Researching developing countries a data resource guide for social scientists

Researching Developing Countries Chandos Information Professional Series Series Editor: Ruth Rikowski (email: Rikowskigr@aol.com) Chandos’ new series of books is aimed at the busy information professional They have been specially commissioned to provide the reader with an authoritative view of current thinking They are designed to provide easy-to-read and (most importantly) practical coverage of topics that are of interest to librarians and other information professionals If you would like a full listing of current and forthcoming titles, please visit www.chandospublishing.com New authors: we are always pleased to receive ideas for new titles; if you would like to write a book for Chandos, please contact Dr Glyn Jones on g.jones.2@ elsevier.com or telephone +44 (0) 1865 843000 Researching Developing Countries A Data Resource Guide for Social Scientists FORREST D WRIGHT AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Chandos Publishing is an imprint of Elsevier Chandos Publishing is an imprint of Elsevier 225 Wyman Street, Waltham, MA 02451, USA Langford Lane, Kidlington, OX5 1GB, UK Copyright © 2016 Forrest Daniel Wright Published by Elsevier Ltd All rights reserved No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein) 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 and the safety of others, including parties for whom they have a professional responsibility To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein ISBN: 978-0-08-100156-1 (Print) ISBN: 978-0-08-100217-9 (Online) British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress For information on all Chandos Publishing visit our website at http://store.elsevier.com/ 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 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 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 xiii 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 Human Development GENERAL RESOURCES United Nations Human Development Indexes http://hdr.undp.org/en/data 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 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: http://dx.doi.org/10.1016/B978-0-08-100156-1.00001-8 Copyright © 2016 Forrest Daniel Wright Published by Elsevier Ltd All rights reserved CONCLUSION Recently, social scientists have expanded their research beyond their immediate fields to better understand the development of countries Economists use environmental data to assess the total impact of rapid development for example, while political scientists dig into demographic data to try to assess future political turmoil This trend will likely continue in future—providing a more holistic evaluation of countries’ development This book was written in part to respond to this trend; so that social scientists can better understand all the resources available to them—inside or outside their immediate field I hope you found this book useful With more data on developing countries going online every year, it is important to both be aware of all the resources at your disposal as well as to know how those resources were developed By expanding the breadth of possible resources for your research while acknowledging the strengths and limitations of that data, scholarship on developing countries will improve 135 BIBLIOGRAPHY Acemoglu, D., & Robinson, J (2012) Why nations fail: The origins of power, prosperity, and poverty New York, NY: Crown Alix-Garcia, J., Bartlett, A., & Saah, D (2013) The landscape of conflict: IDPs, aid and landuse change in Darfur Journal of Economic Geography, 589–617 Bauder, J (2014) The reference guide to data sources Chicago, IL: American Library Association Blonigen, B A., & Piger, J (2014) Determinants of foreign direct investment Canadian Journal of Economics, 47(3), 775–812 Brückner, M., & Ciccone, A (2010) International commodity prices, growth and the outbreak of civil war in sub-Saharan Africa* The Economic Journal, 120, 519–534 Darley, W (2012) Increasing sub-Saharan Africa’s