In 2019 the UK government had net assets worth approximately 176.8 billion US dollars. Between 2000 and 2020, both assets and liabilities grew, however assets increased more than liabilities resulting in an increase in net assets throughout the period.

Presents the balance sheet for the public sector, consistent with the 2010 European system of national and regional accounts (ESA 2010) and Manual on Government Deficit and Debt (MGDD).

Public sector net debt amounted to 95.8 percent of gross domestic product in the United Kingdom during the 2024/25 financial year, or 90 percent when the Bank of England is excluded. UK government debt is at its highest levels since the early 1960s, due to a significant increase in borrowing during the COVID-19 pandemic. After peaking at 251.7 percent shortly after the end of the Second World War, government debt in the UK gradually fell, before a sharp increase in the late 2000s at the time of the global financial crisis. Debt not expected to start falling until 2029/30 In 2022/23, the UK's government expenditure was approximately 1.15 trillion pounds, around 45.3 percent of GDP. This spending was financed by 1.02 trillion pounds of revenue raised, and 1.28 billion pounds of borrowing. Although the UK government can still borrow money in the future, it also needs to abide by certain fiscal rules, one of which is that debt should be falling within a five-year timeframe. Recent forecasts suggest that while this is expected to be the case, it is based on falling government deficits in the next five years. Next government faces hard choices Whoever wins the UK's 2024 general election will face tough economic choices in the coming years. Hitting fiscal targets, such as reducing the national debt, will require a careful balancing of the books, and possibly the need for either spending cuts or tax rises. The two major parties, Labour and the Conservatives, have both ruled out raising the main government tax sources, Income Tax, National Insurance, and VAT, and have so far remained silent on possible spending cuts. With limits on borrowing, and no tax rises or spending cuts, maintaining, let alone improving public services, will prove a challenging prospect for the next government.

United Kingdom UK: General Government: Net Acquisition of Financial Assets data was reported at 25,001.000 GBP mn in 2016. This records an increase from the previous number of 729.000 GBP mn for 2015. United Kingdom UK: General Government: Net Acquisition of Financial Assets data is updated yearly, averaging 9,575.000 GBP mn from Dec 1999 (Median) to 2016, with 18 observations. The data reached an all-time high of 62,893.000 GBP mn in 2008 and a record low of -23,480.000 GBP mn in 2013. United Kingdom UK: General Government: Net Acquisition of Financial Assets data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s UK – Table UK.IMF.IFS: Government Finance: Operations Statement: Annual.

United Kingdom UK: General Government: Net Financial Worth data was reported at -1,733,787.000 GBP mn in Mar 2018. This records an increase from the previous number of -1,749,203.000 GBP mn for Dec 2017. United Kingdom UK: General Government: Net Financial Worth data is updated quarterly, averaging -507,851.000 GBP mn from Mar 1999 (Median) to Mar 2018, with 77 observations. The data reached an all-time high of -250,915.000 GBP mn in Jun 2001 and a record low of -1,783,499.000 GBP mn in Sep 2016. United Kingdom UK: General Government: Net Financial Worth data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s UK – Table UK.IMF.IFS: Government Finance: Balance Sheet: Quarterly.

Quarterly end-of-period balance sheet levels of UK external assets and liabilities, including direct, portfolio and other investment, sector analysis and government reserve assets.

(CDID: NBYK) Year - UK National Accounts, The Blue Book time series Datasets for each of the chapters in The Blue Book 2023 including the national accounts at a glance, financial and non-financial corporations, households and non-profit institutions serving households and summary supply and use tables.

United Kingdom UK: General Government: Net Acquisition of Financial Assets: by Instrument: Other Accounts Receivable data was reported at 2,495.000 GBP mn in Mar 2018. This records an increase from the previous number of 1,904.000 GBP mn for Dec 2017. United Kingdom UK: General Government: Net Acquisition of Financial Assets: by Instrument: Other Accounts Receivable data is updated quarterly, averaging 408.000 GBP mn from Mar 1999 (Median) to Mar 2018, with 77 observations. The data reached an all-time high of 12,895.000 GBP mn in Mar 2010 and a record low of -6,478.000 GBP mn in Jun 2011. United Kingdom UK: General Government: Net Acquisition of Financial Assets: by Instrument: Other Accounts Receivable data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s UK – Table UK.IMF.IFS: Government Finance: Operations Statement: Quarterly.

