Context

The Maddison Project Database provides information on comparative economic growth and income levels over the very long run. The 2020 version of this database covers 169 countries and the period up to 2018. For questions not covered in the documentation, please contact maddison@rug.nl.

Content

We now offer a new 2020 update of the Maddison Project database, which uses a different methodology compared to the 2018 update. The approach of the 2018 update is identical to that of Penn World Tables, and consistent with recent economic and statistical research in this field. However, applying this approach systematically results in historical outcomes that are not consistent with current insights by economic historians, as explained in Bolt and Van Zanden (2020).

The 2020 update has to some extent gone back to the original Maddison approach to remedy for this (see documentation). Both the 2018 and the 2020 datasets incorporate the available recent work by economic historians on long term economic growth, the 2020 is most complete in this respect.

Acknowledgements

Attribution requirement -

All original papers must be cited when:

the data is shown in any graphical form subsets of the full dataset that include less than a dozen (12) countries are used for statistical analysis or any other purposes

A list of original papers can be found in the source sheet of the database. When neither a) or b) apply, then the MPD as a whole should be cited.

Maddison Project Database, version 2020. Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update ”.

Inspiration

You can find some inspiration here : https://ourworldindata.org/global-economic-inequality-introduction

Context

The Maddison Project Database provides information on comparative economic growth and income levels over the very long run. The 2020 version of this database covers 169 countries and the period up to 2018. For questions not covered in the documentation, please contact maddison@rug.nl.

Content

We now offer a new 2020 update of the Maddison Project database, which uses a different methodology compared to the 2018 update. The approach of the 2018 update is identical to that of Penn World Tables, and consistent with recent economic and statistical research in this field. However, applying this approach systematically results in historical outcomes that are not consistent with current insights by economic historians, as explained in Bolt and Van Zanden (2020).

The 2020 update has to some extent gone back to the original Maddison approach to remedy for this (see documentation). Both the 2018 and the 2020 datasets incorporate the available recent work by economic historians on long term economic growth, the 2020 is most complete in this respect.

Acknowledgements

Attribution requirement -

All original papers must be cited when:

the data is shown in any graphical form subsets of the full dataset that include less than a dozen (12) countries are used for statistical analysis or any other purposes

A list of original papers can be found in the source sheet of the database. When neither a) or b) apply, then the MPD as a whole should be cited.

Maddison Project Database, version 2020. Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update ”.

Inspiration

You can find some inspiration here : https://ourworldindata.org/global-economic-inequality-introduction

We provide the data used for this research in both Excel (one file with one matrix per sheet, 'Allmatrices.xlsx'), and CSV (one file per matrix).

Patent applications (Patent_applications.csv) Patent applications from residents and no residents per million inhabitants. Data obtained from the World Development Indicators database (World Bank 2020). Normalization by the number of inhabitants was made by the authors.

High-tech exports (High-tech_exports.csv) The proportion of exports of high-level technology manufactures from total exports by technology intensity, obtained from the Trade Structure by Partner, Product or Service-Category database (Lall, 2000; UNCTAD, 2019)

Expenditure on education (Expenditure_on_education.csv) Per capita government expenditure on education, total (2010 US$). The data was obtained from the government expenditure on education (total % of GDP), GDP (constant 2010 US$), and population indicators of the World Development Indicators database (World Bank 2020). Normalization by the number of inhabitants was made by the authors.

Scientific publications (Scientific_publications.csv) Scientific and technical journal articles per million inhabitants. The data were obtained from the scientific and technical journal articles and population indicators of the World Development Indicators database (World Bank 2020). Normalization by the number of inhabitants was made by the authors.

Expenditure on R&D (Expenditure_on_R&D.csv) Expenditure on research and development. Data obtained from the research and development expenditure (% of GDP), GDP (constant 2010 US$), and population indicators of the World Development Indicators database (World Bank 2020). Normalization by the number of inhabitants was made by the authors.

Two centuries of GDP (GDP_two_centuries.csv) GDP per capita that accounts for inflation. Data obtained from the Maddison Project Database, version 2018 (Inklaar et al. 2018), and available from the Open Numbers community (open-numbers.github.io).

Inklaar, R., de Jong, H., Bolt, J., & van Zanden, J. (2018). Rebasing “Maddison”: new income comparisons and the shape of long-run economic development (GD-174; GGDC Research Memorandum). https://www.rug.nl/research/portal/files/53088705/gd174.pdf

Lall, S. (2000). The Technological Structure and Performance of Developing Country Manufactured Exports, 1985‐98. Oxford Development Studies, 28(3), 337–369. https://doi.org/10.1080/713688318

Unctad. 2019. “Trade Structure by Partner, Product or Service-Category.” 2019. https://unctadstat.unctad.org/EN/.