share of foreign direct investment: Public policy challenges, strategies, and implications Journal of African Business, 13(1), 62–69 Diamond, J (1998) Guns, germs, and steel: The fates of human societies New York, NY: W.W Norton Diarra, G., & Plane, P (2014) Assessing the World Bank’s influence on the good governance paradigm Oxford Development Studies, 1–15 Djankov, S., & Reynal-Querol, M (2010) Poverty and civil war: Revisiting the evidence Review of Economics and Statistics, 1035–1041 Finkel, S., Pérez-Liñán, A., & Seligson, M (2007) The effects of U.S foreign assistance on democracy building, 1990–2003 World Politics, 59(3), 404–439 Fukuyama, F (2013) What is governance? Governance, 26(3), 347–368 Fukuyama, F (2014) Political order and political decay: From the industrial revolution to the globalization of democracy New York, NY: Farrar, Straus and Giroux Giannone, D (2010) Political and ideological aspects in the measurement of democracy:The Freedom House case Democratization, 17(1), 68–97 Gil, E., & Reyes, A (2013) International business research: Strategies and resources Lanham, MD: Scarecrow Press Gaoussou, D., & Plane, P (2014) Assessing the World Bank’s influence on the good governance paradigm Oxford Development Studies, 42(4), 473–487 Hendrix, C., & Salehyan, I (2012) Climate change, rainfall, and social conflict in Africa Journal of Peace Research, 49(1), 35–50 Hessami, Z (2014) Political corruption, public procurement, and budget composition: Theory and evidence from OECD countries European Journal of Political Economy, 34, 372–389 Kalenborn, C., & Lessmann, C (2013) The impact of democracy and press freedom on corruption: Conditionality matters Journal of Policy Modeling, 35(6), 857–886 Kapur, D (2014) Political effects of international migration Annual Review of Political Science, 17, 479–502 Nussbaum, M (2011) Creating capabilities: The human development approach Cambridge, MA: Belknap Press of Harvard University Press Piketty, T., & Goldhammer, A (2014) Capital in the twenty-first century Cambridge, MA: Belknap Press of Harvard University Press Seifert, J., Carlitz, R., & Mondo, E (2013) The Open Budget Index (OBI) as a comparative statistical tool Journal of Comparative Policy Analysis: Research and Practice, 15(1), 87–101 Shortland, A., Christopoulou, K., & Makatsoris, C (2013) War and famine, peace and light? The economic dynamics of conflict in Somalia 1993–2009 Journal of Peace Research, 545–561 137 138 Bibliography Ward, M.D., et al (2013) Comparing GDELT and ICEWS event data Retrieved from: http://mdwardlab.com/sites/default/files/GDELTICEWS_0.pdf Wijeweera, A., & Webb, M (2011) Military spending and economic growth in South Asia: A panel data analysis Defence and Peace Economics, 22(5), 545–554 Wilkinson, R., & Pickett, K (2010) The spirit level:Why greater equality makes societies stronger New York, NY: Bloomsbury Press Wright, F (2015) IMF.org Journal of Business and Finance Librarianship, 20(3) Zhao, F., Collier, A., & Deng, H (2014) A multidimensional and integrative approach to study global digital divide and e-government development Information Technology & People, 27(1), 38–62 INDEX A ACI See Armed Conflict and Intervention (ACI) ACLED See Armed Conflict Location & Event Data (ACLED) Adult Population Survey (APS), 123 AfDB See African Development Bank (AfDB) African conflict DACS, 84–85 University of Denver, 85 African Development Bank (AfDB), 37–38 AfroBarometer survey, 129 Aging populations, 20–21 AidData, 107–108 AidFlows, 108–110 Air, 97 Annual Report Questionnaire (ARQ), 19 APS See Adult Population Survey (APS) ArabBarometer survey, 129–130 Armed Conflict and Intervention (ACI), 74 datasets, 74–75 Armed Conflict Location & Event Data (ACLED), 77–79 ARQ See Annual Report Questionnaire (ARQ) Asian Development Bank, 37 AsianBarometer survey, 130 Asylum seekers, 93–94 A.T Kearney, 43–44 B Barro Lee Educational Attainment Dataset, 9–10 BEC See Broad Economic Category (BEC) Bertelsmann Foundation, 61 Bertelsmann Transformation Index (BTI), 61 Borders, 