A dataset is a collection of data. It containts data points organized under variables. These collections may be thematic, regional, organized in questions, indexes and others.

Accountable Climate Targets

QoG Code: act

Data used in the article: Boräng, F., Felgendreher, S., Harring, N. and Löfgren, Å., 2019. Committing to the climate: a global study of accountable climate targets. Sustainability, 11(7), p.1861. The authors assess and compare the accountability of climate targets as outlined in the nationally determined contributions (NDC) of the Paris Agreement.

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AidData v. 3.1

QoG Code: aid

AidData's Core Research Release 3.1 is a corrected snapshot of AidData's entire project-level database from April 2016. This database includes commitment information for over 1.5 million development finance activities funded between 1947 and 2013, covers 96 donors, and includes ODA, OOF flows, Equity Investments, and Export Credits where available.

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Africa Integrity Indicators

QoG Code: aii

The Africa Integrity Indicators (AII) assesses key social, economic, political and anti-corruption mechanisms at the national level in all 54 African countries in two sections: Transparency and Accountability, and Social Development. The Africa Integrity Indicators are scored by in-country researchers following an evidence-based investigation methodology. The resultant data points are then reviewed blindly by a panel of peer reviewers, drawing on the expertise of a mix of in-country experts as well as outside experts. The Transparency and Accountability indicator is made of sub-indicators in the following categories: rule of law, accountability, elections, public management, civil service integrity, access to information and openness, and social development. For this version of the QoG Datasets, we have decided to only include the scores for the broader components of Transparency and Accountability, given that the Social Development Indicators are already represented by the Mo Ibrahim Foundation's Index of African Governance.

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Settler Mortality

QoG Code: ajr

Data used in the article The Colonial Origins of Comparative Development: An Empirical Investigation.

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Fractionalization

QoG Code: al

The variables reflect the probability that two randomly selected people from a given country will not share a certain characteristic, the higher the number the less probability of the two sharing that characteristic. The data was last updated by the authors in 2003. For the QoG Data, the data from the year 2000 is repeated throughout the other years, then, these variables should be taken as historical variables.

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World Religion Project: National Religion Dataset

QoG Code: arda

The World Religion Dataset (WRD) aims to provide detailed information about religious adherence worldwide since 1945. It contains data about the number of adherents by religion in each of the states in the international system. These numbers are given for every half-decade period (1945, 1950, etc., through 2010). Percentages of the states' populations that practice a given religion are also provided. (Note: These percentages are expressed as decimals, ranging from 0 to 1, where 0 indicates that 0 percent of the population practices a given religion and 1 indicates that 100 percent of the population practices that religion). Some of the religions are divided into religious families. To the extent data are available, the breakdown of adherents within a given religion into religious families is also provided. The project was developed in three stages. The first stage consisted of the formation of a religion tree. A religion tree is a systematic classification of major religions and of religious families within those major religions. To develop the religion tree a comprehensive literature review was prepared, the aim of which was (i) to define a religion, (ii) to find tangible indicators of a given religion of religious families within a major religion, and (iii) to identify existing efforts at classifying world religions. (Please see the original survey instrument to view the structure of the religion tree). The second stage consisted of the identification of major data sources of religious adherence and the collection of data from these sources according to the religion tree classification. This created a dataset that included multiple records for some states for a given point in time. It also contained multiple missing data for specific states, specific time periods and specific religions. The third stage consisted of cleaning the data, reconciling discrepancies of information from different sources and imputing data for the missing cases. The National Religion Dataset: The observation in this dataset is a state-five-year unit. This dataset provides information regarding the number of adherents by religions, as well as the percentage of the state's population practicing a given religion.

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Aquastat

QoG Code: as

AQUASTAT is the FAO global information system on water resources and agricultural water management.

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The ATOP State-Year dataset

QoG Code: atop

The Alliance Treaty Obligations and Provisions (ATOP) project provides data regarding the content of military alliance agreements signed by all countries of the world between 1815 and 2016.

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The Bayesian Corruption Index

QoG Code: bci

The Bayesian Corruption Index is a composite index of the perceived overall level of corruption: with corruption refered to as the ``abuse of public power for private gain''. Perceived corruption: Given the hidden nature of corruption, direct measures are hard to come by, or inherently flawed (e.g. the number of corruption convictions). Instead, we amalgamate the opinion on the level of corruption from inhabitants of the country, companies operating there, NGOs, and officials working both in governmental and supra-governmental organizations. Composite: it combines the information of 20 different surveys and more than 80 different survey questions that cover the perceived level of corruption. It is an alternative to the other well-known indicators of corruption perception: the Corruption Perception Index (CPI) published by Transparency International and the Worldwide Governance Indicators (WGI) published by the World Bank. Methodologically, it is most closely related to the latter as the methodology used in the construction of the BCI can be seen as an augmented version of the Worldwide Governance Indicators' methodology. The augmentation allows an increase of the coverage of the BCI: a 60% to 100% increase relative to the WGI and CPI, respectively. In addition, in contrast to the WGI or CPI, the underlying source data are entered without any ex-ante imputations, averaging or other manipulations. This results in an index that truly represents the underlying data, unbiased by any modeling choices of the composer.

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IUCN Red List of Threatened Species (version 2020-2)

QoG Code: bi

The IUCN Red List of Threatened Species is widely recognized as the most comprehensive, objective global approach for evaluating the conservation status of plant and animal species. From its small beginning, The IUCN Red List has grown in size and complexity and now plays an increasingly prominent role in guiding conservation activities of governments, NGOs and scientific institutions. The introduction in 1994 of a scientifically rigorous approach to determine risks of extinction that is applicable to all species, has become a world standard. Note: For reptiles, fishes, molluscs, other invertebrates, plants, fungi \& protists: there are still many species that have not yet been assessed for the IUCN Red List and therefore their status is not known (i.e., these groups have not yet been completely assessed). Therefore the figures presented below for these groups should be interpreted as the number of species known to be threatened within those species that have been assessed to date, and not as the overall total number of threatened species for each group. We advise users to abstain from making comparisons through time using this data, given that there could be changes to the methodology for the country reports.

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Global Militarization Index

QoG Code: bicc

Compiled by BICC, the Global Militarization Index (GMI) presents on an annual basis the relative weight and importance of a country's military apparatus in relation to its society as a whole. The GMI 2018 covers 155 countries and is based on the latest available figures (in most cases data for 2017). The index project is financially supported by Germany's Federal Ministry for Economic Cooperation and Development.

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Religion and State Project

QoG Code: biu

The Religion and State (RAS) project is a university-based project located at Bar Ilan University in Ramat Gan, Israel. Its goal is to create a set of measures that systematically gauge the intersection between government and religion. Specifically, it examines government religion policy. The project's goals are threefold: - To provide an accurate description of government religion policies worldwide. - To create a tool which will lead to greater understanding of the factors which influence government religion policy. - To provide the means to examine how government religion policy influences other political, social, and economic factors as well as how those factors influence government religion policy. Round 2 of the RAS dataset, which is currently the official version available for download, measures the extent of government involvement in religion (GIR) or the lack thereof for 175 states on a yearly basis between 1990 and 2008. This constitutes all countries with populations of 250,000 or more as well as a sampling of smaller states. The data includes the following information: Official Religion: A 15 value variable which measures the official relationship between religion and the state. This includes five categories of official religions and nine categories of state-religion relationships which range from unofficial support for a single religion to overt hostility to all religion. Religious Support: This includes 51 separate variables which measure different ways a government can support religion including financial support, policies which enforce religious laws, and other forms of entanglement between government and religion. Religious Restrictions: This includes 29 separate variables which measure different ways governments regulate, restrict, or control all religions in the state including the majority religion. This includes restrictions on religion's political role, restrictions on religious institutions, restrictions on religious practices, and other forms of regulation, control, and restrictions. Religious Discrimination: This includes 30 types of restrictions that are placed on the religious institutions and practices of religious minorities that are not placed on the majority group. This includes restrictions on religious practices, restrictions on religious institutions and clergy, restrictions on conversion and proselytizing, and other restrictions. The dataset also includes several sets of detailed variables measuring certain policies in depth. These topics include religious education, the registration of religious organizations, restrictions on abortion, restrictions on proselytizing, and religious requirements for holding public office or citizenship.

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Educational Attainment Dataset

QoG Code: bl

The Barro-Lee Data set provide data disaggregated by sex and by 5-year age intervals. It provides educational attainment data for 146 countries in 5-year intervals from 1950 to 2010. It also provides information about the distribution of educational attainment of the adult population over age 15 and over age 25 by sex at seven levels of schooling - no formal education, incomplete primary, complete primary, lower secondary, upper secondary, incomplete tertiary, and complete tertiary. Average years of schooling at all levels - primary, secondary, and tertiary - are also measured for each country and for regions in the world. Aside from updating and expanding the previous estimates (1993, 1996, and 2001), the accuracy of estimation in the current version is improved by using more information and better methodology. To reduce measurement error, the new estimates are constructed using recently available census/survey observations from consistent census data, disaggregated by age group, and new estimates of mortality rate and completion rate by age and by education.

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Boix-Miller-Rosato Dichotomous Coding of Democracy, 1800-2010

QoG Code: bmr

This data set provides a dichotomous coding of democracy from 1800 until 2015, however QoG data contains information from 1946 onwards. Authors define a country as democratic if it satisfies conditions for both contestation and participation. Specifically, democracies feature political leaders chosen through free and fair elections and satisfy a threshold value of suffrage.

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Event History Coding of Democratic Breakdowns

QoG Code: bnr

Binary coding of all democracies from 1913 until 2005 prepared for use in event history analysis.

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Bertelsmann Transformation Index

QoG Code: bti

The Bertelsmann Stiftung's Transformation Index (BTI) analyzes and evaluates the quality of democracy, a market economy, and political management in 137 developing and transition countries. It measures successes and setbacks on the path towards democracy based on the rule of law and a socially responsible market economy. In-depth country reports provide the basis for assessing the state of transformation and persistent challenges and for evaluating the ability of policymakers to carry out consistent and targeted reforms. The BTI is the first cross-national comparative index that collects data to comprehensively measure the quality of governance during processes of transition.

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The Comparative Abortion Index Project

QoG Code: cai

The comparative abortion index quantifies the permissiveness of abortion policies worldwide, accounting for a variety of considerations. It aims to provide researchers with a tool to assess trends in worldwide reproductive rights, and to study how these changes over time and space occur. It is unique in its breadth and its method. Not only does it include a scale that reflects the number of criteria accepted as grounds for abortion, but it includes a second scale which gives weighted scores to each criterion, based on how common it is. These data are relevant for anyone interested in tracking trends in women's rights, public health policy, and reproductive rights policy over time. The dataset covers 192 countries from 1992-2015. The UN Department of Social and Economic Affairs has published a global review of abortion policy since 1992. For this database, all reviews published between 1992 and 2015 were collected. The report offers seven criteria under which state law may allow access to abortion services; saving a woman's life, preserving a woman's physical health, preserving a woman's mental health, in case of rape or incest, in case of fetal impairment, for social or economic reasons and on request. Each country-year is given a score based on the number of legal criteria accepted as grounds for abortion. In the first version of the index (CAI1), each criterion is given equal weight and the score is a direct reflection of the number of conditions the country accepts. Thus, a country that has no conditions under which a woman can receive an abortion gets a score of 0. A country, in which a woman may access an abortion under all conditions including on request, receives a score of 7. For the purposes of robustness, and to fix a potential measurement flaw in the first index, we also offer a weighted index (CAI2). The first scale does not account for the different degrees of acceptance that each criterion represents. It would be imprecise, for instance, to suggest that the criterion of saving a woman's life is equivalent to (and thus carries the same weight as) allowing abortion on demand. The more permissive the criterion, the less likely that it is universally accepted. Accordingly, the weight of each criterion (Wi) will be determined based on the percentage (Pi) of countries that allow that condition. In the weighted index, countries are given a score on a scale of 0 to1, where 0 represents countries in which there are no conditions for legal abortion, and 1 represents a country that accepts all criteria for abortion, including on request.

