Researching developing countries a data resource guide for social scientists

Researching
Developing Countries


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Researching
Developing Countries
A Data Resource Guide for Social
Scientists

FORREST D. WRIGHT

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Copyright © 2016 Forrest Daniel Wright. Published by Elsevier Ltd. All rights reserved.
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Notices
Knowledge and best practice in this field are constantly changing. As new research and
experience broaden our understanding, changes in research methods, professional practices,
or medical treatment may become necessary.
Practitioners and researchers must always rely on their own experience and knowledge
in evaluating and using any information, methods, compounds, or experiments described
herein. In using such information or methods they should be mindful of their own safety
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To the fullest extent of the law, neither the Publisher nor the authors, contributors, or
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methods, products, instructions, or ideas contained in the material herein.
ISBN: 978-0-08-100156-1 (Print)
ISBN: 978-0-08-100217-9 (Online)
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ABOUT THE AUTHOR
Forrest Wright is a Data Manager for the Global Entrepreneurship Monitor
(GEM). He has published articles and reviews in the Journal of Business and
Finance Librarianship and D-Lib Magazine. He possesses a BA in History
from Clark University and a MSLIS from Drexel University. He lives in
Philadelphia.

vii


PREFACE
This book was conceived in large part out of a personal interest in world
affairs. The other part came out of a need for this type of book aimed at
social scientists who study, evaluate, and compare countries. Often, social
scientists turn to the same data resources (typically the World Bank, UN,
and IMF) to analyze countries—particularly developing ones—and may
not be aware of other resources covering similar topics. Additionally, social
scientists may not pay attention to how their research data was collected
and transformed, perhaps out of a false belief that all data released by
major international organizations is completely reliable, or because accompanying data notes can be frankly intimidating.
This book attempts to address these issues by discussing as many data
sources as possible in the social sciences (including the major sources as
well as lesser-known ones), and by placing emphasis on the methodology
used to develop the data source. The hope is that by reading sections of
this book, researchers will approach each data source with a richer understanding of their possible use as well as their potential limitations.

ix

ACKNOWLEDGMENT
To my always supportive parents.

xi


INTRODUCTION
Every year, hundreds, maybe thousands of books and articles are written
exploring the reason why certain countries develop the way they do. Why
are some countries rich while others are poor? Why are some countries
democracies? Why are some countries demographically and culturally
diverse while others are homogenous? And how do you measure a country’s true quality of life?
Social scientists debate these questions (among many others) and
have come up with just as many explanations. Some prominent examples
include Acemoglu and Robinson (2012) who argue that the inclusiveness of institutions and support for the rule of law explains the difference
in prosperity between nations. Diamond (1998) posits that geographic
and environmental conditions have fostered the relative development of
humans and societies, as opposed to any artificial cultural or governmental
explanation. While Fukuyama (2014) contends that nation building cannot be transposed from one state to the next; historical developments and
other unique circumstances explain why countries develop differently.
Other social scientists pay less attention to governance and material
prosperity as the primary indicators of a country’s success. Instead, they
evaluate a country’s development through the relative well-being of its
inhabitants and other holistic measures. The primary example is of Sen
and Nussbaum’s (2011) “capabilities approach” to evaluating a country’s
success. Beyond material wealth, a nation succeeds when its inhabitants
have long and healthy lives, where freethought and creativity are supported, and participation in politics and society is encouraged. Wilkinson
and Pickett (2010) argue that income equality plays the primary role in

determining a country’s success in areas of physical and mental health, violence, and overall cohesion.
Whatever the argument or theory, social scientists need to support
their work using high-quality data and statistics. Today, that task has never
been easier as more resources are going online and made accessible within
a reasonable time frame. And this does not just apply to the well-known
institutional data suppliers like the UN and the World Bank. There are
many other high-quality databases developed and managed by independent and nonprofit organizations, academic institutions, and think tanks.

