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.

Of the most populous cities in the U.S., San Jose, California had the highest annual income requirement at ******* U.S. dollars annually for homeowners to have an affordable and comfortable life in 2024. This can be compared to Houston, Texas, where homeowners needed an annual income of ****** U.S. dollars in 2024.

In the United States, Hawaii was the state with the most expensive housing, with the typical value of single-family homes in the 35th to 65th percentile range exceeding ******* U.S. dollars. Unsurprisingly, Hawaii also ranked top as the state with the highest cost of living. Meanwhile, a property was the least expensive in West Virginia, where it cost under ******* U.S. dollars to buy the typical single-family home. Single-family home prices increased across most states in the United States between December 2023 and December 2024, except in Louisiana, Florida, and the District of Colombia. According to the Federal Housing Association, house appreciation in 13 states exceeded **** percent in 2023.

Consumer Price Index CPI in the United States increased to 322.56 points in June from 321.46 points in May 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.

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.

The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. This feature layer contains 2022 County Health Rankings data for nation, state, and county levels. The Rankings are compiled using county-level measures from a variety of national and state data sources. Some example measures are:adult smokingphysical inactivityflu vaccinationschild povertydriving alone to workTo see a full list of variables, as well as their definitions and descriptions, explore the Fields information by clicking the Data tab here in the Item Details. These measures are standardized and combined using scientifically-informed weights."By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Counties are ranked within their state on both health outcomes and health factors. Counties with a lower (better) health outcomes ranking than health factors ranking may see the health of their county decline in the future, as factors today can result in outcomes later. Conversely, counties with a lower (better) factors ranking than outcomes ranking may see the health of their county improve in the future.Some new variables in the 2022 Rankings data compared to previous versions:COVID-19 age-adjusted mortalitySchool segregationSchool funding adequacyGender pay gapChildcare cost burdenChildcare centersLiving wage (while the Living wage measure was introduced to the CHRR dataset in 2022 from the Living Wage Calculator, it is not available in the Living Atlas dataset and user’s interested in the most up to date living wage data can look that up on the Living Wage Calculator website).Data Processing Notes:Data downloaded April 2022Slight modifications made to the source data are as follows:The string " raw value" was removed from field labels/aliases so that auto-generated legends and pop-ups would only have the measure's name, not "(measure's name) raw value" and strings such as "(%)", "rate", or "per 100,000" were added depending on the type of measure.Percentage and Prevalence fields were multiplied by 100 to make them easier to work with in the map.Ratios were set to null if negative to make them easier to work with in the map.For demographic variables, the word "numerator" was removed and the word "population" was added where appropriate.Fields dropped from analytic data file: yearall fields ending in "_cihigh" and "_cilow"and any variables that are not listed in the sources and years documentation.Analytic data file was then merged with state-specific ranking files so that all county rankings and subrankings are included in this layer.2010 US boundaries were used as the data contain 2010 US census geographies, for a total of 3,142 counties.

Abstract

The main objectives of the 2018/19 NLSS are: i) to provide critical information for production of a wide range of socio-economic and demographic indicators, including for benchmarking and monitoring of SDGs; ii) to monitor progress in population’s welfare; iii) to provide statistical evidence and measure the impact on households of current and anticipated government policies. In addition, the 2018/19 NLSS could be utilized to improve other non-survey statistical information, e.g. to determine and calibrate the contribution of final consumption expenditures of households to GDP; to update the weights and determine the basket for the national Consumer Price Index (CPI); to improve the methodology and dissemination of micro-economic and welfare statistics in Nigeria.

The 2018/19 NLSS collected a comprehensive and diverse set of socio-economic and demographic data pertaining to the basic needs and conditions under which households live on a day to day basis. The 2018/19 NLSS questionnaire includes wide-ranging modules, covering demographic indicators, education, health, labour, expenditures on food and non-food goods, non-farm enterprises, household assets and durables, access to safety nets, housing conditions, economic shocks, exposure to crime and farm production indicators.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Communities

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2018/19 NLSS sample is designed to provide representative estimates for the 36 states and the Federal Capital Territory (FCT), Abuja. By extension. The sample is also representative at the national and zonal levels. Although the sample is not explicitly stratified by urban and rural areas, it is possible to obtain urban and rural estimates from the NLSS data at the national level. At all stages, the relative proportion of urban and rural EAs as has been maintained.