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Contestation and Inclusiveness, 1950-2000

QoG Code: cam

These are the two principal components of 13-15 indicators of democracy, including those compiled by Freedom House; Polity; Arthur Banks; Alvarez, Cheibub, Limongi, and Przeworski, as updated by Cheibub and Gandhi; Bollen; and Cingranelli and Richards. The dataset covers most countries in the world from 1950 through 2000. In an article in the Journal of Politics (July 2008), the authors argue that these principal components, which capture 75 percent of variation in the most commonly used democracy indicators, measure Robert Dahl's two dimensions of polyarchy: contestation and inclusiveness.

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Central Bank Independence Dataset

QoG Code: cbi

The Central Bank Independence Dataset is the most comprehensive data set on de jure central bank independence (CBI) available to date. The data set identifies statutory reforms affecting CBI, their direction, and the attributes necessary to build the Cukierman, Webb, and Neyapti (1992) (CWN) index in 190 countries between 1970 and 2012. This data set codes the existence of reforms in 6,745 observations and computes the CWN index for 5,840 observations. The data coverage not only allows researchers to test competing explanations on the determinants and effects of CBI in both developed and developing countries, but it also provides a useful instrument for cross-national studies in diverse fields.

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Cooperation in International Climate Change Regime

QoG Code: ccci

The index and its components measure countries' cooperation within the international climate change regime. The Cooperation in International Climate Change Regime Index is an aggregate of five indicators: The United Nations Framework Convention on Climate Change (UNFCCC) and Kyoto Protocol Indicators, which measure countries' commitment to common international goals, and the Reporting, Finance, and Emission Indicators, which measure the degree to which countries follow up on the respective commitments within the international regime.

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Climate Change Knowledge Portal

QoG Code: cckp

The Climate Change Knowledge Portal provides global data on historical and future climate, vulnerabilities, and impacts. The data on historical temperature and rainfall data included in this compilation comes from the historical CRU dataset. The CRU TS version 4.04 gridded historical dataset is derived from observational data and provides quality-controlled temperature and rainfall values from thousands of weather stations worldwide, as well as derivative products including monthly climatologies and long-term historical climatologies. The dataset is produced by the Climatic Research Unit (CRU) of the University of East Anglia (UEA) CRU-(Gridded Product). In order to present historical climate conditions, the World Bank Group's Climate Change Knowledge Portal (CCKP) uses the globally available observational datasets derived from CRU to quantify changes in mean annual temperature and mean annual precipitation for the period 1901-2019 per country.

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Climate Change Laws of the World

QoG Code: ccl

Climate change-related laws and policies refer to legal documents related to reducing energy demand, promoting low carbon energy supply, low-carbon buildings, carbon pricing, lower industry emissions, tackling deforestation and promoting sustainable land use, other mitigation efforts, research and development, sustainable transportation, enhancing adaptation capabilities, and natural disaster risk management. The dataset only included laws and policies that have been passed by legislative branches or published by executive branches, and that are no longer in draft form. The dataset also captures major amendments to legislation. Laws that are outdated, either because they have been repealed, replaced, or reversed, are not included. The database distinguishes between Laws or legislative acts (e.g. acts, laws, decree-laws), which were passed by a parliament or equivalent legislative authority, and Policies, or other executive provisions (e.g. presidential decrees, executive orders, regulations, government policies, strategies, or plans), which were published or decreed by the government, president, or equivalent executive authority.

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Characteristics of National Constitutions

QoG Code: ccp

This dataset presents records of the characteristics of national constitutions written since 1789. Each constitutional text is coded twice by different coders working independently. To maximize the reliability of the final data, the discrepancies between these two codings are reconciled by a third individual - a reconciler. This is the second public release of data (version 2.0) on the content of constitutions. Authors rely on Ward and Gleditsch's list to identify which countries are independent in a given year. There are utilized two concepts to categorize constitutional texts. A constitutional system encompasses the period in which a constitution is in force before it is replaced or suspended. A constitutional event is any change to a country's constitution, including adoption, amendment, suspension, or reinstatement. For years in which there are multiple events, the constitution is coded as it stood in force at the end of the year. For example, if a constitution was amended the same year as it was adopted, the content of the constitution is coded as amended rather than as originally adopted. In addition, since events are (often) in force for multiple years, authors interpolated the data associated each event across all country-years in which that event was in force. Note that this is an extremely conservative interpolation strategy because most constitutional amendments do not change many provisions. As a result, for most variables, one can safely interpolate across constitutional systems.

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Classification of Political Regimes

QoG Code: chga

Classification of political regimes as democracy and dictatorship. Classification of democracies as parliamentary, semi-presidential (mixed) and presidential. Classification of dictatorships as military, civilian and royal.

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The CIRIGHTS Data project

QoG Code: ciri

The CIRIGHTS Data project measures the strength of actual national government practices protecting human rights. The long-term goal of the project is to annually measure all internationally recognized civil and political rights and to use both human and machine-assisted coding procedures to produce scores. The project is hosted by the Binghamton University Human Rights Institute. Note: The three different missing codes -66 (country is occupied by foreign powers), -77 (complete collapse of central authority), -999 (missing) have all been coded as missing.

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Comparative Political Data Set

QoG Code: cpds

The Comparative Political Data Set 1960-2018 (CPDS) is a collection of political and institutional data which have been assembled in the context of the research projects ``Die Hand-lungsspielräume des Nationalstaates'' and ``Critical junctures. An international comparison'' directed by Klaus Armingeon and funded by the Swiss National Science Foundation. This data set consists of (mostly) annual data for 36 democratic OECD and/or EU-member countries for the period of 1960 to 2017. In all countries, political data were collected only for the democratic periods. The data set is suited for cross-national, longitudinal and pooled time-series analyses.

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Corruption Risks Indicators

QoG Code: cri

Measuring high-level corruption is subject to extensive scholarly and policy interest, which has achieved moderate progress in the last decade. This dataset presents four objective proxy measures of high-level corruption in public procurement: single bidding in competitive markets, the share of contracts with ``no published call for tender'' red flag, the share of contracts with ``non-open procedure'' red flag, and share of contracts with ``tax haven'' red flag. Using official government data on 4 million contracts in thirty-two European countries from 2011 to 2018, the authors directly operationalize a common definition of corruption: unjustified restriction of access to public contracts to favour a selected bidder. Corruption indicators are calculated at the contract level, but produce aggregate indices consistent with well-established country-level indicators, and are also validated by micro-level tests.

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CSES datasets

QoG Code: cses

CSES (CSES1, CSES2, CSES3, CSES4 and CSES5) is a collaborative program of research among election study teams from around the world. Participating countries include a common module of survey questions in their post-election studies. The resulting data are deposited along with voting, demographic, district and macro variables. The studies are then merged into a single, free, public dataset for use in comparative study and cross-level analysis. The research agenda, questionnaires, and study design are developed by an international committee of leading scholars of electoral politics and political science. The design is implemented in each country by their foremost social scientists. Note: Portugal 2002 from the initial data Module 1 was exluded, as this module provide data until 2001, therefore these observations are coded incorrectly.

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State Fragility Index and Matrix

QoG Code: cspf

The State Fragility Index and Matrix provides annual state fragility, effectiveness, and legitimacy indices and the eight component indicators for the world's 167 countries with populations greater than 500,000 in 2018.

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Dataset of Electoral Volatility in Western Europe

QoG Code: dev

This dataset provides data on electoral volatility and its internal components in parliamentary elections (lower house) in 20 countries of Western Europe for the period 1945-2020. It covers the entire universe of Western European elections held after World War II under democratic regimes. Data for Greece, Portugal and Spain have been collected after their democratizations in the 1970s. Altogether, a total of 347 elections (or, more precisely, electoral periods) are included. When several elections were held in a single year, the data for the last election is included in the QoG dataset.

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Dataset for Information and Accountability Transparency (2014)

QoG Code: diat

The article ``A global index of information transparency and accountability'' (Williams, 2014) uses a relatively new methodology, similar to Transparency International's Corruption Perceptions Index, to construct composite indicators of Informational Transparency, and Accountability. These new indicators use data from 29 sources, with scores being derived annually between 1980 and 2010 across more than 190 countries.

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KOF Index of Globalization

QoG Code: dr

The KOF Globalization Index measures the economic, social and political dimensions of globalization. It is used in order to monitor changes in the level of globalization of different countries over extended periods of time. The current KOF Globalization Index is available for 185 countries and covers the period from 1970 until 2018. A distinction is drawn between de facto and de jure for the Index as a whole, as well as within the economic, social and political components. The Index measures globalization on a scale of 1 to 100, where higher values indicate a higher degree of globalization. The figures for the constituent variables are expressed as percentiles. This means that outliers are smoothed and ensures that fluctuations over time are lower. Due to the new methodology, the current Index is only to a limited extent comparable to the old KOF Globalization Index.

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EDGAR - Global Air Pollutant Emissions

QoG Code: edgarair

The Emissions Database for Global Atmospheric Research (EDGAR) provides global past and present-day anthropogenic emissions of greenhouse gases and air pollutants by country and on a spatial grid. EDGAR provides emission data for the following air pollutants: Ozone precursor gases: Carbon Monoxide (CO), Nitrogen Oxides (NOx), Non-Methane Volatile Organic Compounds (NMVOC) and Methane (CH4). Acidifying gases: Ammonia (NH3), Nitrogen oxides (NOx) and Sulfur Dioxide (SO2). Primary particulates: Fine Particulate Matter (PM10 and PM2.5 and Carbonaceous speciation (BC, OC). Emissions from large-scale biomass burning with Savannah burning, forest fires, and sources and sinks from land-use, land-use change, and forestry (LULUCF) are excluded. For the energy-related sectors, the activity data are mainly based on the energy balance statistics of IEA (2017) (http://www.oecd-ilibrary.org/energy/co2-emissions-from-fuel-combustion-2017_co2_fuel-2017-en), whereas the activity data for the agricultural sectors originate mainly from FAO (2018) (http://www.fao.org/faostat/en/#home). Additional information can be found in Crippa et al. (2019).

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EDGAR - Fossil CO2 Emissions of All World Countries

QoG Code: edgarghg

The Emissions Database for Global Atmospheric Research (EDGAR) provides global past and present-day anthropogenic emissions of greenhouse gases and air pollutants by country and on a spatial grid. Fossil CO2 emissions of all world countries from EDGAR provides an independent estimate of CO2 emissions for each world country, based on a robust and consistent methodology stemming from the latest IPCC guidelines and most recent activity data. Fossil CO2 emission data are available for the time period 1970-2019.

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The Environmental Democracy Index

QoG Code: edi

The Environmental Democracy Index measures the degree to which countries have enacted legally binding rules that provide for environmental information collection and disclosure, public participation across a range of environmental decisions, and fair, affordable, and independent avenues for seeking justice and challenging decisions that impact the environment. The index evaluates 70 countries across 75 legal indicators, based on objective and internationally recognized standards established by the United Nations Environment Programme’s (UNEP) Bali Guidelines. EDI also includes a supplemental set of 24 limited practice indicators that provide insight on a country's performance in implementation.

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Global Footprint Data

QoG Code: ef

The National Footprint Accounts (NFAs) measure the ecological resource use and resource capacity of nations over time. Based on approximately 15,000 data points per country per year, the Accounts calculate the Footprints of 232 countries, territories, and regions from 1961 to the present, providing the core data needed for all Ecological Footprint analysis worldwide.

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UN E-Government Knowledgebase

QoG Code: egov

The E-Government Development Index presents the state of E-Government Development of the United Nations Member States. Along with an assessment of the website development patterns in a country, the E-Government Development index incorporates the access characteristics, such as the infrastructure and educational levels, to reflect how a country is using information technologies to promote access and inclusion of its people. The EGDI is a composite measure of three important dimensions of e-government, namely: provision of online services, telecommunication connectivity and human capacity. The EGDI is not designed to capture e-government development in an absolute sense; rather, it aims to give a performance rating of national governments relative to one another.

