Cost of food in Nigeria increased 21.87 percent in August of 2025 over the same month in the previous year. This dataset provides - Nigeria Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in Poland decreased to 2.90 percent in August from 3.10 percent in July of 2025. This dataset provides the latest reported value for - Poland Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following areas: Afghanistan, Armenia, Bangladesh, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Congo, Dem. Rep., Congo, Rep., Gambia, The, Guinea, Guinea-Bissau, Haiti, Indonesia, Iraq, Kenya, Lao PDR, Lebanon, Liberia, Libya, Malawi, Mali, Mauritania, Mozambique, Myanmar, Niger, Nigeria, Philippines, Senegal, Somalia, South Sudan, Sri Lanka, Sudan, Syrian Arab Republic, Yemen, Rep.

We report average expected inflation rates over the next one through 30 years. Our estimates of expected inflation rates are calculated using a Federal Reserve Bank of Cleveland model that combines financial data and survey-based measures. Released monthly.

In 2021, the inflation rate in Ghana amounted to about 9.98 percent compared to the previous year. Ghana’s inflation peaked at almost 17.5 percent in 2016 and is predicted to decrease to 8 percent by 2030. Steady is best for inflationAccording to economists, a steady inflation rate between two and three percent is desirable to achieve a stable economy in a country. Inflation is the increase in the price level of consumer goods and services over a certain time period. A high inflation rate is often caused by excessive money supply and can turn into hyperinflation, i.e. if inflation occurs too quickly and rapidly, it can devalue currency and cause a recession and even economic collapse. This scenario is currently taking place in Venezuela , for example. The opposite of inflation, the decrease in the price level of goods and services below zero percent, is called deflation. While hyperinflation devalues money, deflation usually increases its value. Both events can damage an economy severely. Is Ghana’s economy at risk?Ghana’s economy is considered quite stable and fast-growing, and is rich in oil, diamonds, and gold. After struggling in the years around 2015 due to increased government spending and plummeting oil prices, it is now on an upswing again. This is also reflected in the decreasing inflation rate, and other key indicators like unemployment and rapid GDP growth support this theory. However, Ghana’s government debt is still struggling with the consequences of the 2015 crisis and forecast to keep skyrocketing during the next few years.

This dataset is about countries per year in Cyprus. It has 64 rows. It features 4 columns: country, inflation, and electricity production from oil sources.

Inflation Rate in Norway increased to 3.50 percent in August from 3.30 percent in July of 2025. This dataset provides - Norway Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset is about countries per year in Ghana. It has 64 rows. It features 4 columns: country, inflation, and electricity production from oil sources.

Inflation Rate in Thailand decreased to -0.79 percent in August from -0.70 percent in July of 2025. This dataset provides the latest reported value for - Thailand Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset is about countries per year in Korea. It has 64 rows. It features 4 columns: country, inflation, and electricity production from nuclear sources.

Inflation Rate in Indonesia decreased to 2.31 percent in August from 2.37 percent in July of 2025. This dataset provides - Indonesia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset is about countries per year in Tuvalu. It has 64 rows. It features 4 columns: country, inflation, and electricity production from oil sources.

Inflation Rate in South Korea decreased to 1.70 percent in August from 2.10 percent in July of 2025. This dataset provides the latest reported value for - South Korea Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset is about countries per year in Spain. It has 64 rows. It features 4 columns: country, inflation, and electricity production from nuclear sources.

SELECTED ECONOMIC CHARACTERISTICS INCOME AND BENEFITS (IN 2021 2022 INFLATION-ADJUSTED DOLLARS) - DP03 Universe - Total households Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Total income is the sum of the amounts reported separately for wage or salary income; net self-employment income; interest, dividends, or net rental or royalty income or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); public assistance or welfare payments; retirement, survivor, or disability pensions; and all other income. Receipts from the following sources are not included as income: capital gains, money received from the sale of property (unless the recipient was engaged in the business of selling such property); the value of income “in kind” from food stamps, public housing subsidies, medical care, employer contributions for individuals, etc.; withdrawal of bank deposits; money borrowed; tax refunds; exchange of money between relatives living in the same household; gifts and lump-sum inheritances, insurance payments, and other types of lump sum receipts.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: Abia, Borno, Yobe, Katsina, Kano, Kaduna, Gombe, Jigawa, Kebbi, Oyo, Sokoto, Zamfara, Lagos, Adamawa, Market Average

Inflation Rate in Egypt decreased to 12 percent in August from 13.90 percent in July of 2025. This dataset provides - Egypt Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Spring township. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Spring township, the median income for all workers aged 15 years and older, regardless of work hours, was $55,879 for males and $41,837 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 25% between the median incomes of males and females in Spring township. With women, regardless of work hours, earning 75 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetownship of Spring township.

- Full-time workers, aged 15 years and older: In Spring township, among full-time, year-round workers aged 15 years and older, males earned a median income of $70,886, while females earned $61,702, resulting in a 13% gender pay gap among full-time workers. This illustrates that women earn 87 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the township of Spring township.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Spring township.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Spring township median household income by race. You can refer the same here

This dataset is about countries per year in Bhutan. It has 64 rows. It features 4 columns: country, inflation, and electricity production from hydroelectric sources.

DataThis file contains a folder with all raw data for the simulations. More instructions can be found in file "Simulated_data.R" available from the data file "Rproject".RProjectThis file contains folder with the complete RProject for this manuscript, minus the original data files for the simulation project (available as file "Data.tar.gz"). All other temporary (.rda) data files are in in this folder as well.Rproject.tar.gz