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[国际统计年鉴] 世界宏观数据库链接总结(Markus Eberhardt)   [推广有奖]

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Aggregate Economy DataThe [color=rgb(0, 137, 201) !important]Penn World Table (PWT) data compiled by the Center for International Comparison at UPenn is the standard dataset for cross-country analysis of aggregate growth and development. The latest version from August 2009 (PWT 6.3) covers 189 countries for some or all of the years 1950-2007. Base year is 2005. There is also a discussion of the changes made to previous versions, which addresses some of the problems with the data raised by [color=rgb(0, 137, 201) !important]Johnson, Larson,  Papageorgiou and Subramanian (2009). Whether analysing the aggregate economy is the right thing to do is a different question...
March 2011: The last UPenn PWT has just been published (after 2012 PWT will be jointly maintained by Robert Feenstra at UC-Davis, and Marcel Timmer and Robert Inklaar at the University of Groningen): [color=rgb(0, 137, 201) !important]Penn World Table version 7. The data covers 189 countries and territories for 1950-2009, with 2005 as reference year. The official reference is "Heston, Robert Summers and Bettina Aten, Penn World Table Version 7.0, Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania, March 2011."

The World Bank [color=rgb(0, 137, 201) !important]International Comparison Program (ICP)  collected data in 100 (developing and emerging) economies, divided into five regions, and then combined these with a Eurostat-OECD PPP program, bringing the total to 146 economies. Like the PWT these are PPP data, and given the same base year (2005) they now can be combined, compared and contrasted. Coverage: gross domestic product (GDP), GDP per capita, household consumption, collective government consumption, and capital formation for all 146 economies. Estimates aer based on national surveys that priced nearly 1,000 products and services. Comparative price levels are also included. Downside: this isn't a panel. 2005 is the first year this exercise was undertaken, 2011 will be the next wave.

The World Bank has recently published its annual World Development Report, which this year focuses on [color=rgb(0, 137, 201) !important]Conflict, Security and Development. A dedicated [color=rgb(0, 137, 201) !important]website makes the data underlying the analysis in the report easily accessible. The excel spreadsheet covers a total of 211 countries, with maximum coverage over the years 1960-2009. The data is not limited to conflict and political economy issues but also covers geography, colonial history and foreign aid among other topics. All of the data is publicly available (and many datasets are featured here on MEDevEcon), but the unique advantage here is bringing a vast number of conflict-related data from dozens of sources (PRIO, UNHCR, Polity IV, etc.) together in a single spreadsheet (and doing a great job documenting the data and sources.

Fulvio Castellacci and Jose Miguel Natera have created a balanced panel dataset for cross-country analyses of national systems, growth and development ([color=rgb(0, 137, 201) !important]CANA) hosted by the Norwegian Institute of International Affairs. The originality of this dataset (which draws on a variety of sources) is in that the gaps in the data have been filled, using a methodology of multiple (and repeated) imputations by two political scientists, Honaker and King (2010). I have not looked at the [color=rgb(0, 137, 201) !important]Castellaci & Natera paper describing the data construction and robustness checks in detail, but am a priori quite sceptical about imputations: these macro variables are likely to be integrated, so imputations could be rather misleading. On the other hand, missing data is a serious problem for a lot of the dimensions they consider: (1) Innovation and technological capabilities; (2) Education and human capital; (3) Infrastructures; (4) Economic competitiveness; (5) Social capital; (6) Political and institutional factors. There are a total of 41 indicators for 134 countries over the period 1980-2008. The data is in excel format and well-documented. I'd say keep an eye out for reviews and applications of this dataset.

The World Bank has recently reorganised access to the major cross-country panel datasets it produces, all of which are now available (for browsing or download) from a single [color=rgb(0, 137, 201) !important]website. [Gunilla Patterson featured the new site on her excellent[color=rgb(0, 137, 201) !important]devdata website]

[color=rgb(0, 137, 201) !important]World Population, GDP and Per Capita GDP, 1-2003 AD compiled by Angus Maddison at the Groningen Growth & Development Centre (GGDC).
Jerry Dwyer at the Federal Reserve Bank of Atlanta provides [color=#089c9 !important]data from his 2006 Economic Inquiry article with Scott L. Baier and Robert Tamura. This covers output, physical and human capital for 145 countries over a long time horizon (1831-2000); the data provides between 2 and 17 time-series observations per country, with an average of around 7. Additional variables of particular interest include average age and experience of the workforce, which allow for Mincerian wage equation-type analysis at the macro level. The data is provided in a neat excel file with additional information on variable definition and construction also provided (along with the article).

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The UNIDO [color=rgb(0, 137, 201) !important]World Productivity Database compiled by Anders Isaksson at the UN Industrial Development Organisation. Contrary to my initial assumption (oh, bliss), this data does not refer to manufacturing, but to the aggregate economy. Coverage is from 1960 to 2000 for 112 countries. The website is mainly a tool to compute TFP, so you don't really get access to the 'raw' data.

Michael Clemens (CGD) and Lant Prichett (HKS) have produced an interesting alternative measure to per capita income/GDP: 'income per natural' — the mean annual income of persons born in a given country, regardless of where that person now resides. The data is a cross-section for 2000 and the related paper is [color=rgb(0, 137, 201) !important]here. I copied that data into an [color=rgb(0, 137, 201) !important]excel filefor ease of use.