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Environmental Ministries

QoG Code: em

Data on the establishment of environmental ministries from the article: Aklin, M. and Urpelainen, J., 2014. The global spread of environmental ministries: domestic–international interactions. International Studies Quarterly, 58(4), pp.764-780.

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Emergency Events Database

QoG Code: emdat

EM-DAT is a global database on natural and technological disasters, containing essential core data on the occurrence and effects of more than 21,000 disasters in the world, from 1900 to present. EM-DAT is maintained by the Centre for Research on the Epidemiology of Disasters (CRED) at the School of Public Health of the Université catholique de Louvain located in Brussels, Belgium. The database is made up of information from various sources, including UN agencies, non-governmental organizations, insurance companies, research institutes, and press agencies. Priority is given to data from UN agencies, governments, and the International Federation of Red Cross and Red Crescent Societies. This prioritization is not only a reflection of the quality or value of the data, it also reflects the fact that most reporting sources do not cover all disasters or have political limitations that could affect the figures. The entries are constantly reviewed for inconsistencies, redundancy, and incompleteness. CRED consolidates and updates data on a daily basis. A further check is made at monthly intervals, and revisions are made at the end of each calendar year. EM-DAT distinguishes between two generic categories for disasters: natural and technological. The natural disaster category is divided into 5 sub-groups - geophysical (e.g., earthquakes), meteorological (e.g., extreme temperature), hydrological (e.g., flood), climatological (e.g., drought), biological (e.g., epidemic), and extraterrestrial (e.g., asteroids). The 5 sub-groups in turn cover 15 disaster types and more than 30 sub-types. The technological disaster category is divided into 3 sub-groups - industrial, transport, and miscelleanous accidents, - which in turn cover 15 disaster types. For a disaster to be entered into the database at least one of the following criteria must be fulfilled: a) Ten (10) or more people reported killed; b) Hundred (100) or more people reported affected; c) Declaration of a state of emergency; d) Call for international assistance.

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Environmental Non-Governmental Organizations

QoG Code: engo

Data on environmental non-governmental organizations used in the article: Bernauer, T., Böhmelt, T. and Koubi, V., 2013. Is there a democracy–civil society paradox in global environmental governance? Global Environmental Politics, 13(1), pp.88-107.

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Ease of Doing Business - Historical Data

QoG Code: eob

The Doing Business project provides objective measures of business regulations and their enforcement across 190 economies. This EOB 2020 report covers 11 indicator sets and 190 economies. Most indicator sets refer to a case scenario in the largest business city of each economy, except for 11 economies that have a population of more than 100 million as of 2013 (Bangladesh, Brazil, China, India, Indonesia, Japan, Mexico, Nigeria, Pakistan, the Russian Federation and the United States) where Doing Business, also collected data for the second largest business city. The ease of doing business score captures the gap between an economy's performance and a measure of best practice across the entire sample of 41 indicators for 10 Doing Business topics (the labor market regulation indicators are excluded). For starting a business, for example, New Zealand and Georgia have the lowest number of procedures required (1). New Zealand also holds the shortest time to start a business (0.5 days), while Slovenia has the lowest cost (0.0). Calculating the ease of doing business score for each economy involves two main steps. In the first step individual component indicators are normalized to a common unit where each of the 41 component indicators y (except for the total tax and contribution rate) is rescaled using the linear transformation (worst - y)/(worst - best). In this formulation, the highest score represents the best regulatory performance on the indicator across all economies since 2005 or the third year in which data for the indicator were collected. Both the best regulatory performance and the worst regulatory performance are established every five years based on the Doing Business data for the year in which they are established and remain at that level for the five years regardless of any changes in data in interim years. Thus, an economy may establish the best regulatory performance for an indicator even though it may not have the highest score in a subsequent year. Conversely, an economy may score higher than the best regulatory performance if the economy reforms after the best regulatory performance is set. For example, the best regulatory performance for the time to get electricity is set at 18 days. In the Republic of Korea it now takes 13 days to get electricity while in the United Arab Emirates it takes just 10 days. Although the two economies have different times, both economies score 100 on the time to get electricity because they have exceeded the threshold of 18 days. For scores such as those on the strength of legal rights index or the quality of land administration index, the best regulatory performance is set at the highest possible value (although no economy has yet reached that value in the case of the latter). Due to the changes in methodologies, some variables are presented separately, given that they are not comparable given these said changes.

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ENVIPOLCON

QoG Code: epc

ENVIPOLCON is the acronym of "Environmental governance in Europe: the impact of international institutions and trade on policy convergence". The project was carried out between 2003 and 2006 by the University of Konstanz, University of Hamburg, Germany, Free University of Berlin, University of Salzburg, and Radboud University Nijmegen. The project was supported by the EU, RTD programme "Improving the human research potential and the socioeconomic knowledge base", contract no. HPSE-CT-2002-00103. This compilation only includes data on policy instrument adoption from ENVIPOLCON. Each of the instrument variables is coded with scores ranging from 1= obligatory standard to 10 = voluntary instrument. 0 = no instrument because no policy was in place yet. For the variable on the promotion of renewable energy (e.g. ener_i7) the additional instrument "legal obligation to purchase that electricity" was coded as = 11. Other variables from ENVIPOLCON are included into the extension of the dataset - ENVIPOLCONCHANGE, which is also a part of this compilation.

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ENVIPOLCONCHANGE

QoG Code: epcc

The Dataset "ENVIPOLCONCHANGE (Environmental Policy Change). A dataset on environmental regulations in 24 OECD countries from 1970 to 2005" has been collected by the ENVIPOLCON group at the University of Konstanz (Stephan Heichel, Katharina Holzinger, Christoph Knill, Thomas Sommerer) in 2009. Data collection was funded by the German Research Foundation DFG (Grant HO 1811/3-1; KN 891/1-1)." The names of most variables follow the following structure: epcc_*_in2 - the introduction of the policy for the first time; epcc_*_ch2 - change in the policy, including the introduction; epcc_*_s, epcc_car_*, and epcc_lcp_* - standards, such as limit values on emissions and similar, where * is a code of the policy issue.

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Environmental Performance Index Data 2020

QoG Code: epi

The Environmental Performance Index provides a ranking that shines light on how each country manages environmental issues. The Environmental Performance Index (EPI) ranks how well countries perform on high-priority environmental issues in two broad policy areas: protection of human health from environmental harm and protection of ecosystems. Within these two policy objectives the EPI scores country performance in 11 issue areas comprised of 32 indicators. Indicators in the EPI measure how close countries are to meeting internationally established targets or, in the absence of agreed-upon targets, how they compare to the range of observed countries. Note: In many cases the EPI variables lack actual observations and rely on imputation. Please refer to the original documentation on more information about this. Also, some values (usually the value 0) are very unlikely, please use your judgement whether to treat these as the value 0 or as ``Data missing''. The values on the EPI, Policy Objectives, and Issue Categories are not comparable over time, therefore, this compilation only includes data on these variables from the latest release. The raw data on the 32 indicators, however, are comparable over time and, therefore, time-series are included.

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Environmental Policy Stringency Index

QoG Code: eps

The OECD Environmental Policy Stringency Index (EPS) is a country-specific and internationally-comparable measure of the stringency of environmental policy.

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European Quality of Government Index

QoG Code: eqi

The European Quality of Government Index (EQI) is the result of novel survey data regional (e.g. sub-national) level governance within the EU. The data was first gathered and published in 2010 and then repeated in 2013 and 2017, with the next round expected in 2020. The index is based on a large citizen survey where respondents are asked about perceptions and experiences with public sector corruption, along with the extent to which citizens believe various public sector services are impartially allocated and of good quality. It is the first source of data to date that allows researchers to compare QoG within and across countries in a multi-country context. It aims to provide researchers and policy makers a tool to better understand how governance varies within countries and now, over time. It covers all 28 member states and two accession countries (Serbia and Turkey are also included in the 2013 round). The sub-national regions are at the NUTS 1 or NUTS 2 level, depending on the country. Currently, it provides data for up to 206 regions, depending on the year in question. In the three years of the EQI survey, it has roughly 200,000 respondents in total. Here, it provides both the regional level data, as well as the underlying micro data free of charge for researchers and practitioners interested in regional governance in Europe.

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European Social Survey - Wave 1-9

QoG Code: ess

The European Social Survey (ESS) is an academically-driven multi-country survey, which has been administered in over 30 countries to date. Its three aims are: first - to monitor and interpret changing public attitudes and values within Europe and to investigate how they interact with Europe's changing institutions; second - to advance and consolidate improved methods of cross-national survey measurement in Europe and beyond; and third - to develop a series of European social indicators, including attitudinal indicators. This dataset includes two types of variables: 1) percentage of respondents choosing a particular response option, and 2) average response per country, weighted using design weights (dweight), as recommended by the ESS.

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Eurostat Datasets

QoG Code: eu

Eurostat is the statistical office of the European Union situated in Luxembourg. Its mission is to provide high quality statistics for Europe. Its key task is to provide the European Union with statistics at European level that enable comparisons between countries and regions. Eurostat offers a whole range of important and interesting data that governments, businesses, the education sector, journalists and the public can use for their work and daily life.

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Dataset of Electoral Volatility in the European Parliament elections since 1979

QoG Code: evep

This dataset provides data on electoral volatility and its internal components in the elections for the European Parliament (EP) in all European Union (EU) countries since 1979 or the date of their accession to the Union. It also provides data about electoral volatility for both the class bloc and the demarcation bloc. This dataset will be regularly updated so as to include the next rounds of the European Parliament elections.

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Environmental Land Use Data

QoG Code: fao

The FAOSTAT Land Use domain contains data on 47 categories of land use, irrigation and agricultural practices, relevant to monitor agriculture, forestry, and fisheries activities at national, regional and global level. Data are available by country and year, with global coverage and annual updates. Note: Micronesia has been dropped due to duplicate cases.

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Ethnic and Cultural Diversity by Country

QoG Code: fe

Used in the article Ethnic and Cultural Diversity by Country published in Journal of Economic Growth, containing data on 822 ethnic groups in 160 countries that made up at least 1 percent of the country population in the early 1990s. This data was last originally updated in 2003. For this compilation, QoG Data imputes the values from 2003 into 2019.

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Fragile States Index

QoG Code: ffp

The Fragile States Index (Failed States Index), produced by The Fund for Peace, is a critical tool in highlighting not only the normal pressures that all states experience, but also in identifying when those pressures are pushing a state towards the brink of failure. By highlighting pertinent issues in weak and failing states, the FSI - and the social science framework and software application upon which it is built - makes political risk assessment and early warning of conflict accessible to policy-makers and the public at large. The strength of the FSI is its ability to distill millions of pieces of information into a form that is relevant as well as easily digestible and informative. Daily, The Fund for Peace collects thousands of reports and information from around the world, detailing the existing social, economic and political pressures faced by each of the 178 countries. The FSI is based on The Fund for Peace's proprietary Conflict Assessment Software Tool (CAST) analytical platform. Based on comprehensive social science methodology, data from three primary sources is triangulated and subjected to critical review to obtain final scores for the FSI. Millions of documents are analyzed every year. By applying highly specialized search parameters, scores are apportioned for every country based on twelve key political, social and economic indicators (which in turn include over 100 sub-indicators) that are the result of years of painstaking expert social science research. The Fund for Peace's software performs content analysis on this collected information. The scores produced by The Fund for Peace's software are also compared with a comprehensive set of vital statistics - as well as human analysis - to ensure that the software has not misinterpreted the raw data. Though the basic data underpinning the Failed States Index is already freely and widely available electronically, the strength of the analysis is in the methodological rigor and the systematic integration of a wide range of data sources. Note: The principle of data timing was changed. Data from reports correspond to the situation from the previous year. The 2020 Fragile States Index, comprises data collected between January 1, 2019, and December 31, 2019. Therefore data from Report 2020 is recorded for 2019 and the same logic works for all other years.

