Singapore led the Index of Economic Freedom in 2024, with an index score of 83.5 out of 100. Switzerland, Ireland, Taiwan, and Luxembourg rounded out the top five. Economic Freedom Index In order to calculate the Economic Freedom Index, the source takes 12 different factors into account, including the rule of law, government size, regulatory efficiency, and open markets. All 12 factors are rated on a scale of zero to 100 and are weighted equally. Every country is rated within the Index in order to provide insight into the health and freedom of the global economy. Singapore's economy Singapore is one of the four so-called Asian Tigers, a term used to describe four countries in Asia that saw a booming economic development from the 1950s to the early 1990. Today, the City-State is known for its many skyscrapers, and its economy continue to boom. It has one of the lowest tax-rates in the Asia-Pacific region, and continues to be open towards foreign direct investment (FDI). Moreover, Singapore has one of the highest trade-to-GDP ratios worldwide, underlining its export-oriented economy. Finally, its geographic location has given it a strategic position as a center connecting other countries in the region with the outside world. However, the economic boom has come at a cost, with the city now ranked among the world's most expensive.

In 2025, Israel was given a score of **** on the Economic Freedom Index published by The Heritage Foundation. This positions the country's economy as the top 26th most liberal in the world, just below the United States. The world average economic freedom score in 2021 was ****.

The average for 2025 based on 174 countries was 60 index points. The highest value was in Singapore: 84 index points and the lowest value was in North Korea: 3 index points. The indicator is available from 1995 to 2025. Below is a chart for all countries where data are available.

(UNCLASSIFIED) Despite significant progress, Liberia still lags in promoting the effective rule of law. The judicial system remains vulnerable to political interference, and property rights are not strongly protected. Lingering corruption further undermines freedom and hampers the emergence of more vibrant economic activity.Liberia has benefited from over USD 16 billion in FDI commitments since the end of the war in iron ore, forestry, rubber and palm oil. The government is promoting increased local business linkages with these global value chains in order to increase the capacity and value added of the local private sector while also increasing employment and the skills base. However, the capacity of the local private sector currently limits participation, while it is also bound by severe infrastructure constraints. Investment to address infrastructure bottlenecks is moving forward. The business environment, which is being supported by increased dialogue with stakeholders and improved information sharing, will also need further enhancement.Liberia’s average tariff rate is 10.4 percent. The government restricts foreign investment in several sectors. The financial sector remains vulnerable to political influence and institutional instability. The scarce access to financing continues to impede much-needed entrepreneurial activity and private-sector development. The financial sector is dominated by banking, but a large part of the population remains outside of the formal banking sector. Attribute Table Field DescriptionsISO3 - International Organization for Standardization 3-digit country code ADM0_NAME - Administration level zero identification / name ADM1_NAME - Administration level one identification/name ADM2_NAME - Administration level two identification / name NAME - Name of foreign investment project SECTOR - Sector of foreign investment project DESCRIP - Description of foreign investment project LEND_INSTR - Lending Instrument CITY - City location VALUE - Value of foreign investment in millions APP_DATE - Date application was approved APP_YEAR - Year application was approved SPA_ACC - Spatial accuracy of site location (1 – high, 2 – medium, 3 – low, 4 – regional, 5 – country) SOURCE_DT - Primary source creation date SOURCE - Primary source SOURCE2_DT - Secondary source creation date SOURCE2 - Secondary source CollectionThe feature class was generated utilizing data from the UNDP, AFDB, and The World Bank.The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe is not responsible for the accuracy and completeness of data compiled from outside sources.Sources (HGIS)The Heritage Foundation. “Liberia Economy.” Index of Economic Freedom. 2014. Accessed September 29, 2014. http://www.heritage.org.The World Bank. “Liberia.” The World Bank. 2014. Accessed September 29, 2014. http://www.worldbank.org.Sources (Metadata)Hettinger, O.; Kilo, M.; Perrault, F. “Liberia Country Strategy Paper 2013-2017.” African Development Bank Group. June 2013. Accessed September 29, 2014. http://www.afdb.org.The Heritage Foundation. “Liberia Economy.” Index of Economic Freedom. 2014. Accessed September 29, 2014. http://www.heritage.org.Hettinger, P.; James, J. “Liberia 2014.” African Economic Outlook. 2014. Accessed September 29, 2014. http://www.africaneconomicoutlook.org.The World Bank. “Liberia.” The World Bank. 2014. Accessed September 29, 2014. http://www.worldbank.org.

Given both corruption's and bureaucratic inefficiency's importance for development and good governance, understanding their causes is paramount. This paper argues that majority state ownership of most the most important economic sectors of a country results in higher levels of corruption and inefficiency. When political and managerial elites both own and manage the country's most important economic resources, they have greater incentives for corrupt or inefficient behavior. These elites use national resources at their disposal more for short-term personal and political goals than for long-term economic ones. This paper tests this hypothesis on a relatively underused, but often cited, data set from the 1980s. Using a cross-national, regression analysis, this paper finds that the best predictors a country's level of corruption or bureaucratic inefficiency are these: majority state ownership of significant economic sectors, levels of GDP per capita, levels of government spending, and levels of democracy. Other factors, such as common law heritage, percent of population that is Protestant, federalism, economic freedoms, or mineral/ oil exporting, were not consistent, significant predictors of either bureaucratic inefficiency or corruption. We also argue that Tobit may be the best estimation procedure for these data.