125 BP See British Petroleum (BP) BREAD See Bureau for Research and Economic Analysis of Development (BREAD) Breugel, 54–55 British Petroleum (BP), 115–116 Broad Economic Category (BEC), 41 BTI See Bertelsmann Transformation Index (BTI) Bureau for Research and Economic Analysis of Development (BREAD), 22–23 C Carbon Dioxide Information Analysis Center (CDIAC), 101 CCAPS See Climate Change and African Political Stability Program (CCAPS) CCKP See Climate Change Knowledge Portal (CCKP) CDIAC See Carbon Dioxide Information Analysis Center (CDIAC) Center for International Earth Science Information Network (CIESIN), 96 Center for Systemic Peace, 73–74 Centre for Research on the Epidemiology of Disasters (CRED), 104 CHARLS See China Health and Retirement Longitudinal Study (CHARLS) Chicago Project on Security & Terrorism (CPOST), 82 China Health and Retirement Longitudinal Study (CHARLS), 22–23 CIESIN See Center for International Earth Science Information Network (CIESIN) CivED, Civics tests, Climate, 97 Climate change CDIAC, 101 UNDP, 101–102 World Bank, 100–101 WRI, 99–100 Climate Change and African Political Stability Program (CCAPS), 108 Climate Change Knowledge Portal (CCKP), 100–101 139 140 Index Climatic Research Unit (CRU), 100 Computer science and technology, Comtrade Database, 40–42 Conference Board, 30–31 Confidence Index, FDI, 43–44 Conflict See also African conflict ACLED, 77–79 Center for Systemic Peace, 73–74 COW, 71–72 empirical studies, 81–82 GDELT project, 80–81 IEP, 79–80 INSCR datasets, 74–75 SIPRI databases, 75–77 UCDP, 72–73 Correlates of War Project (COW), 71–72 Corruption, 66–67 Corruption Perceptions Index (CPI), 66–67 Country Policy and Institutional Assessment (CPIA), 58–59 COW See Correlates of War Project (COW) CPI See Corruption Perceptions Index (CPI) CPIA See Country Policy and Institutional Assessment (CPIA) CPOST See Chicago Project on Security & Terrorism (CPOST) CRED See Centre for Research on the Epidemiology of Disasters (CRED) Crime, 18–20 CRU See Climatic Research Unit (CRU) D DACS See Data on Armed Conflict and Security (DACS) Darfur Damaged and Destroyed Villages dataset, 125 Data Dashboard, 107–108 Data on Armed Conflict and Security (DACS), 84–85 Data Portal, 38 Data Query tool, 38 Data Sharing for Demographic Research (DSDR), 94 Democracy, 129–132 Demographic and Health Surveys Program (DHS Program), 11–12, 90 Demographics demography data, 89 migration and refugees DSDR, 94 MPI, 94 OECD, 92–93 UNHCR, 93–94 United Nations, 91–92 OECD, 89–90 UN Department of Economic and Social Affairs, 87–88 UNHDP, 90 US Census, 88–89 Density, 127 Development finance, 107–108 DHS Program See Demographic and Health Surveys Program (DHS Program) Direction of Trade Statistics (DOTS), 39–40 Disasters, 104–105 Domestic demand forecast, 35–36 DOTS See Direction of Trade Statistics (DOTS) Drugs, 18–20 DSDR See Data Sharing for Demographic Research (DSDR) E Earth Explorer, 125 Economics exchange rates, 54–55 FDI, 42–44 financial markets, 53–54 general resources Conference Board, 30–31 IMF, 28–29 Maddison Project, 33–34 OECD, 29–30, 35–36 PWT, 31–33 St Louis Federal Reserve, 34–35 trading economics, 36–37 World Bank, 25–28 household spending and inflation OECD, 51–53 industry GGDC 10-Sector Database, 48–49 United Nations, 49–51 labor Index ILO, 44–47 KILM, 46–47 OECD, 47–48 regional resources AfDB, 37–38 Asian Development Bank, 37 IADB, 38–39 trade IMF, 39–40 United Nations, 40–42 EDACS datasets, 84–85 Education Barro Lee educational attainment dataset, 9–10 IEA, 8–9 UNESCO, 7–8 Educational Attainment Dataset, EFCs See Entrepreneurial Framework Conditions (EFCs) E–government, 69 EIA See US Energy Information Administration (EIA) EKS method See Elteto, Koves, and Schultz method (EKS method) Elections guide, 65–66 IDEA, 66 IFES, 65–66 Elteto, Koves, and Schultz method (EKS method), 31 EM-DAT See International Disaster Database Energy BP, 115–116 IEA, 113–114 UN Energy Statistics Database, 114–115 Entrepreneurial Framework Conditions (EFCs), 123–124 Entrepreneurship GEM, 123–124 World