The median annual earnings for full-time employees in the United Kingdom was approximately 37,430 British pounds in 2024, compared with 34,963 pounds in the previous year. At the start of the provided time period, in 1999, the average full-time salary in the UK was 17,803 pounds per year, with median earnings exceeding 20,000 pounds per year in 2002, and 30,000 by 2019. Wages continue to grow faster than inflation in 2024 Between November 2021 and July 2023 inflation was higher than wage growth in the UK, with wages still outpacing inflation as of April 2024. At the peak of the recent wave of high inflation in October 2022, the CPI inflation rate reached a 41-year-high of 11.1 percent, wages were growing much slower at 6.1 percent. Since that peak, inflation remained persistently high for several months, only dropping below double figures in April 2023, when inflation was 8.7 percent, down from 10.1 percent in the previous month. For 2023 as a whole, the average annual rate of inflation was 7.3 percent but is forecast to fall to 2.2 percent in 2024, and 1.5 percent in 2025. Highest and lowest-paid occupations As of 2023, the highest-paid occupation in the UK was that of Chief Executives and Senior Officials, who had an average weekly pay of approximately, 1,576 pounds. By contrast, the lowest-paid occupation that year was that of retail cashiers, and check-out operators, who earned approximately 383 pounds a week. For industry sectors as a whole, people who worked full-time in the electricity, gas, steam and air conditioning supply sector had the highest average earnings, at 955 pounds a week, compared with 505 pounds a week in the accommodation and food services sector, the lowest average earnings in 2023.

How much time do people spend on social media? As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

As of 2024, the average cost of a data breach in the United States amounted to 9.36 million U.S. dollars, down from 9.48 million U.S. dollars in the previous year. The global average cost per data breach was 4.88 million U.S. dollars in 2024. Cost of a data breach in different countries worldwide Data breaches impose a big threat for organizations globally. The monetary damage caused by data breaches has increased in many markets in the past decade. In 2023, Canada followed the U.S. by data breach costs, with an average of 5.13 million U.S. dollars. Since 2019, the average monetary damage caused by loss of sensitive information in Canada has increased notably. In the United Kingdom, the average cost of a data breach in 2024 amounted to around 4.53 million U.S. dollars, while in Germany it stood at 5.31 million U.S. dollars. The cost of data breach by industry and segment Data breach costs vary depending on the industry and segment. For the fourth consecutive year, the global healthcare sector registered the highest costs of data breach, which in 2024 amounted to about nine million U.S. dollars. Financial institutions ranked second, with an average cost of six million U.S. dollars for a data breach. Detection and escalation was the costliest segment in data breaches worldwide, with 1.63 U.S. dollars on average. The cost for lost business ranked second, while response following a breach came across as the third-costliest segment.

United Kingdom UK: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Male: % of Population Aged 15+ data was reported at 96.674 % in 2017. This records a decrease from the previous number of 99.222 % for 2014. United Kingdom UK: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Male: % of Population Aged 15+ data is updated yearly, averaging 96.707 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 99.222 % in 2014 and a record low of 96.674 % in 2017. United Kingdom UK: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider: Male: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (male, % age 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

United Kingdom UK: Broad Money: % of GDP data was reported at 148.452 % in 2017. This records an increase from the previous number of 142.300 % for 2016. United Kingdom UK: Broad Money: % of GDP data is updated yearly, averaging 56.932 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 166.414 % in 2010 and a record low of 30.454 % in 1979. United Kingdom UK: Broad Money: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Money Supply. Broad money (IFS line 35L..ZK) is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler’s checks; and other securities such as certificates of deposit and commercial paper.; ; International Monetary Fund, International Financial Statistics and data files, and World Bank and OECD GDP estimates.; Weighted average; The derivation of this indicator was simplified in September 2012 to be current-year broad money divided by current-year GDP times 100.