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xiv

Introduction

Going forward, researching and analyzing countries will be much easier as
well as more diverse thanks to the surge in data resources going online.
This book is for social scientists and students of the social sciences. It
is an attempt to guide you through the many data sources available for
assessing countries, with an emphasis on developing countries. It attempts
to be as inclusive as possible in terms of topics of interest to social scientists, as well as diverse as possible on the range of quality data resources for
those topics. The book also assumes that the user has at least some understanding of data concepts.
Each chapter represents a broad topic of social science research,
which is divided by subtopics. Most chapters begin with a description of
“General Resources,” which due to their scope cover several aspects of
the topic and would be confusing to separate individually. In order to help
researchers navigate the General Resources section, most entries offer a
“Topics Covered” entry, which provides the user with a sense of the data
content available in the resource. When the Topics Covered is omitted, it is
because the title of the resource is descriptive enough to render such additional notes redundant.

This book places a strong emphasis on discussing the sources and
methodology used to develop each resource. Social scientists (and librarians assisting them) should be aware of these elements because the “who,
what, and how” of a data resource can seriously impact its overall quality
as well as its appropriateness for a research project. Therefore, when possible, each entry typically includes a “Scope and Methodology” section.


CHAPTER 1

Human Development
GENERAL RESOURCES
United Nations
Human Development Indexes
/>Topics Covered: Life expectancy; health; education; income;
income inequality
Description

The UN collects data on human development from a range of sources
and produces several annual topical indexes. These indexes cover general
human development, gender inequality, gender development, and multidimensional poverty in over 180 countries. The UN develops these indexes
by compiling and weighing several human development-related indicators.
It should be noted that no one index can fully capture the true state of
human development in a particular country. The UN itself admits this and
encourages users to use several resources as well as understand the possible
shortcomings of development data when researching this topic. The scope
and methodology for each index is discussed in greater detail below.
Scope and Methodology

Tables 1–3 in the UN database of the UN’s Human Development site
all relate to the UN’s “headline” Human Development Index (HDI). At
its core, the HDI strives to measure a country’s average achievements

in three basic areas of human development: living a long and healthy
life, having access to knowledge, and having a decent standard of living.
Accordingly, the composite indicators of a country’s HDI reflect these
three goals, which are all weighed equally in its calculation. The resulting
HDI is based on a 0–1 scale, normalized, where 1 equals a perfect HDI
score. These indicators include a country’s life expectancy at birth, mean
years of schooling, expected years of schooling, and gross national income
(GNI) per capita. Both the life expectancy data and GNI were adjusted in
the most recent index year, 2013, to reflect new population data collected
Researching Developing Countries. DOI: />Copyright © 2016 Forrest Daniel Wright. Published by Elsevier Ltd. All rights reserved.

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Researching Developing Countries

by the UN population division, as well as new purchasing power parity
(PPP) conversion rates published by the World Bank. The data used for the
component indicators of the HDI was collected by the UN’s Department
of Economic and Social Affairs (UNESA) and UNESCO which compile
statistics from national statistical offices and other sources; Barro and Lee’s
International Educational Attainment Dataset; and from the World Bank
and IMF for GNI data.
Data Source

Human Development Index  Table 1 in the UN database, Human
Development Index and Its Components, contains final HDI for 187
countries and additional aggregated regions, as well as data on the HDI’s

composite indicators. Users will see that the countries are ranked by their
HDI score, and grouped by their development status from “very high”
to “low.” The data is presented as a table and can be downloaded as an
Excel file. Table 2 in the UN database, Human Development Index Trends,
provides each country’s HDI score at various time intervals, from 1980
to the present. Users have more visualization options for this trending
index, including being able to view the data as a map, or by a range of
charts. Additionally, the data can be downloaded in a range of file formats,
including CSV, JSON, XML, RDF, or RSS among others.
Inequality-Adjusted Human Development Index Table 3 in the
UN database, Inequality-Adjusted Human Development Index (IHDI),
attempts to evaluate a country’s achievements in the areas of life expectancy,
educational attainment, and income like the HDI, but taking into account
how these goals are distributed equal among its entire population. This is
achieved utilizing a method that “discounts” each indicator’s average value
according to various dimensions of inequality (for a full explanation, see
Alkire & Foster: The IHDI table then contains
each country’s original HDI score, its newly calculated IHDI score, and
how much inequality has impacted its score as a percentage of “loss” from
the original HDI score. Additionally, the IHDI table contains “Coefficient of
Human Inequality” figures, which represent the average inequality of health,
education, and income of a country, as estimated by averaging the dimensions of inequality. Users can view IHDI data as a map, or by a range of
charts under “visualize.” Additionally, the data can be downloaded in a range
of file formats, including CSV, JSON, XML, RDF, or RSS among others.