United Kingdom UK: General Government: Net Acquisition of Financial Assets: by Instrument: Shares and Other Equity data was reported at -1,023.000 GBP mn in Mar 2018. This records a decrease from the previous number of -569.000 GBP mn for Dec 2017. United Kingdom UK: General Government: Net Acquisition of Financial Assets: by Instrument: Shares and Other Equity data is updated quarterly, averaging -656.000 GBP mn from Mar 1999 (Median) to Mar 2018, with 77 observations. The data reached an all-time high of 25,544.000 GBP mn in Dec 2009 and a record low of -16,571.000 GBP mn in Sep 2013. United Kingdom UK: General Government: Net Acquisition of Financial Assets: by Instrument: Shares and Other Equity data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s UK – Table UK.IMF.IFS: Government Finance: Operations Statement: Quarterly.

This folder contains MATLAB and R software and data to accompany the paper "Sectoral slowdowns in the UK: Evidence from transmission probabilities and economic linkages" by E.F. Janssens and R.L. Lumsdaine published in the Journal of Applied Econometrics.

This version: Feb 2022. The following items are provided:

1. LICENSE AGREEMENT (CC BY-NC-SA 4.0): The software is distributed under a Creative Commons Attribution NonCommericial-ShareAlike (CC BY-NC-SA) 4.0 International Public License, available at https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode .
   The license agreement explains the terms and conditions under which you can use, share and adapt this Software.

2. DATA:

We have directly copied the original data into the Matlab workspace file 'workspace_2020_07_01.mat'. You don't have to do anything with this, the relevant scripts you run will load this data into Matlab for you. The original data sources are:

For the whom-to-whom matrices: https://www.ons.gov.uk/economy/nationalaccounts/uksectoraccounts/datasets/enhancedfinancialaccountsflowoffundstotalfinancialaccountsexperimentalstatistics Here we use what they label as 'the 2018 edition'.

For the total financial assets, liabilities and net worth https://www.ons.gov.uk/economy/nationalaccounts/uksectoraccounts/datasets/unitedkingdomeconomicaccountsflowoffunds/current Here we use the data released on the 31th of March 2020.

These data are made available under the Open Government License v3.0, so we are allowed to redistribute them.

We provide you these data in csv files, under the names 'enhanced_financialaccounts.csv' and 'financial_assets.csv', 'financial_liabilities.csv' and 'financial_networth.csv'. These are the same data as in 'workspace_2020_07_01.mat', which we elaborate on below:

'workspace_2020_07_01.mat' contains the following variables:

financialaccounts_matrix (as in 'enhanced_financialaccounts.csv'): this matrix is 144x90, which is because the initial data comes with 11 sectors (+unknown) and 90 time observations, and this matrix essentially stacks the financial flow matrices between all sectors. Later in our files we merge certain sectors and will end up with a total of 8 sectors (note it also lists NMMF which is a subsection of OFI so we get rid of that too, so there are actually only 10 sectors in this set already). These data are obtained from the enhanced financial accounts linked above. Goes from Jan 1997 to April 2019.

Flowoffundsbasedassets (as in 'financial_assets.csv'), Flowoffundsbasedliab (as in 'financial_liabilities.csv'), Flowoffundsbasednetworth (as in 'financial_networth.csv'): these matrices contain the total assets, total liabilities and total net worth obtained from the flow of funds data linked above. These have 10 different sectors and a longer time period (133 periods, note that the last values in the matrices are nan's which is why their length does not correspond to 133): goes from Jan 1987 to Jan 2020.

N: number of sectors in the financial accounts matrix = 12, but after merging and cleaning this will go to 8.

Sectors: string 1x12 containing all the sector names of the enhanced financial accounts data

T: number of time observations of the enhanced financial accounts matrix, equals 90

Time: months and year for each data observation in the enhanced financial accounts data (1x90 datetime datatype)

1. CODE:

This folder has three scripts you need to run to replicate the results in the paper. The code does not work if you deviate from this order. That is, you need to first run (i) before (ii) and (iii).

(i) NetworkAnalysis_new_fof.m:

This script generates the maximum likelihood estimates. Run this script.

Useful output: - p_i_mode_mode_alt_stdev: this matrix contains the mode and standard deviation of the MLE of p_i, corresponding to those in Table 1 of the paper. Use the second and third row of the matrix. Also in Table 3 and Table E1. - q_i_mode_mode_alt_stdev: this matrix contains the mode and standard deviation of the MLE of p_i, corresponding to those in Table 1 of the paper. Use the second and third row of the matrix. Also in Table 3 and Table E1. - R0c_mean_modealt_stdev: these statistics are reported in Table 1 - R0d_mean_modealt_stdev: these statistics are reported in Table 1 - pijs_mode_mle_alt: these are the values of the pijs reported in Table 1 - pijs_stdev_mle: these are the standard errors of the pijs reported in Table 1

Apart from these statistics, this script generates several figures given in the paper:

Figure C4 in the Online Appendix is figure 11 in the script. Figure C1 in the Online Appendix is made by figure 6 and 7 in the script. Figure C3 in the Online Appendix is made by figure 101 in the script.

