in a country
– HDI varies among groups within countries
– HDI varies across regions in a country
– HDI varies between rural and urban areas

Why is the new New HDI considered an improvement
over linear measures such as the Traditional HDI?
Calculating with a geometric mean
• How does the New HDI compare with the better-known (but no longer active)
Traditional HDI? And other linear combinations of national indexes?
• Probably most consequential: The HDI is now computed with a geometric
mean, instead of an arithmetic mean
• A geometric mean is also used to build up the overall education index from its
two components
• Traditional HDI added the three components, divided by 3 (arithmetic mean)
• The New HDI takes the cube root of the product of the 3 component indexes
• The traditional HDI linear calculation assumed one component traded off
against another as perfect substitutes, a strong assumption
• The reformulation now allows for imperfect substitutability - widely considered
a more plausible way to frame the tradeoffs

Calculating with a geometric mean in the New
HDI
• The New HDI takes the geometric mean, which is the cube root of the
product of the three component indexes Ilife
1/3
, IEducation
1/3
, and IIncome,
which may be written as:
NHDI = (Ilife
1/3
* IEducation
1/3
* IIncome
1/3
).
Or,
NHDI = (Ilife* IEducation * IIncome)1/3
.
• This reformulation allows for imperfect substitutability
• Addresses “how well-rounded” a country’s performance is across the
three dimensions”
• Other differences (choices) made in the components of the sub-indices
• We can see these elements in the textbook’s Example of Ghana:

Calculating the New HDI: Example
• Example: Ghana
• Indicator Value
• Life expectancy at birth (years) 64.6
• Mean years of schooling 7.0
• Expected years of schooling 11.4
• GNI per capita (PPP $) 1,684
• Indexes
• Life expectancy index = (64.6 – 20)/(83.6 – 20) = 0.701
• Mean years of schooling sub-index = (7.0 - 0)/(13.3 – 0) = 0.527
• Expected years of schooling sub-index = (11.4 – 0)/(18.0 – 0) = 0.634
• Education Index = ([√0.527*0.634] – 0)/(0.971 – 0) = 0.596
• Income index = [ln(1,684) - ln100)]/[ln(87,478) - ln(100)] = 0.417
• NHDI = (0.7011/3
* 0.5961/3
* 0.4171/3
) = 0.558
• Comparative examples of underlying data and indexes across countries on supplemental slides
*Note: Example from 12th
Ed. Numbers are rounded. Source: http://hdr.undp.org/sites/default/files/hdr_2013_en_technotes.pdf

Other key differences between the New HDI
and Traditional HDI
• Traditional HDI is still widely taught; students may encounter it in other classes
• A brief summary of other key differences between the New HDI and the
Traditional HDI (in addition to using a geometric mean) follows:
‒ Gross national income per capita replaces gross domestic product per capita
‒ Revised education components: the New HDI uses the average actual
educational attainment of the whole population, and the expected
attainment of today’s children (not enrollment)
‒ The maximum values in each dimension have been increased to the
observed maximum rather than given a predefined cutoff
‒ The lower goalpost for income has been reduced due to new evidence on
lower possible income levels
‒ Note: Please be sure to review example country comparisons to get a sense
of how much HDI rankings can differ from income rankings

Note on HDI And Policy
• Not just that correlation not very strong between
income and HDI
• Also: HDI can be altered by policy
• Example (if a partial one): South Africa

Source: United Nations Development Program
Table 2.4
2018 Human Development Index and its Components for
Selected Countries

Table 2.5
HDI for Countries with Similar Income Levels
Data Source: 2016 Human Development Report 2016, Table 1, Pages 198-201 (New York: United Nations Development Program), 2015 data.

