United States US: Broad Money: Average Annual Growth Rate data was reported at 3.760 % in 2016. This records an increase from the previous number of 3.408 % for 2015. United States US: Broad Money: Average Annual Growth Rate data is updated yearly, averaging 8.143 % from Dec 1961 (Median) to 2016, with 56 observations. The data reached an all-time high of 13.955 % in 1971 and a record low of -2.741 % in 2010. United States US: Broad Money: Average Annual Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Money Supply. Broad money (IFS line 35L..ZK) is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler’s checks; and other securities such as certificates of deposit and commercial paper.; ; International Monetary Fund, International Financial Statistics and data files.; ;

Number of persons in low income, low income rate and average gap ratio by economic family type, annual.

Money Supply M1 in Finland decreased to 141367 EUR Million in October from 141479 EUR Million in September of 2025. This dataset provides - Finland Money Supply M1 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Household Current Income: % Share: CR: Quintile 4 data was reported at 21.100 % in 2015. This records a decrease from the previous number of 21.868 % for 2013. Household Current Income: % Share: CR: Quintile 4 data is updated yearly, averaging 21.400 % from Dec 2011 (Median) to 2015, with 3 observations. The data reached an all-time high of 21.868 % in 2013 and a record low of 21.100 % in 2015. Household Current Income: % Share: CR: Quintile 4 data remains active status in CEIC and is reported by National Statistical Office. The data is categorized under Global Database’s Thailand – Table TH.G042: Household Income & Assets Statistics.

Money Supply M1 in Latvia decreased to 17556.40 EUR Million in October from 17577.60 EUR Million in September of 2025. This dataset provides - Latvia Money Supply M1 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Financial overview and grant giving statistics of Money Management Education Associates Inc.

Financial overview and grant giving statistics of Money Management International Financial Education Foundation

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

Information on the industry distribution of PAYE (Pay As You Earn) tax deducted from pay by tax year. Previously listed under 'Revenue-based Taxes and Benefits: Income tax statistics and distributions'. Source agency: HM Revenue and Customs Designation: National Statistics Language: English Alternative title: Income Tax Deducted from Pay Statistics

Money Supply M0 in Belarus increased to 13864.70 BYN Million in October from 13810.80 BYN Million in September of 2025. This dataset provides - Belarus Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset contains data from California resident tax returns filed with California adjusted gross income and self-assessed tax listed by zip code. This dataset contains data for taxable years 1992 to the most recent tax year available.

Singapore SG: Broad Money: Average Annual Growth Rate data was reported at 3.199 % in 2017. This records a decrease from the previous number of 8.044 % for 2016. Singapore SG: Broad Money: Average Annual Growth Rate data is updated yearly, averaging 10.518 % from Dec 1964 (Median) to 2017, with 54 observations. The data reached an all-time high of 30.249 % in 1998 and a record low of -2.050 % in 2000. Singapore SG: Broad Money: Average Annual Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank.WDI: Money Supply. Broad money (IFS line 35L..ZK) is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler’s checks; and other securities such as certificates of deposit and commercial paper.; ; International Monetary Fund, International Financial Statistics and data files.; ;

Money Supply M1 in Norway increased to 2950588 NOK Million in October from 2938644 NOK Million in September of 2025. This dataset provides - Norway Money Supply M1 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The United States M1 money supply reached approximately **** trillion dollars by September 2025, showing a slight uptick from the previous year. This modest increase follows a period of contraction in late 2022 and early 2023, which stood in stark contrast to the dramatic expansion seen from May 2020 onward. The earlier surge was largely attributed to the Federal Reserve's aggressive quantitative easing measures implemented in response to the economic fallout from the COVID-19 pandemic.

Money Supply M3 in Czech Republic increased to 7233930.80 CZK Million in October from 7202556.37 CZK Million in September of 2025. This dataset provides - Czech Republic Money Supply M3- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Comprehensive YouTube channel statistics for Smart Money Bro, featuring 674,000 subscribers and 45,442,935 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Education category and is based in US. Track 971 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Income, consumption and wealth (ICW) statistics are experimental statistics computed by Eurostat through the statistical matching of three data sources: the EU Statistics on Income and Living Conditions (EU-SILC), the Household Budget Survey (HBS) and the Household Finance and Consumption Survey (HFCS). These statistics enable us to observe at the same time the income that households receive, their expenditures and their accumulated wealth.

The annual collection of EU-SILC was launched in 2003 and is governed by Regulation 1700/2019 (previously: Regulation 1177/2003) of the European Parliament and of the Council. The EU-SILC collects cross-sectional and longitudinal information on income. HBS is a survey conducted every 5 years on the basis of an agreement between Eurostat, the Member States and EFTA countries. Data are collected using national questionnaires and, in most cases, expenditure diaries that respondents are asked to keep over a certain period of time. HFCS collects information on assets, liabilities, and to a limited extent income and consumption, of households. The survey is run by National Central Banks and coordinated by the European Central Bank.

This page focuses on the main issues of importance for the use and interpretation of ICW statistics. Information on the primary data sources can be found on the respective EU-SILC and HBS metadata pages and following the links provided in the sections 'related metadata' and 'annexes' below.

Experimental ICW statistics cover six topics: household economic resources, affordability of essential services, saving rates, poverty, household characteristics and taxation. Each topic contains several indicators with a number of different breakdowns, mainly by income quantile, by the age group of the household reference person, by household type, by the educational attainment level of the reference person, by the activity status of the reference person and by the degree of urbanization of the household. The indicators provide information on the joint distribution of income, consumption and wealth and the links between these three economic dimensions. They help to describe households' economic vulnerability and material well-being. They also help to explain the dynamics of wealth inequalities.