Figure D1 in the Online Appendix is made by figure 23 in the script. Figure F3 in the Online Appendix is made by figure 12 and 13 in the script.

(ii) NetworkAnalysis_new_withpriors_fof.m:

This script generates the Bayesian estimates with scaling factor. Run this script.

Useful output: - pijs_mode_alt: reported in Table 3 - pijs_se: reported in Table 3 - prior_pijs_mean: reported in Table 2 - prior_pijs_se: reported in Table 2 - R0c_mean_mode_var: reported in Table 3 - R0d_mean_mode_var: reported in Table 3 - z_mean_mode_var: reported in Table 3 - n_mean_mode_var: reported in text

In addition, the script produces several figures.

Figure 3 of the main paper is figure 18 in the script. Figure F1 is figure 23 in the script.

(iii) NetworkAnalysis_new_withpriors_noscale_fof.m: This script generates the Bayesian estimates without the scaling factor (z=1). Run this script.

Useful output - pijs_mode_alt: reported in Table E1 - pijs_se: reported in Table E1 - R0c_mean_mode_var: reported in Table E1 - R0d_mean_mode_var: reported in Table E1

In addition, the script generates among others the following figure: Figure E1 is figure 23 in the script

In 2025, the ratio of government expenditure to GDP in the United Kingdom amounts to approximately 43.88 percent.Fluctuating rise between 1980 and 2025A total increase by approximately 4.84 percentage points can be seen between 1980 and 2025. This increase however did not happen continuously.Fluctuating decline between 2025 and 2030In 2030 the ratio will lie at close to 42.90 percent, according to forecasts. Compared to 2025 that is an overall decrease by approximately 0.98 percentage points.Shown here is the general government expenditure as a share of the national gross domestic product. As defined by the International Monetary Fund, the general government expenditure consists of total expense and the net acquisition of nonfinancial assets. The gross domestic product represents the total value of final goods and services produced during a year.

Information on farm household income and farm household composition. Source agency: Environment, Food and Rural Affairs Designation: National Statistics Language: English Alternative title: Farm Household Income and Household Composition, England

If you require the datasets in a more accessible format, please contact fbs.queries@defra.gsi.gov.uk

Background and guidance on the statistics

Information on farm household income and farm household composition was collected in the Farm Business Survey (FBS) for England for the first time in 2004/05. Collection of household income data is restricted to the household of the principal farmer from each farm business. For practical reasons, data is not collected for the households of any other farmers and partners. Two-thirds of farm businesses have an input only from the principal farmer’s household (see table 5). However, details of household composition are collected for the households of all farmers and partners in the business, but not employed farm workers.

Data on the income of farm households is used in conjunction with other economic information for the agricultural sector (e.g. farm business income) to help inform policy decisions and to help monitor and evaluate current policies relating to agriculture in the United Kingdom by Government. It also informs wider research into the economic performance of the agricultural industry.

This release gives the main results from the income and composition of farm households and the off-farm activities of the farmer and their spouse (Including common law partners) sections of the FBS. These sections include information on the household income of the principal farmer’s household, off-farm income sources for the farmer and spouse and incomes of other members of their household and the number of working age and pensionable adults and children in each of the households on the farm (the information on household composition can be found in Appendix B).

This release provides the main results from the 2013/14 FBS. The results are presented together with confidence intervals.

Survey content and methodology

The Farm Business Survey (FBS) is an annual survey providing information on the financial position and physical and economic performance of farm businesses in England. The sample of around 1,900 farm businesses covers all regions of England and all types of farming with the data being collected by face to face interview with the farmer. Results are weighted to represent the whole population of farm businesses that have at least 25 thousand Euros of standard output as recorded in the annual June Survey of Agriculture and Horticulture. In 2013 there were just over 58 thousand farm businesses meeting this criteria.

Since 2009/10 a sub-sample of around 1,000 farms in the FBS has taken part in both the additional surveys on the income and composition of farm households and the off-farm activities of the farmer and their spouse. In previous years, the sub-sample had included over 1,600 farms. As such, caution should be taken when comparing to earlier years.