Bank, 124 Environment See also Climate change environmental data, 96 EPI, 96 GFN, 98–99 OECD, 96–98 protected areas, 105 World Bank, 95–96 141 Environmental Performance Index (EPI), 96 EPA See US Environmental Protection Agency (EPA) EPI See Environmental Performance Index (EPI) Estimates of Migration dataset, 92 Exchange rates, 54–55 F FAO See United Nations Food and Agriculture Organization (FAO) FAS See Financial Access Survey (FAS) FDI See Foreign Direct Investment (FDI) Federal Reserve’s Economic Data tool (FRED tool), 34–35 Fertility, 88–89 Financial Access Survey (FAS), 16–17 Financial accessibility IMF, 16–17 World Bank, 17–18 Financial Inclusion Database See Global Findex Database Financial markets, 53–54 Food and water See also Environment disasters, 104–105 FAO, 102–103 United Nations Water Indicators, 103 Food security indicators, 102–103 Foreign aid AidData, 107–108 AidFlows, 108–110 USAID, 110–111 Foreign assistance data, 110–111 Foreign Direct Investment (FDI), 42, 107 A.T Kearney, 43–44 OECD, 43 World Bank, 42–43 Forest, 97 FRED tool See Federal Reserve’s Economic Data tool (FRED tool) Freedom House, 61–62 G GADM See Global Administrative Areas (GADM) GBAORD See Government budget appropriations or outlays for RD (GBAORD) 142 Index GDDS See General Data Dissemination System (GDDS) GDELT project See Global Database of Events, Language, and Tone project (GDELT project) GDI See Gender-Related Development Index (GDI) GDP data See Gross Domestic Product data (GDP data) Geary-Khamis dollars (GK dollars), 31, 33 GEM See Global Entrepreneurship Monitor (GEM) Gender GDI, 15–16 GII, 14–15 Gender Inequality Index (GII), 14–15 Gender-Related Development Index (GDI), 15–16 General Data Dissemination System (GDDS), 28 Geography See also Urban development GADM, 126 GeoNames, 126 US Department of State, 125–126 US Geological Survey, 125 GFN See Global Footprint Network (GFN) GFS See Government Finance Statistics (GFS) GGDC See Groningen Growth and Development Centre (GGDC) GHCN See Global Historical Climatology Network (GHCN) GHG emissions See Greenhouse gas emissions (GHG emissions) GHO See Global Health Observatory (GHO) GII See Gender Inequality Index (GII) GK dollars See Geary-Khamis dollars (GK dollars) Global Administrative Areas (GADM), 126 Global AgeWatch Index, 20–21 Global Attitudes Survey, 131–132 Global Database of Events, Language, and Tone project (GDELT project), 80–81 Global Entrepreneurship Monitor (GEM), 123–124 Global Findex, 17–18 Global Findex Database, 17–18 Global Footprint Network (GFN), 98–99 Global Health Observatory (GHO), 10 Global health observatory data repository, 10–11 Global Historical Climatology Network (GHCN), 100 Global Metro Monitor [2014], 127–128 Global Migration Database, 91–92 Global Peace Index (GPI), 79–80 Global Roads Open Access Data Set, Version (gRoadsv1), 117–118 Global Terrorism Database (GTD), 79, 83 START, 83–84 Global Terrorism Index (GTI), 79 Globalbarometer Surveys, 129 AfroBarometer, 129 ArabBarometer, 129–130 AsianBarometer, 130 LatinoBarometer, 130–131 GNI See Gross National Income (GNI) Google BigQuery, 81 Governance, 129–130 Bertelsmann Foundation, 61 corruption, 66–67 e-government, 69 elections IDEA, 66 IFES, 65–66 Freedom House, 61–62 government spending and budget IMF, 62–64 OBS, 64–65 Open Spending, 65 World Bank, 62–63 media freedom, 68–69 QoG Institute, 59–60 Rule of Law, 67–68 V-Dem project, 60–61 World Bank CPIA, 58–59 WGIs, 57–58 Government budget appropriations or outlays for RD (GBAORD), 122 Index Government Finance Statistics (GFS), 63–64 Government spending and budget IMF, 62–64 OBS, 64–65 Open Spending, 65 World Bank, 62–63 GPI See Global Peace Index (GPI) Greenhouse gas emissions (GHG emissions), 99–100 gRoadsv1 See Global Roads Open Access Data Set,Version (gRoadsv1) Groningen Growth and Development Centre (GGDC), 49 10-Sector Database, 48–49 Gross Domestic Product data (GDP data), 35–36 Gross National Income (GNI), 1–2, 25–26, 29–30 GTD See Global Terrorism Database (GTD) GTI See Global Terrorism Index (GTI) H