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.

In June 2025, 62 percent of households in Great Britain reported that their cost of living had increased in the previous month, compared with 72 percent in April. Although the share of people reporting a cost of living increase has generally been falling since August 2022, when 91 percent of households reported an increase, the most recent figures indicate that the Cost of Living Crisis is still ongoing for many households in the UK. Crisis ligers even as inflation falls Although various factors have been driving the Cost of Living Crisis in Britain, high inflation has undoubtedly been one of the main factors. After several years of relatively low inflation, the CPI inflation rate shot up from 2021 onwards, hitting a high of 11.1 percent in October 2022. In the months since that peak, inflation has fallen to more usual levels, and was 2.5 percent in December 2024, slightly up from 1.7 percent in September. Since June 2023, wages have also started to grow at a faster rate than inflation, albeit after a long period where average wages were falling relative to overall price increases. Economy continues to be the main issue for voters Ahead of the last UK general election, the economy was consistently selected as the main issue for voters for several months. Although the Conservative Party was seen by voters as the best party for handling the economy before October 2022, this perception collapsed following the market's reaction to Liz Truss' mini-budget. Even after changing their leader from Truss to Rishi Sunak, the Conservatives continued to fall in the polls, and would go onto lose the election decisively. Since the election, the economy remains the most important issue in the UK, although it was only slightly ahead of immigration and health as of January 2025.

The household living-costs price index (HLPI) provides insights into the inflation experienced by 13 different household groups: beneficiaries, Māori, income quintiles (five groups), expenditure quintiles (five groups), and superannuitants. An all-households HLPI is published for comparison.

The available data collection compiles the most important price indices of living costs published in official price statistics. The price indices for the standard of living are to show, in which measure the haouseholds’ standard of living increased or decreased in price due to price alteration, but unaffected by changes by consumers’ behaviour. Therefore, the consumer price indices are to measure the pure price development, isolated from changes in quantity or quality. Basis of the index is the supposition, that the structure of private households’ consumer expenditures doesn’t have changed since the basis-year (Laspeyres-Index). The consumer price index covers groups of goods, which are bought and/or used by the private households. The private households’ expenditure structure is the basis of this price index, therefore the index is to be regarded as a “purchase price index” for private ultimate consumer. Aim of the consumer price statistics is – as it is the aim of the whole official price statistics – the registration of price changes. Therefore their most important results are price indices to a certain base year and not average prices in absolute height. Furthermore, living-cost price indices informs about the percental increas or decrease of the goods’ and achievments’ prices (in relation to a base year). Topics List of data-tables in the search- and downloadsystem HISTAT: A. Living-cost price index of all private households and living-cost price index by household-types (1948-2001). B. Living-cost price index by consumption-groups and main groups; structure by goods, achievements and use of dwellings; structuring by COICOP; housing rents, motorist-price index (1948-2001); C. Consumer prices since 1881; Cost of living since 1924; Price index for nutrition (1881-1913); Realm index figures for living-cost: blue-colour-worker-households with 5 persons by consumption groups (1924-1944); D. Monthly values: Living-cost-price index of all private households (1962-2001); Living-cost-price index of a 4-persons-household with middle income (1950-2001), base years: 1913/14, 1938 = 100 (1948-1994); E. Living-cost price index: international tables (1960-2001).

The housing costs inflation rate for low-income households in the United Kingdom was noticeably higher than that of high-income ones between April 2022 and April 2023, during a serious cost of living crisis in the UK. As of June 2024, however, the inflation rate for high-income households was higher than that of middle or low incomes ones.

This table contains figures on the housing costs of private households in independent homes. Households living (temporarily) in a house free of charge are not included. The figures are presented for both owners and tenants and can be further divided into various characteristics of the household and the dwelling. Data available as of year: 2009-2015 Status of the figures: final. Changes as of 4 april 2019: None, this table was stopped. When will new figures be published? This table is stopped. This table is stopped as a consequence of a revision of the income data in 2015. The housing costs are based on this income data. Therefore it is no longer possible to determine the housing costs for WoON 2018 in the same way as before. Consequently the housing costs for WoON 2012 and 2015 have also been revised. For WoON 2009 this however was not possible, since 2011 was the last year of the revision. Subsequently the housing costs for WoON 2012, 2015 and 2018 are included in the new table Housing costs of households; household and dwelling characteristics. See the link in paragraph 3.

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.

In June 2024, the household cost inflation rate (HCI) for low-income households in the United Kingdom was 1.7 percent, compared with 2.3 percent for middle-income households, and 3.3 percent for high-income households. Unlike other measures of inflation such as the consumer price index (CPI) the HCI isn't based on a fixed basket of goods, but is weighted to show how price changes affect different households by their economic status.