The World Bank [color=rgb(0, 137, 201) !important]PovcalNet is an interactive tool to calculate poverty lines and compare them across countries.

[color=rgb(0, 137, 201) !important]Wikiprogress is the official platform for the OECD-hosted Global Project on "Measuring the Progress of Societies" and[color=rgb(0, 137, 201) !important]Wikiprogress.Stat allows users to upload their data and metadata, and to navigate through a robust database of progress indicators. Themes on the website include Ecosystems Condition, Human Well-Being, Economy, Social and Welfare Statistics and Peace. There's a wealth of indicators here (sometimes cross-sectional or limited to a few time-series observations) and the data sources are clearly identified. Available for download to Excel. [Thanks to Angela Costrini Hariche, OECD Development Centre and Statistics Directorate and Project Manager of Wikiprogress]

The World Bank [color=rgb(0, 137, 201) !important]Doing Business project 'provides objective measures of business regulations and their enforcement across 181 economies and selected cities at the subnational and regional level.' The raw data for these surveys (run from 2004 onwards but with varying coverage for individual countries) is available via [color=rgb(0, 137, 201) !important]summary reports, which can then be accessed in excel.

Many of the above are featured on the resource website [color=rgb(0, 137, 201) !important]Macro Data 4 Stata which homogenises several commonly used macroeconomic datasets and imports them into Stata. The project is run by Giulia Catini, Ugo Panizza and Carol Saadeand started uploading .dta files fairly recently. The library at present includes data from the Penn World Table and the Groningen Growth and Development Data Centre. The [color=rgb(0, 137, 201) !important]AAA Codes dataset looks particularly handy for anybody doing cross-country analysis  [thanks to Aid-man [color=rgb(0, 137, 201) !important]Nic Van de Sijpe for pointing me to this resource].Without wanting to sound patronising, I applaud anybody's attempts to make data more widely available, so congratulations to a new upstart called Google, offering access to some World Bank, Eurostat and US data on their [color=#089c9 !important]website. Don't try and google "Google data" as you won't find it that way ;-) This resource is useful primarily for their data visualisation tool - for individual variable country series can be graphed as lines over time, bars or with the use of maps [thanks to Paddy Carter at Bristol for the pointer].

Funded by the IADB, the Oxford Latin American Economic History Database ([color=rgb(0, 137, 201) !important]OxLAD) contains statistical series for a wide range of economic and social indicators covering twenty countries in the region for the period 1900-2000. Its purpose is to provide economic and social historians worldwide with a systematic recompilation of available statistical information in a single on-line source. The website also provides other resources including a long list of references, many of them in Spanish, and detailed discussion of the methodology of data construction. Downloads are in csv format.

A useful resource to learn about how macro data is collected (among other things): the UK Economic and Social Data Service (ESDS) has produced [color=rgb(0, 137, 201) !important]'Countries and Citizens: Linking international macro and micro data'. This is "an interactive training resource with online tutorials, activities, study guides and videos, designed to show how to combine socio-economic data from country-level aggregate databanks (macro data) with individual-level survey datasets (micro data). It comprises five units, each of which was written by a subject specialist and has been designed as a self guided learning resource. Though specifically for postgraduates and researchers, it may also be of interest to undergraduates." Unit 2 seems quite useful.

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Country-Specific Macro dataJohn Muellbauer and Janine Aaron at CSAE run a research project on 'Structural Macro-Modelling of the South African Economy' ([color=rgb(0, 137, 201) !important]SMMSAE). They provide a number of indicators and indices they constructed, including FLIB (financial liberalisation) and trade openness indicators in excel/CSV format. The SMMSAE website also links to the papers they have written on macro-modelling for SA.
Marc Muendler at UCSD has brought together a number of useful tools for the analysis of Brazilian [color=#089c9 !important]data (and some data, too). This includes various price indices, sectoral FDI (1980-2000), tariffs and exchange rates.

The Institute for Applied Economic Research (Ipea) in Brazil provides a range of [color=#089c9 !important]macro data
for the country and its regions. The link is for the Portuguese site, there's also an English version. [Thanks to[color=#089c9 !important]Manoel Bittencourt, Senior Lecturer at the University of Pretoria/South Africa
, for the link]

Chinese macro and micro data: when researching provincial FDI I frequently made use of the [color=#089c9 !important]China Data Center at U Michigan. Much of the more recent data (primarily statistical yearbooks for various topics as well as provincial statistical yearbooks) is downloadable as Excel worksheets, whereas the earlier data is available in pdf format. There are also the China Survey Data Network and various census datasets. Researchers at Universities may find that their institution has forked out for the annual subscription fee and that they can access these data without additional cost. Statistical Yearbooks for 1996-2001 were freely accessible at the time of writing.

The Socio-Economic Database for Latin America and the Caribbean ([color=#089c9 !important]SEDLAC) provides statistics on poverty and other distributional and social variables from 25 Latin American and Caribbean countries, based on microdata from households surveys. [Masa featured the new site on his excellent [color=#089c9 !important]Devecondata website]


Cultural and Social Norms and Value, Faith and ReligionThe World Values Survey represents 5 waves of data from the early 1980s to the late 2000s, covering survey data on social norms and values from 87 nations. The [color=rgb(0, 137, 201) !important]data is provided in SPSS, STATA and SAS formats. Variables related to individuals' happiness, how they feel, what is important in their lives, qualities their children should learn etc.