Human Development

3

World Bank
World Development Indicators: People
/>Topics Covered: Millennium Development Goals; population;
education; health; reproductive health; employment; mortality;
unemployment; social protection; gender; demographics; poverty;
income
Description

The World Bank’s World Development Indicators (WDI) project transforms economic and human development data from 214 countries into
comparable cross-country indicators. The WDI is highly influential
in development circles, and the World Bank’s release of its annual WDI
report often catches the eyes of policy makers and journalists. The annual
WDI report is released in April of each year, while the online database is
updated three times a year. The WDI is divided into six segments: World
View, People, Environment, Economy, States and Markets, and Global
Links. Below I will discuss the “People” section.
Scope and Methodology

As part of its annual WDI project, the World Bank provides human
development indicators for over 200 countries within the “People” section. Specifically, this series of indicators covers the topics of education,
health, jobs, social protection, and gender; as well as population, poverty,
and prosperity. Many of these indicators are used in measuring the UN’s
MDG. Depending on the indicator, the WDI may provide disaggregated
socioeconomic and gender variables, such as age, gender, and wealth status.
Most indicators range in coverage from approximately 2000 to 2013 or
present, though some vary depending on the scope of the indicator and
the data availability. The WDI’s most recent release for 2015 includes a
new indicator: Shared Prosperity. This indicator measures the income of a
country’s bottom 40% of wealth population, and calculates its annualized
growth rate from a previous baseline year per capita.

User Guide

By clicking on the specific indicator of interest, users can view the related
data in a table for all countries with available data. Typically, each indicator contains several related figures either disaggregated by age, gender,
and wealth, or in terms of measurement (e.g., GDP per capita and GDP


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Researching Developing Countries

PPP). Users can download the data table in Excel or PDF at the top right
of the page.
Data for the WDI’s “People” indicators is collected from multiple
sources. For a detailed description of the data sources and methodology for calculation, please consult the WDI’s most recent report (http://
data.worldbank.org/sites/default/files/wdi-2014-book.pdf) and find the
“About the Data” section under the People chapter.

United Nations
DevInfo Database
/>Topics Covered: Demographics; development assistance; income;
education; literacy; energy; environment; water; pollution; health;
diseases; information and communication technologies; gender
Scope and Methodology

The UN’s DevInfo Database provides the official UN statistics used to
monitor countries’ progress toward their MDG. These goals cover eight
areas related to human development, such as the eradication of poverty,
hunger, and preventable diseases; promotion of universal education gender
equality; and progress toward sustainability in almost every country and territory in the world. The data is collected from reporting agencies (typically

national statistics offices) in each country charged with monitoring MDG.
Users can view the list of reporting agencies with related links in the
DevInfo Catalog ( />User Guide

Users can access the DevInfo data through three search options: Quick
Data Search, Topic, and Area. The Quick Data Search allows users to
search for MDG data by keyword. The search box autopopulates as users
begin typing. Once the user has selected the data they are looking for,
they can add it to their “cart” then view the data in a table. From the
table, users can visualize the data in a variety of charts or download it in
Excel. Users who may not know what specifically they are looking for can
use the Topic search, which allows them to view all the MDGs organized into topics. Once a selection is made, they can view the results and
again add the data to their “cart” to view it in the table. Similarly, the Area
search option allows viewers to sort by country, and view the resulting
data as a table.


