The OECD Income Distribution database (IDD) has been developed to benchmark and monitor countries' performance in the field of income inequality and poverty. It contains a number of standardised indicators based on the central concept of "equivalised household disposable income", i.e. the total income received by the households less the current taxes and transfers they pay, adjusted for household size with an equivalence scale. While household income is only one of the factors shaping people's economic well-being, it is also the one for which comparable data for all OECD countries are most common. Income distribution has a long-standing tradition among household-level statistics, with regular data collections going back to the 1980s (and sometimes earlier) in many OECD countries.

Achieving comparability in this field is a challenge, as national practices differ widely in terms of concepts, measures, and statistical sources. In order to maximise international comparability as well as inter-temporal consistency of data, the IDD data collection and compilation process is based on a common set of statistical conventions (e.g. on income concepts and components). The information obtained by the OECD through a network of national data providers, via a standardized questionnaire, is based on national sources that are deemed to be most representative for each country.

Small changes in estimates between years should be treated with caution as they may not be statistically significant.

Fore more details, please refer to: https://www.oecd.org/els/soc/IDD-Metadata.pdf and https://www.oecd.org/social/income-distribution-database.htm

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The World Bank, the World Inequality Database (WID), and the Luxembourg Income Study (LIS) are all sources of data on poverty and inequality. They differ in terms of the income measure they use, the countries they cover, and the frequency of their data updates.

The World Bank uses a measure of income after taxes and transfers, which is called disposable income. It covers a wide range of countries, but the data is not updated as frequently as the data from the other two sources. The WID uses a measure of net national income after taxes, which is called net national income per adult. It covers a smaller range of countries than the World Bank, but the data is updated more frequently. The LIS uses a measure of disposable household income per capita. It covers a smaller range of countries than the World Bank or the WID, but the data is very detailed and goes back further in time. In general, the LIS data is considered to be the most reliable source of data on poverty and inequality. However, the World Bank and WID data are also useful, especially for countries that are not covered by the LIS.

Graph and download economic data for Real Disposable Personal Income (DSPIC96) from Jan 1959 to Aug 2025 about disposable, personal income, personal, income, real, and USA.

Cross-national research on the causes and consequences of income inequality has been hindered by the limitations of the existing inequality datasets: greater coverage across countries and over time has been available from these sources only at the cost of significantly reduced comparability across observations. The goal of the Standardized World Income Inequality Database (SWIID) is to meet the needs of those engaged in broadly cross-national research by maximizing the comparability of income inequality data while maintaining the widest possible coverage across countries and over time. The SWIID’s income inequality estimates are based on thousands of reported Gini indices from hundreds of published sources, including the OECD Income Distribution Database, the Socio-Economic Database for Latin America and the Caribbean generated by CEDLAS and the World Bank, Eurostat, the World Bank’s PovcalNet, the UN Economic Commission for Latin America and the Caribbean, national statistical offices around the world, and academic studies while minimizing reliance on problematic assumptions by using as much information as possible from proximate years within the same country. The data collected and harmonized by the Luxembourg Income Study is employed as the standard. The SWIID currently incorporates comparable Gini indices of disposable and market income inequality for 199 countries for as many years as possible from 1960 to the present; it also includes information on absolute and relative redistribution.

Middle East Poultry Meat Market size was valued at USD 15 Billion in 2024 and is expected to reach USD 22 Billion by 2032, growing at a CAGR of 5% from 2026 to 2032.Key Market Drivers:Growing Population and Increasing Disposable Income: The Middle East is seeing tremendous population expansion and increasing disposable incomes, which are directly driving poultry meat consumption. According to the World Bank, the combined population of Middle Eastern countries is expected to expand by 20% by 2030, with Saudi Arabia's population growing at 1.6% every year. Furthermore, the International Monetary Fund (IMF) forecasts that the UAE's GDP per capita expanded by 17.1% between 2020 and 2023, reaching around USD 47,900, allowing consumers to buy more protein-rich diets, including poultry products.Increasing Health Awareness and Protein Demand: Due to health concerns, Middle Eastern consumers increasingly prefer poultry meat to red meat. The World Health Organization (WHO) Middle East report indicates that 65% of consumers in the region are actively seeking healthier protein alternatives, with poultry consumption rising at an annual rate of 4.2%.