Figure 2.3
Improvements in Human Development Since 1990, by
Region
Source: Human Development Report Office, UNDP – Human Development Report, 2016, p. 27

Comparing characteristics among developing
countries
• Ten points of comparison - both among developing countries,
and between developing and developed countries:
‒ Lower levels of living and productivity
‒ Lower levels of human capital
‒ Higher levels of inequality and absolute poverty
‒ Higher population growth rates
‒ Greater social fractionalization
‒ Larger rural population - rapid migration to cities
‒ Lower levels of industrialization and manufactured exports
‒ Adverse geography
‒ Underdeveloped financial and other markets
‒ Colonial Legacies – quality of institutions

Figure 2.4
Under-5 Mortality Rates, 1990 and 2017

Table 2.6
The 12 Most- and Least-Populated Countries and
Their Per Capita Income, 2017
Source: World Bank World Development Indicators

Table 2.7
Primary School Enrolment and Pupil–Teacher
Ratios, 2017

Source: Population Reference Bureau: Births per 1,000 population
Table 2.8
Crude Birth Rates Around the World, 2018

Source: World Bank, World Development Indicators, 2013 (Washington, D.c.: World Bank, 2013), tab. 2.3
Share of the Population Employed in the Agricultural,
Industrial, and Service Sectors in Selected Countries,
1990–92 and 2008–2011 (%)

Figure 2.5
The growth of real output per person since 1750
Source: Data from Maddison Project Database

2.6 Are Living Standards Converging across
Countries?
• A Great Divergence followed the Industrial Revolution
• Two reasons to think (re-)convergence likely
1) Diminishing returns to capital (though as economies develop they often
find ways to compensate)
2) Diffusion of ideas across countries, so can skip trial and error and grow
fast while catching up
• Latter elated to “advantages of backwardness” (Gerschenkron), or “the
latecomer’s advantage”
• But - at least until this century - evidence of unconditional national average
income convergence has been unconvincing
• Continued evidence of divergence between middle and low income countries
• There is also evidence of “per capita income convergence,” weighting changes
in per capita income by population size
• (We consider “conditional” convergence - observed after accounting for other
factors - in a general way in context of the Solow neoclassical growth model)

Figure 2.7
Relative Country Convergence: World, Developing
Countries, and OECD
Data Source: Penn World Table

Figure 2.8
Growth Convergence versus Absolute Income
Convergence
Data Source: Penn World Table

Nature and Role of Economic Institutions
• Institutions provide “rules of the game” of economic life
– Follows general framework of Nobel Laureate Douglass North
• Salient institutions include the nature and extent of:
• Property rights
• Contract enforcement
• Restriction of coercive, fraudulent and anti-competitive behavior
• Provision of access to opportunities for the broad population
• Constraining the power of elites
• Conflict management
• Other institutions provide improved coordination; social
insurance; and predictable macroeconomic stability

The Nature and Role of Economic Institutions:
Some Caveats and Nuances
• Most importantly: Good institutions may both cause development, and
improve as a result of development
• In addition:
‒ The institutions on the previous slide are correlated
‒ It is not clear which of these institutions matter most
‒ Unclear how specific in form institutions must be to fulfill their main
function
‒ Progress may be made when only some institutions are of high quality; but
further progress may require improving quality of additional institutions
‒ The specifics of their relative importance, and the sequence of improving
them, may well vary by country
‒ China provides an important case of transitional institutions, examined in
case study for Chapter 4
‒ Note : A “free market economy” is not the only example of a market
economy

Figure 2.9
Schematic Representation of Leading Theories of
Comparative Development

Explaining Long-Run Causes of Comparative
Development: Fig. 2.10 Summary
• Arrow 1: Geography: Important in pre-modern era; limited effect in
modern era
• Arrow 2: However, exogenous geography affected how colonists
viewed opportunities they could exploit in colonies; and so in part…
• Arrow 3: Geography was a determinant of whether colonists created
extractive or inclusive institutions; this fact facilitates analysis of role of
institutions
• Arrow 4: Geography presumably affected indigenous institutions…
• Arrow 5: A Note: Difficult to quantify; but colonial institutions may
have been influenced by indigenous institutions
• Arrow 6: Geography affected comparative advantages: resources and
people