Human Development

5

UNICEF
Statistics and Monitoring
/>Topics Covered: Children; women; vulnerable populations; health;
life expectancy; education; nutrition
Scope and Methodology

UNICEF, a UN program dedicated to providing assistance for children
and mothers in developing countries, provides data on children and vulnerable populations for 195 countries and territories. UNICEF collects
this data in part through their Multiple Indicator Cluster Surveys (MCIS),

which polls households in more than 100 low- and middle-income countries. The MCIS is used to develop internationally comparable data on
more than 100 indicators assessing children and women’s situation in areas
of education, health, gender equality, rights, and protection. The MCIS
has been executed four times (1995–1996, 2000–2001, 2005–2006, 2009–
2012), and a fifth is currently being completed and should be available in
September 2015. Other data provided by the UN is drawn from sources
maintained by UNICEF’s network of 140 in-country offices. All UNICEF
data is updated annually.
User Guide

UNICEF’s statistics and monitoring customized tables allow users to view
specific data on children and women by country, groups of countries, or
regions. Next, users can select from a range of indicators, organized by
topic and release. Users will note that each indicator group contains the
acronym “SOWC,” which stands for State of the World’s Children, an annual
report published by UNICEF that uses this data to identify trends for children and women of the world. Therefore, the years associated with the
SOWC reflect that year’s most recently available data. Users can select
from indicators according to a range of topics. The “Basic Indicators” represent some of the more used and all-encompassing indicators, including
under-five mortality rates, infant mortality rates, annual number of births,
and life expectancy among others. Additionally, users can select from 13
other indicator categories, including nutrition, HIV/AIDs, education, and
child protection among others, all of which contain several related indicators. Once a location and indicator (or set of indicators) have been
selected, the results are displayed in a table. Users can download these
results in Excel.


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Researching Developing Countries

Social Progress Imperative
Social Progress Index
/>Topics Covered: Well-being; human needs; opportunity
Scope and Methodology

The Social Progress Imperative represents the international Social Progress
Network, which partners institutions and governments in promoting social and environmental progress. The Imperative’s Social Progress
Index measures multiple dimensions of human progress in 131 countries,
based on 52 indicators. These indicators cover the three dimensions of
progress according to the Social Progress Imperative: basic human needs,
foundations of well-being, and opportunity. These three dimensions are
evaluated based on related indicators collected from international organizations ranging from the World Health Organization (WHO), Institute for
Economics and Peace, and World Bank among many others. To see a list of
the indicators and their associated data sources used to develop the Index,
users should consult the data definitions page ( Each indicator is weighed within its
social progress component. According to the Social Progress Imperative,
the Index uses a principal component analysis method to determine how
best to weigh each indicator for a holistic assessment of each country.
Each country is scored on a scale of 0 to 100 by each component of social
progress, and then given a total score based on their performance in each
of those components, also on a 0–100 scale. The most recent Index was
released in 2015 and includes more countries and indicators compared to
the 2014 release.
User Guide

From the Social Progress Index’s homepage, users will see a map color
coded to represent each country’s total index score. Above the map, users
can select the Performance or Data Table tabs for comparative views of
how countries fared from best to worst. Users looking for specific data
on how each country fared by individual components of social progress

can select “By Component” at the top of the page. Users can download
the entire dataset for 2015 in Excel format by selecting “export” to the
right of the page. Additionally, the Social Progress Index offers a companion annual report. This report is available under “Findings” (http://www.
socialprogressimperative.org/data/spi/findings).


Human Development

7

EDUCATION
United Nations Educational, Scientific and Cultural
Organization (UNESCO)
UNESCO Institute for Statistics—Education
/>Topics Covered: International students; out-of-school children; school completion; school participation; literacy; school
resources; teaching resources; study abroad
Scope and Methodology