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Freedom in the World

QoG Code: fh

Freedom in the World is an annual global report on political rights and civil liberties, composed of numerical ratings and descriptive texts for each country and a select group of territories. The 2020 edition covers developments in 195 countries and 15 territories from January 1, 2019, through December 31, 2019. The report's methodology is derived in large measure from the Universal Declaration of Human Rights, adopted by the UN General Assembly in 1948. Freedom in the World is based on the premise that these standards apply to all countries and territories, irrespective of geographical location, ethnic or religious composition, or level of economic development. Freedom in the World operates from the assumption that freedom for all people is best achieved in liberal democratic societies. Freedom in the World assesses the real-world rights and freedoms enjoyed by individuals, rather than governments or government performance per se. Political rights and civil liberties can be affected by both state and nonstate actors, including insurgents and other armed groups. To read more about the methodology used by Freedom House, please visit https://freedomhouse.org/reports/freedom-world/freedom-world-research-methodology. These subcategories, drawn from the Universal Declaration of Human Rights, represent the fundamental components of freedom, which include an individual's ability to: - Vote freely in legitimate elections; - Participate freely in the political process; - Have representatives that are accountable to them; - Exercise freedoms of expression and belief; - Be able to freely assemble and associate; - Have access to an established and equitable system of rule of law; - Enjoy personal freedoms, including free movement, the right to hold private property, social freedoms, and equal access to economic opportunities. Note: The 1982 edition of Freedom in the World covers the period Jan 1981 - Aug 1982 (=1981 in our dataset). The 1983-84 edition covers the period Aug 1982 - Nov 1983 (=1983 in our dataset). This leaves 1982 empty. For 1972, South Africa was in the original data rated as ``White'' (fh_cl: 3, fh_pr: 2, fh_status: Free) and ``Black'' (fh_cl: 6, fh_pr: 5, fh_status: Not Free). We treat South Africa 1972 as missing.

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Freedom on the Net

QoG Code: fhn

Freedom on the Net is a Freedom House project consisting of cutting-edge analysis, fact-based advocacy, and on-the-ground capacity building. It features a ranked, country-by-country assessment of online freedom, a global overview of the latest developments, as well as in depth country reports. Freedom on the Net measures the subtle and not-so-subtle ways that governments and non-state actors around the world restrict our intrinsic rights online. Each country assessment includes a detailed narrative report and numerical score, based on methodology developed in consultation with international experts. This methodology includes three categories: 1. Obstacles to Access details infrastructural and economic barriers to access, legal and ownership control over internet service providers , and independence of regulatory bodies; 2. Limits on Content analyzes legal regulations on content, technical filtering and blocking of websites, self-censorship, the vibrancy/diversity of online news media, and the use of digital tools for civic mobilization; 3. Violations of User Rights tackles surveillance, privacy, and repercussions for online speech and activities, such as imprisonment, extralegal harassment, or cyberattacks. Freedom on the Net is a collaborative effort between a small team of Freedom House staff and an extensive network of local researchers and advisors in 65 countries.

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Freedom of the Press

QoG Code: fhp

Freedom of the Press assesses the degree of print, broadcast, and digital media freedom in 199 countries and territories. Published since 1980, it provides numerical scores and country narratives evaluating the legal environment for the media, political pressures that influence reporting, and economic factors that affect access to news and information. Freedom of the Press is the most comprehensive data set available on global media freedom and serves as a key resource for policymakers, international institutions, journalists, activists, and scholars worldwide. Note: The number in the variable names indicate what time period they refer to. 1: 1979-1987 2: 1988-1992 3: 1993-1995 4: 1996-2000 5: 2001-2016

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Economic Freedom of the World Dataset

QoG Code: fi

The index published in Economic Freedom of the World measures the degree to which the policies and institutions of countries are supportive of economic freedom. The cornerstones of economic freedom are personal choice, voluntary exchange, freedom to enter markets and compete, and security of the person and privately owned property. The EFW index now ranks 159 countries and territories. Data are available for approximately 100 nations and territories back to 1980, and many back to 1970. This data set makes it possible for scholars to analyze the impact of both cross-country differences in economic freedom and changes in that freedom across a time frame of three and a half decades. For a consistent time-series for a particular country and/or longitudinal data for a panel of countries, the Fraser Institute previously developed and reported a chain-linked version of the index. One of the problems with the chain-linked index was that it was limited to just the 123 countries that were available in the chain-link's ``base year'' of 2000. With this year's report, the Institute is replacing the chain-linked index with the EFW Panel Dataset, which reports area and summary ratings for all countries for which we have a regular EFW index score in any given year. The EFW Panel Dataset adjusts the regular EFW index in two ways. (1) From the most-recent year annually back to 2000, whenever possible, any missing data is estimated by autoregressively ``backcasting'' the data, meaning the actual values are used in later years to estimate the missing values for earlier years. For example, if a country is missing a data value for a particular component from 2000-2004, this method estimates the missing 2000-2004 values based on data available in 2005 and thereafter. This approach allows to have area and summary ratings for up to the entire 159 countries in the EFW index. (2) For 1970, 1975, 1980, 1985, 1990, and 1995, the index is chain-linked as described in previous editions. That is, using 2000 as the base year, changes in a country's scores backward in time are based only on changes in components that were present in adjoining years. It should be noted that the EFW Panel Dataset contains area and summary ratings only for those years in which the country received a regular EFW index rating.

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State Capacity, Minority Shareholder Protections, and Stock Market Development

QoG Code: gc

A longitudinal dataset on the adoption of minority shareholders' legal protections and the development of the stock market in 78 countries between 1970 and 2016.

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Global Corruption Barometer

QoG Code: gcb

The Global Corruption Barometer is the only world wide public opinion survey about the views and experiences of corruption. The Global Corruption Barometer asks for people's views on corruption in their country generally, how the level of corruption has changed and in which institution's the problem of corruption is most severe. It also provides a measure of people's experience of bribery in the past year across six different services. The survey asks people how well or badly they think their government has done at stopping corruption. For the 2015-2017 version all the values have been assigned the year 2016. Note: Only valid answers are used when calculating the averages, ``Unknown'', ``Don't know'' etc. are excluded. For the 2003-2013 version, the data for a country is marked as missing if there are less than 100 respondents per year, if there are 100 or more, the value corresponds to the mean of all answers.

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The Political Terror Scale

QoG Code: gd

The PTS measures violations of physical integrity rights carried out by states or their agents, covering some 200 countries or territories from 1976 to 2016. The PTS seeks to measure political terror. The authors define political terror as violations of basic human rights to the physical integrity of the person by agents of the state within the territorial boundaries of the state in question. It is important to note that political terror as defined by the PTS is not synonymous with terrorism or the use of violence and intimidation in pursuit of political aims. The concept is also distinguishable from terrorism as a tactic or from criminal acts.

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Global Educational Attainment 1970-2015

QoG Code: gea

These are IHME results data from a global analysis of educational attainment spanning the last 50 years. These data are an update to earlier estimates (Educational Attainment and Child Mortality Estimates by Country 1970-2009) and inform the IHME policy report ``A Hand Up: Global Progress Towards Universal Education'', as well as the Social Determinants of Health Visualization, which is supported by the Center for Health Trends and Forecasts at IHME. This data file provides estimates of average years of educational attainment per capita for people over the age of 15 for the years 1970-2015 by year, sex, and age group for 188 countries, 21 GBD regions, 7 GBD super regions, and the global aggregate. Age-standardized and population-weighted estimates are included for females 15-44 and for both sexes for the age group 25+.

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IMF GFS - Expenditure by Functions of Government (COFOG)

QoG Code: gfs

The IMF Government Finance Statistics (GFS) database contains fiscal data for all reporting countries in the framework of the Government Finance Statistics Manual 2014 (GFSM 2014). It includes detailed data on revenues, expenditures, transactions in financial assets and liabilities, and balance sheet data and includes data for the general government sector and its subsectors (e.g., central government, local government, state government and social security funds). GFS data are compiled by country authorities and reported to the IMF Statistics Department annually. The data reported in the QoG Datasets is retrieved from Expenditure by Function of Government (COFOG) dataset, as the percentage of total expenditure by general government.

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Green Growth

QoG Code: gg

The OECD Green Growth database contains selected indicators for monitoring progress towards green growth to support policy making and inform the public at large. The database synthesises data and indicators across a wide range of domains including a range of OECD databases as well as external data sources. The database covers OECD member and accession countries, key partners (including Brazil, China, India, Indonesia and South Africa) and other selected non-OECD countries. The indicators have been selected according to well-specified criteria and embedded in a conceptual framework, which is structured around four groups to capture the main features of green growth: (1) Environmental and resource productivity: indicate whether economic growth is becoming greener with more efficient use of natural capital and to capture aspects of production which are rarely quantified in economic models and accounting frameworks; (2) The natural asset base: indicate the risks to growth from a declining natural asset base; (3) Environmental dimension of quality of life: indicate how environmental conditions affect the quality of life and wellbeing of people; (4) Economic opportunities and policy responses: indicate the effectiveness of policies in delivering green growth and describe the societal responses needed to secure business and employment opportunities.

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The Global Gender Gap Index 2006-2019

QoG Code: gggi

The Global Gender Gap Report benchmarks 153 countries on their progress towards gender parity across four thematic dimensions: Economic Participation and Opportunity, Educational Attainment, Health and Survival, and Political Empowerment.

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The Gender Inequality Index

QoG Code: gii

The Gender Inequality Index (GII) reflects gender-based disadvantage in three dimensions - reproductive health, empowerment and the labour market - for as many countries as data of reasonable quality allow. It shows the loss in potential human development due to inequality between female and male achievements in these dimensions. It ranges from 0, where women and men fare equally, to 1, where one gender fares as poorly as possible in all measured dimensions.

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Expanded Trade and GDP Data

QoG Code: gle

The dataset by Kristian Gleditsch provides estimates of trade flows between independent states (1948-2000) and GDP per capita of independent states (1950-2011). Version 6. In order to fill in gaps in the Penn World Table's mark 5.6 and 6.2 data (see: Heston, Summers \& Aten), Gleditsch has imputed missing data by using an alternative source of data (the CIA World Fact Book), and through extrapolation beyond available time-series.

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Democratic Electoral Systems Around the World 1946-2016

QoG Code: gol

The data focus on national-level (lower house) legislative and presidential elections in democratic regimes. A regime is classified as a democracy at the time of an election if (i) the chief executive is elected, (ii) the legislature is elected, (iii) there is more than one party competing in elections, and (iv) an alternation under identical electoral rules has taken place. A regime is classified as a dictatorship at the time of an election if any of these four conditions do not hold (Przeworski et al., 2000; Cheibub, Gandhi and Vreeland, 2010). Note: The original values of -99 (the information is missing but should theoretically be available) and -88 (there is no single value for this particular variable) have been recoded to ''.'' (missing).

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Global Peace Index

QoG Code: gpi

The Global Peace Index (GPI), which ranks 163 independent states and territories according to their level of peacefulness. Produced by the Institute for Economics and Peace (IEP), the GPI is the world's leading measure of global peacefulness. The complete version of the GPI covers 99.7 per cent of the world's population, using 23 qualitative and quantitative indicators from highly respected sources, and measures the state of peace using three thematic domains: the level of Societal Safety and Security; the extent of Ongoing Domestic and International Conflict; and the degree of Militarisation. Please refer to the original source to see all of the indicators.

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Centripetal Democratic Governance

QoG Code: gtm

Data used in the book A Centripetal Theory of Democratic Governance (Gerring, John and Thacker, Strom C, 2008).

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Financing the State: Government Tax Revenue from 1800 to 2012

QoG Code: gtr

The Financing the State: Government Tax Revenue from 1800 to 2012 dataset provides information on the size and composition of government tax revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. It provides a comprehensive picture of the sources of government funding starting with the establishment or independence of modern nation states in the early 19th century. The original dataset contains further information on sub-categories of direct and indirect taxes, such as revenues received through property, income, excise, consumption and custom taxes.

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Autocratic Regime Data: Autocratic Regimes

QoG Code: gwf

When the leader of an autocratic regime loses power, one of three things happens. The incumbent leadership group is replaced by democratically elected leaders. Someone from the incumbent leadership group replaces them, and the regime persists. Or the incumbent leadership group loses control to a different group that replaces it with a new autocracy. The data set facilitates the investigation of all three kinds of transition. The data identify how regimes exit power, how much violence occurs during transitions, and whether the regimes that precede and succeed them are autocratic. The data identify autocratic regime breakdowns regardless of whether the country democratizes, which makes possible the investigation of why the ouster of dictators sometimes leads to democracy but often does not, and many other questions.