Explaining Long-Run Causes of Comparative
Development: Fig. 2.10 Summary (Continued)
• Arrow 7: Geography helps explain “motivation” for institutions:
extractive when comparative advantage (CA) was in activities with (a
range of) increasing returns (e.g. sugar cane, mining); inclusive when
CA was in constant returns activities (e.g. wheat)
• Arrow 8-9: Reflects that state of development of the colonizer also had
an effect
• Arrow 10: Key: Institutions were persistent from colonial to post-
colonial periods
• Arrow 11: Bad institutions created high inequality which also had bad
effects on growth and development outcomes
• Arrow 12: Especially difficult to reform institutions with high inequality
• Results (arrows 14-22): “Bad” institutions and high inequality led to
slower growth and slow improvement of human capital and other
development outcomes

Role of Institutions and Inequality: Findings
• Acemoglu, Johnson, and Robinson: “reversal of
fortune” and extractive institutions
• Bannerjee and Iyer: “Property rights institutions.”
Landlords versus cultivators
• Easterly: “Inequality does cause underdevelopment”

An Approach to Addressing Causality:
Instrumental Variables
• Addressing causality by searching for an instrumental variable (IV)
• To identify effect of a causal variable c (e.g. inequality) on outcome
variable d (e.g. income), find instrument e that affects d only through
e’s effect on c.
• An instrument has no independent effect on the outcome variable of
interest
• There are two examples of findings using this method in Chapter 2:
1. Acemoglu, Johnson, Robinson used settler mortality as IV for
institutions
2. Easterly used “abundance of land suitable for growing wheat
relative to that suitable for growing sugarcane” as an IV for
inequality

Does Inequality [Negatively] Cause
Development?
• Among others, Acemoglu, Johnson, Robinson found good institutions
cause development (details in Chapter 2, Section 2.6)
• Does (extreme) inequality (general, or inequality of opportunity) harm
development?
• One approach: Painstaking economic history analysis, most
prominently of Sokoloff and Engerman (E&S)
• Also, quantitative analysis: Inspired by E&S, Easterly used “abundance
of land suitable for growing wheat relative to that suitable for growing
sugarcane” as an IV for inequality
• Confirmed that “agricultural endowments predict inequality and
inequality predicts development”
• Identified mechanisms by which higher inequality lowers per capita
income, via poor institutional quality - and schooling

Impact of Institutions on Development
Findings: the Banerjee and Iyer Study of India
• Evidence on importance of institutions from a study of the impact of land revenue
institutions established by the British Raj in India
• Areas where the British took over land revenue collection between 1820 and 1856
(not before or after) much more likely to have a non-landlord system
• Being conquered in this period used as an IV for having a non-landlord system
• Authors also used additional statistical tests that showed results were robust
• Finding: Historical differences in property rights institutions led to sustained
differences in economic outcomes
• Where property rights given to landlords, significantly lower agricultural investments
and productivity post-independence than where property rights given to cultivators
• Authors concluded the divergence occurred because historical differences in
institutions led to different policy choices
• Regions where landlords received proprietary rights also had significantly lower
investments in health and education in the postcolonial period

38
BOX 2.3 FINDINGS: The Persistent Effects of Colonial
Forced Labor on Poverty and Development
• Mita, a forced labor system instituted by the Spanish government in Peru and Bolivia
was established in 1573 and only formally abolished in 1812
• A sharp Mita boundary: on one side, all communities had to send the same percent of
population to work; on the other side, all communities were exempt
• This discrete change at the border suggests a special statistical approach for evaluating
the long-term effects of the Mita: The Regression discontinuity design (RD) approach
• Uses fact that the Mita boundary forms a discontinuity in longitude–latitude space
• Key Findings: Impact: Lowered household consumption by approx. 25%; and
• Increases the prevalence of stunted growth in children by around 6 percentage points
• Mechanisms: What forces led to these impacts? Long-run mechanism is not obvious:
• Negative impacts of Mita persisted through impacts on land tenure and public goods;
• Mita districts historically had fewer large landowners and lower educational attainment
• Today, these districts are less integrated into road networks and their residents are
substantially more likely to be subsistence farmers
• *From Melissa Dell. “The Persistent Effects of Peru’s Mining Mita.” Econometrica 78 (2010): 1863–1903