Fulvio Castellacci and Jose Miguel Natera have created a balanced panel dataset for cross-country analyses of national systems, growth and development ([color=rgb(0, 137, 201) !important]CANA
) hosted by the Norwegian Institute of International Affairs. The originality of this dataset (which draws on a variety of sources) is in that the gaps in the data have been filled, using a methodology of multiple (and repeated) imputations by two political scientists, Honaker and King (2010). I have not looked at the [color=rgb(0, 137, 201) !important]Castellaci & Natera paper
describing the data construction and robustness checks in detail, but am a priori quite sceptical about imputations: these macro variables are likely to be integrated, so imputations could be rather misleading. On the other hand, missing data is a serious problem for a lot of the dimensions they consider: (1) Innovation and technological capabilities; (2) Education and human capital; (3) Infrastructures; (4) Economic competitiveness; (5) Social capital; (6) Political and institutional factors. There are a total of 41 indicators for 134 countries over the period 1980-2008. The data is in excel format and well-documented. I'd say keep an eye out for reviews and applications of this dataset.

Robert Barro and Rachel McCleary have compiled a cross-country dataset on the share of religious people in the population. "Adherence fractions of population are shown for 10 religion groups and non-religion (incl. atheists) in 1970, 2000, and 1900 (from Barrett)." Data is available for download in excel format from Barro's Harvard [color=rgb(0, 137, 201) !important]data page. His working paper page offers a considerable number of papers on the topic of religion and growth. [via Masa Kudamatsu's [color=rgb(0, 137, 201) !important]DevEconData blog]

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Human Capital (i): Formal Education/Schooling
The seminal dataset on educational attainment, compiled by Robert Barro and Jong-Wha Lee (the 'Barro-Lee data'), is available from a new dedicated [color=#089c9 !important]website
. The data is available for download in full for 146 countries by 5-year age group or 15 years, 25years, and over in 5-year intervals for the period 1950-2010 (in xls, csv, or dta format). The site also links to some previous versions of the dataset and other resources, including Soto and Cohen (2006) and a few select academic papers [Thanks to [color=#089c9 !important]Adrian Wood
for the pointer to the new site.]


The Washington-based Education Policy and Data Center ([color=#089c9 !important]EPDC) "provides global education data, tools for data visualization, and policy-oriented analysis aimed at improving schools and learning in developing countries." They say they have "the world’s largest international education database with over 3.8 millon data points from 200 countries. The data comes from national and international websites including household survey datasets as well as studies and reports." This is not just macro data, but also household surveys and census data; another very useful thing they do is to provide Stata do-files to construct indicators from the hh data.

Mauro Caselli, Jörg Mayer and Adrian Wood have compiled a unique extension to the Barro-Lee (2001) and Cohen-Soto (2001) data on average adult years of schooling (attainment) using UNESCO data on literacy rates. Missing values are imputed based on a regression model investigating the link between average adult education and literacy rates in the available data and applied to countries where the attainment variable is missing but literacy rates are available.  Of the 133 countries covered, no imputations were needed for 95, imputations for some but not all years for 19, and imputations for all years for 19. The [color=#089c9 !important]link
is for a zipped folder containing Excel and Stata files as well as detailed documentation. The data is applied in a [color=#089c9 !important]paper by Jörg and Adrian
investigating the global impact of China's industrialisation on other LDCs' structural change. [Thanks to [color=#089c9 !important]Adrian Wood for making the data available.]

Marcelo Soto and Daniel Cohen have constructed a rival to the Barro & Lee gold standard of data on average years of schooling across 95 countries. From the abstract of their Journal of Economic Growth [color=#089c9 !important]paper (Vol.12(1), 2007): "We present a[color=#089c9 !important]new dataset for years of schooling across countries for the 1960–2000 period. The series are constructed from the OECD database on educational attainment and from surveys published by UNESCO. Two features that improve the quality of our data with respect to other series, particularly for series in first-differences, are the use of surveys based on uniform classification systems of education over time, and an intensified use of information by age groups."  [thanks to my man [color=#089c9 !important]Fabio Manca for pointing me to this resource].

Christian Morrisson and Fabrice Murtin from the OECD have constructed a historical [color=#089c9 !important]database (entry under 'A century of education') on educational attainment in 74 countries for the period 1870-2010 (decadal estimates), using the perpetual inventory methods before 1960 and then the above Cohen and Soto (2007) database. This data should be particularly interesting in combination with for instance the Maddison data.

Fulvio Castellacci and Jose Miguel Natera have created a balanced panel dataset for cross-country analyses of national systems, growth and development ([color=#089c9 !important]CANA) hosted by the Norwegian Institute of International Affairs. The originality of this dataset (which draws on a variety of sources) is in that the gaps in the data have been filled, using a methodology of multiple (and repeated) imputations by two political scientists, Honaker and King (2010). I have not looked at the [color=#089c9 !important]Castellaci & Natera paper describing the data construction and robustness checks in detail, but am a priori quite sceptical about imputations: these macro variables are likely to be integrated, so imputations could be rather misleading. On the other hand, missing data is a serious problem for a lot of the dimensions they consider: (1) Innovation and technological capabilities; (2) Education and human capital; (3) Infrastructures; (4) Economic competitiveness; (5) Social capital; (6) Political and institutional factors. There are a total of 41 indicators for 134 countries over the period 1980-2008. The data is in excel format and well-documented. I'd say keep an eye out for reviews and applications of this dataset.