The median annual earnings in the United Kingdom was 37,430 British pounds per year in 2024. Annual earnings varied significantly by region, ranging from 47,455 pounds in London to 32,960 pounds in the North East. Along with London, two other areas of the UK had median annual earnings above the UK average; South East England, and Scotland, at 39,038 pounds and 38,315 pounds respectively. Regional Inequality in the UK Various other indicators highlight the degree of regional inequality in the UK, especially between London and the rest of the country. Productivity in London, as measured by output per hour, was 33.2 percent higher than the UK average. By comparison, every other UK region, except the South East, fell below the UK average for productivity. In gross domestic product per head, London was also an outlier. The average GDP per head in the UK was 31,947 pounds in 2021, but for London it was 56,431 pounds. Again, the South East's GDP per head was slightly above the UK average, with every other region below it. Within London itself, there is also a great degree of inequality. In 2021, for example, the average earnings in the historic City of London borough were 1,138 pounds per week, compared with 588 pounds in Redbridge, a borough in the North East of London. Wages finally catch up with inflation in 2023 After the initial economic disruption caused by the COVID-19 pandemic subsided, wages began to steadily grow in the UK. This reached a peak in June 2021, when weekly wages for regular pay were growing at 7.3 percent, or 5.2 percent when adjusted for inflation. By that November, however, prices began to rise faster than wage growth, with inflation surging throughout 2022. In October 2022, for example, while regular pay was growing by 6.1 percent, the inflation rate had surged to 11.1 percent, Although inflation peaked in that month, it wasn't until June 2023 that wages started to outpace inflation. By this point, the damage caused by high energy and food inflation has precipitated the worst Cost of Living Crisis in the UK for a generation.

GDHI is the amount of money individuals in the household sector have available for spending or saving. This is money left over after expenditure associated with income, for example taxes, social contributions, property ownership and provision for future pension income. It should be noted that these estimates relate to totals for all individuals within the household sector for a region rather than to an actual average household or family unit. GDHI per head estimates give values for each person, not each household.

This statistic shows total domestic consumption expenditure in the United Kingdom (UK) from 2005 to 2023. In 2023, consumer spending in the UK increased compared to the previous year, and amounted to approximately 1.6 trillion British pounds. Household consumption expenditure looks at the overall spending on consumer goods and services of a wide variety. Some examples are government licenses and permits, such as a passport renewal or the price of train tickets to get to work. Housing may also be accounted for in these figures. This figure is measured by how much the consumer actually pays at the point of sale. All fast moving consumer goods such a beer, or cigarettes are also accounted for in this data. One part of the United Kingdom, Scotland, has seen as increase in its overall household expenditure year over year since 2009, with figures reaching over 100 billion British pounds in 2018. There was a small decrease in expenditure in 2009, which was possibly a result of the economic recession which hit all of the United Kingdom hard at this time. This drop can also be seen when looking at the whole of the United Kingdom in this statistic.

Abstract

Syngenta is committed to increasing crop productivity and to using limited resources such as land, water and inputs more efficiently. Since 2014, Syngenta has been measuring trends in agricultural input efficiency on a global network of real farms. The Good Growth Plan dataset shows aggregated productivity and resource efficiency indicators by harvest year. The data has been collected from more than 4,000 farms and covers more than 20 different crops in 46 countries. The data (except USA data and for Barley in UK, Germany, Poland, Czech Republic, France and Spain) was collected, consolidated and reported by Kynetec (previously Market Probe), an independent market research agency. It can be used as benchmarks for crop yield and input efficiency.

Geographic coverage

National coverage

Analysis unit

Agricultural holdings

Kind of data

Sample survey data [ssd]

Sampling procedure

A. Sample design Farms are grouped in clusters, which represent a crop grown in an area with homogenous agro- ecological conditions and include comparable types of farms. The sample includes reference and benchmark farms. The reference farms were selected by Syngenta and the benchmark farms were randomly selected by Kynetec within the same cluster.

B. Sample size Sample sizes for each cluster are determined with the aim to measure statistically significant increases in crop efficiency over time. This is done by Kynetec based on target productivity increases and assumptions regarding the variability of farm metrics in each cluster. The smaller the expected increase, the larger the sample size needed to measure significant differences over time. Variability within clusters is assumed based on public research and expert opinion. In addition, growers are also grouped in clusters as a means of keeping variances under control, as well as distinguishing between growers in terms of crop size, region and technological level. A minimum sample size of 20 interviews per cluster is needed. The minimum number of reference farms is 5 of 20. The optimal number of reference farms is 10 of 20 (balanced sample).

C. Selection procedure The respondents were picked randomly using a “quota based random sampling” procedure. Growers were first randomly selected and then checked if they complied with the quotas for crops, region, farm size etc. To avoid clustering high number of interviews at one sampling point, interviewers were instructed to do a maximum of 5 interviews in one village.