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Political Constraint Index (POLCON) Dataset

QoG Code: h

The measure of political constraints employed estimates the feasibility of policy change (the extent to which a change in the preferences of any one actor may lead to a change in government policy) using the following methodology. First, extracting data from political science databases, it identifies the number of independent branches of government (executive, lower and upper legislative chambers) with veto power over policy change. The preferences of each of these branches and the status quo policy are then assumed to be independently and identically drawn from a uniform, unidimensional policy space. This assumption allows for the derivation of a quantitative measure of institutional hazards using a simple spatial model of political interaction.

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Index of Economic Freedom

QoG Code: hf

The Index of Economic Freedom covers 10 freedoms - from property rights to entrepreneurship - in 186 countries. Note: For the 2015, most data covers the second half of 2013 through the first half of 2014. To the extent possible, the information considered for each factor was current as of June 30, 2014. It is important to understand that some factors are based on historical information. For example, the monetary policy factor is a 3-year weighted average rate of inflation from January 1, 2011, to December 31, 2013.

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HRV Transparency Project

QoG Code: hrv

The HRV Transparency project examines the causes and consequences of government transparency both through theoretical and empirical approaches with the measure of government transparency or HRV Index. The HRV index contrasts with other measurements because it relies on a precise and narrow conception of transparency: the disclosure of policy-relevant information by the government to the public. The HRV Index focuses on the availability of credible aggregate economic data. It does so by examining patterns of missing data and treating transparency as the latent term which best reflects the tendency to disclose. This measure provides observations for 125 countries from 1980-2010 and can be used to measure relationships between transparency and other issues such as democracy, accountability, or political instability. Transparency encompasses many dimensions. The HRV index measures a specific aspect of government transparency: reporting national data to international organizations. Rather than rely on expert but subjective judgments, the measure is based on objective criteria. The HRV team uses ``Item Response Theory'' a highly sophisticated and computationally intense method to estimate transparency. This method assigns different weights for reporting distinct measures of the economy, based on how many other countries actually reported data on the measure, and how much a country distinguishes itself from other countries by reporting data on a given measure. (Technically, the model estimates ``difficulty'' and ``discrimination'' parameters for each economic variable.) The model analyzes 240 measures of the economy consistently collected by the World Bank's World Development Indicators. Since the World Bank obtains its data from other international agencies that, in turn, obtain their data from national statistical offices, the HRV measure is a valid indicator of governments' efforts to collect and disseminate economically relevant information. Moreover, because the World Bank omits data considered ``questionable'', this index reflects the collection and dissemination of generally credible information about a country's national economy.

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The Authoritarian Regime Dataset

QoG Code: ht

The Authoritarian Regimes Dataset version 6.0 covers the time period 1972-2014 and includes all 192 nations recognized as members of the UN except the four micro states of Europe (Andorra, Liechtenstein, Monaco and San Marino) and two micro states in the Pacific that are not members of the World Bank (Nauru and Tuvalu).

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Institutions and Elections Project Data

QoG Code: iaep

Institutions and Elections Project Data (version 2.0). The objective of the data from the Institutions and Elections Project (IAEP) is to describe the formal institutions that are in place, even if practice does not comport with those formal rules. The data refers to the situation January 1st each year. Note: According to the documentation of the data many of the cases ``have more than one executive; [...] the executive referred to may be any one of the executives established in a country''. We urge users to refer to the documentation at the IAEP web site for information about which executive each particular case refers to. Note: Changes from the original version: The dataset has two types of missing values, logical missing values and actual missing values. In the QoG data, logical missing values were recoded to actual missing values. To access data with logical missing values please use original dataset. Source: IAEP (Wig et al, 2015). Find the article at http://journals.sagepub.com/doi/abs/10.1177/2053168015579120

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Open Budget Survey Data

QoG Code: ibp

The Open Budget Survey is a comprehensive analysis and survey that evaluates whether governments give the public access to budget information and opportunities to participate in the budget process at the national level. The Survey also assess the capacity and independence of formal oversight institutions. The IBP works with civil society partners in 100 countries to collect the data for the survey. These materials were developed by the International Budget Partnership. IBP has given us permission to use the materials solely for noncommercial, educational purposes.

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Information Capacity Dataset

QoG Code: icd

The original Information Capacity Dataset offers numerical data on five institutions and policies that modern states use to collect information about their populations and territories: (1) the regular implementation of a reliable census, (2) the regular release of statistical yearbooks, the operation of (3) civil and (4) population registers, and (5) the establishment of a government agency tasked with processing statistical information. Based on these five indicators, an overall index of “information capacity” is calculated for 85 polities from 1750 to 2015.

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ICRG Indicator of Quality of Government

QoG Code: icrg

ICRG collects political information and financial and economic data, converting these into risk points.

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ICTD/UNU-WIDER Government Revenue Dataset

QoG Code: ictd

The GRD aims to present a complete picture of government revenue and tax trends over time and allows for analysis at the country, regional or cross-country level. Where possible, figures are expressed both inclusive and exclusive of natural resource revenues, which helps to overcome a major obstacle to cross-country comparisons in existing data sources.

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Electoral System Design

QoG Code: ideaesd

The Electoral System Design Database is comprised of various reviews of the electoral legislation of countries from around the world. The database research was sourced from national legal documents from different sources, including the official web portals of governments, regional organizations that work in the area of democracy and electoral processes, and research institutes specialized in the area of elections and politics in general.

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Voter Turnout Database

QoG Code: ideavt

The Voter Turnout Database is the best resource for a wide array of statistics on voter turnout from around the world. It contains the most comprehensive global collection of voter turnout statistics from presidential and parliamentary elections since 1945. Always growing, the database also includes European Parliament elections, as presented by country using both the number of registered voters and voting age population as indicators, and in some cases the data includes statistics on spoilt ballot rate.

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International Environmental Agreements Database Project

QoG Code: iead

International Environmental Agreements (IEA) include efforts to regulate human interactions with the environment that involve legally binding commitments ("agreements") among governments ("international") that have environmental protection as a primary objective ("environmental").The IEAs include: - instruments designated as convention, treaty, agreement, accord, or their non-English equivalents, and protocols and amendments to such instruments; - instruments, regardless of designation, establishing intergovernmental commissions; - instruments, regardless of designation, identified as binding by reliable sources (e.g., by a secretariat, UNEP, or published legal analysis); or - instruments, regardless of designation, whose texts fit accepted terminologies of legally-binding agreements. Intergovernmental "soft laws," such as action plans, agreed measures, codes of conduct, declarations, resolutions, and similar policies that are not binding are excluded. European Union (EU) directives are also excluded due to their unique status.

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Global Burden of Disease Study 2017

QoG Code: ihme

IHME provides rigorous and comparable measurement of the world's most important health problems and evaluates the strategies used to address them.

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Ibrahim Index of African Governance

QoG Code: iiag

The Ibrahim Index of African Governance (IIAG) is a tool that measures and monitors governance performance in African countries. The IIAG governance framework comprises four categories: Safety \& Rule of Law, Participation \& Human Rights, Sustainable Economic Opportunity and Human Development. These categories are made up of 14 sub-categories, consisting of 100 indicators. The IIAG is refined on an annual basis. Refinements may be methodological, or based on the inclusion or exclusion of indicators. Different IIAG datasets are not comparable between themselves as they cover a different ten-year period, data are revised retrospectively, and the theoretical framework is updated between iterations. Users of the Index should therefore always reference the most recent version of the IIAG data set.

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Index of Public Integrity

QoG Code: ipi

This dataset contains data used in the construction of the Index of Public Integrity (IPI). The overall IPI score is the arithmetic average of the following six components scores: Judicial Independence, Administrative Burden, Trade Openness, Budget Transparency, E-Citizenship, and Freedom of the Press. Several indices currently show that corruption remains a key issue not only in developing countries but also in many modern societies. How to control it better has thus become a major question of international development. Yet, the common corruption indices tell us mainly about how citizens and experts perceive the state of corruption in their society. They do not tell us anything about the causes of corruption nor about how the situation could be improved. The Index of Public Integrity ipi-toolbar takes a different approach. It assesses a society's capacity to control corruption and ensure that public resources are spent without corrupt practices. It is based on years of research and the evaluation of the efforts of different societies to make advances in the control of corruption. Evidence from comparisons across countries shows that establishing effective control of corruption requires much more than the mere adoption of specific tools and strict legal regulations. It relies on a balance between a state calibrated to reduce the possibility of the abuse of influence and a society's capacity to hold its government accountable. The IPI highlights the most important dimensions of that mechanism. It correlates with the World Bank's and Transparency International's measures of control of corruption, but in contrast to them it is more objective and transparent.

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Inter-Parliamentary Union Data

QoG Code: ipu

The data has been compiled by the Inter-Parliamentary Union on the basis of information provided by National Parliaments. Comparative data on the world and regional averages as well as data concerning the two regional parliamentary assemblies elected by direct suffrage can be found on separate pages. Note: The figures for South Africa on the distribution of seats in the Upper House do not include the 36 special rotating delegates appointed on an ad hoc basis, and all percentages given are therefore calculated on the basis of the 54 permanent seats. Included in the QoG Dataset are the data for January each year.

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The International Social Survey Programme. Environment Module

QoG Code: issp-environment

The International Social Survey Programme (ISSP) is an annual program of cross-national survey collaboration, covering a wide range of topics important for social science research. Since 1985 the ISSP provides international data sets, enabling cross-cultural and cross-temporal research. "Environment" is one of the eleven ISSP topic modules. Central themes are attitudes towards environment-related issues, such as environmental protection, respondents' behavior, and respondents' preferences regarding governmental measures on environmental protection. This dataset includes two types of variables: 1) percentage of respondents choosing a particular response option, and 2) average response per country, unweighted, primarily because weights are unavailable for some countries. Correlation between weighted and unweighted means for countries that do provide weights is above .95 for most of the included variables and does not go below .89.

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Electoral Systems and the Personal Vote

QoG Code: jw

This database updates and expands the coding of electoral systems presented in Gaviria et al's (2003) Database of Particularism. Data now cover up to 180 countries from 1978-2005 and distinguish electoral systems by the degree to which electoral institutions create incentives for candidates to cultivate a personal vote - as described theoretically in Carey and Shugart (1995) and Gaviria et al. (2003) - including the amount of vote pooling among co-partisan candidates, the amount of parties' control over ballot access, and whether voters cast their votes for candidates or parties. The database also contains several variables that rank-order electoral systems by tier, distinguish mixed-member and other multi-tier electoral systems, capture district magnitude (in two ways), and record election years. Database created 2007. Database last updated 2010.

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Institutional Quality Dataset

QoG Code: kun

More than 30 established institutional indicators can be clustered into three homogeneous groups of formal institutions: legal, political and economic, which capture to a large extent the complete formal institutional environment of a country. The latent qualities of legal, political and economic institutions for every country in the world and for every year are calculated. On this basis, a legal, political and economic World Institutional Quality Ranking are proposed, through which one can follow whether a country is improving or worsening its relative institutional environment. The calculated latent institutional quality measures can be useful in further panel data applications and add to the usual practice of using simply one or another index of institutional quality to capture the institutional environment.

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Luxembourg Income Study Database and the Luxembourg Wealth Study Database

QoG Code: lis

LIS, formerly known as The Luxembourg Income Study, is a data archive and research center dedicated to cross-national analysis. LIS is home to two databases, the Luxembourg Income Study Database, and the Luxembourg Wealth Study Database. The Luxembourg Income Study Database (LIS), under constant expansion, is the largest available database of harmonised microdata collected from multiple countries over a period of decades. The newer Luxembourg Wealth Study Database (LWS), is the only cross-national wealth microdatabase in existence.