The UNESCO Institute for Statistics (UIS) provides comprehensive education data for nearly 200 countries. The 14 categories covered in the
UNESCO education database include figures on out-of-school children,
participation, progression and literacy rates; educational attainment, international student mobility (study abroad); human and financial resources;
school resources and teaching conditions (for Africa only) adult education
(for Latin America and the Caribbean only), total school-age population,
information on school system entrance age and expected duration. There
are several indicators within each category that provide disaggregated population data such as the age, gender, and level of education, depending on
the specific indicator.
UIS collects its education data from official national statistical offices
who respond to annual questionnaires covering educational topics. This
data is reviewed and developed into internationally comparable indicators.
UIS will sometimes generate estimates for missing data when possible,

based on information found in other reliable sources of national education data. When this occurs, it is indicated next to the data point with a ǂ
symbol to represent a UIS estimate. When data is missing in the database
entirely, it is most likely because the UIS did not receive all data necessary
to calculate the indicator for that country and year. All UIS education data
is updated three times a year to reflect new data points or to revise previous data. The database covers from 1970 to the present, though not all
countries have data dating back that far.
User Guide

Users can access UIS educational data by browsing through the 14 categories mentioned above and selecting individual indicators. This brings
users to the UIS database where they can view education figures for each
country in a table. The default view is for 1999 to the present, however


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Researching Developing Countries

this time range can be expanded by selecting “Time” to the left of 1999 in
the table. The data can be visualized as a map, bar chart, line graph, or scatter plot under the “Draw Chart” menu at the top of the page. Users can
also view the other education indicators from this screen by selecting from
the list of categories on the left. All data can be downloaded in Excel, CSV,
or XML format.

International Association for the Evaluation of Education
Achievement
IEA Study Data Repository
/>Topics Covered: International student assessment; literacy;
mathematics; science; civics; computer science
Scope and Methodology

The International Association for the Evaluation of Education
Achievement (IEA) is a nongovernmental organization that implements
comparative research studies in partnership with nearly 70 IEA member
countries, both from the developed and developing world. Studies cover a
variety of subjects, including math and science, reading literacy, civics, and
computer science and information technology. Not all members participated in all studies; rather they range from a couple to dozen countries participating to more than 50, depending on the scope and content study. On
behalf of its members, the IEA manages and makes accessible the results of
international education studies through the IEA Study Data Repository.
The IEA Study Data Repository hosts results from CivED, ICCS,
ICILS, Joint TIMSS & PIRLS, PIRLS, PrePIRLS, RL II, SITES, TIMSS,
TIMSS Advanced, and TED international comparative studies. These acronyms may not mean much to users outside the world of international
education studies, so the following section describes these studies and their
scope.
Civics Tests: The CivED is a one-time 1999 study on civics for grades 8
and 12; the ICCS (International Civic and Citizenship Education Study)
is an irregularly occurring test, completed once in 2009, and occurring
again in 2016 for grades 8 and 9.
Computer Science and Technology: The ICILS (International Computer
and Information Literacy Study) is a one-time 2013 study for grade 8; the
SITES study (Second Information Technology in Education Study) has
occurred in both 2006 and 2013, but does not focus on a specific grade.


Human Development

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Mathematics and Science: The TIMSS (Trends in International
Mathematics and Science Study) study occurs every four years, with the
most recent results from 2011 (the 2015 is underway). TIMSS includes

results from grades 4 and 8. TIMSS Advanced measures mathematics and
physics competency for students in their final year of secondary school. It
has occurred in 1995 and 2008, with a 2015 module underway.
Reading Literacy: The PIRLS (Progress in International Reading
Literacy Study) study occurs every five years, with the most recent results
from 2011 (a 2016 study is in preparation). PIRLS assesses literacy for
grade 4 students.
User Guide

Users can access the study data by selecting “Search” from the IEA Study
Data Repository. This brings them to the list of studies mentioned above.
By clicking on the particular study, the user can choose the grade and year
of study they’d like to view, as well as the countries and scoring classification system they’d like to compare. Once these selections are made, the
data can be downloaded in SAS or SPSS format, along with supporting
documentation. The user can name the download, add it to their basket,
then click “View Basket” to download the actual files.