Harmonized Coding and Description System (HS), 41 HBS See Household Budget Surveys (HBS) HCTB See High Casualty Terrorist Bombings (HCTB) HDI See Human Development Index (HDI) Health DHS Program, 11–12 WHO, 10–11 Health Risk Factors, 10–11 Help Age International, 20–21 HIES See Household Income and Expenditure (HIES) High Casualty Terrorist Bombings (HCTB), 75 HIU See Humanitarian Information Unit (HIU) Household debt, 51 financial assets, 52 143 income, 12 net worth, 52 Household Budget Surveys (HBS), 102–103 Household Income and Expenditure (HIES), 102–103 Household spending and inflation OECD household disposable income data, 51–52 prices/inflation data, 52–53 Household surveys, 21 BREAD, 22–23 IHSN, 22 HS See Harmonized Coding and Description System (HS) Human development aging and older populations, 20–21 crime and drugs, 18–20 education Barro Lee educational attainment dataset, 9–10 IEA, 8–9 UNESCO, 7–8 financial accessibility IMF, 16–17 World Bank, 17–18 gender GDI, 15–16 GII, 14–15 health DHS Program, 11–12 WHO, 10–11 household surveys, 21–23 income inequality and poverty OECD, 12–13 United Nations, 13–14 information and technology, 21 resources social progress imperative, 6–7 UNICEF, 5–6 United Nations, 1–5 World Bank, 3–4 Human Development Index (HDI), 1–2 “Human Index” files, 81 Humanitarian Information Unit (HIU), 125–126 144 Index I IADB See Inter-American Development Bank (IADB) IAEA See International Atomic Energy Agency (IAEA) IATI See International Aid Transparency Initiative (IATI) IBP See International Budget Partnership (IBP) ICCS See International Civic and Citizenship Education Study (ICCS) ICILS See International Computer and Information Literacy Study (ICILS) ICT See Information and communications technology (ICT) IDB See International Data Base (IDB) IDEA See Institute for Democracy and Electoral Assistance (IDEA) IDPs See Internally displaced persons (IDPs) IDSB See Industrial Demand-Supply Balance Database (IDSB) IEA See International Energy Agency (IEA) IEP See Institute for Economics & Peace (IEP) IFES See International Foundation for Electoral Systems (IFES) IFLS See Indonesia Family Life Survey (IFLS) IFS See International financial statistics (IFS) IHDI See Inequality-Adjusted Human Development Index (IHDI) IHDS See India Human Development Survey (IHDS) IHSN See International Household Survey Network (IHSN) ILO See International Labor Organization (ILO) IMF See International Monetary Fund (IMF) Income inequality and poverty OECD, 12–13 United Nations, 13–14 India Human Development Survey (IHDS), 22–23 Indicators Database, 131–132 Indonesia Family Life Survey (IFLS), 22–23 Industrial Demand-Supply Balance Database (IDSB), 50 Industry GGDC 10-Sector Database, 48–49 United Nations, 49–51 Inequality indicators, 12–13 Inequality-Adjusted Human Development Index (IHDI), Information and communications technology (ICT), 21 Information and technology, 21 Infrastructure investment, 116 OECD, 116–117 SEDAC, 117–118 World Bank, 117 Innovation intellectual property USPTO, 120 WIPO, 119–120 R&D OECD, 120–122 World Bank, 122–123 INSCR datasets See Integrated Network for Societal Conflict Research datasets (INSCR datasets) Institute for Democracy and Electoral Assistance (IDEA), 66 Institute for Economics & Peace (IEP), 79–80 Integrated Network for Societal Conflict Research datasets (INSCR datasets), 74 ACI datasets, 74–75 Matrix dataset, 75 State Fragility Index, 75 Intellectual property USPTO, 120 WIPO, 119–120 Inter-American Development Bank (IADB), 38–39 Internally displaced persons (IDPs), 93 Index International Aid Transparency Initiative (IATI), 107–108 International Atomic Energy Agency (IAEA), 114 International Budget Partnership (IBP), 64–65 International Civic and Citizenship Education Study (ICCS), International Computer and Information Literacy Study (ICILS), International Data Base (IDB), 88–89 International Disaster Database, 104–105 International dollar, 33 International Energy Agency (IEA), 96, 113–114 International financial statistics (IFS), 28–29 International