This dataset contains statistics relating to the number and types of students receiving Student Allowances, and the amounts received.

Opinions of Londoners are at the heart of policy making at the Greater London Authority (GLA). City Hall conducts regular research with Londoners to provide evidence and insight into public opinion and behaviours, in order to support effective and impactful policy making and the development of strategies and programmes of work. These pages detail the latest research conducted by the GLA on public attitudes and behaviours in relation to the cost of living in 2022. All figures, unless otherwise stated, are from YouGov Plc on behalf of the GLA. The surveys were carried out online. The figures have been weighted and are representative of all London adults (aged 18+).

Opinions of Londoners are at the heart of policy making at the Greater London Authority (GLA). City Hall conducts regular research with Londoners to provide evidence and insight into public opinion and behaviours, in order to support effective and impactful policy making and the development of strategies and programmes of work. These pages detail the latest research conducted by the GLA on public attitudes and behaviours in relation to the cost of living in 2022. All figures, unless otherwise stated, are from YouGov Plc on behalf of the GLA. The surveys were carried out online. The figures have been weighted and are representative of all London adults (aged 18+).

CPIH is the most comprehensive measure of inflation. It extends CPI to include a measure of the costs associated with owning, maintaining and living in one's own home, known as owner occupiers' housing costs (OOH), along with council tax. This dataset provides CPIH time series (2005 to latest published month), allowing users to customise their own selection, view or download.

The data and programs replicate tables and figures from "Living in limbo: Economic and social costs for refugees", by Ukrayinchuk and Havrylchyk. Please see the ReadMe file for additional details.

InvaCost is the most up-to-date, comprehensive, standardized and robust data compilation and description of economic cost estimates associated with invasive species worldwide1. InvaCost has been constructed to provide a contemporary and freely available repository of monetary impacts that can be relevant for both research and evidence-based policy making. The ongoing work made by the InvaCost consortium2,3,4 leads to constantly improving the structure and content of the database (see sections below). The list of actual contributors to this data resource now largely exceeds the list of authors listed in this page. All details regarding the previous versions of InvaCost can be found by switching from one version to another using the “version” button above. IMPORTANT UPDATES: 1. All information, files, outcomes, updates and resources related to the InvaCost project are now available on a new website: http://invacost.fr/2. The names of the following columns have been changed between the previous and the current version: ‘Raw_cost_estimate_local_currency’ is now named ‘Raw_cost_estimate_original_currency’; ‘Min_Raw_cost_estimate_local_currency’ is now named ‘Min_Raw_cost_estimate_original_currency’; ‘Max_Raw_cost_estimate_local_currency’ is now named ‘Max_Raw_cost_estimate_original_currency’; ‘Cost_estimate_per_year_local_currency’ is now named ‘Cost_estimate_per_year_original_currency’3. The Frequently Asked Questions (FAQ) about the database and how to (1) understand it, (2) analyse it and (3) add new data are available at: https://farewe.github.io/invacost_FAQ/. There are over 60 questions (and responses), so there’s probably yours.4. Accordingly with the continuous development and updates of the database, a ‘living figure’ is now available online to display the evolving relative contributions of different taxonomic groups and regions to the overall cost estimates as the database is updated: https://borisleroy.com/invacost/invacost_livingfigure.html5. We have now added a new column called ‘InvaCost_ID’, which is now used to identify each cost entry in the current and future public versions of the database. As this new column only affects the identification of the cost entries and not their categorisation, this is not considered as a change of the structure of the whole database. Therefore, the first level of the version numbering remains ‘4’ (see VERSION NUMBERING section).

CONTENT: This page contains four files: (1) 'InvaCost_database_v4.1' which contains 13,553 cost entries depicted by 66 descriptive columns; (2) ‘Descriptors 4.1’ provides full definition and details about the descriptive columns used in the database; (3) ‘Update_Invacost_4.1’ has details about the all the changes made between previous and current versions of InvaCost; (4) ‘InvaCost_template_4.1’ (downloadable file) provides an easier way of entering data in the spreadsheet, standardizing all the terms used on it as much as possible to avoid mistakes and saving time at post-refining stages (this file should be used by any external contributor to propose new cost data).

METHODOLOGY: All the methodological details and tools used to build and populate this database are available in Diagne et al. 20201 and Angulo et al. 20215. Note that several papers used different approaches to investigate and analyse the database, and they are all available on our website http://invacost.fr/.

