Living Costs and Food Survey technical report: financial year ending March 2025

• This report contains response information, questionnaire changes and new or changed methodology for financial year ending (FYE) 2025.

• The purpose of this report is to update the FYE 2024 technical report and accompanies the Family spending in the UK: April 2024 to March 2025 bulletin.

• Further supporting data can be found in the updated Living Costs and Food Survey (LCF) technical report data tables.

Background

This report contains response information, questionnaire changes and methodology updates for the Living Costs and Food Survey (LCF) for financial year ending (FYE) 2025 (April 2024 to March 2025).

It does not describe methodology that changed before FYE 2025. For earlier changes, users should refer to the relevant edition of our Family spending in the UK bulletin, which links to that year's technical report.

For a more in-depth explanation of LCF processes and methodology, users should refer to our LCF quality and methodology information (QMI) report. 

The purpose of this report is to update our FYE 2024 technical report. It also accompanies our Family spending in the UK: April 2024 to March 2025 bulletin. 

We also publish information on response, characteristics of the sample, confidence intervals and interview metrics alongside this report in our LCF Survey: technical report data tables.

The overall achieved sample for the Living Costs and Food Survey (LCF) in financial year ending (FYE) 2025 in the UK was 4,998 households. Of these, 276 households were from Northern Ireland (NI) and 4,722 from Great Britain (GB).

The rest of this section refers to the GB sample only. We directly collect GB data, while NI data are collected by the Northern Ireland Statistics and Research Agency (NISRA). For more information on this, please refer to our LCF quality and methodology information (QMI) report.

The overall response rate for the LCF in FYE 2025 in GB was 26%. This decreased by 2 percentage points compared with FYE 2024. The issued sample of 20,001 households was an increase of approximately 5,200 households, compared with FYE 2024. For more information on the achieved sample see Table 7 in our accompanying dataset.

We were unable to contact 23% of addresses in the eligible sample for FYE 2025, and a further 50% refused to take part. Non-response remains high since the coronavirus (COVID-19) pandemic. Of the 4,722 responding households in GB, 4,663 cooperated fully, meaning they completed both the interview and (14-day) record of spend (RoS) task.

Partial responses accounted for 1.2% of all cooperating households in FYE 2025. All of these occurred because one or more adults in the household refused to keep the RoS but did take part in the interview, with the household's main shopper completing both the interview and RoS (see Table 6 in our accompanying dataset). 

Interviewers record the main reason why people refuse before or during an interview. These are spontaneous results, coded against a list of preset answers, with an "other" option available. The two most commonly cited reasons for refusing to take part in the survey in FYE 2025 (see Table 10 in our accompanying dataset) were: 

• cannot be bothered (30%); the top reason cited, the same as in the previous year

• temporarily too busy (15%), which is a level similar to the previous year

Changes during FYE 2025

Several changes were implemented throughout financial year ending (FYE) 2025, with the majority implemented at the start of the survey year.

Questions removed

• Obsolete questions, such as questions relating to cost of living payments.

• Removals and amendments to existing questions relating to Class 2 National Insurance contributions for self-employed people.

Questions added or amended

• A set of questions requesting the value of some types of financial assets were added.

• Some income questions relating to employee bonuses, employer refunds to employees, and employee Income Tax and National Insurance have been amended to streamline the questionnaire and improve data quality.

• The Standard Occupational Classification coding frame was updated.

• Answer options for marital status and civil partnership questions were amended to conform with harmonised standards.

• To ensure that we are capturing the full range of mortgage types effectively, a response option relating to equity release mortgages has been added to questions about mortgages.

• To improve the quality and granularity of data collected on loans and hire purchases, a new set of questions was added requesting details on the interest rate.

For more detailed information on Living Costs and Food Survey (LCF) variables and changes, see the user guides that support LCF microdata deposits to the UK Data Service. The introduction volume (PDF, 451KB) provides an overview of the LCF Survey User Documentation, together with information on database and survey definitions, as well as the survey background.

Standard errors

The methodology used to produce standard errors (SE) and confidence intervals for the Living Costs and Food Survey (LCF) has been updated as part of a wider transition from legacy software to open-source programming.

