When inflation occurs in a country, the value of the currency decreases. That means that the purchasing power consumers have with a fixed amount of money decreases. Wages, especially lower and middle class wages, usually increase at a MUCH slower rate than prices of consumer goods; so consumers are likely to make the same wage, but are not able to buy the same amount of goods and services. Consumers in countries with hyperinflation suffer greatly because of this economic phenomenon.

Data was downloaded from: Link

For notes/metadata regarding the definition, measurement, or data collection for a certain country or group can be found by downloading the excel file from the linked webpage.

Original data provider: International Monetary Fund, World Development Indicators. License : CC BY-4.0.

INDICATOR_CODE: FP.CPI.TOTL.ZG

INDICATOR_NAME: Inflation, consumer prices (annual %)

SOURCE_NOTE: Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly.
The Laspeyres formula is generally used.

Years included: 1960-2016

The following countries have no values for any year:

• Somalia

• Puerto Rico

• Guam

• US Virgin Islands

The dataset also conains some records that refer to groups of countries, which may be useful for those with no recorded values. Some of those groups are:

• Fragile and conflict affected situations

• Heavily indebted poor countries (HIPC)

• Caribbean small states

• Latin America & Caribbean (excluding high income)

• Latin America & the Caribbean (IDA & IBRD countries)

• East Asia & Pacific (excluding high income)

• East Asia & Pacific (IDA & IBRD countries)

• Least developed countries: UN classification

• Middle East & North Africa (IDA & IBRD countries)

If this data is being used for the Kiva Crowdfunding Data Science for Good event; The following countries (as they are named in this dataset), are named slightly differently in the Kiva dataset (to the best of my knowledge). For example, West Bank in Gaza is referred to as Palestine in the Kiva Dataset.

• Congo, Dem. Rep.

• Congo, Rep.

• Kyrgyz Republic

• Lao PDR

• Myanmar

• West Bank and Gaza

• St. Vincent and the Grenadines

• Virgin Islands (U.S.)

• Yemen, Rep.

Here 3 DataSet for a complete overview of the economy of the country you are interested in.

Big Mac Index, Inflation forecast and Average Salary

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Big Mac Index

The Big Mac index was invented by The Economist in 1986 as a lighthearted guide to whether currencies are at their “correct” level. It is based on the theory of purchasing-power parity (PPP). By diverting the average national Big Mac prices to U.S. dollars, the same goods can be informally compared. So when the price of a burger is considered, the economic value of all these factors is accounted for. Thus, comparing the prices of similar burgers in two countries reflects a region’s cost of living and affordability. This is the theory behind Burgernomics.

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Inflation forecast

Inflation forecast is measured in terms of the consumer price index (CPI) or harmonised index of consumer prices (HICP) for euro area countries, the euro area aggregate and the United Kingdom. Inflation measures the general evolution of prices. It is defined as the change in the prices of a basket of goods and services that are typically purchased by households. Projections are based on an assessment of the economic climate in individual countries and the world economy, using a combination of model-based analyses and expert judgement. The indicator is expressed in annual growth rates.

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Average Salary (income)

The average salary is calculated based on reported salaries of respondents. The average salary definition is to add the salaries in the sample together, then divide by the number of respondents. The result is the average salary for everyone surveyed.

This dataset provides statistics on real gross domestic product (GDP) and real GDP per capita for subnational regions. Real values are deflation-adjusted using the Regional Producer Price Index (ROPI), where available.

Data source and definition

Regional gross domestic product data is collected at current prices, in millions of national currency from Eurostat (reg_eco10) for EU countries and via delegates of the OECD Working Party on Territorial Indicators (WPTI), as well as from national statistical offices' websites.

To allow comparability over time and between countries, data at current prices are transformed into constant prices and purchasing power parity measures. Regional GDP per capita is calculated by dividing regional GDP by the average annual population of the region.

See method and detailed data sources in Regions and Cities at a Glance 2024, Annex.

Definition of regions

Regions are subnational units below national boundaries. OECD countries have two regional levels: large regions (territorial level 2 or TL2) and small regions (territorial level 3 or TL3). The OECD regions are presented in the OECD Territorial grid (pdf) and in the OECD Territorial correspondence table (xlsx).

Use of economic data on small regions

When economic analyses are carried out at the TL3 level, it is advisable to aggregate data at the metropolitan region level when several TL3 regions are associated to the same metropolitan region. Metropolitan regions combine TL3 regions when 50% or more of the regional population live in a functionnal urban areas above 250 000 inhabitants. This approach corrects the distortions created by commuting. Correspondence between TL3 and metropolitan regions:(xlsx).

Small regions (TL3) are categorized based on shared characteristics into regional typologies. See the economic indicators aggregated by territorial typology at country level on the access to City typology (link) and by urban-rural typology (link).