Before designing the sample for the 2018/19 NLSS, the results from the 2009/10 HNLSS were analysed to extract the sampling properties (variance, design effect, etc.) and estimate the required sample size to reach a desired precision for poverty estimates in the 2018/19 NLSS.

EA SELECTION: The sampling frame for the 2018/19 NLSS was based on the national master sample developed by the NBS, referred to as the NISH2 (Nigeria Integrated Survey of Households 2). This master sample was based on the enumeration areas (EAs) defined for the 2006 Nigeria Census Housing and Population conducted by National Population Commission (NPopC). The NISH2 was developed by the NBS to use as a frame for surveys with state-level domains. NISH2 EAs were drawn from another master sample that NBS developed for surveys with LGA-level domains (referred to as the “LGA master sample”). The NISH2 contains 200 EAs per state composed of 20 replicates of 10 sample EAs for each state, selected systematically from the full LGA master sample. Since the 2018/19 NLSS required domains at the state-level, the NISH2 served as the sampling frame for the survey.

Since the NISH2 is composed of state-level replicates of 10 sample EAs, a total of 6 replicates were selected from the NISH2 for each state to provide a total sample of 60 EAs per state. The 6 replicates selected for the 2018/19 NLSS in each state were selected using random systematic sampling. This sampling procedure provides a similar distribution of the sample EAs within each state as if one systematic sample of 60 EAs had been selected directly from the census frame of EAs.

A fresh listing of households was conducted in the EAs selected for the 2018/19 NLSS. Throughout the course of the listing, 139 of the selected EAs (or about 6%) were not able to be listed by the field teams. The primary reason the teams were not able to conduct the listing in these EAs was due to security issues in the country. The fieldwork period of the 2018/19 NLSS saw events related to the insurgency in the north east of the country, clashes between farmers and herdsman, and roving groups of bandits. These events made it impossible for the interviewers to visit the EAs in the villages and areas affected by these conflict events. In addition to security issues, some EAs had been demolished or abandoned since the 2006 census was conducted. In order to not compromise the sample size and thus the statistical power of the estimates, it was decided to replace these 139 EAs. Additional EAs from the same state and sector were randomly selected from the remaining NISH2 EAs to replace each EA that could not be listed by the field teams. This necessary exclusion of conflict affected areas implies that the sample is representative of areas of Nigeria that were accessible during the 2018/19 NLSS fieldwork period. The sample will not reflect conditions in areas that were undergoing conflict at that time. This compromise was necessary to ensure the safety of interviewers.

HOUSEHOLD SELECTION: Following the listing, the 10 households to be interviewed were selected from the listed households. These households were selected systemically after sorting by the order in which the households were listed. This systematic sampling helped to ensure that the selected households were well dispersed across the EA and thereby limit the potential for clustering of the selected households within an EA.

Occasionally, interviewers would encounter selected households that were not able to be interviewed (e.g. due to migration, refusal, etc.). In order to preserve the sample size and statistical power, households that could not be interviewed were replaced with an additional randomly selected household from the EA. Replacement households had to be requested by the field teams on a case-by-case basis and the replacement household was sent by the CAPI managers from NBS headquarters. Interviewers were required to submit a record for each household that was replaced, and justification given for their replacement. These replaced households are included in the disseminated data. However, replacements were relatively rare with only 2% of sampled households not able to be interviewed and replaced.

Sampling deviation

Although a sample was initially drawn for Borno state, the ongoing insurgency in the state presented severe challenges in conducting the survey there. The situation in the state made it impossible for the field teams to reach large areas of the state without compromising their safety. Given this limitation it was clear that a representative sample for Borno was not possible. However, it was decided to proceed with conducting the survey in areas that the teams could access in order to collect some information on the parts of the state that were accessible.