The new approach improves alignment with the broader Household Financial Surveys weighting framework and strengthens quality assurance within the production process. This change affects Family spending outputs, specifically Workbook 1: Table A1, and the LCF Survey technical report – Table 14 for the periods financial year ending (FYE) 2023, 2024 and 2025, with the updated methodology being included in published tables.

As this methods update has been applied to published tables from FYE 2023 and onwards, comparisons of methods have been made to the period before this, FYE 2022 (Table 1).

Equivalisation

From FYE 2025 onwards, the method used to calculate equivalisation in our published data tables has been updated.

Equivalisation is based on the modified OECD scale (PDF, 166KB) using a two-person reference household, replacing the previous single-person reference household approach. This change reflects the average number of adult respondents per household (1.6). For FYE 2025, published tables (Workbook 1, Workbook 2, Workbook 4) show both methods, side by side for comparison.

Under the revised two-person reference household, the lower boundaries of all income quintiles increased by 50%, while total spend within each quintile changed by less than 1%.

The Living Costs and Food Survey (LCF) is undergoing a range of developments, with changes starting to be implemented from early 2026 onwards. This is detailed in our recent Office for National Statistics (ONS) Survey Improvement and Enhancement Plan for Economic Statistics article.

Completed changes

A sample boost

• The LCF sample boost was implemented in April 2026 and aims to mitigate the decline in response rates compared with pre-coronavirus (COVID-19) pandemic levels; it will also partially account for the 2025 cessation of the Survey on Living Conditions, data from which were previously combined with the LCF to produce household income statistics.

• The issued annual sample size was increased from approximately 20,000 (for financial year ending (FYE) 2026) to 32,420 (for FYE 2027) households across Great Britain.

• The boost was applied to England and Wales; there was no additional boost to the sample in Scotland beyond its original size in FYE 2026, as FYE 2026 already included a Scottish boost, which was maintained for FYE 2027.

• There was no boost to the sample in Northern Ireland; the Northern Ireland data are collected and funded by the Northern Ireland Statistics and Research Agency (NISRA).

A new LCF record of spending (RoS) tool

• The new tool was successfully launched, replacing an Excel tool used by interviewers to record detailed spending data provided by respondents; it is expected to reduce interviewer administration and improve quality.

• The tool's implementation marks the first step in uplifting the LCF to Blaise 5 (a computer-assisted interviewing system) – improving data quality and operational efficiency.

Improved data processing pipeline

• The LCF uses a complex delivery system, "Deliver", to process and manipulate raw data collected from the questionnaire and RoS to produce data that can be used for analysis; this system is an essential part of the data processing journey.

• The system we have been using has been classified as legacy; as such, a new pipeline has been developed, using open-source software (Python), and adhering to reproducible analytical pipeline standards and best practice.

• The process to implement this new pipeline was to build, test and evaluate (parallel running and comparing outputs from the new versus old system), before final evaluation confirming the pipeline was fit for purpose; the pipeline was implemented into LCF processing as of January 2026.

• This new pipeline has several benefits; it is robust and transparent, and more efficient in terms of time and storage, ultimately improving the production of data outputs (efficiency, quality, transparency and ease of use). This results in an improved service for our users. 

Ongoing changes

Ongoing changes we are continuing to progress throughout 2026 and beyond.

COICOP 2018

• The LCF questionnaire, coding frame and processing systems are in the process of being updated to enable us to deliver data categorised according to the latest (2018) version of the Classification of Individual Consumption by Purpose (COICOP) framework.

• This includes increasing the granularity of data collected in the coding frame, and some areas of the questionnaire.

• The updates are being designed to enable continued delivery of data categorised to the previous (1999) COICOP framework, concurrently with other important existing stakeholder requirements.

• Our economic statistics outputs will transition to COICOP 18 over the coming years, as detailed in our Plan for Economic Statistics.

Future developments

Beyond introducing updated COICOP classifications, we also have a series of wider medium- to long-term improvements planned for the LCF questionnaire and processing methodology, to enhance data quality and improve sustainability, as referenced in our ONS Survey Improvement and Enhancement Plan for Economic Statistics.