Barro Lee Educational Attainment Dataset
/>Topics Covered: International students; educational attainment
The Educational Attainment Dataset developed by well-known economists Robert J. Barro and Jong-Wha Lee provides data on educational
attainment for 146 countries from 1950 to 2010. The data is disaggregated by sex, and is divided into five-year age intervals. The data for this
dataset was collected from a range of censuses and surveys as compiled
by UNESCO, Eurostat, and other sources. According to Barro and Lee,
missing educational observations have been estimated by forward and
backward extrapolations of the available data. For a full description of the
dataset and its methodology, users should consult Barro and Lee’s explanatory paper available in: The dataset is regularly updated when new data is made available, as evidenced by
recent updates highlighted on the site’s homepage.
Users can access the Barro and Lee data by selecting “Data Query”
at the top of the page. The user is then given two options: Full Dataset,
which allows users to download educational datasets (to be discussed);

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Researching Developing Countries

or Country Report, where users can view all available education data at
the individual country level, using filters for time, gender, age group, and
education level. The Full Dataset option allows users to download crosscountry education data in one of three categories: attainment for population aged 15 and over, 25 and over, or by age group in five-year intervals.
Each of these categorical datasets can be downloaded in Excel, CSV, or
State file format.

HEALTH
World Health Organization
Global Health Observatory Data Repository
/>Topics Covered: Millennium Development Goals; mortality;
public health; urban health; diseases; infectious diseases; injuries;
violence; child health; health systems
Scope and Methodology

The WHO, an agency of the UN, is often the go-to organization for
global health data. For data-driven users, the WHO provides a massive
data repository called the Global Health Observatory (GHO) covering a
range of topical categories, including: health-related MDG, mortality figures, public health and environment, health equity, urban health, neglected
tropical diseases, substance abuse and mental health, infectious diseases,
violence, HIV/AIDs, and tuberculosis among other topics. Within each
category, users can view specific indicators and datasets. The repository
covers all 193 member states of the WHO. Most countries have data from
the mid-1990s onwards, however some countries provide data going back
to the late 1970s. The data on each topic has been collected primarily

from official registers and surveys from each member state. Datasets in the
repository are updated regularly to reflect the most recent available data.
User Guide

Depending on the dataset, users will either be able to view the data in a
straightforward table format, or will have to view the data via an external site (with a link provided). For example, within the category, Urban
Health, users can navigate to “Health Risk Factors” to view tobacco consumption data according to education level, sex, and wealth for WHO
countries, presented in a table. While in the category Infectious Diseases,


Human Development

11

and the dataset “Influenza virological surveillance data since 1995,” users
are linked to the WHO’s FluNet database. Similarly, depending on the
dataset, users can typically download their results data in Excel or CSV
format, as well as HTML, XML, and JSON formats. The WHO has also
developed an application program interface (API) for its GHO data.

Demographic and Health Surveys Program
StatCompiler
/>Topics Covered: International health surveys; household health
surveys; fertility; family planning; diseases; nutrition; gender
Scope and Methodology

The Demographic and Health Surveys (DHS) Program, funded primarily by US Agency for International Development (USAID) and implemented by ICF International, collects and disseminates data on health
and population trends in developing countries through detailed surveys.
These surveys, called DHS, are administered in-country and typically
include 5000 to 30,000 households per sample. The DHS surveys cover

the topics of fertility, family planning, maternal and child health, gender,
HIV/AIDS, malaria, and nutrition. Each survey iteration selects from new
households and some questions may change over time (in this instance, the
coded variable for the old question is not reused, so as to avoid confusion
in studies over time). The survey results are coded, then weighed and calculated to develop nationally representative indicators (for a detailed discussed of data collection and methodology, please visit the Data Collection
page: DHS surveys have been conducted in around 90 countries. Some countries have
submitted surveys very recently, while others have not submitted a survey
in over a decade or longer. Users can view the type and dates of surveys
submitted by each country in the “Where We Work” section of the site
( This
might be a good starting point if users want to get a sense of what data is
even available for their country of interest.
User Guide

The DHS StatCompiler ( allows users to view
indicators developed for DHS survey responses. From the homepage,
users can choose to display the data as a table, column chart, line graph,


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Researching Developing Countries

thematic map, or scatter plot. Within, users can select a country or group
of countries, and then associated indicators covering the areas of fertility,
family planning, maternal and child health, gender, HIV/AIDS, malaria,
and nutrition. Users can select from a list of the most popular indicators
used by researchers, or search for them via a search function or through a
list of categories. The results page displays the data and offers some additional visualization functions to further filter the data. The results data can
be downloaded in Excel.