The “financial development index” symbolizes the degree of financial development of a country in 2010. Well-developed financial systems may reduce climate change impact because it underlying the diffusion of services and tertiary economic activity that reduce the dependence to agriculture income of a certain population. The index results from the first cluster of the Principal Component Analysis preformed among 9 potential variables. The analysis identifies three dominant variables, namely “investment per capita”, “global commerce volume per capita” and “gross national saving per capita”, assigning weights of 0.35, 0.35 and 0.3, respectively. Before to perform the analysis all variables were log transformed to shorten the extreme variation and then were score-standardized (converted to distribution with average of 0 and standard deviation of 1) in order to be comparable. Country based data for “investment per capita” (expressed as a ratio of total investment in current local currency and GDP in current local currency. Investment or gross capital formation is measured by the total value of the gross fixed capital formation and changes in inventories and acquisitions less disposals of valuables for a unit or sector), “global commerce volume per capita” (expressed as a ratio of commerce volume in current local currency and GDP in current local currency. Commerce volume is the sum of exports and imports of goods and services) and “gross national saving per capita” (expressed as a ratio of gross national savings in current local currency and GDP in current local currency. Gross national saving is gross disposable income less final consumption expenditure after taking account of an adjustment for pension funds) were collected jointly from International Monetary Fund and World Bank (for global commerce volumes) and records the average of the period 2008-2012. The variables represent the share of GDP, thus they were multiplied by total GDPppp in order to have absolute value in international dollars and then divided by population to calculate the per capita values of each variable. The tabular data were linked by country unit to the national boundaries shapefile (FAO/GAUL) and then converted into raster format (resolution 0.5 arc-minute). Investment and global commerce per capita are proxy of economic transition out of agriculture, while national gross saving represents the financial resources buffer that can facilitate the implementation of climate change adaptation strategies. This dataset has been produced in the framework of the “Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)” project, Work Package 4 (WP4). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

In 2024, about 943.5 million people lived in urban regions in China and 464.8 million in rural. That year, the country had a total population of approximately 1.41 billion people. As of 2024, China was the second most populous country in the world. Urbanization in China Urbanization refers to the process by which people move from rural to urban areas and how a society adapts to the population shift. It is usually seen as a driving force in economic growth, accompanied by industrialization, modernization and the spread of education. Urbanization levels tend to be higher in industrial countries, whereas the degree of urbanization in developing countries remains relatively low. According to World Bank, a mere 19.4 percent of the Chinese population had been living in urban areas in 1980. Since then, China’s urban population has skyrocketed. By 2024, about 67 percent of the Chinese population lived in urban areas. Regional urbanization rates In the last decades, urbanization has progressed greatly in every region of China. Even in most of the more remote Chinese provinces, the urbanization rate surpassed 50 percent in recent years. However, the most urbanized areas are still to be found in the coastal eastern and southern regions of China. The population of Shanghai, the largest city in China and the world’s seventh largest city ranged at around 24 million people in 2023. China’s urban areas are characterized by a developing middle class. Per capita disposable income of Chinese urban households has more than doubled between 2010 and 2020. The emerging middle class is expected to become a significant driver for the continuing growth of the Chinese economy.

MEA Handbags Market size was valued at USD 3.20 Billion in 2024 and is projected to reach USD 5.50 Billion by 2032, growing at a CAGR of 7% from 2026 to 2032.

MEA Handbags Market Dynamics

The key market dynamics that are shaping the MEA Handbags Market include:

Key Market Drivers:

Growing Urbanization and Changing Lifestyles: The rapid urbanization in the Middle East and Africa (MEA) region, particularly in countries like UAE, Saudi Arabia, and South Africa, is driving demand for handbags. The World Bank predicts a 64% urban population growth by 2030, leading to increased disposable incomes and a preference for fashion-conscious, convenience-oriented products like handbags. As city life becomes more fast-paced, handbags become a practical and stylish necessity.

Rising Disposable Income and Luxury Spending: The MEA Handbags Market is driven by the increasing disposable income in GCC countries, particularly Qatar, UAE, and Saudi Arabia.