BF Screened from Philippines were selected based on the following criterion: (a) smallholder rice growers Location: Luzon - Mindoro (Southern Luzon) mid-tier (sub-optimal CP/SE use): mid-tier growers use generic CP, cheaper CP, non hybrid (conventional) seeds
Smallholder farms with average to high levels of mechanization
Should be Integrated Pest Management advocates
less accessible to technology: poor farmers, don't have the money to buy quality seeds, fertilizers,... Don't use machinery yet
simple knowledge on agronomy and pests
influenced by fellow farmers and retailers
not strong financial status: don't have extra money on bank account and so need longer credit to pay (as a consequence: interest increases) may need longer credit

Mode of data collection

Face-to-face [f2f]

Research instrument

Data collection tool for 2019 covered the following information:

(A) PRE- HARVEST INFORMATION

PART I: Screening PART II: Contact Information PART III: Farm Characteristics a. Biodiversity conservation b. Soil conservation c. Soil erosion d. Description of growing area e. Training on crop cultivation and safety measures PART IV: Farming Practices - Before Harvest a. Planting and fruit development - Field crops b. Planting and fruit development - Tree crops c. Planting and fruit development - Sugarcane d. Planting and fruit development - Cauliflower e. Seed treatment

(B) HARVEST INFORMATION

PART V: Farming Practices - After Harvest a. Fertilizer usage b. Crop protection products c. Harvest timing & quality per crop - Field crops d. Harvest timing & quality per crop - Tree crops e. Harvest timing & quality per crop - Sugarcane f. Harvest timing & quality per crop - Banana g. After harvest PART VI - Other inputs - After Harvest a. Input costs b. Abiotic stress c. Irrigation

See all questionnaires in external materials tab.

Cleaning operations

Data processing:

Kynetec uses SPSS (Statistical Package for the Social Sciences) for data entry, cleaning, analysis, and reporting. After collection, the farm data is entered into a local database, reviewed, and quality-checked by the local Kynetec agency. In the case of missing values or inconsistencies, farmers are re-contacted. In some cases, grower data is verified with local experts (e.g. retailers) to ensure data accuracy and validity. After country-level cleaning, the farm-level data is submitted to the global Kynetec headquarters for processing. In the case of missing values or inconsistences, the local Kynetec office was re-contacted to clarify and solve issues.

Quality assurance Various consistency checks and internal controls are implemented throughout the entire data collection and reporting process in order to ensure unbiased, high quality data.

• Screening: Each grower is screened and selected by Kynetec based on cluster-specific criteria to ensure a comparable group of growers within each cluster. This helps keeping variability low.

• Evaluation of the questionnaire: The questionnaire aligns with the global objective of the project and is adapted to the local context (e.g. interviewers and growers should understand what is asked). Each year the questionnaire is evaluated based on several criteria, and updated where needed.

• Briefing of interviewers: Each year, local interviewers - familiar with the local context of farming -are thoroughly briefed to fully comprehend the questionnaire to obtain unbiased, accurate answers from respondents.

• Cross-validation of the answers: o Kynetec captures all growers' responses through a digital data-entry tool. Various logical and consistency checks are automated in this tool (e.g. total crop size in hectares cannot be larger than farm size) o Kynetec cross validates the answers of the growers in three different ways: 1. Within the grower (check if growers respond consistently during the interview) 2. Across years (check if growers respond consistently throughout the years) 3. Within cluster (compare a grower's responses with those of others in the group) o All the above mentioned inconsistencies are followed up by contacting the growers and asking them to verify their answers. The data is updated after verification. All updates are tracked.

• Check and discuss evolutions and patterns: Global evolutions are calculated, discussed and reviewed on a monthly basis jointly by Kynetec and Syngenta.

• Sensitivity analysis: sensitivity analysis is conducted to evaluate the global results in terms of outliers, retention rates and overall statistical robustness. The results of the sensitivity analysis are discussed jointly by Kynetec and Syngenta.

• It is recommended that users interested in using the administrative level 1 variable in the location dataset use this variable with care and crosscheck it with the postal code variable.

Data appraisal

Due to the above mentioned checks, irregularities in fertilizer usage data were discovered which had to be corrected:

For data collection wave 2014, respondents were asked to give a total estimate of the fertilizer NPK-rates that were applied in the fields. From 2015 onwards, the questionnaire was redesigned to be more precise and obtain data by individual fertilizer products. The new method of measuring fertilizer inputs leads to more accurate results, but also makes a year-on-year comparison difficult. After evaluating several solutions to this problems, 2014 fertilizer usage (NPK input) was re-estimated by calculating a weighted average of fertilizer usage in the following years.

Average Earnings Excluding Bonus in the United Kingdom remained unchanged at 5.90 percent in January. This dataset includes a chart with historical data for the United Kingdom Average Earnings Excluding Bonus YoY.

Corporate Profits in the United Kingdom decreased to 147267 GBP Million in the fourth quarter of 2024 from 148826 GBP Million in the third quarter of 2024. This dataset provides the latest reported value for - United Kingdom Corporate Profits - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

A dataset of vehicle MPG ratings and fuel cost calculations based on manufacturer, model, and fuel type.

The benchmark interest rate in the United Kingdom was last recorded at 4.50 percent. This dataset provides - United Kingdom Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.