Jerry Dwyer at the Federal Reserve Bank of Atlanta provides [color=#089c9 !important]data from his 2006 Economic Inquiry article with Scott L. Baier and Robert Tamura. This covers output, physical and human capital for 145 countries over a long time horizon (1831-2000); the data provides between 2 and 17 time-series observations per country, with an average of around 7. Additional variables of particular interest include average age and experience of the workforce, which allow for Mincerian wage equation-type analysis at the macro level. The data is provided in a neat excel file with additional information on variable definition and construction also provided (along with the article).

A collaborative effort by the IIASA World Population Program and the Vienna Institute of Demography (VID) has reconstructed [color=#089c9 !important]population data by Age, Gender and Level of Educational Attainment for 120 Countries over the 1970-2000 period. The authors use a method which 'backprojects' the past levels from 2000 data. The files are in excel format and there are a number of working papers with technical details, comparison with observed data, etc. [Thanks to my buddy and human capital wizard [color=#089c9 !important]Fabio Manca for the link]

[color=#089c9 !important]Rural and Urban Education
data (1960-1985) by C Peter Timmer is available in Chapter 29, 'Agriculture and economic development', of the Handbook of Agricultural Economics, Volume 2, Part 1, 2002, Pages 1487-1546. The link above is for the IDEAS RePec entry of this article: this is a copyrighted publication, but if you have access to the Handbook through your library you can easily copy the data. The coverage is exclusively for developing countries (N=65), and the data offers average years of schooling per person over the age of 25 for the rural and non-rural areas. OECD data on the same topic should allow for the inclusion of developed countries in the analysis.




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The World Bank [color=#089c9 !important]EdStats (hit Data Query link) provide access to UNESCO Institute for Statistics (UIS) data on education. It presents a large number of indicators for more than 200 countries since 1970. Indicators are organized by category, including Pre-primary, Primary, Secondary, Tertiary, Expenditure, Labor, Population, Teachers and Other. In February 2011 UIS launched [color=#089c9 !important]historical time series data for key indicators of school enrolment and completion (gross enrolment ratios, repetition and completion rates) covering pre-primary to tertiary education. They are reported on a roughly five-year basis since 1970 (some countries more frequently). As far as I could see most of this data ends in the late 1990s... but the other data provided by UNESCO ([color=#089c9 !important]UIS Data Center) begins at the same period - not sure why they didn't bring these together.

The Lynch School of Education at Boston College provides two unique [color=#089c9 !important]resources for comparative analysis of educational achievements: (i) the Trends in International Mathematics and Science Study (TIMMS), which "is the largest and most ambitious international study of student achievement ever conducted" and has data from 40 countries in 1995 and a partially overlapping sample for three more recent waves (next wave is 2011); (ii) the Progress in International Reading Literacy Study (PIRLS), which has waves in 2001, 2006 and 2011 (forthcoming), evaluating 150,000 fourth graders (9- and 10-year-olds) in thirty-five (2001) and fourty-odd (2006) countries. Some of these are middle-income countries (e.g. TTO, MAR, IND, IRN).

The same database provides IMF data on [color=#089c9 !important]public spending on education
, from 1985-2000 for 147 countries (via Gunilla Petterson).  This module presents the IMF data on public spending on education from 1985-2000 for 147 developing and transition economies (excel sheets). There are two indicators in the module: (1) total public spending on education as a percent of GDP; and (2) total public spending on education as a percent of total government spending. The underlying data, in millions of local currency, are provided. The breakdown of total education spending into current and capital spending are provided when available.

Quite a number of years ago Aaron Benavot, now at SUNY Albany, and Phyllis Riddle, now at St Vincent College, PA, wrote an article entitled The Expansion of Primary Education, 1870-1940: Trends and Issues, which provides new estimates of [color=#089c9 !important]primary school enrollment rates
for 126 nations and colonies from 1870 to 1940. The data is printed in the Appendix and can easily be imported into Excel. The article was published in the journal Sociology of Education, Vol.61(3), July 1988, pp.191-210. [via Masa Kudamatsu's [color=#089c9 !important]DevEconData blog]

Emma Smith at the School of Education, University of Birmingham provides a number of [color=#089c9 !important]resources and data links for educational and social research, including Afrobarometer, Asiabarometer, PISA and World Value Survey. Her website acts as a portal for all the sources of secondary data that are listed in her book ('Using Secondary Data in Educational and Social Research', OUP 2008), as well as providing links to new sources and current developments in the field of secondary data analysis.

[color=#089c9 !important]Human Capital Inequality, basically adjustments to the above Barro-Lee data, is provided on Rafael Domenech's website, covering 134 countries from 1960-1999, based on his work with Amparo Castello. This dataset was mentioned on the brilliant[color=#089c9 !important]DEVECONDATA blog.

The World Bank provides [color=#089c9 !important]GenderStats, which basically pulls out the relevant variables from the WDI database. Hit "Create your own query" to access the database. Education/schooling-related variables are often taken as a proxy for gender equality.

UNESCO has data on [color=#089c9 !important]literacy in their data centre, with data series beginning in the mid-70s or early 80s. There are also lots of variables on schooling, and public funding for schooling. Data on the number of illiterates per cohort is available [color=#089c9 !important]here for developing countries from 1970 in 5-year intervals.