The limited area that field staff could safely operate in in Borno necessitated an alternative sample selection process from the other states. The EA selection occurred in several stages. Initially, an attempt was made to limit the frame to selected LGAs that were considered accessible. However, after selection of the EAs from the identified LGAs, it was reported by the NBS listing teams that a large share of the selected EAs were not safe for them to visit. Therefore, an alternative approach was adopted that would better ensure the safety of the field team but compromise further the representativeness of the sample. First, the list of 788 EAs in the LGA master sample for Borno were reviewed by NBS staff in Borno and the EAs they deemed accessible were identified. The team identified 359 EAs (46%) that were accessible. These 359 EAs served as the frame for the Borno sample and 60 EAs were randomly selected from this frame. However, throughout the course of the NLSS fieldwork, additional insurgency related events occurred which resulted in 7 of the 60 EAs being inaccessible when they were to be visited. Unlike for the main sample, these EAs were not replaced. Therefore, 53 EAs were ultimately covered from the Borno sample. The listing and household selection process that followed was the same as for the rest of the states.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two sets of questionnaires – household and community – were used to collect information in the NLSS2018/19. The Household Questionnaire was administered to all households in the sample. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

Household Questionnaire: The Household Questionnaire provides information on demographics; education; health; labour; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; agriculture and land tenure; and other sources of household income.

Community Questionnaire: The Community Questionnaire solicits information on access to transported and infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

Cleaning operations

CAPI: The 2018/19 NLSS was conducted using the Survey Solutions Computer Assisted Person Interview (CAPI) platform. The Survey Solutions software was developed and maintained by the Development Economics Data Group (DECDG) at the World Bank. Each interviewer and supervisor was given a tablet

In 2024, the CPI in U.S. cities averaged at 313.7. However, the CPI for the New York-Newark-Jersey City metropolitan area amounted to about 334.21. Prices in New York City were significantly higher than the U.S. average. Nonetheless, the San Diego-Carlsbad area ranked first with a CPI of 373.32.The monthly inflation rate for the United States can be found here.

Geneva stands out as Europe's most expensive city for apartment purchases in early 2025, with prices reaching a staggering 15,720 euros per square meter. This Swiss city's real estate market dwarfs even high-cost locations like Zurich and London, highlighting the extreme disparities in housing affordability across the continent. The stark contrast between Geneva and more affordable cities like Nantes, France, where the price was 3,700 euros per square meter, underscores the complex factors influencing urban property markets in Europe. Rental market dynamics and affordability challenges While purchase prices vary widely, rental markets across Europe also show significant differences. London maintained its position as the continent's priciest city for apartment rentals in 2023, with the average monthly costs for a rental apartment amounting to 36.1 euros per square meter. This figure is double the rent in Lisbon, Portugal or Madrid, Spain, and substantially higher than in other major capitals like Paris and Berlin. The disparity in rental costs reflects broader economic trends, housing policies, and the intricate balance of supply and demand in urban centers. Economic factors influencing housing costs The European housing market is influenced by various economic factors, including inflation and energy costs. As of April 2025, the European Union's inflation rate stood at 2.4 percent, with significant variations among member states. Romania experienced the highest inflation at 4.9 percent, while France and Cyprus maintained lower rates. These economic pressures, coupled with rising energy costs, contribute to the overall cost of living and housing affordability across Europe. The volatility in electricity prices, particularly in countries like Italy where rates are projected to reach 153.83 euros per megawatt hour by February 2025, further impacts housing-related expenses for both homeowners and renters.

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP.

The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.

The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.

Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage.

The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage.

Secure Access FRS data
In addition to the standard End User Licence (EUL) version, Secure Access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 9256. Prospective users of the Secure Access version of the FRS will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from http://ukdataservice.ac.uk/media/178323/secure_frs_application_guidance.pdf" style="background-color: rgb(255, 255, 255);">Guidance on applying for the Family Resources Survey: Secure Access.

FRS, HBAI and PI
The FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The EUL versions of HBAI and PI are held under SNs 5828 and 8503, respectively. The Secure Access versions are held under SN 7196 and 9257 (see above).