Foundation for Electoral Systems (IFES), 65–66 International Household Survey Network (IHSN), 22 International Labor Organization (ILO), 14–15, 38, 44 ILOSTAT database, 45–46 International Monetary Fund (IMF), 16– 17, 28–29, 39–40, 62–63 GFS, 63–64 World Bank, 62–63 International programs data, 88–89 International Standard Industrial Classification (ISIC), 50 International Telecommunications Union (ITU), 21 International Transportation Forum (ITF), 116 International Union for Conservation of Nature (IUCN), 105 International Water Management Institute (IWMI), 100 ISIC See International Standard Industrial Classification (ISIC) ITF See International Transportation Forum (ITF) ITU See International Telecommunications Union (ITU) IUCN See International Union for Conservation of Nature (IUCN) 145 IWMI See International Water Management Institute (IWMI) K Key Indicators of Labor Market (KILM), 44, 46–47 KILM See Key Indicators of Labor Market (KILM) L Labor ILO, 44–47 KILM, 46–47 OECD, 47–48 Labor Force Survey (LFS), 45 Labor productivity (LP), 31 LABORSTA database, 44 Latin Macro Watch, 38–39 LatinoBarometer survey, 130–131 Law Index, WJP, 67–68 LFS See Labor Force Survey (LFS) Limited liability companies (LLCs), 124 Living Standard Measurement Surveys (LSMS), 102–103 LLCs See Limited liability companies (LLCs) LP See Labor productivity (LP) LSMS See Living Standard Measurement Surveys (LSMS) M Maddison Project, 33–34 Maintenance, infrastructure, 116–117 Malawi Longitudinal Study of Families and Health (MLSFH), 22–23 Mapping, 125–126 Maternal Mortality Estimation Group (MMEIG), 14–15 Mathematics, Matrix dataset, 75 MCIS See Multiple Indicator Cluster Surveys (MCIS) Media freedom, 68–69 Mexico Peace Index, 79 Migration indicators, 92 and refugees 146 Index Migration (Continued ) United Nations, 91–92 DSDR, 94 MPI, 94 OECD, 92–93 UNHCR, 93–94 Migration Policy Institute (MPI), 94 Military aid, 110 Mining and Utilities Statistics Database (MINSTAT), 50 MINSTAT See Mining and Utilities Statistics Database (MINSTAT) MLSFH See Malawi Longitudinal Study of Families and Health (MLSFH) MMEIG See Maternal Mortality Estimation Group (MMEIG) Mortality, 88, 90 MPI See Migration Policy Institute (MPI); Multidimensional Poverty Index (MPI) Multidimensional Poverty Index (MPI), 13–14 Multifactor productivity, 48 Multiple Indicator Cluster Surveys (MCIS), N NABS See Nomenclature for Analysis and Comparison of Scientific Programmes and Budgets (NABS) National Center for Atmospheric Research (NCAR), 100 National Centers for Environmental Prediction (NCEP), 100 National Expert Survey (NES), 123–124 National Income Data, 29–30 National Income Dynamics Study (NIDS), 22–23 National Oceanographic and Atmospheric Agency (NOAA), 84–85 NCAR See National Center for Atmospheric Research (NCAR) NCEP See National Centers for Environmental Prediction (NCEP) NES See National Expert Survey (NES) NIDS See National Income Dynamics Study (NIDS) NOAA See National Oceanographic and Atmospheric Agency (NOAA) Nomenclature for Analysis and Comparison of Scientific Programmes and Budgets (NABS), 122 O OBS See Open Budget Survey (OBS) ODA See Official development assistance (ODA) OECD See Organisation for Economic Co-operation and Development (OECD) Official development assistance (ODA), 109 OLADE See Organización Latinoamericana de Energía (OLADE) Older populations, 20–21 “Online Data Analysis” tool, 130–131 OPEC See Organization of Petroleum Exporting Countries (OPEC) Open Budget Survey (OBS), 64–65 Open Spending, 65 Organisation for Economic Co-operation and Development (OECD), 12–13, 43, 50, 89–90, 92–93 air, 97 business enterprise R&D, 121 climate, 97 environmental data, 96 government budgets on R&D, 122 gross domestic expenditure on R&D, 121 household disposable income data, 51–52 infrastructure, 116–117 prices/inflation data, 52–53 R&D personnel by sector, 121 RDS, 120–121 water, 97–98 Organización Latinoamericana de Energía (OLADE), 114 Organization of Petroleum Exporting Countries (OPEC), 114 P Patents, statistics on, 119 