The OECD provides access to [color=#089c9 !important]PISA data (Programme for International Student Assessment) for 2000 to 2009 (4 waves). The most recent data wave will be made availabe on 7 December 2010. The data is in SAS, SPSS or Text format and contains student, school and parent information/questions. This is for 30 OECD/high- and middle-income countries. There is a vast number of variables so you had better see for yourself. [via Gunilla Pettersson's [color=#089c9 !important]developmentdata.org]

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Human Capital (ii): Health & Subjective Well-being
The MARA/ARMA (Mapping Malaria Risk in Africa/Atlas du Risque de la Malaria en Afrique) project has published [color=rgb(0, 137, 201) !important]extensive data related to malaria, including the MARA LITe malaria prevalence data, malaria distribution maps and estimated populations at risk (as 'raw data' and maps); also available are entomological inoculation rates and reported presence/absence of six species of the anopheles gambiae group (to you and me: mosquitoes) in Africa and islands. The website also features a wealth of resources on malaria in Africa.

The [color=rgb(0, 137, 201) !important]Global Health Observatory (GHO) database is the World Health Organization's main health statistics repository. You can find a range of health topics like mortality, the burden of disease, infectious diseases, risk factors and health expenditures. I had a quick look at the figures for 'Number of people (all ages) living with HIV' which provides full coverage of mortality rate estimates (i.e. extrapolation/interpolation, etc., distinguished by reporting confidence intervals) for 1990-2009 across a very large number of countries. [referred to in a [color=rgb(0, 137, 201) !important]paper by Paul Calu, World Bank, and Falilou Fall, Sorbonne]

[color=rgb(0, 137, 201) !important]Wikiprogress is the official platform for the OECD-hosted Global Project on "Measuring the Progress of Societies" and[color=rgb(0, 137, 201) !important]Wikiprogress.Stat allows users to upload their data and metadata, and to navigate through a robust database of progress indicators. Themes on the website include Ecosystems Condition, Human Well-Being, Economy, Social and Welfare Statistics and Peace. There's a wealth of indicators here (sometimes cross-sectional or limited to a few time-series observations) and the data sources are clearly identified. Available for download to Excel. [Thanks to Angela Costrini Hariche, OECD Development Centre and Statistics Directorate and Project Manager of Wikiprogress]

The [color=rgb(0, 137, 201) !important]Complex Emergency Database (CE-DAT) is an international initiative that monitors and evaluates the health status of populations affected by complex emergencies. CE-DAT is managed by the Centre for Research on the Epidemiology of Disasters (CRED), based at the School of Public Health of the Université catholique de Louvain in Brussels, Belgium. The data is at subnational level (building on over 2,000 surveys) and covers 1998-2010 (with gaps). It can be viewed in table format or as a map.

The WHO maintains [color=rgb(0, 137, 201) !important]WHOSIS (Statistical Information System) which has data on mortality, health services coverage, inequities in health care access among other rubrics. Time series begin in 1990 but are not annual.

The World Health Organisation (WHO) offers the [color=rgb(0, 137, 201) !important]Global Health Atlas. "In a single electronic platform, the WHO’s Communicable Disease Global Atlas is bringing together for analysis and comparison standardized data and statistics for infectious diseases at country, regional, and global levels... [The database covers] the major diseases of poverty including malaria, HIV/AIDS, tuberculosis, the diseases on their way towards eradication and elimination (such as guinea worm, leprosy, lymphatic filariasis) and epidemic prone and emerging infections for example meningitis, cholera, yellow fever and anti-infective drug resistance."

The World Health Organisation (WHO) offers the [color=rgb(0, 137, 201) !important]Global Atlas of the Health Workforce, which features two datasets: the first, aggregated dataset "includes estimates of the stock (absolute numbers) and density (per 1000 population) of health workers for up to 9 occupational categories." In the second, disaggregated dataset "estimates of the stock of health workers are available for some countries for up to 18 occupational categories, reflecting greater distinction of some categories of workers according to assumed differences in skill level and skill specialization".

The visualisation folk at [color=rgb(0, 137, 201) !important]Gapminder (including multiple Roslings) provide very convenient access to a lot of demographic and health data (HIV/AIDS, birthrates, cancer, ...) alongside other useful development data (aid, trade, employment). "Gapminder is a non-profit venture – a modern 'museum' on the Internet – promoting sustainable global development and achievement of the United Nations Millennium Development Goals... The initial activity was to pursue the development of the Trendalyzer software. Trendalyzer sought to unveil the beauty of statistical time series by converting boring numbers into enjoyable, animated and interactive graphics... In March 2007, Google acquired Trendalyzer from the Gapminder Foundation and the team of developers who formerly worked for Gapminder joined Google in California in April 2007." Poor chaps: New salary = googol*previous salary? The data commonly span several decades and are available for download in excel format (wide). [Thanks to Christoph Lakner at CSAE for the pointer.]



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A bunch of data from the UN DESA - Population Division, including [color=rgb(0, 137, 201) !important]World Contraceptive Use 2010, [color=rgb(0, 137, 201) !important]International Migrant Stock, [color=rgb(0, 137, 201) !important]World Population Prospects, [color=rgb(0, 137, 201) !important]World Urbanization Prospects (very 'open data', these last three: you can pick a max of 5 countries... Muppets)... [Thanks to Jackie Carter for the [color=rgb(0, 137, 201) !important]tweet]

The World Bank’s comprehensive database of [color=rgb(0, 137, 201) !important]Health, Nutrition and Population (HNP) statistics also cover aspects of education and literacy. It offers data on the number of individuals per age cohort. The series nominally begin in 1960 and go to 2006/7 for up to 220 countries, although coverage varies wildly across indicators.
Betsey Stevenson at the Wharton School of UPenn has a bunch of [color=rgb(0, 137, 201) !important]data on subjective well-being, both US and cross-country, which resulted in a couple of papers with her colleague Justin Wolfers. Zipped data is in Stata 9 or 10 format (huge files!).