VERSION NUMBERING: InvaCost is regularly updated with contributions from both authors and future users in order to improve it both quantitatively (by new cost information) and qualitatively (if errors are identified). Any reader or user can propose to update InvaCost by filling the ‘InvaCost_updates_template’ file with new entries or corrections, and sending it to our email address (updates@invacost.fr). Each updated public version of InvaCost is stored in this figShare repository, with a unique version number. For this purpose, we consider the original version of InvaCost publicly released in September 2020 as ‘InvaCost_1.0’. The further updated versions are named using the subsequent numbering (e.g., ‘InvaCost_2.0’, InvaCost_2.1’) and all information on changes made are provided in a dedicated file called ‘Updates-InvaCost’ (named using the same numbering, e.g., ‘Updates-InvaCost_2.0’, ‘Updates-InvaCost_2.1’). We consider changing the first level of this numbering (e.g. ‘InvaCost_3.x’ ‘InvaCost_4.x’) only when the structure of the database changes. Every user wanting to have the most up-to-date version of the database should refer to the latest released version.

RECOMMENDATIONS: Every user should read the ‘Usage notes’ section of Diagne et al. 20201 before considering the database for analysis purposes or specific interpretation. InvaCost compiles cost data published in the literature, but does not aim to provide a ready-to-use dataset for specific analyses. While the cost data are described in a homogenized way in InvaCost, the intrinsic disparity, complexity, and heterogeneity of the cost data require specific data processing depending on the user objectives (see our FAQ). However, we provide necessary information and caveats about recorded costs, and we have now an open-source software designed to query and analyse this database6.

CAUTION: InvaCost is currently being analysed by a network of international collaborators in the frame of the InvaCost project2,3,4 (see https://invacost.fr/en/outcomes/). Interested users may contact the InvaCost team if they wish to learn more about or contribute to these current efforts. Users are in no way prevented from performing their own independent analyses and collaboration with this network is not required. Nonetheless, users and contributors are encouraged to contact the InvaCost team before using the database, as the information contained may not be directly implementable for specific analyses.

RELATED LINKS AND PUBLICATIONS:

1 Diagne, C., Leroy, B., Gozlan, R.E. et al. InvaCost, a public database of the economic costs of biological invasions worldwide. Sci Data 7, 277 (2020). https://doi.org/10.1038/s41597-020-00586-z

2 Diagne C, Catford JA, Essl F, Nuñez MA, Courchamp F (2020) What are the economic costs of biological invasions? A complex topic requiring international and interdisciplinary expertise. NeoBiota 63: 25–37. https://doi.org/10.3897/neobiota.63.55260

3 Researchgate page: https://www.researchgate.net/project/InvaCost-assessing-the-economic-costs-of-biological-invasions

4 InvaCost workshop: https://www.biodiversitydynamics.fr/invacost-workshop/

5 Angulo E, Diagne C, Ballesteros-Mejia L. et al. (2021) Non-English languages enrich scientific knowledge: the example of economic costs of biological invasions. Science of the Total Environment 775:144441. https://doi.org/10.1016/j.scitotenv.2020.144441

6Leroy B, Kramer A M, Vaissière A-C, Courchamp F and Diagne C (2020) Analysing global economic costs of invasive alien species with the invacost R package. BioRXiv. doi: https://doi.org/10.1101/2020.12.10.419432

Inflation is generally defined as the continued increase in the average prices of goods and services in a given region. Following the extremely high global inflation experienced in the 1980s and 1990s, global inflation has been relatively stable since the turn of the millennium, usually hovering between three and five percent per year. There was a sharp increase in 2008 due to the global financial crisis now known as the Great Recession, but inflation was fairly stable throughout the 2010s, before the current inflation crisis began in 2021. Recent years Despite the economic impact of the coronavirus pandemic, the global inflation rate fell to 3.26 percent in the pandemic's first year, before rising to 4.66 percent in 2021. This increase came as the impact of supply chain delays began to take more of an effect on consumer prices, before the Russia-Ukraine war exacerbated this further. A series of compounding issues such as rising energy and food prices, fiscal instability in the wake of the pandemic, and consumer insecurity have created a new global recession, and global inflation in 2024 is estimated to have reached 5.76 percent. This is the highest annual increase in inflation since 1996. Venezuela Venezuela is the country with the highest individual inflation rate in the world, forecast at around 200 percent in 2022. While this is figure is over 100 times larger than the global average in most years, it actually marks a decrease in Venezuela's inflation rate, which had peaked at over 65,000 percent in 2018. Between 2016 and 2021, Venezuela experienced hyperinflation due to the government's excessive spending and printing of money in an attempt to curve its already-high inflation rate, and the wave of migrants that left the country resulted in one of the largest refugee crises in recent years. In addition to its economic problems, political instability and foreign sanctions pose further long-term problems for Venezuela. While hyperinflation may be coming to an end, it remains to be seen how much of an impact this will have on the economy, how living standards will change, and how many refugees may return in the coming years.