All indicators are to be understood to describe households, not persons. Breakdowns by age group, educational attainment level and activity status refer to the household reference person, which is the person with the highest income. The only exception are the tables icw_pov_01, icw_pov_10, icw_pov_11 and icw_pov_12 for which the income, consumption and wealth of households have been equivalised such that equal shares were attributed to each household member. Values in tables icw_aff are calculated for households reporting non-zero values only.

Note on table icw _res_01 and icw_res_02: The indicator “Households” [HH] in icw_res_01 shows the share of households in the selection, which hold the corresponding shares of total disposable income [INC_DISP], consumption expenditure [EXPN_CONS] and net wealth [WLTH_NET] of the entire population. In theory, turning two of the three dimensions [quant_inc, quant_expn, quant_wlth] to TOTAL and the third one to any quintile, should result into a share of 20% of households. Nevertheless, this share is often below or above 20% of the total population of households in the country. The reason for this is that our figures are based on sample surveys. This means that the share of households corresponds indeed to 20% of households in the sample, however when we multiply each household of the sample with its sampling weight, the resulting shares of households in the total population differ from the 20%. If, for example, we disregard the income and wealth of households in our sample, the first consumption quintile contains the 20% of households with lowest consumption in the sample. However, multiplying this selection of households with their corresponding sampling weights may result into a different share of the total population. The “Households” [HH] indicator indicates the real share of households in the population that make up the theoretical quintile.

Income, consumption and wealth (ICW) statistics are experimental statistics computed by Eurostat through the statistical matching of three data sources: the EU Statistics on Income and Living Conditions (EU-SILC), the Household Budget Survey (HBS) and the Household Finance and Consumption Survey (HFCS). These statistics enable us to observe at the same time the income that households receive, their expenditures and their accumulated wealth.

The annual collection of EU-SILC was launched in 2003 and is governed by Regulation 1700/2019 (previously: Regulation 1177/2003) of the European Parliament and of the Council. The EU-SILC collects cross-sectional and longitudinal information on income. HBS is a survey conducted every 5 years on the basis of an agreement between Eurostat, the Member States and EFTA countries. Data are collected using national questionnaires and, in most cases, expenditure diaries that respondents are asked to keep over a certain period of time. HFCS collects information on assets, liabilities, and to a limited extent income and consumption, of households. The survey is run by National Central Banks and coordinated by the European Central Bank.

This page focuses on the main issues of importance for the use and interpretation of ICW statistics. Information on the primary data sources can be found on the respective EU-SILC and HBS metadata pages and following the links provided in the sections 'related metadata' and 'annexes' below.

Experimental ICW statistics cover six topics: household economic resources, affordability of essential services, saving rates, poverty, household characteristics and taxation. Each topic contains several indicators with a number of different breakdowns, mainly by income quantile, by the age group of the household reference person, by household type, by the educational attainment level of the reference person, by the activity status of the reference person and by the degree of urbanization of the household. The indicators provide information on the joint distribution of income, consumption and wealth and the links between these three economic dimensions. They help to describe households' economic vulnerability and material well-being. They also help to explain the dynamics of wealth inequalities.

All indicators are to be understood to describe households, not persons. Breakdowns by age group, educational attainment level and activity status refer to the household reference person, which is the person with the highest income. The only exception are the tables icw_pov_01, icw_pov_10, icw_pov_11 and icw_pov_12 for which the income, consumption and wealth of households have been equivalised such that equal shares were attributed to each household member. Values in tables icw_aff are calculated for households reporting non-zero values only.

Note on table icw _res_01 and icw_res_02: The indicator “Households” [HH] in icw_res_01 shows the share of households in the selection, which hold the corresponding shares of total disposable income [INC_DISP], consumption expenditure [EXPN_CONS] and net wealth [WLTH_NET] of the entire population. In theory, turning two of the three dimensions [quant_inc, quant_expn, quant_wlth] to TOTAL and the third one to any quintile, should result into a share of 20% of households. Nevertheless, this share is often below or above 20% of the total population of households in the country. The reason for this is that our figures are based on sample surveys. This means that the share of households corresponds indeed to 20% of households in the sample, however when we multiply each household of the sample with its sampling weight, the resulting shares of households in the total population differ from the 20%. If, for example, we disregard the income and wealth of households in our sample, the first consumption quintile contains the 20% of households with lowest consumption in the sample. However, multiplying this selection of households with their corresponding sampling weights may result into a different share of the total population. The “Households” [HH] indicator indicates the real share of households in the population that make up the theoretical quintile.

Key information about Norway Money Supply M1

• Norway Money Supply M1 was reported at 291.632 USD bn in Oct 2025
• This records a decrease from the previous number of 294.332 USD bn for Sep 2025
• Norway Money Supply M1 data is updated monthly, averaging 115.167 USD bn from Dec 1992 to Oct 2025, with 395 observations
• The data reached an all-time high of 321.114 USD bn in Mar 2022 and a record low of 24.117 USD bn in Jul 1993. Norway Money Supply M1 data remains active status in CEIC and is reported by CEIC Data
• The data is categorized under World Trend Plus’s Global Economic Monitor – Table: Money Supply M1: USD: Monthly