World Bank. (2020). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators

Context

Life expectancy at birth is defined as the average number of years that a newborn could expect to live if he or she were to pass through life subject to the age-specific mortality rates of a given period. The years are from 1950 to 2018.

Content

For regional- and global-level data pre-1950, data from a study by Riley was used, which draws from over 700 sources to estimate life expectancy at birth from 1800 to 2001.

Riley estimated life expectancy before 1800, which he calls "the pre-health transition period". "Health transitions began in different countries in different periods, as early as the 1770s in Denmark and as late as the 1970s in some countries of sub-Saharan Africa". As such, for the sake of consistency, we have assigned the period before the health transition to the year 1770. "The life expectancy values employed are averages of estimates for the period before the beginning of the transitions for countries within that region. ... This period has presumably the weakest basis, the largest margin of error, and the simplest method of deriving an estimate."

For country-level data pre-1950, Clio Infra's dataset was used, compiled by Zijdeman and Ribeira da Silva (2015).

For country-, regional- and global-level data post-1950, data published by the United Nations Population Division was used, since they are updated every year. This is possible because Riley writes that "for 1950-2001, I have drawn life expectancy estimates chiefly from various sources provided by the United Nations, the World Bank’s World Development Indicators, and the Human Mortality Database".

For the Americas from 1950-2015, the population-weighted average of Northern America and Latin America and the Caribbean was taken, using UN Population Division estimates of population size.

Acknowledgements

Life expectancy:

Data publisher's source: https://www.lifetable.de/RileyBib.pdf Data published by: James C. Riley (2005) – Estimates of Regional and Global Life Expectancy, 1800–2001. Issue Population and Development Review. Population and Development Review. Volume 31, Issue 3, pages 537–543, September 2005., Zijdeman, Richard; Ribeira da Silva, Filipa, 2015, "Life Expectancy at Birth (Total)", http://hdl.handle.net/10622/LKYT53, IISH Dataverse, V1, and UN Population Division (2019) Link: https://datasets.socialhistory.org/dataset.xhtml?persistentId=hdl:10622/LKYT53, http://onlinelibrary.wiley.com/doi/10.1111/j.1728-4457.2005.00083.x/epdf, https://population.un.org/wpp/Download/Standard/Population/ Dataset: https://ourworldindata.org/life-expectancy

GDP per capita:

Data publisher's source: The Maddison Project Database is based on the work of many researchers that have produced estimates of economic growth for individual countries. Data published by: Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update”. Link: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 Dataset: https://ourworldindata.org/life-expectancy

Inspiration

The life expectancy vs GDP per capita analysis.

Version history:This data are a new version of Geiger et al (2017, http:doi.org/10.5880/PIK.2017.003). Please use this updated version of this dataset which contains the following correction of errors in the original dataset: The linear interpolation in GDP per capita for Aruba (ABW) between observations in 2005 and SSP2 projections in 2010 was replaced by observed GDP per capita values for the years 2006-2009, as the SSP2 projection for Aruba turned out to be incorrect. As a result of this, the national GDP per capita and GDP timeseries for Aruba between 2006 and 2009 is different from the previous version. We here provide three different economic time series that amend or combine various existing time series for Gross Domestic Product (GDP), GDP per capita, and population to create consistent and continuous economic time series between 1850 and 2009 for up to 195 countries. All data, including the data description are included in a zip folder (2018-010_GDP_1850-2009_Data_v2.zip): (1) A continuous table of global income data (in 1990 Geary-Khamis $) based on the Maddison Project data base (MPD) for 160 individual countries and 3 groups of countries from 1850-2010: Maddison_Project_data_completed_1850-2010.csv. (2) A continuous table of global income data (in 2005 PPP $, PPP = purchasing power parity) for 195 countries based on a merged and harmonized dataset between MPD and Penn World Tables (PWT, version v8.1) from 1850-2009, and additionally extended using PWT v9.0 and World Development Indicators (WDI), that is consistent with future GDP per capita projections from the Shared Socioeconomic Pathways (SSPs): GDP-per-capita-national_PPP2005_SSP-harmonized_1850-2009_v2.csv. (3) A continuous table of global GDP data (in 2005 PPP $) for 195 countries from 1850-2009 based on the second income data set multiplied by country population data, again consistent with future SSP GDP projections: GDP-national_PPP2005_SSP-harmonized_1850-2009_v2.csv. These data are supplemented by a masking table indicating MPD original data and amended data based on current country definitions (Maddison_data_availability_masked_1850-2010.csv) and a file with PPP conversion factors used in this study (PPP_conversion_factors_PPP1990-PPP2005.csv). We use various interpolation and extrapolation methods to handle missing data and discuss the advantages and limitations of our methodology. Despite known shortcomings this data set aims to provide valuable input, e.g., for climate impact research in order to consistently analyze economic impacts from pre-industrial times to the distant future. More information about data sources and data format description is given in the data description file (2018-010_Data-Description-GDP_1850-2009_v2.pdf).