PCMDI See Program for Climate Model Diagnosis and Intercomparison (PCMDI) Index Penny World Table (PWT), 31–33 Pew Research Center scope and methodology, 131 user guide, 131–132 PGIS See Pinkerton Global Intelligence Services (PGIS) Pinkerton Global Intelligence Services (PGIS), 84 PIRLS See Progress in International Reading Literacy Study (PIRLS) Political participation, 64–66 Political violence, 74 Population division data, 87–88 Poverty indicators, 13 PPI See Producer price indices (PPI) PPP See Purchasing power parity (PPP) Principal Investigator, 132 Producer price indices (PPI), 52–53 Productivity data, 47–48 Program for Climate Model Diagnosis and Intercomparison (PCMDI), 100 Progress in International Reading Literacy Study (PIRLS), Protected areas, 105 Protected planet, 105 Public Opinion Globalbarometer Surveys, 129–131 Pew Research Center, 131–132 WVS, 132–133 Purchasing power parity (PPP), 1–2, 31–32 PWT See Penny World Table (PWT) Q QoG Institute See Quality of Governance Institute (QoG Institute) QPSD See Quarterly Public Sector Debt (QPSD) Quality of Governance Institute (QoG Institute), 59–60 Quarterly Public Sector Debt (QPSD), 62–63 “Question Search” section, 131–132 R R&D See Research and development (R&D) RAND Corporation, 82–83 147 RAND Corporation Database of Worldwide Terrorism Incidents (RDWTI), 83 RDS See Research and Development Statistics (RDS) RDWTI See RAND Corporation Database of Worldwide Terrorism Incidents (RDWTI) Reading literacy, Real effective exchange database, 54–55 Real effective exchange rate (REER), 54–55 REER See Real effective exchange rate (REER) Research and development (R&D), 120–121 OECD, 120–122 World Bank, 122–123 Research and Development Statistics (RDS), 120–121 Research datasets, 108 Resources social progress imperative, 6–7 UNICEF, 5–6 United Nations, 1–5 World Bank, 3–4 Rule of Law, 67–68 S Sanitation, 127 Savings rate, 30 SCAD See Social Conflict in Africa Database (SCAD) Science, SDBS See Statistical Database System (SDBS) SDDS See Special Data Dissemination Standard (SDDS) SEDAC See Socioeconomic Data and Applications Center (SEDAC) Sexual Violence in Armed Conflict (SVAC), 85–86 SIPRI See Stockholm International Peace Research Institute (SIPRI) SITC See Standard International Classification (SITC) 148 Index Social Conflict in Africa Database (SCAD), 85 Social progress imperative, 6–7 index, 6–7 Society data, 89–90 Socioeconomic Data and Applications Center (SEDAC), 117–118 Special Data Dissemination Standard (SDDS), 28 St Louis Federal Reserve, 34–35 Standard International Classification (SITC), 41 StatCompiler, 11–12 State Fragility Index, 75 Statistical Country Profiles, 120 Statistical Database System (SDBS), 37 Statistical Online Population Database, 93–94 Stockholm International Peace Research Institute (SIPRI), 75 arms embargoes database, 77 arms transfers database, 76–77 military expenditure database, 76 multilateral peace operations database, 75–76 SVAC See Sexual Violence in Armed Conflict (SVAC) T TED See Total Economy Database (TED) Terrorism See also Conflict RAND Corporation, 82–83 University of Chicago, 82 University of Maryland, 83–84 TIMSS See Trends in International Mathematics and Science Study (TIMSS) Total Economy Database (TED), 30–31 Trade IMF, 39–40 United Nations, 40–42 Trading economics, 36–37 Transformation index, 61 Transparency International, 66–67 Trends in International Mathematics and Science Study (TIMSS), U UCDP See Uppsala University’s Conflict Data Program (UCDP) UEA See University of East Anglia (UEA) UIS See UNESCO Institute for Statistics (UIS) UN See United Nations (UN) UN Department of Economic and Social Affairs, 87–88 UN Energy Statistics Database, 114–115 UN Human Development Reports (UNHDP), 90 UN Industrial Development Organization (UNIDO), 49–51 UN Office of Drugs and Crime (UNODC), 18–20 UN Spatial Data Infrastructure Transport (UNSDI-T), 117–118 UN’s Department of Economic and Social Affairs (UNESA), 1–2 UNDP See United Nations Development Programme (UNDP) UNeGovDD See United Nations