The Washington-based Center for Global Development (Roodman, Radelet, Subramanian, Birdsall, Clemens and many others) have a [color=rgb(0, 137, 201) !important]link to datasets on their publications website. Highlights include data on African Health Professionals Abroad (Gunilla Petterson worked on this dataset).


Human Capital (iii): Labour & Demography
The Minnesota Population Center is the "world’s leading developer" of [color=#089c9 !important]historical and international census demographic data
, most of which are focused on the US and Western Europe, although the IPUMS (Intergrated Public Use Microdata Series) International data covers 44 countries using 130 censuses.

The International Labor Organization (ILO) maintains the [color=#089c9 !important]LABORSTA
database. This provides data for up to 200 countries under the rubrics of (un-)employment, wages, strikes and lockouts, as well as international labour migration (among others).

The PBL Netherlands Environmental Assessment Agency provides the [color=#089c9 !important]History Database of the Global Environment
(interestingly, the acronym is HYDE). HYDE presents (gridded) time series of population and land use for the last 12,000 years ! It also presents various other indicators such as GDP, value added, livestock, agricultural areas and yields, private consumption, greenhouse gas emissions and industrial production data, but only for the last century.

A bunch of data from the UN DESA - Population Division, including [color=#089c9 !important]World Contraceptive Use 2010, [color=#089c9 !important]International Migrant Stock, [color=#089c9 !important]World Population Prospects, [color=#089c9 !important]World Urbanization Prospects (very 'open data', these last three: you can pick a max of 5 countries... Muppets)... [Thanks to Jackie Carter for the [color=#089c9 !important]tweet]

The visualisation folk at [color=#089c9 !important]Gapminder (including multiple Roslings) provide very convenient access to a lot of demographic and health data (HIV/AIDS, birthrates, cancer, ...) alongside other useful development data (aid, trade, employment). "Gapminder is a non-profit venture – a modern 'museum' on the Internet – promoting sustainable global development and achievement of the United Nations Millennium Development Goals... The initial activity was to pursue the development of the Trendalyzer software. Trendalyzer sought to unveil the beauty of statistical time series by converting boring numbers into enjoyable, animated and interactive graphics... In March 2007, Google acquired Trendalyzer from the Gapminder Foundation and the team of developers who formerly worked for Gapminder joined Google in California in April 2007." Poor chaps: New salary = googol*previous salary? The data commonly span several decades and are available for download in excel format (wide). [Thanks to Christoph Lakner at CSAE for the pointer.]

The [color=#089c9 !important]Complex Emergency Database (CE-DAT) is an international initiative that monitors and evaluates the health status of populations affected by complex emergencies. CE-DAT is managed by the Centre for Research on the Epidemiology of Disasters (CRED), based at the School of Public Health of the Université catholique de Louvain in Brussels, Belgium. The data is at subnational level (building on over 2,000 surveys) and covers 1998-2010 (with gaps). It can be viewed in table format or as a map.

Jerry Dwyer at the Federal Reserve Bank of Atlanta provides [color=#089c9 !important]data from his 2006 Economic Inquiry article with Scott L. Baier and Robert Tamura. This covers output, physical and human capital for 145 countries over a long time horizon (1831-2000); the data provides between 2 and 17 time-series observations per country, with an average of around 7. Additional variables of particular interest include average age and experience of the workforce, which allow for Mincerian wage equation-type analysis at the macro level. The data is provided in a neat excel file with additional information on variable definition and construction also provided (along with the article).

The UN body which covers trade and investment, UNCTAD, has created a snazzy website that combines all of its statistical databases: [color=#089c9 !important]UNCTADstat
has lots of data on trade (merchandise, services), FDI flows and stocks (inward FDI from 1970!), external finance (incl. remittances), labour force/employment, global commodity price indices (from 1960!) as well as some more recent rubrics such as the creative and information economies and maritime transport (from around 2000).


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PovertyThe people at OPHI (Oxford Poverty & Human Development Initiative) have developed a [color=#089c9 !important]new poverty index, which is 'multi-dimensional' (MPI). Sabina Alkire and Maria Emma Santos designed the MPI using a technique for multidimensional measurement created by Sabina Alkire and James Foster. OPHI analysed poverty across 78% of the world’s people in 104 developing countries using the MPI and released the results in advance of the 2010 HDR. For now this is sort of a cross-section, available for download in Excel format.


Migration (incl Tourism and Forced Displacement/Trafficking) and Remittances
[color=rgb(0, 137, 201) !important]Panel Data on International Migration (1975-2000) compiled by Maurice Schiff and Mirja Channa Sjoblom at the World Bank. This includes data on sending and receiving countries, split by 'level of education'.
The [color=#089c9 !important]Global Bilateral Migration Database compiled by the World Bank provides "global matrices of bilateral migrant stocks spanning the period 1960-2000, disaggregated by gender and based primarily on the foreign-born concept... Over one thousand census and population register records are combined to construct decennial matrices corresponding to the last five completed census rounds". Data for up to 226 countries can be downloaded into an excel file.