FRS 2022-23

The impact of the coronavirus (COVID-19) pandemic on the FRS 2022-23 survey was much reduced when compared with the two previous survey years. Throughout the year, there was a gradual return to pre-pandemic fieldwork practices, with the majority of interviews being conducted in face-to-face mode. The achieved sample was just over 25,000 households. Users are advised to consult the FRS 2022-23 Background Information and Methodology document for detailed information on changes, developments and issues related to the 2022-23 FRS data set and publication. Alongside the usual topics covered, the 2022-2023 FRS also includes variables for Cost of Living support, including those on certain state benefits; energy bill support; and Council Tax support. See documentation for further details.

FRS 2021-22 and 2020-21 and the coronavirus (COVID-19) pandemic

The coronavirus (COVID-19) pandemic has impacted the FRS 2021-22 and 2020-21 data collection in the following ways:

• In 2020-21, fieldwork operations for the FRS were rapidly changed in response to the coronavirus (COVID-19) pandemic and the introduction of national lockdown restrictions. The established face-to-face interviewing approach employed on the FRS was suspended and replaced with telephone interviewing for the whole of the 2020-21 survey year.

• This change impacted both the size and composition of the achieved sample. This shift in mode of interview has been accompanied by a substantial reduction in the number of interviews achieved: just over 10,000 interviews were achieved this year, compared with 19,000 to 20,000 in a typical FRS year. While we made every effort to address additional biases identified (e.g. by altering our weighting regime), some residual bias remains. Please see the FRS 2020-21 Background Information and Methodology document for more information.
• The FRS team have published a technical report for the 2020-21 survey, which provides a full assessment of the impact of the pandemic on the statistics. In line with the Statistics Code of Practice, this is designed to assist users with interpreting the data and to aid transparency over decisions and data quality issues.

• In 2021-22, the interview mode was largely telephone, with partial return to face-to-face interviews towards end of survey year. The achieved sample was over 16,000 households. This is a return towards the number expected in a normal survey year (around 20,000 households).
• In both survey years, there remain areas where users are advised to exercise caution when making comparisons to other survey years. More details on how the results for the 2020 to 2021 and 2021-22 survey years were affected by the coronavirus (COVID-19) pandemic can be found in the FRS 2020 to 2021 Background Information and Methodology and FRS 2021 to 2022 Background Information and Methodology.

The FRS team are seeking users' feedback on the 2020-21 and 2021-22 FRS. Given the breadth of groups covered by the FRS data, it has not been possible for DWP statisticians to assess or validate every breakdown which is of interest to external researchers and users. Therefore, the FRS team are inviting users to let them know of any insights you may have relating to data quality or trends when analysing these data for your area of interest. Please send any feedback directly to the FRS Team Inbox: team.frs@dwp.gov.uk

Latest edition information

For the second edition (May 2025), the data were redeposited. The following changes have been made:

• An ONS-delivered fix to the highest level of qualification (EDUCQUAL) which for several adults had been erroneously recorded.
• For ESA (benefit 16 on the BENEFITS table) the associated VAR3 has now been populated using ESA admin data, to show whether cases are Support Group etc.
• For Pension Credit recipients (benefit 4 on the BENEFITS table) adding the low-income benefits and tax credits Cost of Living Payment as benefit 124; with its flag CLPAYIRB set on the ADULT table.

In 2023, the real median household income in the state of Alabama was 60,660 U.S. dollars. The state with the highest median household income was Massachusetts, which was 106,500 U.S. dollars in 2023. The average median household income in the United States was at 80,610 U.S. dollars.

Out of all 50 states, New York had the highest per-capita real gross domestic product (GDP) in 2023, at 90,730 U.S. dollars, followed closely by Massachusetts. Mississippi had the lowest per-capita real GDP, at 39,102 U.S. dollars. While not a state, the District of Columbia had a per capita GDP of more than 214,000 U.S. dollars. What is real GDP? A country’s real GDP is a measure that shows the value of the goods and services produced by an economy and is adjusted for inflation. The real GDP of a country helps economists to see the health of a country’s economy and its standard of living. Downturns in GDP growth can indicate financial difficulties, such as the financial crisis of 2008 and 2009, when the U.S. GDP decreased by 2.5 percent. The COVID-19 pandemic had a significant impact on U.S. GDP, shrinking the economy 2.8 percent. The U.S. economy rebounded in 2021, however, growing by nearly six percent. Why real GDP per capita matters Real GDP per capita takes the GDP of a country, state, or metropolitan area and divides it by the number of people in that area. Some argue that per-capita GDP is more important than the GDP of a country, as it is a good indicator of whether or not the country’s population is getting wealthier, thus increasing the standard of living in that area. The best measure of standard of living when comparing across countries is thought to be GDP per capita at purchasing power parity (PPP) which uses the prices of specific goods to compare the absolute purchasing power of a countries currency.