Following the approval of sustainable development goals at the global level, the link between fiscal policy, institutional quality, and economic growth has attracted special attention in economic literature. This study scrutinizes the effect of government revenue-institutional quality interaction on the economic growth of 43 Sub-Saharan Africa countries for the period of 2012–2022. Methodology-wise, the study employed the System Generalized Method of Moment (SGMM) to analyze the panel data gained from dependable data sources; the World Development Indicator and the Heritage Economic Freedom Index. The novelty of this study emanates from the estimation technique designated and the introduction of revenue-institutional quality into the economic growth model of SSA. The result of the study reveals that government revenue adversely affects economic growth while institutional quality positively enhances economic growth before interacting with each other. However, the interactive coefficient of government revenue and economic growth positively affected the real GDP growth rate of SSA countries over the study periods. Precisely, before interacting with institutional quality, a percentage change in government revenue, keeping all other things constant, leads to a 0.0866 percent decline in economic growth while it marks a 0.2329 percent upsurge in economic growth in the presence of institutional quality. The result of the study further shows that government revenue promotes the economic growth of the region when combined with institutional quality. On the other hand, foreign direct investment and openness to trade were the key sources of economic growth whereas the population growth rate adversely impacted economic growth in SSA countries. The policy implication of the study is that SSA needs to strengthen government revenue management. Further, the finding of the study implies that SSA countries need to improve institutional quality through promoting efficiency of the regulatory quality and the size of the SSA governments. In addition to this, the fast real GDP growth rate of SSA countries demands improved institutional quality indicators such as the rule of law and extended access to the open market.

This is a small dataset of various global indicators developed for use in a course teaching research methods at the Croft Institute for International Studies at the University of Mississippi. The data is ready to be directly imported into SPSS, Stata, or other statistical packages. A brief codebook includes descriptions of each variable, the indicator's reference year(s), and links to the original sources. The data is cross-sectional, country-level data centered on 2015 as the primary reference year. Some data come from the most recent election or averages from a handful of years. The dataset includes socioeconomic and political data drawn from sources and indicators from the World Bank, the UNDP, and International IDEA. It also includes popular indexes (and some key components) from Freedom House, Polity IV, the Economist's Democracy Index, the Heritage Foundation's Index of Economic Freedom, and the Fund for Peace's Fragile States Index. The dataset also includes various types of data (nominal, ordinal, interval, and ratio), useful for pedagogical examples of how to handle statistical data.

This file assembles data from multiple sources, but many of the measures are from the ARDA's coding of the 2003 US State Department's International Religious Freedom Reports. This coding produced data on 195 different countries and territories (see Grim and Finke 2006 for a list of countries coded), but excluded the United States. Additional data on religious regulation and favoritism in the smaller countries not covered by the State Department Reports were provided by researchers at the World Christian Database. In addition, this project assembled (with permission) other cross-national measures of interest to researchers on religion, economics, and politics. They include adherent information from the World Christian Database, scales from Freedom House and the Heritage Foundation, and various socio-economic measures from the United Nations. Measures for religious persecution (AESTIMA) and ethnic identity (DETHNIC) were added to this file in August 2007.

(Note: This dataset was previously available for download under the title "Cross-National Data: Religion Indexes, Religious Adherents, and Other Data.")

France: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la France de 1995 à 2025. La valeur moyenne pour France pendant cette période était de 62 index points avec un minimum de 57 index points en 2000 et un maximum de 66 index points en 2020.

Côte d'Ivoire: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la Côte d'Ivoire de 1995 à 2025. La valeur moyenne pour Côte d'Ivoire pendant cette période était de 57 index points avec un minimum de 50 index points en 1996 et un maximum de 63 index points en 2017.

Bénin: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la Bénin de 1996 à 2025. La valeur moyenne pour Bénin pendant cette période était de 57 index points avec un minimum de 52 index points en 2005 et un maximum de 62 index points en 1998.

Pays-Bas: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la Pays-Bas de 1996 à 2025. La valeur moyenne pour Pays-Bas pendant cette période était de 75 index points avec un minimum de 69 index points en 1998 et un maximum de 80 index points en 2022.

Burkina Faso: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la Burkina Faso de 1996 à 2025. La valeur moyenne pour Burkina Faso pendant cette période était de 57 index points avec un minimum de 49 index points en 1996 et un maximum de 61 index points en 2011.

Colombie: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la Colombie de 1995 à 2025. La valeur moyenne pour Colombie pendant cette période était de 65 index points avec un minimum de 59 index points en 2024 et un maximum de 72 index points en 2015.

États-Unis: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la États-Unis de 1995 à 2025. La valeur moyenne pour États-Unis pendant cette période était de 77 index points avec un minimum de 70 index points en 2024 et un maximum de 81 index points en 2006.

Canada: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la Canada de 1995 à 2025. La valeur moyenne pour Canada pendant cette période était de 76 index points avec un minimum de 68 index points en 1997 et un maximum de 81 index points en 2009.

Belize: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la Belize de 1995 à 2025. La valeur moyenne pour Belize pendant cette période était de 61 index points avec un minimum de 55 index points en 2019 et un maximum de 66 index points en 2001.

Argentine: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la Argentine de 1995 à 2025. La valeur moyenne pour Argentine pendant cette période était de 56 index points avec un minimum de 44 index points en 2015 et un maximum de 75 index points en 1996.

Norvège: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la Norvège de 1996 à 2025. La valeur moyenne pour Norvège pendant cette période était de 70 index points avec un minimum de 65 index points en 1996 et un maximum de 78 index points en 2024.

République dominicaine: Economic freedom, overall index (0-100): Pour cet indicateur, The Heritage Foundation fournit des données pour la République dominicaine de 1995 à 2025. La valeur moyenne pour République dominicaine pendant cette période était de 59 index points avec un minimum de 54 index points en 1997 et un maximum de 64 index points en 2025.