Dataset for regime changes following a tripartite classification: democracy, anocracy and autocracy. The dataset is an aggregation of data from Polity IV, the World Bank's World Development Indicators and the Angus Maddison Project. We develop a world-wide trichotomous classification of political regime types that includes the intermediate category of anocracy between democracy and autocracy, as well as the subsequent hexachotomous typology of regime changes, from 1800 to 2013. We find six types of regime change: Partial opening (from autocracy to anocracy); complete opening (from anocracy to democracy); Transition (from autocracy to democracy); partial closing (from democracy to anocracy); Complete closing (from anocracy to autocracy); Breakdown (from democracy to autocracy)

Context

This complete CO2 and Greenhouse Gas Emissions dataset is a collection of key metrics maintained by Our World in Data. It is updated regularly and includes data on CO2 emissions (annual, per capita, cumulative and consumption-based), other greenhouse gases, energy mix, and other relevant metrics.

Content

• CO2 emissions: this data is sourced from the Global Carbon Project. The Global Carbon Project typically releases a new update of CO2 emissions annually.
• Greenhouse gas emissions (including methane, and nitrous oxide): this data is sourced from the CAIT Climate Data Explorer, and downloaded from the Climate Watch Portal.
• Energy (primary energy, energy mix and energy intensity): this data is sourced from a combination of two sources. The BP Statistical Review of World Energy is published annually, but it does not provide data on primary energy consumption for all countries. For countries absent from this dataset, we calculate primary energy by multiplying the World Bank, World Development Indicators metric Energy use per capita by total population figures. The World Bank sources this metric from the IEA.
• Other variables: this data is collected from a variety of sources (United Nations, World Bank, Gapminder, Maddison Project Database, etc.). More information is available in our codebook.

Acknowledgements

Our World in Data Edouard Mathieu Bobbie Macdonald Hannah Ritchie Daniel Dias

The PRIMAP-hist Socio-Eco dataset combines several published datasets to create a comprehensive set of population and Gross domestic product (GDP) pathways for every country covering the years 1850 to 2017, and all UNFCCC (United Nations Framework Convention on Climate Change) member states, as well as most non-UNFCCC territories. The data has no sector resolution. List of datasets included in this data publication: (1) PMHSOCIOECO21_GDP_26-Jul-2019.csv: contains the GDP data for all countries(2) PMHSOCIOECO21_Population_26-Jul-2019.csv: contains the population data for all countries(3) PRIMAP-hist_SocioEco_data_description.pdf: including CHANGELOG(all files are also included in the .zip folder) When using this dataset or one of its updates, please cite the DOI of the precise version of the dataset. Please consider also citing the relevant original sources when using the PRIMAP-hist Socio-Eco dataset. See the full citations in the References section further below. A data description article is in preparation. Until it is published we refer to the description article of the PRIMAP-hist emissions time series for the methodology used. SOURCES: - UN World Population Prospects 2019 (UN2019)- World Bank World Development Indicators 2019 (July) (WDI2019B). We use the NY.GDP.MKTP.PP.KD variable for GDP.- Penn World Table version 9.1 (PWT91). We use the cgdpe variable for GDP (Robert and Feenstra, 2019; Feenstra et al., 2015)- Maddison Project Database 2018 (MPD2018). We use the cgdppc variable for GDP (Bolt et al,, 2018)- Anthropogenic land use estimates for the Holocene – HYDE 3.2 (HYDE32)(Klein Goldewijk, 2017)- Continuous national gross domestic product (GDP) time series for 195 countries: past observations (1850–2005) harmonized with future projections according to the Shared Socio-economic Pathways (2006–2100) (Geiger2018, Geiger and Frieler, 2018)Full references are available in the data description document.