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Data used in the article "The Quality of Government"

QoG Code: lp

Original sources for the Religion variables: Barrett (1982), Worldmark Encyclopedia of the Nations (1995), Statistical Ab-stract of the World (1995), United Nations (1995) and CIA (1996).

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Maddison Project Database 2018

QoG Code: mad

The Maddison Project Database provides information on comparative economic growth and income levels over the very long run. The 2018 version of this database covers 169 countries and the period up to 2018.

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National Elections Across Democracy and Autocracy V5

QoG Code: nelda

The National Elections across Democracy and Autocracy (NELDA) dataset provides detailed information on all election events from 1945-2015. To be included, elections must be for a national executive figure, such as a president, or for a national legislative body, such as a parliament, legislature, constituent assembly, or other directly elected representative bodies. In order for an election to be included, voters must directly elect the person or persons appearing on the ballot to the national post in question. Voting must also be direct, or ``by the people'' in the sense that mass voting takes place.

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Democracy Time-series Data Release 3.0, January 2009

QoG Code: no

This dataset is in a country-year case format, suitable for cross-national time-series analysis. It contains data on the social, economic and political characteristics of 191 nations with over 600 variables from 1971 to 2007. In particular, it merges the indicators of democracy by Freedom House, Vanhanen, Polity IV, and Cheibub and Gandhi, selected institutional classifications and also socioeconomic indicators. Note that you should check the original codebook for the definition and measurement of each of the variables. The period for each series also varies. This is the replication dataset used in the book, Driving Democracy.

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Natural Resource Management Index Data

QoG Code: nrmi

The Natural Resource Protection and Child Health Indicators, 2019 Release, is produced in support of the U.S. Millennium Challenge Corporation (MCC) as selection criteria for funding eligibility. The Natural Resource Protection Indicator (NRPI) and Child Health Indicator (CHI) are based on proximity-to-target scores ranging from 0 to 100 (at target). The NRPI covers 234 countries and is calculated based on the weighted average percentage of biomes under protected status. The CHI is a composite index for 195 countries derived from the average of three proximity-to-target scores for access to at least basic water and sanitation, along with child mortality. The 2019 release includes a consistent time series of NRPI scores for 2015 to 2019 and CHI scores for 2010 to 2018.

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Country Ruggedness and Geographical Data (2012)

QoG Code: nunn

The dataset of terrain ruggedness and other geographical characteristics of countries was created by Nathan Nunn and Diego Puga for their article `Ruggedness: The blessing of bad geography in Africa', published in the Review of Economics and Statistics 94(1), February 2012: 20-36.

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Country Statistical Profiles

QoG Code: oecd

The Country Statistical Profiles database from the Organisation for Economic Cooperation and Development (OECD) includes a wide range of indicators on economy, education, energy, environment, foreign aid, health, information and communication, labour, migration, R\&D, trade, and society that better reflect key figures about the member states of the OECD. Historical data refer to the latest eight time periods. Please note we have selected some of these variables for this version of the QoG Datasets. Find the full list of variables in the source's website.

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Environmentally Adjusted Multifactor Productivity

QoG Code: oecd_eamp

Environmentally adjusted multifactor productivity (EAMFP) takes into account the reliance of national economies on natural resources and national efforts to mitigate environmental damage.

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OECD Environment Statistics

QoG Code: oecd_env

The OECD Environmental Statistics database provide a unique collection of policy-relevant environmental statistics.

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Environmental Protection Expenditure Accounts (EPEA)

QoG Code: oecd_epea

The Environmental Protection Expenditure Account (EPEA) is a monetary description of environmental protection activities in accordance with the System of Environmental-Economic Accounting (SEEA) central framework. It is coherent with the European System of Accounts (ESA 2010) which applies to national accounts and related satellite accounts.

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Policy Instruments for the Environment

QoG Code: oecd_pine

Policy Instruments for the Environment (PINE) is originally developed by OECD in co-operation with the European Environment Agency (EEA). The database contains detailed qualitative and quantitative information on environmentally related taxes, fees and charges, tradable permits, deposit-refund systems, environmentally motivated subsidies, and voluntary approaches used for environmental policy. The dataset covers OECD member countries, accession countries and selected non-OECD countries since the year 1994, and it has been cross-validated and complemented with Revenue statistics from the OECD Tax statistics database and official national sources.

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Exposure to PM2.5 in Countries and Regions

QoG Code: oecd_pm

The underlying PM2.5 concentration estimates are taken from the Global Burden of Disease (GBD) 2019 project. They are derived by integrating satellite observations, chemical transport models, and measurements from ground monitoring station networks. The concentration estimates are population-weighted using gridded population datasets from the Joint Research Center Global Human Settlement project. These are produced by distributing census-derived population estimates from the Gridded Population of the World, version 4 from the NASA Socioeconomic Data and Applications Center according to the density and distribution of built-up areas. For political and administrative boundaries, OECD (2020) territorial grid units are used where available, for the remaining countries, the FAO (2015) Global Administrative Unit Layers (GAUL 2014) are used (see below for details). The OECD (2020) Functional Urban Area definition is used for cities. The accuracy of these exposure estimates varies considerably by location. Accuracy is poorer in areas with few monitoring stations and in areas with very high concentrations such as Africa, the Middle-East and South Asia. Accuracy is generally good in regions with dense monitoring station networks (such as most advanced economies). See Shaddick et al. (2018) for further details. See Green Growth dataset for further measures of PM exposure.

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The Ocean Health Index Data

QoG Code: ohi

The Ocean Health Index is a valuable tool for the ongoing assessment of ocean health. By providing a means to advance comprehensive ocean policy and compare future progress, the Index can inform decisions about how to use or protect marine ecosystems. The Index is a collaborative effort, made possible through contributions from more than 65 scientists/ocean experts and partnerships between organizations including the National Center for Ecological Analysis and Synthesis, Sea Around Us, Conservation International, National Geographic, and the New England Aquarium. The Index assesses the ocean based on 10 widely-held public goals for a healthy ocean. They are: Food Provision, Artisanal Fishing Opportunities, Natural Products, Carbon Storage, Coastal Protection, Sense of Place, Coastal Livelihoods \& Economies, Tourism \& Recreation, Clean Waters, Biodiversity.

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Polity V Annual Time-Series, 1800-2018

QoG Code: p

The Polity project is one of the most widely used data resource for studying regime change and the effects of regime authority.Polity5 Project, Political Regime Characteristics and Transitions, 1800-2018, annual, cross-national, time-series and polity-case formats coding democratic and autocratic ''patterns of authority'' and regime changes in all independent countries with total population greater than 500,000 in 2018 (167 countries in 2018). Please note that the codes -99, -88, -77 and -66 has been recoded to missing.

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Electoral Integrity Project (Version 7.0)

QoG Code: pei

This dataset by the Electoral Integrity Project evaluates the quality of elections held around the world. Based on a rolling survey collecting the views of election experts, this research provides independent and reliable evidence to compare whether countries meet international standards of electoral integrity. PEI-7.0 cumulative release covers 336 national parliamentary and presidential contests held worldwide in 166 countries from 1 July 2012 to 31 December 2018.

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The Property Rights Protection index

QoG Code: prp

Over the last two decades, numerous studies have tried to quantify the effect of property rights on a wide range of societal outcomes, including growth, trade, and, to a lesser extent, inequality. However, a major limitation of these studies has been the data measuring property rights. These suffer from a number of shortcomings, including a lack of availability, focus, and objectivity. Ouattara and Standaert address this gap by composing a new index of property rights that strictly focuses on the protection of these rights. As is common with indicators of governance, there is little to no objective data available that can be used to directly compare the security of property rights across countries. Instead, perception-based indicators such as survey-data or expert assessments are used to capture the opinion of a range of actors. The researchers approach is to combine a data set of 18 such indicators from 7 different sources. The selection of an indicator depending on whether it directly measured 'the degree to which a country's laws protect private property rights and the degree to which its government enforces those laws, including the probability that private property is expropriated'. By focusing on property rights alone, this allows the researchers to disentangle its effect from that of the overall quality of the judicial system and other aspects of the institutional framework. This ensures a better match between theoretical models and empirical tests on the effects of property rights. This is done for as wide a group of countries and as long a time span as possible, increasing the index coverage by as much as 45% compared to other indexes - this index covers 191 countries cross twenty-year period between 1994 - 2014.

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New Parties and Party System Innovation in Western Europe

QoG Code: psi

This dataset identifies and lists all the new parties emerged in Western Europe since 1945 and provides data about party system innovation, defined as the aggregate level of 'newness' recorded in a party system at a given election. Data are based on parliamentary elections (lower house) of 20 Western European countries since 1945. This dataset covers the entire universe of Western European elections held after World War II under democratic regimes. Data for Greece, Portugal and Spain have been collected after their democratizations in the 1970s.

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The Economic Effects of Constitutions

QoG Code: pt

Persson and Tabellini only include countries of democratic rule in their sample. To be included in the cross-section, an average of the Freedom House indices for civil liberties and political rights (fh_cl and fh_pr) lower than an average of 5 for the 1990-1998 period is required. For the 1960- 1998 panel data, Persson and Tabellini include country-years that obtain a score greater than zero on the Polity democracy indicator (p_polity2) (For details, see Persson and Tabellini 2003, 74- 77).

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Penn World Table

QoG Code: pwt

PWT version 9.1 is a database with information on relative levels of income, output, input and productivity, covering 182 countries between 1950 and 2017. In Penn World Table the users are offered two different series of data for China. ''China Version 1'' uses the official growth rates for the whole period. ''China Version 2'' uses the recent modifications of official Chinese growth rates. We have chosen to include China Version 1.

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The QoG Expert Survey (2014 wave)

QoG Code: qs

The QoG Survey is a data set on the structure and behavior of public administration, based on a web survey. The dataset covers key dimensions of quality of government, such as politicization, professionalization, openness, and impartiality. Included in the QoG dataset are three indexes, each based on a group of questions from the survey. When constructing the indexes authors excluded countries with less than three responding experts. The confidence interval variables give the higher and lower limits of the 95% confidence interval.

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Ethnolinguistic Fractionalization (ELF) Indices, 1961 and 1985

QoG Code: r

Indices are computed from population estimates of different sources. For details, please follow link above.

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Oil and Gas Data, 1932-2014

QoG Code: ross

Global dataset of oil and natural gas production, prices, exports, and net exports. These data are based on the best available information about the volume and value of oil and natural gas production in all countries from 1932 to 2014. The volume figures are from the documents listed in the original source; to calculate the total value of production, the author multiplies the volume by the world price for oil or gas. Since these are world prices for a single (benchmark) type of oil/gas, they only approximate the actual price - which varies by country according to the quality, the terms of contracts, the timing of the transactions, and other factors. These figures do not tell how much revenues were collected by governments or companies - only the approximate volume and value of production. Data on oil production from 1946 to 1969, and gas production from 1955 (when it first was reported) to 1969, are from the US Geological Survey Minerals Yearbook, for various years.

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World Press Freedom Index

QoG Code: rsf

The Reporters Without Borders World Press Freedom Index ranks the performance of 180 countries according to a range of criteria that include media pluralism and independence, respect for the safety and freedom of journalists, and the legislative, institutional and infrastructural environment in which the media operate.

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Extended State History Index

QoG Code: sai

The data set extends and replaces previous versions of the State Antiquity Index (originally created by Bockstette, Chanda and Putterman, 2002). The updated data extends the previous Statehist data into the years before 1 CE, to the first states in Mesopotamia (in the fourth millennium BCE), along with filling in the years 1951 - 2000 CE that were left out of past versions of the Statehist data. The construction of the index follows the principles developed by Bockstette et al (2002). First, the duration of state existence is established for each territory defined by modern-day country borders. Second, this duration is divided into 50-year periods. For each half-century from the first period (state emergence) onwards, the authors assign scores to reflect three dimensions of state presence, based on the following questions: 1) Is there a government above the tribal level? 2) Is this government foreign or locally based? 3) How much of the territory of the modern country was ruled by this government?

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The Comparative Welfare Entitlements Dataset

QoG Code: sc

This data set collection provides systematic data on institutional features of social insurance programs in eighteen countries spanning much of the post-war period. Its purpose is to provide an essential complement to program spending data that is available from international sources like the OECD's Social Expenditure Database.