Giovanni Peri of UC Davis has now published the [color=#089c9 !important]bilateral migration data
used in some of his recent work (aka the Ortega-Peri Database). These can be downloaded in Stata format from Giovanni's personal website where the papers are also available. The data cover 1980-2008, 15 migration destinations in the developed world and 221 migration source countries. [Thanks to [color=#089c9 !important]Chris Parsons
at Oxford's International Migration Institute for the pointer; Chris' own efforts have helped to build a decadal bilateral migration matrix which includes developing economies as recipient countries --- this is the dataset in the entry immediately above]

Other World Bank datasets on migration (no long panels, though) are available [color=#089c9 !important]here.

The World Bank publishes the [color=#089c9 !important]Migration and Remittances Factbook (2011) as part of the OpenData initiative. This covers inflows and outflows of remittances from 1970 to 2009 (+2010 estimated) for basically all countries in the world (naturally: lots of missing observations, but from the mid-1970s onwards the data coverage is pretty impressive).

The Global Trade Policy Analysis group at the AgEcon Department of Purdue University provides a number of datasets related to trade but also climate change and migration. "The GTAP Data Base is a [color=#089c9 !important]fully documented, publicly available global data base which contains complete bilateral trade information, transport and protection linkages among [color=#089c9 !important]113 regions for all [color=#089c9 !important]57 GTAP commodities for a single year (2004 in the case of the GTAP 7 Data Base)." Single academic user licenses for GTAP 7 are $520, but a large number of free datasets (including summaries of GTAP, Social Accounting Matrix [SAM] extraction, the Global [bilateral] FDI Dataset, [color=#089c9 !important]Project on Bilateral Labor Migration, CO2 emissions) can be found [color=#089c9 !important]here.

The International Labor Organization (ILO) maintains the [color=#089c9 !important]LABORSTA database. This provides data for up to 200 countries under the rubrics of (un-)employment, wages, strikes and lockouts, as well as international labour migration (among others).

The UN body which covers trade and investment, UNCTAD, has created a snazzy website that combines all of its statistical databases: [color=#089c9 !important]UNCTADstat has lots of data on trade (merchandise, services), FDI flows and stocks (inward FDI from 1970!), external finance (incl. remittances), labour force/employment, global commodity price indices (from 1960!) as well as some more recent rubrics such as the creative and information economies and maritime transport (from around 2000).

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The UN High Commissioner for Refugees (UNHCR) publishes a [color=rgb(0, 137, 201) !important]statistical yearbook, covering "Trends in Displacement, Protection and Solutions". It contains statistics on refugees, asylum-seekers, internally displaced persons (IDPs), returnees (refugees and IDPs), stateless persons, among others. From 2000 to 2009 these reports include excel files for download, from 1994-1999 the data tables are contained in pdf files.

A bunch of data from the UN DESA - Population Division, including [color=rgb(0, 137, 201) !important]World Contraceptive Use 2010, [color=rgb(0, 137, 201) !important]International Migrant Stock, [color=rgb(0, 137, 201) !important]World Population Prospects, [color=rgb(0, 137, 201) !important]World Urbanization Prospects (very 'open data', these last three: you can pick a max of 5 countries... Muppets)... [Thanks to Jackie Carter for the [color=rgb(0, 137, 201) !important]tweet]

[color=rgb(0, 137, 201) !important]Seo-Young Cho (Goettingen), [color=rgb(0, 137, 201) !important]Axel Dreher (Heidelberg) and [color=rgb(0, 137, 201) !important]Eric Neumayer (LSE) have created the 3P Anti-Trafficking Policy Index and a dedicated [color=rgb(0, 137, 201) !important]website. Sub-indices cover three policy dimensions: Prosecution, Prevention, Protection; score 1 (worst) 5 (best). Annual data are available for up to 177 countries over the 2000-2009 period.

Louis Putterman at Brown University provides another historical dataset, the [color=rgb(0, 137, 201) !important]World Migration Matrix (1950-2000), detailing for each of 165 countries "the proportion of the ancestors in 1500 of that country's population today that were living within what are now the borders of that and each of the other countries." There's a lot of documentation provided to reference all these estimates.

It sits a little awkward alongside economic migration, but the UN WTO (World Tourism Organisation) provides data on headcount and spending of tourists from 1995-2008 for around 90 countries on the [color=rgb(0, 137, 201) !important]UNdata website.


Entrepreneurship, SMEs, Privatisation and Business EnvironmentOn his [color=rgb(0, 137, 201) !important]website Thorsten Beck at Tilburg University provides access to data on small and medium enterprises (SME) share of employment in firms with less than 250 employees in manufacturing.

The [color=rgb(0, 137, 201) !important]Global Entrepreneurship Monitor (GEM) research program is an annual assessment of the national level of entrepreneurial activity. Data is collected for 'activity', 'aspirations', and 'attitudes and perceptions' (multiple variables under each rubric). Started as a partnership between London Business School and Babson College, it was initiated in 1999 with 10 countries, expanded to 21 in the year 2000, with 29 countries in 2001 and 37 countries in 2002. GEM 2009 is set to conduct research in 56 countries. GEM data for 1999 - 2006 is currently in the public domain. Full GEM datasets are made available to the public three years after the end of an annual data collection cycle. As such, GEM 2007 data will be made available to the public in January 2011. The data is in SPSS format.

