Inflation Rate in the United States remained unchanged at 2.70 percent in July. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Core consumer prices in the United States increased 3.10 percent in July of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Inflation, consumer prices for the United States (FPCPITOTLZGUSA) from 1960 to 2024 about consumer, CPI, inflation, price index, indexes, price, and USA.

Cost of food in the United States increased 2.90 percent in July of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In economics, the inflation rate is a measure of the change in price of a basket of goods. The most common measure being the consumer price index. It is the percentage rate of change in price level over time, and also indicates the rate of decrease in the purchasing power of money. The annual rate of inflation for 2023, was 4.1 percent higher in the United States when compared to the previous year. More information on inflation and the consumer price index can be found on our dedicated topic page. Additionally, the monthly rate of inflation in the United States can be accessed here. Inflation and purchasing power Inflation is a key economic indicator, and gives economists and consumers alike a look at changes in prices in the wider economy. For example, if an average pair of socks costs 100 dollars one year and 105 dollars the following year, the inflation rate is five percent. This means the amount of goods an individual can purchase with a unit of currency has decreased. This concept is often referred to as purchasing power. The data presents the average rate of inflation in a year, whereas the monthly measure of inflation measures the change in prices compared with prices one year ago. For example, monthly inflation in the U.S. reached a peak in June 2022 at 9.1 percent. This means that prices were 9.1 percent higher than they were in June of 2021. The purchasing power is the extent to which a person has available funds to make purchases. The Big Mac Index has been published by The Economist since 1986 and exemplifies purchasing power on a global scale, allowing us to see note the differences between different countries currencies. Switzerland for example, has the most expensive Big Mac in the world, costing consumers 6.71 U.S. dollars as of July 2022, whereas a Big Mac cost 5.15 dollars in the United States, and 4.77 dollars in the Euro area. One of the most important tools in influencing the rate of inflation is interest rates. The Federal Reserve of the United States has the capacity to make changes to the federal interest rate . Changes to the rate of inflation are thought to be an imbalance between supply and demand. After COVID-19 related lockdowns came to an end there was a sudden increase in demand for goods and services with consumers having more funds than usual thanks to reduced spending during lockdown and government funded economic support. Additionally, supply-chain related bottlenecks also due to lockdowns around the world and the Russian invasion of Ukraine meant that there was a decrease in the supply of goods and services. By increasing the interest rate, the Federal Reserve aims to reduce spending, and thus bring demand back into balance with supply.

At the end of 2024, Zimbabwe had the highest inflation rate in the world, at 736.11 percent change compared to the previous year. Inflation in industrialized and in emerging countries Higher inflation rates are more present in less developed economies, as they often lack a sufficient central banking system, which in turn results in the manipulation of currency to achieve short term economic goals. Thus, interest rates increase while the general economic situation remains constant. In more developed economies and in the prime emerging markets, the inflation rate does not fluctuate as sporadically. Additionally, the majority of countries that maintained the lowest inflation rate compared to previous years are primarily oil producers or small island independent states. These countries experienced deflation, which occurs when the inflation rate falls below zero; this may happen for a variety of factors, such as a shift in supply or demand of goods and services, or an outflow of capital.

The Consumer Price Index in the United States increased 0.20 percent in July of 2025 over the previous month. This dataset provides - United States Inflation Rate MoM - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

This dataset includes economic statistics on inflation, prices, unemployment, and pay & benefits provided by the Bureau of Labor Statistics (BLS)

Documentation

Update frequency: Monthly Dataset source: U.S. Bureau of Labor Statistics Terms of use: This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset. See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/bls-public-data/bureau-of-labor-statistics

This dataset provides values for INFLATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

Dataset Overview

This dataset provides historical housing price indices for the United States, covering a span of 20 years from January 2000 onwards. The data includes housing price trends at the national level, as well as for major metropolitan areas such as San Francisco, Los Angeles, New York, and more. It is ideal for understanding how housing prices have evolved over time and exploring regional differences in the housing market.

Why This Dataset?

The U.S. housing market has experienced significant shifts over the last two decades, influenced by economic booms, recessions, and post-pandemic recovery. This dataset allows data enthusiasts, economists, and real estate professionals to analyze long-term trends, make forecasts, and derive insights into regional housing markets.