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Swedish Formal Instruction Dataset

QoG Code: se_agency

This database consists of a comprehensive sample of administrative agencies in the Swedish executive bureaucracy between 1960 and 2014. The database is constituted by three distinct datasets: one that focuses on an agency's formal instruction; one that focuses on an agency's head; and one that focuses on an agency's budget. Note that each dataset has its own unit of analysis. The agency's head data can be found at SND. The data was originally assembled for the project "The Politics of Administrative Design" (financed by the Swedish Research Council through grant 2014-947), which focused on how partisan shifts in government can affect the staff, structure, and process of public bureaucracies. The purpose of the dataset is to provide a quantitative catalogue of Swedish agencies for public use. For the instruction data, one observation corresponds to one agency instruction, while the variables cover factors such as the agency's management structure and formal functions. Finally, all three datasets contain relevant time-period indicators to enable users to determine the temporal coverage of an observation (e.g., enactment and revocation dates for the instructions). In total, the database covers 1925 agency instructions, 2315 agency heads, and 7102 fiscal years. Importantly, while each dataset has its own unit of analysis, we have also included a unifying agency identification number that can be used to link variables across all three datasets. For example, suppose that we are interested in the School Inspectorate ("Skolinspektionen"). We can then start our investigation in either of the three datasets, and use the agency's ID number to match the agency's various instructions, heads, and budgets over time. Note, however, that because the units do not perfectly overlap (e.g., one fiscal year may cover more than one agency head), merging the datasets will require substantive decisions about how to structure the information in each dataset. For this reason, we have left it to the user's discretion to decide whether and how to merge the datasets, rather than impose any particular structure on all three datasets. In total, the database contains information on 664 unique agencies.

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Swedish Budget Dataset

QoG Code: se_budget

This database consists of a comprehensive sample of administrative agencies in the Swedish executive bureaucracy between 1960 and 2014. The database is constituted by three distinct datasets: one that focuses on an agency's formal instruction; one that focuses on an agency's head; and one that focuses on an agency's budget. Note that each dataset has its own unit of analysis. The agency's head data can be found at SND. The data was originally assembled for the project "The Politics of Administrative Design" (financed by the Swedish Research Council through grant 2014-947), which focused on how partisan shifts in government can affect the staff, structure, and process of public bureaucracies. The purpose of the dataset is to provide a quantitative catalogue of Swedish agencies for public use. For the agency budget data, one observation corresponds to one fiscal year, while the variables cover factors such as the amount of funds that were allocated and withdrawn from the agency during that year. Finally, all three datasets contain relevant time-period indicators to enable users to determine the temporal coverage of an observation (e.g., enactment and revocation dates for the instructions). In total, the database covers 1925 agency instructions, 2315 agency heads, and 7102 fiscal years. Importantly, while each dataset has its own unit of analysis, we have also included a unifying agency identification number that can be used to link variables across all three datasets. For example, suppose that we are interested in the School Inspectorate ("Skolinspektionen"). We can then start our investigation in either of the three datasets, and use the agency's ID number to match the agency's various instructions, heads, and budgets over time. Note, however, that because the units do not perfectly overlap (e.g., one fiscal year may cover more than one agency head), merging the datasets will require substantive decisions about how to structure the information in each dataset. For this reason, we have left it to the user's discretion to decide whether and how to merge the datasets, rather than impose any particular structure on all three datasets. In total, the database contains information on 664 unique agencies.

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Swedish Agency Head Dataset

QoG Code: se_head

This database consists of a comprehensive sample of administrative agencies in the Swedish executive bureaucracy between 1960 and 2014. The database is constituted by three distinct datasets: one that focuses on an agency's formal instruction; one that focuses on an agency's head; and one that focuses on an agency's budget. Note that each dataset has its own unit of analysis. The agency's head data can be found at SND. The data was originally assembled for the project "The Politics of Administrative Design" (financed by the Swedish Research Council through grant 2014-947), which focused on how partisan shifts in government can affect the staff, structure, and process of public bureaucracies. The purpose of the dataset is to provide a quantitative catalogue of Swedish agencies for public use. For the agency head data, one observation corresponds to one agency head, while the variables cover factors such as the head's education and background experience. Finally, all three datasets contain relevant time-period indicators to enable users to determine the temporal coverage of an observation (e.g., enactment and revocation dates for the instructions). In total, the database covers 1925 agency instructions, 2315 agency heads, and 7102 fiscal years. Importantly, while each dataset has its own unit of analysis, we have also included a unifying agency identification number that can be used to link variables across all three datasets. For example, suppose that we are interested in the School Inspectorate ("Skolinspektionen"). We can then start our investigation in either of the three datasets, and use the agency's ID number to match the agency's various instructions, heads, and budgets over time. Note, however, that because the units do not perfectly overlap (e.g., one fiscal year may cover more than one agency head), merging the datasets will require substantive decisions about how to structure the information in each dataset. For this reason, we have left it to the user's discretion to decide whether and how to merge the datasets, rather than impose any particular structure on all three datasets. In total, the database contains information on 664 unique agencies.

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Sustainable Governance Indicators

QoG Code: sgi

The Sustainable Governance Indicators (SGI) is a platform built on a cross-national survey of governance that identifies reform needs in 41 EU and OECD countries. SGI explores how governments target sustainable development and advocate for more sustainable governance built on three pillars: 1) Policy Performance; 2) Democracy; and 3) Governance.

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Shadow Economies: Model Based estimates (2012)

QoG Code: shec

The authors use a two-sector dynamic general equilibrium model; they developed an approach to estimate the size of the shadow economy. Compared to the methods used in the current literature, this approach overcomes three main issues. First, it does not rely on ad-hoc econometric specifications and assumptions. Second, as it does not estimate the size of the shadow economy using statistical methods, it does not include statistical errors. Finally, as opposed to the currently existing methods, it does not lack micro-foundations.

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Social Insurance Entitlements dataset (SIED)

QoG Code: sied

The Social Insurance Entitlements dataset (SIED) consists of gross and net value variables of the four insurance programs in the 34 countries between 1930 and 2015. The Social Insurance Entitlements dataset (SIED) is a continuation of the Social Citizenship Indicator Program(SCIP), but carries on data collection beyond 2005 for a larger number of countries. The SIE dataset closely follows the structure of SCIP, thus covering the same social insurance programs and sharing the same variable names. The SIE dataset includes the original 18 SCIP countries, but also stores data for all EU Member States as of 2010. The current version of SIED stores three waves of data for all EU countries, 2005 to 2015. Data for Greece, Portugal and Spain goes back to 1980. Used abbreviations: APW= Average Production Worker, APWW= Average Production Workers Wage, RR= Replacement Rate.

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The Long-Term Effects of Africa's Slave Trades Dataset (2008)

QoG Code: slavet

To construct a measure of the total number of slaves taken from each country during the four slave trades between 1400 and 1900, Nunn collected data that report the total number of slaves exported from each port or region in Africa and data that reports the ethnic identity of slaves shipped from Africa. There were a number of ways Nunn identified the ethnicity or nation of a slave: The easiest was often by a slave's name. Slaves were often given a Christian first name and a surname that identified their ethnicity (e.g., Tardieu [2001]). As well, a slave's ethnicity could often be determined from ethnic markings, such as cuts, scars, hairstyles, or the filing of teeth (Karasch 1987, pp. 4-9). Information on the ethnicities of slaves shipped during the trans-Atlantic slave trade comes from 54 different samples, totalling 80,656 slaves, with 229 distinct ethnic designations reported. The ethnicity data for the Indian Ocean slave trade come from six samples, with a total of 21,048 slaves and 80 different ethnicities reported. The data for the Red Sea slave trade are from two samples: one from Jedda, Saudi Arabia, and the other from Bombay, India. The samples provide information for 67 slaves, with 32 different reported ethnicities. For the trans-Saharan slave trade two samples are available: one from central Sudan and the other from western Sudan. The samples provide information on the origins of 5,385 slaves, with 23 different ethnicities recorded. The shipping data from Austen (1992) also provide additional information on which caravan slaves were shipped on, the city or town that the caravan originated in, the destination of the caravan, and in some cases the ethnic identity of the slaves being shipped. Nunn combines the data in the following way: Using the shipping data, Nunn first calculates the number of slaves shipped from each coastal country in Africa. In an example 100,000 slaves were shipped from Country A and 250,000 were shipped from Country C. The problem with relying on the shipping data alone is that many of slaves shipped from Country A may have come from Country B, which lies landlocked behind Country A. Then, using the ethnicity data, Nunn calculates the ratio of slaves from each coastal country relative to any landlocked countries located inland of the coastal country. This requires to map ethnicities to countries and aggregate up to the country level. In practice, this step relied on a great amount of past research by African historians, linguists, and ethnographers. The sources most heavily used are Koelle (1854), Murdock (1959), Curtin (1969), Higman (1984), and Hall (2005).

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Stock of Climate Laws and Policies

QoG Code: slaws

Data on the stock of climate change mitigation laws and policies used in the paper: Eskander, S.M. and Fankhauser, S., 2020. Reduction in greenhouse gas emissions from national climate legislation. Nature Climate Change, 10(8), pp.750-756. Mitigation laws and policies refer to a legislative or executive disposition focused on curbing a country's greenhouse gases emissions in one sector or more. Measures can be directly related to emissions reductions, such as laws establishing a national carbon budget or cap and trade system, or indirectly related, such as laws or policies establishing relevant institutions or providing additional funding for research and development into low carbon technologies. Laws and policies addressing forests and land use are included as long as they explicitly support climate change mitigation through activities that reduce emissions and increase carbon removals. General forest management and conservation laws are not included, even if they may have implicit consequences for climate change mitigation.

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Social Progress Index

QoG Code: spi

The Social Progress Index (SPI) is a well-established measure, published since 2013, that is meant to catalyze improvement and drive action by presenting social outcome data in a useful and reliable way. The 2020 Social Progress Index ranks 163 countries on social progress. It combines 50 social and environmental outcome indicators to calculate an overall score for these countries, based on tiered levels of scoring that include measures in health, safety, education, technology, rights, and more. In addition to the overall scores, three broad dimensions of social progress are also measured: Basic Human Needs, Foundations of Wellbeing, and Opportunity. It also considers the data of 30 additional countries, calculating component and dimension scores when enough data are available. In all, the SPI measures at least some aspects of social progress across more than 99.85% of the world's population.

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The Societal Violence Scale

QoG Code: svs

The Societal Violence Scale seeks to develop measures of societal violence based on annual US State Department's Human Rights reports. The Societal Violence Scale ranks countries on a 5-point scale (from the lowest level of societal violence to the highest) based on three criteria. First, the authors look at scope: the proportion of society that is victimized. Thus, widespread violence against women (who account for 50 percent of the population) figures more heavily in the final score than widespread abuses against human rights defenders, who represent a very small number. The authors also look at the severity of abuses. For example, evidence that human rights defenders are killed weighs more heavily than beatings of human rights defenders. Likewise, while women are routinely subjected to sexual violence and domestic violence, the addition of other types of violence against women like gang rape, sex trafficking, and/or FGM/C adds to the assessment of severity.

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Comparative Political Parties Dataset

QoG Code: sw

Dataset captures characteristics of political parties in Australia, Austria, Belgium, Canada, Denmark, Finland, France, West Germany, Ireland, Italy, Japan, Netherlands, New Zealand, Norway, Sweden, Switzerland, United Kingdom, United States, Greece, Portugal, and Spain between 1950 to 2011. This dataset uses the following categories for parties: Left: communist; socialist, social democratic, and labor; and other various left-wing parties (e.g., left-libertarian parties); Right: far-right (e.g., neo-fascist, right-wing populist), classical liberal, Conservative Christian Democratic, and other various right-wing parties; Centrist Christian Democratic (Centrist CD): non-conservative Catholic parties; Secular Center (Secular Cent): non-catholic parties of the center. The data set also includes a total Christian Democratic party category and all variables for Radical Right-Wing Populist and Left-Libertarian parties.