For users looking for the raw data used to develop the DHS indicators,
the DHS offers a list of available datasets that users can download (http://
www.dhsprogram.com/data/available-datasets.cfm). Within each country,
there are zipped raw files in a variety of formats (STATA, SPSS, SAS, and
flat file format) available for download. Datasets not available in this list
can be requested for access, which may or may not be granted depending on the purpose of the research. To do so, users must register at: http://
www.dhsprogram.com/data/new-user-registration.cfm.

INCOME INEQUALITY AND POVERTY
OECD
Inequality Indicators
/>Topics Covered: Income inequality; poverty; household income;
Gini coefficients
Scope and Methodology

The OECD provides two indicators, Income Inequality and Poverty
Rates, for OECD member countries. In order to accurately compare
inequality and poverty figures between countries, household income has
been defined as the total income received by a household less current
taxes and transfers, and adjusted for size so that a 1:1 equivalence exists
between countries’ households. Income data is collected by the OECD
through a standardized questionnaire submitted to individual countries’
statistical offices. For a list of each country’s exact source of household
income data, users should consult the metadata page for this database:
/>Inequality Indicators  The Income Inequality Indicator offers a series
of household income figures designed to demonstrate various levels of


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13

inequality. The default view is a chart of Gini coefficients for each OECD
country, a measurement scale of 0 to 1, where 0 represents complete
equality of income in a country and 1 represents 1 person having all of
the income in a particular country. Users can also view the ratio of the
highest household income levels compared to the lowest and median
household levels. These views are available by selecting from one of the
interdecile measures under “Perspectives.” The data ranges from 1974 to
2011 (most recent date available), though not all countries have data for
the earlier years. The data can be visualized in a chart or table format and
downloaded as an Excel file.
Poverty Indicators  The Poverty Rates Indicator provides ratios of the
number of people whose income falls below the poverty line, which as a
blunt measure is considered half the median household income of the total
population. Users can view the poverty rate of an OECD country for the
total population or for only people of ages 0–17 (under the “Perspectives”
button). The data ranges from 1974 to 2011 (most recent date available),
though not all countries have data for the earlier years. The data can be
visualized in a chart or table format and downloaded as an Excel file.

United Nations
Multidimensional Poverty Index
/>Topics: Poverty; household surveys; human deprivation; health;
education; standards of living
Scope and Methodology

The UN’s Multidimensional Poverty Index (MPI) identifies and measures
the multiple deprivations experienced by households and individuals in
poverty. The MPI is based on household surveys in 91 countries covering the topics of health, education, and standard of living, where certain

criteria constitute a “deprivation” of poverty. For health, the criterion for
deprivation is having at least one household member who is malnourished or a child who has died; for education, it is having no household
member who has completed six years of school, as well as having at least
one school-age kid who is not attending school; and for standard of living,
any of the following criteria constitutes deprivation: not having electricity,
clean water, adequate sanitation, clean fuel sources for cooking, a dirt floor,
and not owning a mode of transportation. Each of these components


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Researching Developing Countries

indicators is calculated and weighed within the categories of health, education, and standard of living for all households in a country. The resulting MPI value for a country represents the mean deprivation scores for all
households in a survey, so an MPI of 0.33 (or 33%) means that households
in that the population in that country is very likely to suffer from at least
one deprivation of poverty. MPI values from closer to 0 means low levels
of multidimensional poverty in a country, while those higher than 0.5
means severe levels of poverty. The calculation of MPI is a bit complicated,
so for a full description of methodology, users are encouraged to read the
technical notes, section 5, here: />hdr14_technical_notes.pdf).
User Guide

Table 6 on the UN’s Human Development Data site, MPI, contains 91
countries, with their corresponding MPI value and the most recent year of
household survey data available. Because not all surveys are administered
at the same time, it is difficult to make cross-country comparisons, and
for that reason the countries are not “ranked” like the UN’s HDI table. In
addition to MPI values, each country in the table possesses corresponding poverty figures, including the intensity of deprivation (representing the
level of MPI within only poor households, a subset of the entire population), population near multidimensional poverty, population in severe poverty, and the contribution of education to poverty. The MPI data can be

downloaded as an Excel file.