Cite this dataset

OECD Regions and Cities databases http://oe.cd/geostats

Further information

• The interactive web-tool OECD Regions and Cities Statistical Atlas
• The report OECD Regions and Cities at a Glance

Contact: RegionStat@oecd.org

Economic growth is easy to understand: it means that people have access to goods and services of increasing quantity and quality. What is hard, however, is to measure economic growth. This chart shows two ways of doing this for US growth over the past 160 years. The purple lines represent a straightforward approach: each line tracks the share of households with access to one specific good or service. Starting from the top, you see the rising provision of basic infrastructure like running water, flush toilets, and electric power. You can also see the increasing availability of communication technology: radios, TVs, the Internet, and mobile phones. And further down, you see the rise of technologies that reduced work at home: vacuum cleaners, washing machines, dryers, and dishwashers. This approach is very concrete; it shows practical ways in which the production and consumption of specific goods increased over time. The downside is that it only captures a limited number of particular goods. Millions of goods and services are produced and consumed, and most are not recorded with such precision. A way to measure how people’s access to the full range of goods and services changes is to measure people’s incomes. This way of measuring growth is shown in the top left panel. The data on average income, here measured by GDP per capita, tells us that the average American was 13 times poorer in 1860 than in 2022 (adjusted for inflation). These two ways of measuring economic growth have pros and cons: one is concrete but not comprehensive, the other is comprehensive but quite abstract. If we want to understand what growth means for our societies, I find it helpful to combine them both.

View data of PCE, an index that measures monthly changes in the price of consumer goods and services as a means of analyzing inflation.

This dataset provides statistics on real gross value added by broad 10 activities for regions. Real values are deflation-adjusted using the Regional Producer Price Index (ROPI), where available.

Data source and definition

Regional gross value added data is collected at current prices, in millions of national currency from Eurostat (reg_eco10) for EU countries and via delegates of the OECD Working Party on Territorial Indicators (WPTI), as well as from national statistical offices' websites. In order to allow comparability over time and across countries, data in current prices are transformed into constant prices and PPP measures.

See method and detailed data sources in Regions and Cities at a Glance 2024, Annex.

Definition of regions

Regions are subnational units below national boundaries. OECD countries have two regional levels: large regions (territorial level 2 or TL2) and small regions (territorial level 3 or TL3). The OECD regions are presented in the OECD Territorial grid (pdf) and in the OECD Territorial correspondence table (xlsx).

Use of economic data on small regions

When economic analyses are carried out at the TL3 level, it is advisable to aggregate data at the metropolitan region level when several TL3 regions are associated to the same metropolitan region. Metropolitan regions combine TL3 regions when 50% or more of the regional population live in a functionnal urban areas above 250 000 inhabitants. This approach corrects the distortions created by commuting. Correspondence between TL3 and metropolitan regions:(xlsx).

Small regions (TL3) are categorized based on shared characteristics into regional typologies. See the economic indicators aggregated by territorial typology at country level on the access to City typology (link) and by urban-rural typology (link).

Cite this dataset

OECD Regions and Cities databases http://oe.cd/geostats

Further information

• The interactive web-tool OECD Regions and Cities Statistical Atlas
• The report OECD Regions and Cities at a Glance

Contact: RegionStat@oecd.org

Japan JP: Core Inflation Index: YoY data was reported at 2.001 % in 2026. This records an increase from the previous number of 1.835 % for 2025. Japan JP: Core Inflation Index: YoY data is updated yearly, averaging 1.608 % from Dec 1966 (Median) to 2026, with 61 observations. The data reached an all-time high of 20.576 % in 1974 and a record low of -1.182 % in 2010. Japan JP: Core Inflation Index: YoY data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Japan – Table JP.OECD.EO: Consumer and Wholesale Price Index: Forecast: OECD Member: Annual. PCORE_YTYPCT - Core inflationOECD group, all items non-food non-energy. See exceptions at the country's serie metadata; OECD definition differs from the official Japanese core inflation.

This dataset provides statistics on labour productivity for large and small regions. Real values are deflation-adjusted using the Regional Producer Price Index (ROPI), where available.

Data source and definition

Labour productivity is measured as gross value added per employment at place of work by main economic activity. Regional gross value added and employment data are collected from Eurostat (reg_eco10) for EU countries and via delegates of the OECD Working Party on Territorial Indicators (WPTI), as well as from national statistical offices' websites. In order to allow comparability over time and across countries, data in current prices are transformed into constant prices and PPP measures.

See method and detailed data sources in Regions and Cities at a Glance 2024, Annex.

Definition of regions

Regions are subnational units below national boundaries. OECD countries have two regional levels: large regions (territorial level 2 or TL2) and small regions (territorial level 3 or TL3). The OECD regions are presented in the OECD Territorial grid (pdf) and in the OECD Territorial correspondence table (xlsx).

Use of economic data on small regions

When economic analyses are carried out at the TL3 level, it is advisable to aggregate data at the metropolitan region level when several TL3 regions are associated to the same metropolitan region. Metropolitan regions combine TL3 regions when 50% or more of the regional population live in a functionnal urban areas above 250 000 inhabitants. This approach corrects the distortions created by commuting. Correspondence between TL3 and metropolitan regions:(xlsx).

Small regions (TL3) are categorized based on shared characteristics into regional typologies. See the economic indicators aggregated by territorial typology at country level on the access to City typology (link) and by urban-rural typology (link).

Cite this dataset

OECD Regions and Cities databases http://oe.cd/geostats

Further information

• The interactive web-tool OECD Regions and Cities Statistical Atlas
• The report OECD Regions and Cities at a Glance

Contact: RegionStat@oecd.org

The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families' balance sheets, pensions, income, and demographic characteristics.

Unemployment Rate in South Africa decreased to 31.90 percent in the third quarter of 2025 from 33.20 percent in the second quarter of 2025. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.