Appendixes

Appendix: Holistic Measures of Living Levels
and Capabilities - The Traditional HDI
• Income is one indicator, but supplement with others
• Health, e.g. Life Expectancy
• Education, e.g., school enrollment levels
• Other indicators can be and are considered in various indices
• Traditional HDI was developed in 1990 as a holistic measure of living
levels; takes into account income, health, and education
• It is still used by some as an alternative to the New HDI
• What many still think of as the current HDI, so worth knowing
• HDI can be calculated for groups and regions in a country
– HDI varies among groups within countries
– HDI varies across regions in a country
– HDI varies between rural and urban areas

Holistic Measures of Living Levels and
Capabilities: Traditional HDI
• From the Appendix: Traditional HDI
• A detailed calculation (example of Bangladesh) is found
in Appendix 2.1
• Unlike the New HDI, the Traditional HDI is calculated
using an arithmetic mean:

Table A2.1.1
2009 Traditional Human Development Index for 24
Selected Countries (2007 Data)
Source: Data from United Nations Development Programme, Human Development Report, 2009, tab. 1.

Table A2.1.2
2009 Human Development Index Variations for Similar
Incomes (2007 Data)
Source: Data from United Nations Development Programme, Human Development Report, 2009, tab. 1.

Figure A2.1.1
Human Development Disparities Within Selected
Countries
Source: From Human Development Report, 2005, figs. 10–12. Reprinted with permission from the United Nations Development Programme.

Figure A2.1.1
Human Development Disparities Within Selected
Countries (Continued)
Source: From Human Development Report, 2005, figs. 10–12. Reprinted with permission from the United Nations Development Programme.

Appendix 2.2:
How Low-Income Countries Trying to Launch Accelerated Growth
Today Differ from Developed Countries in Their Earlier Stages
• Eight Relatively Widespread Aspects of Differences:
1. Physical and human resource endowments
2. Per capita incomes and levels of GDP in relation to the rest of
the world
3. Climate
4. Population size, distribution, and growth
5. Historic role of international migration
6. International trade benefits
7. Basic scientific/technological research and development
capabilities
8. Efficacy of domestic institutions

*Note on National Income Definitions and
Calculations*
• The “Atlas” method for computing Gross National Income (GNI) is the sum of value
added by all resident producers plus any product taxes (less subsidies) not included in
the valuation of output plus net receipts of primary income (compensation of
employees and property income) from abroad
• Data are in current U.S. dollars converted using the World Bank Atlas method
• Gross national income, in purchasing power parity, is GNI converted to international
dollars using PPP rates. An international dollar has the same purchasing power over
GNI that a U.S. dollar has in the United States.
• Gross national income per capita is GNI divided by midyear population.
• Gross domestic product is the sum of value added by all resident producers plus any
product taxes (less subsidies) not included in the valuation of output.
• Growth is calculated from constant price GDP data in local currency.
• Gross domestic product per capita is GDP divided by midyear population.
*For further details see “Sources and Methods,” in World Development Indicators (WDI), 2017

Concepts for Review
• Absolute poverty
• Brain drain
• Capital stock
• Convergence
• Crude birth rate
• Dependency burden
• Depreciation (of the capital
stock)
• Diminishing Marginal Utility
• Divergence
• Economic Institutions
• Fractionalization
• Free trade
• Gross domestic product (GDP)
• Gross national income (GNI)
• Human capital
• Human Development Index
(HDI)

Concepts for Review (Continued)
• Imperfect market
• Incomplete information
• Infrastructure
• Least developed countries
• Low-income countries (LICs)
• Middle-income countries
• Newly industrializing countries
(NICs)
• Purchasing power parity (PPP)
• Research and development
(R&D)
• Resource endowment
• Terms of trade
• Value added
• World Bank

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