GENDER
United Nations
Gender Inequality Index
/>Topics Covered: Gender inequality; reproductive health; female
empowerment; education; female labor market participation;
female political participation
Scope and Methodology

The Gender Inequality Index (GII) strives to measure a country’s level
of gender inequality in the areas of reproductive health, empowerment,
and labor market participation. To develop a country’s GII value, UN uses
maternal mortality ratios and adolescent birth rate as proxy indicators of


Human Development

15

reproductive health; share of seats held by females in a country’s parliament as well as secondary education participation indicators for empowerment; and finally, female labor market participation rates. GII values range
from 0 to 1, with 0 representing full equality for women. The UN collects
maternal mortality rates from their Maternal Mortality Estimation Group
(MMEIG), which represents a joint statistical collaboration between the
WHO, UNICEF, UNFPA, and the World Bank; adolescent birth rates
from the UNDESA; educational statistics from both UNESCO as well as
Barro and Lee’s International Educational Attainment Dataset; parliamentary participation rates from the International Parliamentary Union; and
labor participation rates from the International Labor Organization (ILO).
User Guide

Table 4 of the UN’s Human Development Site, Gender Inequality Index
(GII), contains final GII scores for most of the 187 countries in the table.
The countries are ranked according to their HDI ranking, accompanied
by their corresponding GII value and performance on the indicators
noted above. The data can be downloaded as an Excel file.

United Nations
Gender-Related Development Index
/>Topics Covered: Gender gap; female achievement; male
achievement; education; health
Scope and Methodology

The Gender-Related Development Index (GDI) strives to measure the
gender gap in countries. The GDI is similar to the GII, however it makes
more explicit comparisons between female and male achievements to
assess a country’s gender gap. The UN accomplishes this by comparing
health outcomes, measured by female and male life expectancy at birth;
education, measured by female and male expected years of schooling for
children, as well as female and male mean years of schooling for adults of
ages 25 and older; and command over resources, measured by female and
male estimated earned income. To develop GDI, the UN calculates each
country’s HDI, for men and women separately, and therefore the GDI is
represented as the “ratio of female to male HDI” in the table. This ratio is
expressed on a scale of 0 to 1, where 1 represents full parity. The data for
life expectancy rates is collected from UNDESA, data on education from


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Researching Developing Countries

UNESCO as well as Barro and Lee’s International Educational Attainment
Dataset, and economic data from the ILO, UNDESA, and World Bank.
User Guide

Table 5 of the UN’s Human Development site, Gender-Related
Development Index (GDI) contains female-to-male ratio of HDI for most
of the 187 countries in the table. Countries are organized by their HDI
rank, accompanied by their related gender indicators. The data can be
downloaded as an Excel file.

FINANCIAL ACCESSIBILITY
International Monetary Fund
Financial Access Survey
Topics Covered: Financial inclusion; financial access for vulnerable populations; mobile banking; physical banking; bank
accounts; loans; debt
Scope and Methodology

The IMF’s Financial Access Survey (FAS) database provides data on
households and business’ ability to access financial services. The FAS currently contains financial accessibility for 189 countries, dating from 2004
to 2013. The data is collected from surveys distributed by the IMF, which
cover both the geographical outreach and use of financial services. The
geographical outreach indicators include the number of financial institutions, branches (excluding branches), ATMs, and mobile money outlets
in a given country. The financial services indicator covers the number of
depositors, deposits accounts, borrowers, and loan accounts; as well as the
value of outstanding deposits, loans, and mobile money accounts. It should
be noted that in 2014, the IMF began surveying and reporting on mobile
banking access, which has become increasingly popular (and important) in
many developing countries that do not have a strong enough financial system to support many traditional banks.
User Guide

Users can access the FAS by selecting its box from the IMF’s Data Portal
( and selecting “More” on the
bottom right. This brings users to the FAS’ homepage, where one can