In the 2023 edition of the globalization index, Switzerland had the highest index score at 90.75. Belgium followed behind, with the Netherlands in third. Overall, globalization declined in 2020 due to the COVID-19 outbreak, but increased somewhat in 2021, even though it was still below pre-pandemic levels.

About the index

The KOF Index of Globalization aims to measure the rate of globalization in countries around the world. Data used to construct the 2023 edition of the index was from 2021. The index is based on three dimensions, or core sets of indicators: economic, social, and political. Via these three dimensions, the overall index of globalization tries to assess current economic flows, economic restrictions, data on information flows, data on personal contact, and data on cultural proximity within surveyed countries.

Defining globalization

Globalization is defined for this index as the process of creating networks of connections among actors at multi-continental distances, mediated through a variety of flows including people, information and ideas, capital and goods. It is a process that erodes national boundaries, integrates national economies, cultures, technologies and governance and produces complex relations of mutual interdependence.

According to the Global Hunger Index 2024, hunger worldwide decreased since 2000, but the pace of the reduction has slowed since 2016. In the Middle East and North Africa, for instance, the hunger index value was the same in 2024 as in 2016, and it had even increased marginally in Latin America and the Caribbean. In 2024, Somalia had the highest index score worldwide, meaning it was the country where hunger was most prevalent. The World Hunger Index combines four indicators: undernourishment, child stunting, child wasting, and child mortality.

This dataset shows Qatar’s score and ranking in the Global Gender Gap Index. The index measures gender-based disparities across four key areas: economic participation and opportunity, educational attainment, health and survival, and political empowerment.

The Global Cybersecurity Index (GCI) is a trusted reference that measures the commitment of countries to cybersecurity at a global level – to raise awareness of the importance and different dimensions of the issue. As cybersecurity has a broad field of application, cutting across many industries and various sectors, each country's level of development or engagement is assessed along five pillars – (i) Legal Measures, (ii) Technical Measures, (iii) Organizational Measures, (iv) Capacity Development, and (v) Cooperation – and then aggregated into an overall score.​

The global gender gap index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2025, the country offering the most gender equal conditions was Iceland, with a score of 0.93. Overall, the Nordic countries make up 3 of the 5 most gender equal countries worldwide. The Nordic countries are known for their high levels of gender equality, including high female employment rates and evenly divided parental leave. Sudan is the second-least gender equal country Pakistan is found on the other end of the scale, ranked as the least gender equal country in the world. Conditions for civilians in the North African country have worsened significantly after a civil war broke out in April 2023. Especially girls and women are suffering and have become victims of sexual violence. Moreover, nearly 9 million people are estimated to be at acute risk of famine. The Middle East and North Africa have the largest gender gap Looking at the different world regions, the Middle East and North Africa have the largest gender gap as of 2023, just ahead of South Asia. Moreover, it is estimated that it will take another 152 years before the gender gap in the Middle East and North Africa is closed. On the other hand, Europe has the lowest gender gap in the world.

This series is an updated index of global real economic activity in industrial commodity markets, as proposed in Kilian (2009) (https://doi.org/10.1257/aer.99.3.1053), with the correction discussed in Kilian (2019) (https://doi.org/10.1016/j.econlet.2019.03.001). This business-cycle index is expressed in percent deviations from trend. It is derived from a panel of dollar-denominated global bulk dry cargo shipping rates and may be viewed as a proxy for the volume of shipping in global industrial commodity markets. For further discussion of the advantages of this index compared with measures of global real GDP or global industrial production see Kilian and Zhou (2018) (https://doi.org/10.1016/j.jimonfin.2018.07.001).

Broad Based Index Fund Market Outlook

The global broad-based index fund market size was valued at USD 5.3 trillion in 2023 and is projected to reach USD 11.2 trillion by 2032, growing at a compound annual growth rate (CAGR) of 8.5% during the forecast period. This substantial growth is driven by increasing investor interest in passive investment strategies, along with the rising emphasis on cost-effective and diversified portfolio management.