In 2024, the consumer price index (CPI) was 315.61. Data represents U.S. city averages. The monthly inflation rate for the United States can be found here. United States urban Consumer Price Index (CPI) The U.S. Consumer Price Index is a measure of change in the price of consumer goods and services purchased by households. The CPI is defined by the United States Bureau of Labor Statistics as "a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services." To calculate the CPI, the Bureau of Labor Statistics considers the price of goods and services from various categories: housing, transportation, apparel, food & beverage, medical care, recreation, education and other/uncategorized. The CPI is a useful measure, as it indicates how the cost of urban living in the United States has changed over time, compared to a base period. CPI is also used to calculate inflation, or change in the purchasing power of money. According to the U.S. Bureau of Labor Statistics, the U.S. urban CPI has been rising steadily since 1992. As of 2023, the CPI was 304.7, up from 233 ten years earlier and up from 184 twenty years earlier. This indicates the extent to which, compared to a base period 1982-1984 = 100, the price of various goods and services has risen.

In 2024, the U.S. GDP increased from the previous year to about 29.18 trillion U.S. dollars. Gross domestic product (GDP) refers to the market value of all goods and services produced within a country. In 2024, the United States has the largest economy in the world. What is GDP? Gross domestic product is one of the most important indicators used to analyze the health of an economy. GDP is defined by the BEA as the market value of goods and services produced by labor and property in the United States, regardless of nationality. It is the primary measure of U.S. production. The OECD defines GDP as an aggregate measure of production equal to the sum of the gross values added of all resident, institutional units engaged in production (plus any taxes, and minus any subsidies, on products not included in the value of their outputs). GDP and national debt Although the United States had the highest Gross Domestic Product (GDP) in the world in 2022, this does not tell us much about the quality of life in any given country. GDP per capita at purchasing power parity (PPP) is an economic measurement that is thought to be a better method for comparing living standards across countries because it accounts for domestic inflation and variations in the cost of living. While the United States might have the largest economy, the country that ranked highest in terms of GDP at PPP was Luxembourg, amounting to around 141,333 international dollars per capita. Singapore, Ireland, and Qatar also ranked highly on the GDP PPP list, and the United States ranked 9th in 2022.

In January 2025, the unadjusted consumer price index (CPI) of all items for urban consumers in the United States amounted to about 317.67. The data represents U.S. city averages. The base period was 1982-84=100. The CPI is defined by the United States Bureau of Labor Statistics as “a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services”. The annual consumer price index for urban consumers in the U.S. can be accessed here. Consumer Price Index The Consumer Price Index (CPI) began in 1919 under the Bureau of Labor Statistics and is published every month. The CPI for all urban consumers includes urban households in Metropolitan Statistical Areas and regions with over 2,500 inhabitants, as well as non-farm consumers living in rural regions. This index was established in 1978 and includes about 80 percent of the U.S. population. The monthly CPI of urban consumers in the United States increased from 292.3 in May 2022 to 304.13 in 2023. Inflation tends not to impact everyone equally for a variety of reasons, including geography - CPI often differs between regions, with a high of 287.49 in the Western region as of 2021. There are also disparities in inflation between income quartiles, in which inflation is generally felt more heavily by lower income households. The annual CPI in the United States has increased steadily over the past two decades, from 140.3 in 1992 to 292.56 in 2022. A forecast of the CPI expects this positive trend to continue, reaching 325.6 by 2027. As of March 2023, the CPI of the nation’s education had increased by 3.5 percent. Further, in the same month costs of recreation, rent, housing, medical care, and food and beverages, gasoline, and transportation increased. Comparatively, the CPI in Hong Kong reached 103.3 in 2022.