Aggregate data at the level of the FRG about party preferences and the economic situation, in monthly intervals for the years 1949 to 1974.

Topics: Proportion of votes of the most important parties; price index for the cost of living; unemployment figures; those employed in industry; share price index; popularity of the federal chancellor.

Monthly indexes and percentage changes for major components and special aggregates of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.

The UK's average credit card debt per household grew by 151 British pounds between December 2021 and December 2022, the first increase since 2020. Standing at 2,229 British pounds at December 2022, the figure contrasts with the decline in 2020 – when the debt declined from 2,594 British pounds to 2,083 British pounds. That particular drop was likely a result of Covid-19's economic impact, and consumers trying to get rid of their credit card debt. The increase in 2022 may be caused by growing interest rates and the cost of living crisis beginning to take shape.

The analysis of real wages has a long tradition in Germany. The focus of the acquisition is on company wages, on wages of certain branches or for categories of workers as well as on the investigation of long term aggregated nominal and real wages. The study of Ashok V. Desai on the development of real wages in the German Reich between 1871 and 1913 is an important contribution to historical research on wages. The study is innovative and methodically on an exemplary level. But mainly responsible for the upswing in the historical research on wages in the 50s and 60s is an extraordinary publication by Jürgen Kuczynski. “The new historical research on wages in Germany is insolubly connected with Jürgen Kuczynski. In his broad researches the history of wages is only one section among many other themes but it is a very important one can be seen as the core piece of his work.” (Kaufhold, K.H., 1987: Forschungen zur deutschen Preis- und Lohngeschichte (seit 1930). In: Historia Socialis et Oeconomica. Festschrift für Wolfgang Zorn zum 65. Geburtstag. Stuttgart: Franz Steiner Verlag, S, 83). In his first study on long series on nominal and real wages in Germany he used a broad empirical basis and encouraged more research in this area. His weaknesses are methodological inconsistencies and a restricted representativeness. For example he includes tariff wages but also actually paid wages. Some important industries like food or textile industry are not taken into account. Wages in agriculture were often estimated but without enough material necessary for a good estimation. Wages for work at home are not regraded in the calculation of the index. The weight of cities in the calculation of the index is relatively too high compared to rural regions and therefor it leaks regional representativeness.In his study Desai uses the reports of trade associations for the Reich´s insurance office on the persons who are insured in the accident insurance and their wages as a basis for the calculation of annual nominal average wages. Desais focusses on industrial wages because only for them long term series are available. As the insurance premiums are calculated according to the income level the documents of the trade associations can be used for the calculation of an index for wages development. Desais study is also very useful regarding the calculation of a new index for costs of living based the model of a typical worker family. „F. Grumbach and H. König have used the same sources to derive indices of industrial earnings. The main differences between their series and ours are: (a) we have adopted the industrial classification followed by the Reichsversicherungsamt, while Grumbach and König have made larger industrial groups, (b) we have calculated average annual earnings, while they claim to have calculated average daily earnings (i.e. to have adjusted the annual figures for the average number of days worked per year per worker), and (c) they have failed to correct distortions in the original data” (Desai, A.V., 1968: Real Wages in Germany 1871–1913. Oxford. Clarendon Press, S. 4). Register of tables in HISTAT:A. OverviewsA.1 Overview: Different estimations of the real and nominal gross wages in the German Reich, index 1913 = 100 (1871-1913)A.2 Overview: Development of costs of living, index 1913 = 100 (1871-1913)A.3 Overview: Development of nominal and real wages, index 1913=100 (1844-1937) D. Study by Ashok V. DesaiD.01 Different estimations of real wages in the German Reich, index 1895 = 100 (1871-1913)D.02 Annual average wage (1871-1886)D.03 Annual gross wages in chosen production segments (1887-1913)D.04 Annual average wage in industry, transportation and trade (1871-1913)D.05 Construction of an index for costs of living, 1895 = 100 (1871-1913)D.06 Real wages, in constant prices from 1895 (1871-1913)D.07 Wheat prices and prices for wheat bread (1872-1913)D.08 Rye prices and prices for rye bread (1872-1913)D.09 Average export prices by product groups, index 1895 = 100 (1872-1913)D.10 Average import prices by product groups, index 1895 = 100 (1872-1913)D.11 Average export prices, import prices and terms of trade, index 1895 = 100 (1872-1913) O. Study by Thomas J. OrsaghO. Adjusted indices for costs of living and real wages after Orsgah, index 1913 = 100 (1871-1913)

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.