The surge in demand for broad-based index funds can be attributed to several key growth factors. Firstly, the growing awareness and education about the benefits of passive investing over active management have played a significant role. Investors are increasingly leaning towards index funds due to their lower expense ratios, tax efficiency, and the ability to provide broad market exposure with minimal effort. Secondly, technological advancements and the rise of fintech have made these funds more accessible to a wider audience through online platforms and robo-advisors, democratizing investment opportunities for retail investors globally. Lastly, regulatory changes in many regions are encouraging greater transparency and lower fees in the financial services industry, which further bolsters the attractiveness of index funds as a preferred investment vehicle.

The popularity of broad-based index funds is also bolstered by their performance resilience during market volatility. Historical data indicates that while actively managed funds often struggle to outperform the market consistently, index funds tend to provide more stable returns over the long term. This trend has been particularly noticeable during economic downturns and periods of market uncertainty, where investors seek the relative safety and predictability offered by broad-based diversified portfolios. Additionally, the increased focus on retirement planning and the shift from defined benefit to defined contribution retirement plans have spurred the growth of index funds as they are often the preferred choice in retirement accounts due to their long-term growth potential and lower costs.

The regional outlook for the broad-based index fund market highlights significant growth potential across various geographies. North America, particularly the United States, remains the largest market for index funds, driven by the deep-rooted culture of investing and a well-established financial infrastructure. Europe follows closely, with growth fueled by regulatory support and increasing investor awareness. The Asia Pacific region is expected to witness the highest growth rate, propelled by the burgeoning middle class, rising disposable incomes, and increasing penetration of financial services. Latin America and the Middle East & Africa are also anticipated to demonstrate steady growth as financial markets in these regions continue to develop and mature.

Mutual Funds Sales have seen a notable uptick as investors increasingly seek diversified investment options that align with their financial goals. This trend is particularly evident in the context of broad-based index funds, where mutual funds offer a structured approach to investing in a wide array of assets. The appeal of mutual funds lies in their ability to pool resources from multiple investors, enabling access to a diversified portfolio that might otherwise be unattainable for individual investors. This collective investment model not only reduces risk but also provides investors with professional management and oversight. As the financial landscape evolves, mutual funds continue to play a crucial role in facilitating access to index funds, thereby driving sales and expanding their market presence.

Fund Type Analysis

Equity index funds represent a significant portion of the broad-based index fund market. These funds track a variety of stock indices, such as the S&P 500, NASDAQ, and MSCI World Index, providing investors with exposure to a wide array of equity markets. The appeal of equity index funds lies in their ability to offer broad market diversification at a low cost. Investors benefit from the lower fees associated with passive management and the reduced risk of individual stock selection. As a result, equity index funds have become a staple in both retail and institutional portfolios, driving robust demand and growth in this segment.

Bond index funds, though smaller in market share compared to their equity counterparts, are gaining traction as investors seek stable income and risk diversifi

Finland leads the quality of life sub-index in the Global Retirement Index 2023 with a score of ** percent. All four Nordic neighbors (Denmark, Sweden, Norway, and Iceland) follow behind together with Switzerland, with index scores ranging from ** to ** percent. Norway tops the Retirement Index, an index which measures the quality and security for pensioners.

Zimbabwe ZW: Human Capital Index (HCI): Female: Scale 0-1 data was reported at 0.415 NA in 2010. Zimbabwe ZW: Human Capital Index (HCI): Female: Scale 0-1 data is updated yearly, averaging 0.415 NA from Dec 2010 (Median) to 2010, with 1 observations. Zimbabwe ZW: Human Capital Index (HCI): Female: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zimbabwe – Table ZW.World Bank.WDI: Human Capital Index. The HCI calculates the contributions of health and education to worker productivity. The final index score ranges from zero to one and measures the productivity as a future worker of child born today relative to the benchmark of full health and complete education.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498.; ;

The Global Gender Gap Index (by World Economic Forum) benchmarks the evolution of gender-based gaps among four key dimensions. The following information are visualized for each country: Economic Participation and Opportunity, Educational Attainment, Health and Survival, and Political Empowerment.