E-Government Development Database (UNeGovDD) UNEP See United Nations Environment Programme (UNEP) UNESA See UN’s Department of Economic and Social Affairs (UNESA) UNESCO See United Nations Educational, Scientific and Cultural Organization (UNESCO) UNESCO Institute for Statistics (UIS), UNFCC See United Nations Framework Convention on Climate Change (UNFCC) UNHCR See United Nations High Commissioner for Refugees (UNHCR) UNHDP See UN Human Development Reports (UNHDP) UNICEF, 5–6 UNIDO See UN Industrial Development Organization (UNIDO) Unit labor costs, 48 Index United Nations (UN), 1, 13–14 Comtrade Database, 40–42 DevInfo Database, 4–5 E–government, 69 Estimates of Migration dataset, 92 GDI, 15–16 GII, 14–15 Global Migration Database, 91–92 HDI data source, 2–3 development, scope and methodology, 1–2 migration indicators, 92 UNIDO, 49–51 United Nations Development Programme (UNDP), 101–102 United Nations E-Government Development Database (UNeGovDD), 69 United Nations Educational, Scientific and Cultural Organization (UNESCO), 7–8 United Nations Environment Programme (UNEP), 105 United Nations Food and Agriculture Organization (FAO), 98, 102–103 United Nations Framework Convention on Climate Change (UNFCC), 97 United Nations High Commissioner for Refugees (UNHCR), 93–94 United Nations Water Indicators, 103 University of Chicago, 82 University of East Anglia (UEA), 100 University of Maryland, 83–84 UNODC See UN Office of Drugs and Crime (UNODC) UNSDI-T See UN Spatial Data Infrastructure Transport (UNSDI-T) Uppsala University’s Conflict Data Program (UCDP), 72–73 Urban development See also Geography Brookings Institute, 127–128 World Bank, 127 US Agency for International Development (USAID), 11, 110–111 US Census, 88–89 149 U.S Committee for Refugees and Immigrants (USCRI), 74 US Department of State, 125–126 US Energy Information Administration (EIA), 99 US Environmental Protection Agency (EPA), 99 US Geological Survey, 125 US Patent and Trademark Office (USPTO), 120 USAID See US Agency for International Development (USAID) USCRI See U S Committee for Refugees and Immigrants (USCRI) USPTO See US Patent and Trademark Office (USPTO) V V-Dem project See Varieties of Democracy project (V-Dem project) Value added by activity, 29 Varieties of Democracy project (V-Dem project), 60–61 Violence datasets, 81–82 Voter Turnout Database, 66 W Waste, 97 Water, 97–98 WCO See World Customs Organization (WCO) WDI See World Development Indicators (WDI) WDPA See World Database on Protected Areas (WDPA) WGIs See Worldwide Governance Indicators (WGIs) WHO See World Health Organization (WHO) WIPO See World Intellectual Property Organization (WIPO) WJP See World Justice Project (WJP) World Bank, 3–4, 17–18, 25–28, 42–43, 53–54, 62–63, 122–123, 127 CCKP, 100–101 CPIA, 58–59 entrepreneurship data, 124 150 Index World Bank (Continued ) Global Financial Development, 53–54 infrastructure, 117 WDI, 25–28, 95–96 science and technology, 122 WGIs, 57–58 World Customs Organization (WCO), 41 World Database on Protected Areas (WDPA), 105 World Development Indicators (WDI), 3, 25, 95–96, 117, 122, 127 Economy, 25–26 Global Links, 27 science and technology, 122 States and Markets, 26–27 transport services, 117 World Health Organization (WHO), 6, 10–11, 103 World Intellectual Property Organization (WIPO), 119–120 World Justice Project (WJP), 67–68 World Pop, 90 World population trends dataset, 87–88 World Press Freedom Index, 68–69 World Resources Institute (WRI), 99–100 World Values Survey (WVS), 132 scope and methodology, 132 user guide, 132–133 Worldwide Governance Indicators (WGIs), 57–58 WRI See World Resources Institute (WRI) WVS See World Values Survey (WVS) Y Yale Center for Environmental Law and Policy (YCELP), 96 ... International Educational Attainment Dataset; parliamentary participation rates from the International Parliamentary Union; and labor participation rates from the International Labor Organization... 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,... (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