The World Bank [color=rgb(0, 137, 201) !important]World Business Environment Survey (WBES 2000) was administered to enterprises in 80 countries in late 1999 and early 2000, using a standard core enterprise questionnaire methodology. This comprehensive survey of over 10,000 firms covers enterprise responses to multiple questions on the investment climate and business environment as shaped by domestic economic policy; governance; regulatory, infrastructural and financial impediments, as well as assessments of public service quality. There is no access to the raw data from this website, so you will have to go through the variable and sample selection process and then ask for the data in spreadsheet format.

The World Bank [color=rgb(0, 137, 201) !important]Doing Business project 'provides objective measures of business regulations and their enforcement across 181 economies and selected cities at the subnational and regional level.' The raw data for these surveys (run from 2004 onwards but with varying coverage for individual countries) is available via [color=rgb(0, 137, 201) !important]summary reports, which can then be accessed in excel.

The World Bank offers some statistics and details on [color=rgb(0, 137, 201) !important]privatisation transactions in excess of $1million within developing countries. The searchable database is for 2000-2007, but there is also a link to an Excel spreadsheet for the period 1988-1999. Apart from summary statistics on deal value etc., this resource provides transaction-level information (name of the company, sector, year and value of the deal) for developing and emerging economies. There is also a link for this and other World Bank data (e.g. infrastructure, Doing Business) to be mapped on a global scale - unfortunately these google-map based charts do not use standard colouring-in of countries but labels instead, which means they're not that helpful (plus: they cannot be exported). However, I imagine the new World Bank data mapper will supersede this tool very soon.

Labour Regulation data: Andrei Shleifer's [color=rgb(0, 137, 201) !important]website provides links to a number of datasets he has compiled and used with various co-authors. This includes 'Private Credit in 129 Countries' (JFE 2007, with S. Djankov and C. McLiesh), with data from 1978-2002 and data on the 'unofficial economy' (primarily cross-section data).

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Macro Stability, Business Cycles, Banking, Finance and Financial CrisesFor Public Finance see section on [color=#089c9 !important]Social Security, Taxes and the State.

The IADB website hosts the [color=#089c9 !important]data used in the work on trade intensity and business cycles
by César Calderón, Alberto Chong and Ernesto Stein (2006, JIE). From the abstract: "Using annual information for 147 countries for the period 1960-99 we find that the impact of trade intensity on business cycle correlation among developing countries is positive and significant, but substantially smaller than that among industrial countries. Our findings suggest that differences in the responsiveness of cycle synchronization to trade integration between industrial and developing countries are explained by differences in the patterns of specialization and bilateral trade."  

A New Database on Financial Development and Structure (1960-2007), produced by Thorsten Beck, Asli Demirguc-Kunt and Ross Levine, is available on the World Bank [color=#089c9 !important]website
. This is the updated version (April 2010) and provides indicators of financial development and structure (in total 22 variables) across countries (211 countries listed, but there are of course missing observations) and over time.

[color=#089c9 !important]Systemic Banking Crises: A New Database (1970-2007) is presented by Luc Laeven and Fabian Valencia in their IMF working paper No. 08/224. This paper presents a new database on the timing of systemic banking crises and policy responses to resolve them. The database covers the universe of systemic banking crises for the period 1970-2007, with detailed data on crisis containment and resolution policies for 42 crisis episodes, and also includes data on the timing of currency crises and sovereign debt crises. The database extends and builds on the Caprio, Klingebiel, Laeven, and Noguera (2005) banking crisis database, and is the most complete and detailed database on banking crises to date.

The personal website of Luc Laeven (Deputy Division Chief in the Research Department of the [color=#089c9 !important]International Monetary Fundand Full Professor of Finance at CentER, [color=#089c9 !important]Tilburg University) carries a number of interesting [color=#089c9 !important]datasets for cross-country analysis, including the 'Banking Crisis Database (2010)', Crisis resolution database and Deposit Insurance Database, together with some papers he's written describing and analysing the data. [Thanks to my buddy [color=#089c9 !important]Andrea Presbitero at Università Politecnica delle Marche for the pointer]

On his [color=#089c9 !important]website Thorsten Beck at Tilburg University provides cross-section data (2003) on access and use of banking services across 99 developing and developed countries: number of branches, ATMs, loans, deposits. This is from joint workwith A.Demirgüç-Kunt and M. Martinez Peria. Thorsten also has panel data on financial development (private credit) for up to 72 countries, from work with A. Demirgüç-Kunt and R. Levine.

The World Bank (Cihák, Demirgüç-Kunt, Feyen & Levine) provides the [color=#089c9 !important]Global Financial Development Database (GFDD) which covers 1960-2010 for 203 countries. "The Global Financial Development Database is based on this 4x2 framework. It builds on, updates, and extends previous efforts, in particular the data collected for the “Database on Financial Development and Structure”, the Financial Access Survey, the Global Findex and Financial Soundness Indicators. The database includes measures of (a) size of financial institutions and markets (financial depth), (b) degree to which individuals can and do use financial services (access), (c) efficiency of financial intermediaries and markets in intermediating resources and facilitating financial transactions (efficiency), and (d) stability of financial institutions and markets (stability). The dataset can be used to document cross-country differences and time series trends." Data can be downloaded in an Excel file and there is additional documentation.

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