The Global Gender Gap index benchmarks 156 countries, providing a tool for cross-country comparison and to prioritize the most effective policies needed to close gender gaps. The methodology of the index has remained stable since its original conception in 2006, providing a basis for robust cross-country and time-series analysis. The Global Gender Gap Index measures scores on a 0 to 100 scale and scores can be interpreted as the distance to parity (i.e. the percentage of the gender gap that has been closed).

This dataset includes indicators from 2006 to 2021.

In 2023, Singapore ranked first with a health index score of ****, followed by Japan and South Korea. The health index measures the extent to which people are healthy and have access to the necessary services to maintain good health, including health outcomes, health systems, illness and risk factors, and mortality rates. The statistic shows the health and health systems ranking of countries worldwide in 2023, by their health index score.

As of 2022, Oceania was the region with the most affordable internet worldwide. The Internet value index in the area was 0.19, 154 percent higher than the global average of 0.07. Europe ranked second, with 0.13 index points, while Asia followed with an index score of 0.08. The lowest internet affordability was in Africa, with an index score of approximately 0.004 points. The Internet value index measures internet affordability in comparison with the quality worldwide.

The Global Cybersecurity Index (GCI) measures the commitment of countries to cybersecurity at a global level. As cybersecurity has a broad field of application, cutting across many industries and various sectors, each country’s level of development or engagement is assessed along five pillars – (i) Legal Measures, (ii) Technical Measures, (iii) Organizational Measures, (iv) Capacity Development, and (v) Cooperation – and then aggregated into an overall score.​

Togo TG: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 43.100 % in 2015. This records a decrease from the previous number of 46.000 % for 2011. Togo TG: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 43.100 % from Dec 2006 (Median) to 2015, with 3 observations. The data reached an all-time high of 46.000 % in 2011 and a record low of 42.200 % in 2006. Togo TG: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Togo – Table TG.World Bank: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Over the last 2 decades, financial systems have been studied and analyzed from the perspective of complex networks, where the nodes and edges in the network represent the various financial components and the strengths of correlations between them. Here, we adopt a similar network-based approach to analyze the daily closing prices of 69 global financial market indices across 65 countries over a period of 2000–2014. We study the correlations among the indices by constructing threshold networks superimposed over minimum spanning trees at different time frames. We investigate the effect of critical events in financial markets (crashes and bubbles) on the interactions among the indices by performing both static and dynamic analyses of the correlations. We compare and contrast the structures of these networks during periods of crashes and bubbles, with respect to the normal periods in the market. In addition, we study the temporal evolution of traditional market indicators, various global network measures, and the recently developed edge-based curvature measures. We show that network-centric measures can be extremely useful in monitoring the fragility in the global financial market indices.

Explore LSEG S&P Global Purchasing Managers Index (PMI) for monthly surveys that provide up-to-date, accurate, and unique indicators of economic trends.

The Compass Series of Indexes is comprised of three unique and complementary Indexes that gauge the extent of global political, macroeconomic, and geopolitical risk: A Military Conflict Risk Index in five key geopolitical conflict regions, a Cold War Two Index in Russia, the US, and China, and a Polarization Risk Index in the G7 economies. Collectively, they provide investors, policymakers, and other decision makers with otherwise unavailable and comprehensive datafeeds that allow them to confirm and refute hypotheses and confidently navigate these risks.

The Cold War Index The Cold War II Index tracks – in Russia, the US, and China – six public sentiment indicators related to the geopolitical conflict and five current and future economic conditions indicators. The Index runs 24/7 and, unlike typical polls in these countries, draws on broad-based, anonymous, non-incented opinion.

The Military Conflict Risk Index The Military Conflict Risk Index measures, on a continuous, real-time basis, the perceptions of military conflict intensification from citizens in five major geopolitical conflicts: Russia-Ukraine, China-Taiwan, India-Pakistan, Iran-Israel, and South Korea-North Korea.