At **** U.S. dollars, Switzerland has the most expensive Big Macs in the world, according to the January 2025 Big Mac index. Concurrently, the cost of a Big Mac was **** dollars in the U.S., and **** U.S. dollars in the Euro area. What is the Big Mac index? The Big Mac index, published by The Economist, is a novel way of measuring whether the market exchange rates for different countries’ currencies are overvalued or undervalued. It does this by measuring each currency against a common standard – the Big Mac hamburger sold by McDonald’s restaurants all over the world. Twice a year the Economist converts the average national price of a Big Mac into U.S. dollars using the exchange rate at that point in time. As a Big Mac is a completely standardized product across the world, the argument goes that it should have the same relative cost in every country. Differences in the cost of a Big Mac expressed as U.S. dollars therefore reflect differences in the purchasing power of each currency. Is the Big Mac index a good measure of purchasing power parity? Purchasing power parity (PPP) is the idea that items should cost the same in different countries, based on the exchange rate at that time. This relationship does not hold in practice. Factors like tax rates, wage regulations, whether components need to be imported, and the level of market competition all contribute to price variations between countries. The Big Mac index does measure this basic point – that one U.S. dollar can buy more in some countries than others. There are more accurate ways to measure differences in PPP though, which convert a larger range of products into their dollar price. Adjusting for PPP can have a massive effect on how we understand a country’s economy. The country with the largest GDP adjusted for PPP is China, but when looking at the unadjusted GDP of different countries, the U.S. has the largest economy.

In January 2025, prices had increased by three percent compared to January 2024 according to the 12-month percentage change in the consumer price index — the monthly inflation rate for goods and services in the United States. The data represents U.S. city averages. In economics, the inflation rate is a measure of the change in price level over time. The rate of decrease in the purchasing power of money is approximately equal. A projection of the annual U.S. inflation rate can be accessed here and the actual annual inflation rate since 1990 can be accessed here. InflationOne of the most important economic indicators is the development of the Consumer Price Index in a country. The change in this price level of goods and services is defined as the rate of inflation. The inflationary situation in the United States had been relatively severe in 2022 due to global events relating to COVID-19, supply chain restrains, and the Russian invasion of Ukraine. More information on U.S. inflation may be found on our dedicated topic page. The annual inflation rate in the United States has increased from 3.2 percent in 2011 to 8.3 percent in 2022. This means that the purchasing power of the U.S. dollar has weakened in recent years. The purchasing power is the extent to which a person has available funds to make purchases. According to the data published by the International Monetary Fund, the U.S. Consumer Price Index (CPI) was about 258.84 in 2020 and is forecasted to grow up to 325.6 by 2027, compared to the base period from 1982 to 1984. The monthly percentage change in the Consumer Price Index (CPI) for urban consumers in the United States was 0.1 percent in March 2023 compared to the previous month. In 2022, countries all around the world are experienced high levels of inflation. Although Brazil already had an inflation rate of 8.3 percent in 2021, compared to the previous year, while the inflation rate in China stood at 0.85 percent.

The gross domestic product (GDP) of California was about 3.23 trillion U.S. dollars in 2023, meaning that it contributed the most out of any state to the country’s GDP in that year. In contrast, Vermont had the lowest GDP in the United States, with 35.07 billion U.S. dollars. What is GDP? Gross domestic product, or GDP, is the total monetary value of all goods and services produced by an economy within a certain time period. GDP is used by economists to determine the economic health of an area, as well as to determine the size of the economy. GDP can be determined for countries, states and provinces, and metropolitan areas. While GDP is a good measure of the absolute size of a country's economy and economic activity, it does account for many other factors, making it a poor indicator for measuring the cost or standard of living in a country, or for making cross-country comparisons. GDP of the United States The United States has the largest gross domestic product in the world as of 2023, with China, Japan, Germany, and India rounding out the top five. The GDP of the United States has almost quadrupled since 1990, when it was about 5.9 trillion U.S. dollars, to about 25.46 trillion U.S. dollars in 2022.

In 2023, the average annual expenditures of consumer units in the United States totaled to 77,280 U.S. dollars. This is an increase from the previous year, when the average annual expenditures of consumer units totaled to 72,967 U.S. dollars.