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Corruption Perceptions Index

QoG Code: ti

The CPI focuses on corruption in the public sector and defines corruption as the abuse of public office for private gain. The surveys used in compiling the CPI tend to ask questions in line with the misuse of public power for private benefit, with a focus, for example, on bribe-taking by public officials in public procurement. The sources do not distinguish between administrative and political corruption. The CPI Score relates to perceptions of the degree of corruption as seen by business people, risk analysts and the general public and ranges between 100 (highly clean) and 0 (highly corrupt). Note: The time-series information in the CPI scores can only be used if interpreted with caution. Year-to-year shifts in a country's score can result not only from a changing perception of a country's performance but also from a changing sample and methodology. That is, with differing respondents and slightly differing methodologies, a change in a country's score may also relate to the fact that different viewpoints have been collected and different questions have been asked. Moreover, each country's CPI score is composed as a 3-year moving average, implying that if changes occur they only gradually affect a country's score. For a more detailed discussion of comparability over time in the CPI, see Lambsdorff 2005. Note: In 2012 TI changed methodology for which the data is no comparable and only data from 2012 can be compared. Also, the observation ''Belgium/Luxembourg'' from the 1995 data has been dropped. The Corruption Perception Index (2018) by Transparency International is licensed under CC-BY-ND 4.0

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World Inequality Database

QoG Code: top

Built to accompany the publishing of the two books Top Incomes: a Global Perspective (2010, Oxford University Press) and Top Incomes over the XX Century (2007, Oxford University Press), the World Top Incomes Database offers the most comprehensive set of historical series on income inequality available so far. In the 2010 book, the authors analyze the long term evolution of top incomes in 12 new countries (after the 10 initial countries analysed in the 2007 book).

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UCDP Dyadic Dataset version 20.1

QoG Code: ucdp

The UCDP Dyadic Dataset is a project within the Uppsala Conflict Data Program (UCDP) at the Department of Peace and Conflict Research, Uppsala University. The UCDP Dyadic dataset builds on the UCDP/PRIO Armed Conflict dataset, but goes beyond the conflict level and focuses on dyads within each conflict. As such, it constitutes a disaggregated version of the UCDP/PRIO Armed Conflict dataset.

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Unified Democracy Scores

QoG Code: uds

The Unified Democracy Scores (UDS) now covers the time period 1946-2012. These new scores incorporate recent updates to three of the ten original measures - Freedom House (2014), Polity IV (Marshall et al. 2012), and VanHanen (2012) - that feature in the analysis that the authors report in their 2010 article. In addition, the current release adds a recently developed measure of democracy - Economist Intelligence Unit (2012) - to its framework.

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Human Development Report

QoG Code: undp

The Human Development Report (HDR) is an annual report published by the Human Development Report Office of the United Nations Development Programme (UNDP). The entire series of Human Development Index (HDI) values and rankings are recalculated every year using the most recent (revised) data and functional forms. The HDI rankings and values in the 2014 Human Development Report cannot therefore be compared directly to indices published in previous Reports. Please see hdr.undp.org for more information. The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes.

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UNESCO Institute for Statistics

QoG Code: une

The UNESCO Institute for Statistics (UIS) is the official and trusted source of internationally-comparable data on education, science, culture and communication. As the official statistical agency of UNESCO, the UIS produces a wide range of state-of-the-art databases to fuel the policies and investments needed to transform lives and propel the world towards its development goals. The UIS provides free access to data for all UNESCO countries and regional groupings from 1970 to the most recent year available.

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Measures of Democracy 1810-2018

QoG Code: van

The data contain three different variables, created by Tatu Vanhanen. The variables in question are political competition, political participation and the index of democratization.

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Varieties of Democracy Dataset version 10

QoG Code: vdem

Varieties of Democracy (V-Dem) is a new approach to conceptualizing and measuring democracy. It provides a multidimensional and disaggregated dataset that reflects the complexity of the concept of democracy as a system of rule that goes beyond the simple presence of elections. The V-Dem project distinguishes between five high-level principles of democracy: electoral, liberal, participatory, deliberative, and egalitarian, and collects data to measure these principles.

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The ICTWSS database version 6.0

QoG Code: vi

The ICTWSS database covers four key elements of modern political economies: trade unionism, wage setting, state intervention and social pacts. The database contains annual data for all OECD and EU Member States.

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Global Terrorism Index

QoG Code: voh

The Global Terrorism Index (GTI) is a comprehensive study which accounts for the direct and indirect impact of terrorism in 162 countries in terms of its effect on lives lost, injuries, property damage and the psychological after-effects of terrorism. This study covers 99.6 per cent of the world's population. It aggregates the most authoritative data source on terrorism today, the Global Terrorism Database (GTD) collated by the National Consortium for the Study of Terrorism and Responses to Terrorism (START) into a composite score in order to provide an ordinal ranking of nations on the negative impact of terrorism. The GTD is unique in that it consists of systematically and comprehensively coded data on domestic as well as international terrorist incidents and now includes more than 140,000 cases.

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V-Party Dataset

QoG Code: vparty

V-Party provides expert-coded assessments of party organization and identity for most parties in most countries over 1970-2019. Using V-Dem methodology (Coppedge et al., 2020), in January 2020, 665 experts rated the policy positions and organizational capacity of political parties across elections in a given country. Specifically, as a general rule, experts coded data for all parties that reached more than 5% of the vote share at a given election. The expert-coded data are aggregated using V-Dem’s Bayesian Item Response Theory measurement model (Pemstein et al., 2020). The result is data on 1,955 political parties across 1,560 elections in 169 countries; in total 6,330 party-election year units. Typically, at least 4 coders provided their assessment per observation.

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The Worldwide Governance Indicators

QoG Code: wbgi

These indicators are based on several hundred individual variables measuring perceptions of governance, drawn from 31 separate data sources constructed by 25 different organizations. These individual measures of governance are assigned to categories capturing key dimensions of governance. An unobserved component model is used to construct six aggregate governance indicators. Point estimates of the dimensions of governance, the margins of error as well as the number of sources are presented for each country. The governance estimates are normally distributed with a mean of zero and a standard deviation of one each year of measurement. This implies that virtually all scores lie between -2.5 and 2.5, with higher scores corresponding to better outcomes. Note: Since the estimates are standardized (with a mean of zero and a standard deviation of one) each year of measurement, they are not directly suitable for over-time comparisons within countries. Kaufmann et al. (2006) however find no systematic time-trends in a selection of indicators that do allow for comparisons over time, which suggests that time-series information in the WBGI scores can be used if interpreted with caution.

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World Development Indicators

QoG Code: wdi

The primary World Bank collection of development indicators, compiled from officially-recognized international sources. This is an adaptation of an original work by The World Bank. Views and opinions expressed in the adaptation are the sole responsibility of the author or authors of the adaptation and are not endorsed by The World Bank.

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Global Competitiveness Report 2019

QoG Code: wef

The Global Competitiveness Index 4.0 assesses the competitiveness landscape of 140 economies, measuring national competitiveness - defined as the set of institutions, policies and factors that determine the level of productivity. The Report presents information and data that were compiled and/or collected by the World Economic Forum organized into 12 pillars: Institutions, Infrastructure, ICT adoption, Macroeconomic Stability, Health, Skills, Product Market, Labor Market, Financial System, Market Size, Business Dynamism, and Innovation Capabilities.

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Data from Freedom Rising by Christian Welzel

QoG Code: wel

The World Values Survey measures of secular values and emancipative values are theoretically explained and empirically tested for their cross-cultural reliability and validity in Freedom Rising , pp. 57-105. The backward estimates of emancipative values for decades before available survey data are explained in Freedom Rising, pp. 157-161.

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The WhoGov Dataset

QoG Code: wgov

The WhoGov dataset enables researchers to take a new approach to studying governing elites in autocracies and democracies. We provide bibliographic information, such as gender and party affiliation, on cabinet members in July every year in the period 1966-2016 in all countries with a population of more than 400,000 citizens. In total, the dataset contains data on 50,197 cabinet members in 177 countries, adding up to 8,057 country-years. WhoGov makes it possible to answer questions such as; what is the share of female cabinet members globally, which type of regime has the highest cabinet turnover, and have cabinets increased in size over time? and many others. The dataset is highly flexible and can be used to calculate countless variables of interest, including the number of female ministers, ministerial experience, cabinet turnover and cabinet size at the country-year level. The data is based on cabinet compositions in July for all years apart from 1966, where data was only available for September and 1970, where we are using January instead of July. Apart from the cross-sectional dataset that is used for the QoG Compilations, within-country dataset is available in the original source.

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Global Health Observatory data repository

QoG Code: who

The GHO data repository is WHO's gateway to health-related statistics for its 194 Member States. It provides access to over 1000 indicators on priority health topics including mortality and burden of diseases, the Millennium Development Goals (child nutrition, child health, maternal and reproductive health, immunization, HIV/AIDS, tuberculosis, malaria, neglected diseases, water and sanitation), non communicable diseases and risk factors, epidemic-prone diseases, health systems, environmental health, violence and injuries, equity among others.

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World Happiness Index

QoG Code: whr

The World Happiness Report is a landmark survey of the state of global happiness that ranks 156 countries by how happy their citizens perceive themselves to be.

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Autocratic Regime Data: All Political Regimes

QoG Code: wr

Data to identify and analyze autocracy-to-autocracy transitions. Version 1.2. When the leader of an autocratic regime loses power, one of three things happens. The incumbent leadership group is replaced by democratically elected leaders. Someone from the incumbent leadership group replaces him, and the regime persists. Or the incumbent leadership group loses control to a different group that replaces it with a new autocracy. Much scholarship exists on the first kind of transition, but little on transitions from one autocracy to another, though they make up about half of all regime changes.

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World Values Survey

QoG Code: wvs

The World Values Survey is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The European Values Study started in 1981 when a thousand citizens in the European Member States of that time were interviewed using standardized questionnaires. Every nine years, the survey is repeated in a variable number of countries. The fourth wave in 2008 covers no less than 47 European countries/regions, from Iceland to Georgia and from Portugal to Norway. EVS is cooperating with WVS for the data collection in Europe and both datasets can be integrated. The variables are country averages calculated using the population weight provided by WVS/EVS.

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Worldwide Bureacracy Indicators

QoG Code: wwbi

The Worldwide Bureaucracy Indicators (WWBI) database is a unique cross-national dataset on public sector employment and wages that aims to fill an information gap, thereby helping researchers, development practitioners, and policymakers gain a better understanding of the personnel dimensions of state capability, the footprint of the public sector within the overall labor market, and the fiscal implications of the public sector wage bill. The dataset is derived from administrative data and household surveys, thereby complementing existing, expert perception-based approaches. The WWBI includes 192 indicators that are estimated from microdata drawn from the labor force and household welfare surveys and augmented with administrative data for 202 economies in five categories: the demographics of the private and public sector workforces; public sector wage premiums; relative wages and pay compression ratios, gender pay gaps; and the public sector wage bill. The micro and administrative data utilized in the construction of the WWBI are drawn from data catalogs housing surveys conducted by national statistical organizations (NSO) or multilateral organization data teams. Together, these provide an important, albeit narrow, picture of the skills and incentives of bureaucrats. Indicators on public employment track key demographic characteristics including the size of the public sector workforce (in absolute and relative numbers), their age, and distributions across genders, industries, income quintiles, and academic qualifications. Variables on compensation capture both the competitiveness of public sector wages (compared to the private sector) as well as wage differentials across industry or occupation of employment, genders, education, and income quintiles within the public and private sectors as well as pay compression ratios in public and private sectors. The indicators on the size of the wage bill offer a glimpse into the structure and affordability of the public sector within the larger economy.

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Youth Representation Index

QoG Code: yri

The Youth Representation Index assesses the magnitude of youths' under-representation across countries using the last year of election available for 91 countries. Rather than calculating youths' representation by the percentage of Members of Parliament 35 or 40 years old and younger or legislatures' median age, the authors argue that scholars should assess youths' parliamentary presence relative to their proportion of the voting-age population.

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