What’s Included?

Time Period: January 2000 to the latest available data (specific end date depends on the dataset). Frequency: Monthly data. Regions Covered: 20+ U.S. cities, states, and aggregates.

Columns Description

Each column represents the housing price index for a specific region or aggregate, starting with a date column:

Date: Represents the date of the housing price index measurement, recorded with a monthly frequency. U.S. National: The national-level housing price index for the United States. 20-City Composite: The aggregate housing price index for the top 20 metropolitan areas in the U.S. CA-San Francisco: The housing price index for San Francisco, California. CA-Los Angeles: The housing price index for Los Angeles, California. WA-Seattle: The housing price index for Seattle, Washington. NY-New York: The housing price index for New York City, New York. Additional Columns: The dataset includes more columns with housing price indices for various U.S. cities, which can be viewed in the full dataset preview.

Potential Use Cases

Time-Series Analysis: Investigate long-term trends and patterns in housing prices. Forecasting: Build predictive models to forecast future housing prices using historical data. Regional Comparisons: Analyze how housing prices have grown in different cities over time. Economic Insights: Correlate housing prices with economic factors like interest rates, GDP, and inflation.

Who Can Use This Dataset?

This dataset is perfect for:

Data scientists and machine learning practitioners looking to build forecasting models. Economists and policymakers analyzing housing market dynamics. Real estate investors and analysts studying regional trends in housing prices.

Example Questions to Explore

Which cities have experienced the highest housing price growth over the last 20 years? How do housing price trends in coastal cities (e.g., Los Angeles, Miami) compare to midwestern cities (e.g., Chicago, Detroit)? Can we predict future housing prices using time-series models like ARIMA or Prophet?

Inflation Expectations in the United States increased to 3.10 percent in July from 3 percent in June of 2025. This dataset provides - United States Consumer Inflation Expectations- actual values, historical data, forecast, chart, statistics, economic calendar and news.

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

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in United States. Based on the latest 2022 1-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in United States. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2022

In terms of income distribution across age cohorts, in United States, householders within the 45 to 64 years age group have the highest median household income at $90,748, followed by those in the 25 to 44 years age group with an income of $83,783. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $53,963. Notably, householders within the under 25 years age group, had the lowest median household income at $42,079.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

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 United States median household income by age. You can refer the same here

The International Macroeconomic Data Set provides data from 1969 through 2030 for real (adjusted for inflation) gross domestic product (GDP), population, real exchange rates, and other variables for the 190 countries and 34 regions that are most important for U.S. agricultural trade. The data presented here are a key component of the USDA Baseline projections process, and can be used as a benchmark for analyzing the impacts of U.S. and global macroeconomic shocks.

Expected Inflation Term Structure is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

About this dataset

Context

The dataset presents the median household income across different racial categories in United States. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of United States population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 63.44% of the total residents in United States. Notably, the median household income for White households is $83,784. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $113,106. This reveals that, while Whites may be the most numerous in United States, Asian households experience greater economic prosperity in terms of median household income.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in United States.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 United States median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in United States. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in United States. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2022

In terms of income distribution across age cohorts, in United States, householders within the 45 to 64 years age group have the highest median household income at $94,554, followed by those in the 25 to 44 years age group with an income of $86,950. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $56,955. Notably, householders within the under 25 years age group, had the lowest median household income at $42,810.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

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 United States median household income by age. You can refer the same here

Consumer Price Index CPI in the United States increased to 323.05 points in July from 322.56 points in June of 2025. This dataset provides the latest reported value for - United States Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus 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 State College. 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 State College, the median income for all workers aged 15 years and older, regardless of work hours, was $11,239 for males and $8,018 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 29% between the median incomes of males and females in State College. With women, regardless of work hours, earning 71 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in theborough of State College.

- Full-time workers, aged 15 years and older: In State College, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,601, while females earned $54,907, resulting in a 14% gender pay gap among full-time workers. This illustrates that women earn 86 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 borough of State College.

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 State College.

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 State College median household income by race. You can refer the same here