The farms that responded to the additional survey on household incomes and off-farm activities of the farmer and spouse had similar characteristics to those farms in the main FBS in terms of farm type and geographical location. However, there is a smaller proportion of very large farms in the additional survey than in the main FBS. Full details of the characteristic of responding farms can be found at Appendix A of the notice.

For further information about the Farm Business Survey please see: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey

Data analysis

The results from the FBS relate to farms which have a standard output of at least 25,000 Euros. Initial weights are applied to the FBS records based on the inverse sampling fraction for each design stratum (farm type by farm size). These weights are then adjusted (calibration weighting) so that they can produce unbiased estimators of a number of different target variables. Completion of the additional survey on household incomes and off-farm activities of the farmer and spouse was voluntary and a sample of around 1,000 farms was achieved. In order to take account of non-response, the results have been reweighted using a method that preserves marginal totals for populations according to farm type and farm size groups. As such, farm population totals for other classifications (e.g. regions) will not be in-line with results using the main FBS weights, nor will any results produced for variables derived from the rest of the FBS (e.g. farm business income).

Accuracy and reliability of the results

We show 95% confidence intervals against the results. These show the range of values that may apply to the figures. They mean that we are 95% confident that this range contains the true value. They are calculated as the standard errors (se) multiplied by 1.96 to give the 95% confidence interval. The standard errors only give an indication of the sampling error. They do not reflect any other sources of survey errors, such as non-response bias. For the Farm Business Survey, the confidence limits shown are appropriate for comparing groups within the same year only; they should not be used for comparing with previous years since they do not allow for the fact that many of the same farms will have contributed to the Farm Business Survey in both years.

Availability of results

This release contains headline results for each section. The full set of results can be found at: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey#publications

Defra statistical notices can be viewed on the on the statistics pages of the Defra website at https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/about/statistics. This site also shows details of future publications, with pre-announced dates.

Data Uses

Data from the Farm Business Survey (FBS) are provided to the EU as part of the Farm Accountancy Data Network (FADN). The data have been used to help inform policy decisions (e.g. Reform of Pillar 1 and Pillar 2 of Common Agricultural Policy) and to help monitor and evaluate current policies relating to agriculture in England (and the EU). It is also widely used by the industry for benchmarking and informs wider research into the economic performance of the agricultural industry.

User engagement

As part of our ongoing commitment to compliance with the Code of Practice for Official Statistics http://www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html, we wish to strengthen our engagement with users of these statistics and better understand the use made of them and the types of decisions that they inform. Consequently, we invite users to make themselves known, to advise us of the use they do, or might, make of these statistics, and what their wishes are in terms of engagement. Feedback on this notice and enquiries about these statistics are also welcome.

Definitions

Household income of the principal farmer Principal farmer’s household income has the following components: (1) The share of farm business income (FBI) (including income from farm diversification) attributable to the principal farmer and their spouse. (2) Principal farmer’s and spouse’s off farm income from employment and self-employment, investment income, pensions and social payments. (3) Income of other household members. The share of farm business income and all employment and self-employment incomes, investment income and pension income are recorded as gross of income tax payments and National Insurance contributions, but after pension contributions. In addition, no deduction is made for council tax.

Household A household is defined as a single person or group of people living at the same address as their only or main residence, who either share one meal a day together or share the living accommodation. A household must contain at least one person who received drawings from the farm business or who took a share of the profit from the business.

Drawings Drawings represent the monies which the farmer takes from the business for their own personal use. The percentage of total drawings going to each household is collected and is used to calculate the total share of farm business income for the principal farmer’s household.

Mean Mean household income of individuals is the ”average”, found by adding up the weighted household incomes for each individual farm in the population for analysis and dividing the result by the corresponding weighted number of farms. In this report average is usually taken to refer to the mean.

Percentiles These are the values which divide the population for analysis, when ranked by an output variable (e.g. household income or net worth), into 100 equal-sized groups. E.g. twenty five per cent of the population would have incomes below the 25th percentile.

Median Median household income divides the population, when ranked by an output variable, into two equal sized groups. The median of the whole population is the same as the 50th percentile. The term is also used for the midpoint of the subsets of the income distribution

Quartiles Quartiles are values which divide the population, when ranked by an output variable, into four equal-sized groups. The lowest quartile is the same as the 25th percentile. The divisions of a population split by quartiles are referred to as quarters in this publication.

Quintiles Quintiles are values which divide the population, when ranked by an output variable, into five equal-sized groups. The divisions of a population split by quintiles are referred to as fifths in this publication.

Assets Assets include