The Polarization Risk Index The Polarization Risk Index measures, on a quarterly basis, polarization within each G7 country as a key indicator of political stability. The Index uniquely draws on broad-based, anonymous opinion, minimizing biases associated with conventional polling.

Iceland Consumer Price Index (CPI): Weights: Educational Services: ow Not Defined data was reported at 1.000 Per 10TH in 2014. This records a decrease from the previous number of 2.000 Per 10TH for 2013. Iceland Consumer Price Index (CPI): Weights: Educational Services: ow Not Defined data is updated yearly, averaging 4.000 Per 10TH from Feb 2002 (Median) to 2014, with 13 observations. The data reached an all-time high of 22.000 Per 10TH in 2004 and a record low of 1.000 Per 10TH in 2014. Iceland Consumer Price Index (CPI): Weights: Educational Services: ow Not Defined data remains active status in CEIC and is reported by Statistics Iceland . The data is categorized under Global Database’s Iceland – Table IS.I009: Consumer Price Index: Weights.

Oman OM: Depth of Credit Information Index: 0=Low To 8=High data was reported at 6.000 NA in 2017. This stayed constant from the previous number of 6.000 NA for 2016. Oman OM: Depth of Credit Information Index: 0=Low To 8=High data is updated yearly, averaging 6.000 NA from Dec 2013 (Median) to 2017, with 5 observations. The data reached an all-time high of 6.000 NA in 2017 and a record low of 6.000 NA in 2017. Oman OM: Depth of Credit Information Index: 0=Low To 8=High data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Oman – Table OM.World Bank.WDI: Business Environment. Depth of credit information index measures rules affecting the scope, accessibility, and quality of credit information available through public or private credit registries. The index ranges from 0 to 8, with higher values indicating the availability of more credit information, from either a public registry or a private bureau, to facilitate lending decisions.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year. Data before 2013 are not comparable with data from 2013 onward due to methodological changes.

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/about/competitive-programs/measures) Vegetation Index and Phenology (VIP) global datasets were created using Advanced Very High Resolution Radiometer (AVHRR) N07, N09, N11, and N14 datasets (1981 - 1999) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra MOD09 surface reflectance data (2000 - 2014). The VIP Vegetation Index (VI) product was developed to provide consistent measurements of the Normalized Difference Vegetation Index (NDVI) and modified Enhanced Vegetation Index (EVI2) spanning more than 30 years of data from multiple sensors. The EVI2 is a backward extension of AVHRR. Vegetation indices such as NDVI and EVI2 are useful for assessing the biophysical properties of the land surface, and are used to characterize vegetation phenology. Phenology tracks the seasonal life cycle of vegetation, and provides information on the biotic response to environmental changes. The VIP01 VI data product is a daily global file at 0.05 degree (5600 meter (m)) spatial resolution in geographic (Lat/Lon) grid format. The data are stored in Hierarchical Data Format-Earth Observing System (HDF-EOS) file format. The VIP01 VI product contains 11 Science Datasets (SDS), which includes the calculated VIs (NDVI and EVI2) as well as information on the quality assurance/pixel reliability, the input Visible/Near Infrared (VNIR) surface reflectance data, and viewing geometry. The Blue and Middle Infrared (MIR) surface reflectance data are only available for the MODIS era (2000 - 2014). Gaps in the daily product are filled using long term mean VI records derived from the more than 30 year time series of data, and are indicated as gap-filled in the Pixel Reliability SDS. A low resolution browse image showing NDVI as a color map is also available.Known Issues The Relative Azimuth Angle (RAA) for the input MODIS data is computed based on absolute values of the finer resolution pixels resulting in positive values and has minor usefulness. The RAA for the input AVHRR data contain values in the -360° to 360° range. The routine to restrict the values in the -180° to 180° range was accidentally missed and can be corrected using the following routine described in Section 4.2.1 of the User Guide and Algorithm Theoretical Basis Document: * SinRelativeAz=sin(RAA) CosRelativeAz=cos(RAA) Correct-RAA = atan2(SinRelativeAz,CosRelativeAz)