Measures of monthly UK inflation data including CPIH, CPI and RPI. These tables complement the consumer price inflation time series dataset.

Inflation Rate in the United Kingdom increased to 3.80 percent in July from 3.60 percent in June of 2025. This dataset provides - United Kingdom Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Introduction This note summarises trends in pay in London and the UK since 2010 and compares them to inflation trends. The focus is on median gross weekly earnings for all employees (full- and part-time) working in London. The counterfactual analysis is based on annual pay estimates. Notes on the data The employee pay estimates in this note do not cover self-employed jobs and come from a survey of UK businesses. There are, moreover, several discontinuities in the ONS ASHE series (e.g. in 2004, 2006, 2011 and 2021). The growth rates calculated over these periods are illustrative, not precise figures. During the pandemic earnings estimates were affected by compositional changes and the furlough scheme, making interpretation more difficult. Data collection disruption and lower response rates also mean that estimates for 2020 and 2021 are subject to greater uncertainty. Real earnings (earnings adjusted for inflation) have been calculated by adjusting nominal (unadjusted) earnings using the Consumer Prices Index including owner occupiers’ housing costs (CPIH). The CPIH is the most comprehensive measure of inflation in the UK.

Average weekly earnings for the whole economy, for total and regular pay, in real terms (adjusted for consumer price inflation), UK, monthly, seasonally adjusted.

Cost of food in the United Kingdom increased 4.90 percent in July of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United Kingdom Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Construction Output Price Indices (OPIs) from January 2014 to June 2025, UK. Summary

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 England. 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 England, the median income for all workers aged 15 years and older, regardless of work hours, was $35,179 for males and $34,318 for females.

Based on these incomes, we observe a gender gap percentage of approximately 2%, indicating a significant disparity between the median incomes of males and females in England. Women, regardless of work hours, still earn 98 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.09 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

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

Quarterly house price data based on a sub-sample of the Regulated Mortgage Survey.

Energy Inflation in the United Kingdom increased to 1.40 percent in July from -0.70 percent in June of 2025. This dataset includes a chart with historical data for the United Kingdom Energy Inflation.

Abstract copyright UK Data Service and data collection copyright owner. The purpose of this survey was to explore influences on the pressure for pay increases. Main Topics: Variables Areas covered include: (a) Characteristics of jobs (b) Assessments of adequacy and fairness of (i) pay; (ii) pay increase; (iii) household income (c) Runcimen style questioning on feelings of relative deprivation and comparative reference groups (d) Views about inflation. Multi-stage stratified random sample Face-to-face interview

About this dataset

Context

The dataset tabulates the England household income by gender. The dataset can be utilized to understand the gender-based income distribution of England income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• England, AR annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• England, AR annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of England income distribution by gender. You can refer the same here

Labour share of income, unit labour costs (ULCs), unit wage costs (UWCs) and average labour compensation per hour worked (ALCH).

This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

Examples of Annotated Headlines


    Forex Pair
    Headline
    Sentiment
    Explanation




    GBPUSD 
    Diminishing bets for a move to 12400 
    Neutral
    Lack of strong sentiment in either direction


    GBPUSD 
    No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft 
    Positive
    Positive sentiment towards GBPUSD (Cable) in the near term


    GBPUSD 
    When are the UK jobs and how could they affect GBPUSD 
    Neutral
    Poses a question and does not express a clear sentiment


    JPYUSD
    Appropriate to continue monetary easing to achieve 2% inflation target with wage growth 
    Positive
    Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply


    USDJPY
    Dollar rebounds despite US data. Yen gains amid lower yields 
    Neutral
    Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other


    USDJPY
    USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains 
    Negative
    USDJPY is expected to reach a lower value, with the USD losing value against the JPY


    AUDUSD

RBA Governor Lowe’s Testimony High inflation is damaging and corrosive

    Positive
    Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD.

Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

This is the total gross value added (GVA) generated from human health and social work activities in the area calculated using a balanced approach to GVA.These figures are presented in £ millions at current basic prices. They do not allow for different regional price levels or changes in prices over time (inflation). Balanced GVA estimates are produced by combining the existing income and production GVA estimates using weighted quality metrics.

Income GVA estimates are calculated by adding up the income generated by individuals or corporations in the production of goods and services whilst the Production Approach estimates GVA by calculating the total output of goods and services less the value of goods and services used up in the production process. A Balanced approach evaluates the strengths and weaknesses of these two opposing approaches and gives them an appropriate weighting in informing a single ‘balanced’ estimate of GVA.

GVA estimates are on a workplace basis, that being they are allocated to where the economic activity took place. Please note, figures can be rather volatile. If you see erratic movements in the time series, you should use caution in interpreting the data.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Average weekly earnings at industry level including manufacturing, construction and energy, Great Britain, monthly, non-seasonally adjusted. Monthly Wages and Salaries Survey.

The total investment through all training, off-the-job training and on-the-job training, as well as investment in training per employee and trainee between 2011 and 2022. Original figures and figures adjusted for 2022 inflation are included. Indicators can be broken down by UK nation, region, sector and establishment size.

This dataset contains the indices of UK hourly Construction Wage Costs (quarterly; not seasonally adjusted; 2000 = 100) and UK Construction Material Prices for New Housing, Other New Work, Repair and Maintenance, and All Work (monthly; 2010 = 100).

Average weekly earnings at sector level including manufacturing, finance and services, Great Britain, monthly, non-seasonally adjusted. Monthly Wages and Salaries Survey.

Labour Costs in the United Kingdom increased to 117.20 points in the first quarter of 2025 from 115.90 points in the fourth quarter of 2024. This dataset provides the latest reported value for - United Kingdom Labour Costs - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.