An R package for accessing data published by the Office for Budget Responsibility (OBR).

The Office for Budget Responsibility is the UK's independent fiscal watchdog. It was created in 2010 by the coalition government to provide an independent check on the government's fiscal plans - a role previously held by HM Treasury itself.

The distinction matters. HM Treasury is the government department that sets fiscal policy: it decides tax rates, spending plans, and how much the government intends to borrow. The OBR's job is to scrutinise those plans independently, producing its own economic and fiscal forecasts that are not influenced by ministers. Think of it as the equivalent of the Bank of England's independence for monetary policy, but applied to public finances.

In practice, this means the OBR publishes forecasts at each Budget and Autumn Statement showing whether it thinks the government is on track to meet its own fiscal rules - and it has no political incentive to be optimistic.

install.packages("obr")

# Or install the development version from GitHub
# install.packages("devtools")
devtools::install_github("charlescoverdale/obr")

This package covers all five datasets listed above.

All OBR data is freely available at obr.uk. The problem is how it is available: as Excel files with non-standard layouts, inconsistent headers, and footnote-laden sheets that require significant wrangling before they are usable in R.

For example, the Public Finances Databank has column headers buried in row 4 of the spreadsheet, data starting in row 8, and trailing footnote numbers appended to column names. The Historical Forecasts Database stores forecasts as a vintage matrix - rows are fiscal events, columns are fiscal years - which needs reshaping into a long format before it can be plotted or analysed.

This package handles all of that automatically. One function call returns a clean, tidy data frame. Data is cached locally so subsequent calls are instant.

# Without this package
path <- "~/Downloads/Public_finances_databank_March_2025.xlsx"
raw  <- readxl::read_excel(path, sheet = "Aggregates (£bn)", col_names = FALSE)
series_names <- as.character(unlist(raw[4, ]))
# ... 30 more lines of wrangling ...

# With this package
library(obr)
get_psnb()

Every data-returning function returns an obr_tbl: a data.frame with attached metadata recording the OBR publication, the publication vintage, the source URL, when the data was retrieved, and the MD5 fingerprint of the underlying spreadsheet. The provenance prints automatically as a header above the data.

library(obr)
get_efo_fiscal()
#> # obr_tbl: <rows> x <cols>
#> # Source:       OBR Economic and Fiscal Outlook, <vintage>
#> # URL:          https://obr.uk/download/<vintage-slug>/
#> # Retrieved:    <timestamp>
#> # File MD5:     <md5 prefix>
#> # Package:      obr <version>
#>
#> <data rows ...>

Use obr_provenance() to extract the metadata as a list, or summary() for the full provenance card. Provenance survives [ subsetting and is stripped only on explicit as.data.frame(). This means an analysis pinned against an obr_tbl always carries the audit trail of which OBR publication produced the numbers.

psnb <- get_psnb()
obr_provenance(psnb)
# Returns a list with: publication, vintage, source_url,
# retrieved (POSIXct), file_md5, package_version, notes

All download functions accept refresh = TRUE to force a fresh download from the OBR website.

library(obr)

psnb <- get_psnb()
psnb[psnb$year %in% c("2018-19", "2019-20", "2020-21", "2021-22", "2022-23"), ]
#>       year  psnb_bn
#>  2018-19     42.5
#>  2019-20     57.1
#>  2020-21    317.8   # ← COVID year
#>  2021-22    144.8
#>  2022-23     87.6

The UK borrowed £318bn in 2020-21 - roughly seven times the pre-pandemic level - to fund furlough, bounce-back loans, and emergency NHS spending.

The OBR first forecast 2024-25 borrowing at £37bn (March 2022). By November 2025, that estimate had risen to £149bn - four times the original figure.

psnb_fc <- get_forecasts("PSNB")
fc_2425 <- psnb_fc[psnb_fc$fiscal_year == "2024-25", c("forecast_date", "value")]
fc_2425
#>    forecast_date   value
#>     March 2022    36.5
#>  November 2022    84.3
#>     March 2023    85.4
#>  November 2023    84.6
#>     March 2024    87.2
#>   October 2024   127.5
#>     March 2025   137.3
#>  November 2025   149.5

The get_forecasts() function returns every published forecast across all fiscal events, making it straightforward to visualise forecast drift and assess how fiscal plans have evolved.

psnb <- get_psnb()

# Years with a surplus (negative PSNB = receipts exceed spending)
psnb[psnb$psnb_bn < 0, ]
#>       year  psnb_bn
#>  1969-70    -0.5
#>  1970-71    -1.3
#>  1971-72    -0.1
#>  1988-89    -9.0
#>  1989-90    -8.0
#>  1990-91    -0.1
#>  1997-98   -12.7
#>  1998-99   -14.5
#>  1999-00   -17.9
#>  2000-01    -0.5

The UK last ran a surplus in 2000-01. In the 24 years since, the government has borrowed every year. Combine with get_forecasts("PSNB_pct") to see whether the OBR projects any future surpluses.

receipts <- get_receipts()

# Top tax sources in 2023-24
r <- receipts[receipts$year == "2023-24", ]
r <- r[order(-r$value), ]
head(r[, c("series", "value")], 8)
#>                              series   value
#>   Public sector current receipts   1101.5
#>                       Income tax    290.4
#>                              VAT    183.1
#>    National insurance contributions 182.4
#>                    Corporation tax   88.4
#>                       Council tax   44.9
#>                         Fuel duty   24.5
#>                    Stamp duties     18.4

Income tax, VAT, and National Insurance together account for around 60% of all government receipts. Breaking this down over time reveals long-run shifts - such as the rising share of income tax as fiscal drag pulls more earners into higher bands.

efo <- get_efo_fiscal()
efo[efo$series == "Net borrowing", ]
#>   fiscal_year        series value_bn
#>       2025-26 Net borrowing    132.7
#>       2026-27 Net borrowing    115.5
#>       2027-28 Net borrowing     96.5
#>       2028-29 Net borrowing     86.0
#>       2029-30 Net borrowing     63.4
#>       2030-31 Net borrowing     59.0

The EFO detailed tables also include the full breakdown: current receipts, current expenditure, depreciation, net investment, and net borrowing - enabling you to see exactly how the deficit is projected to narrow.

Because the OBR revises its forecast at every Budget and Statement, an analysis run today and the same analysis run six months from now can return materially different numbers. The vintage layer pins to a specific EFO so the analysis is reproducible.

# What did the OBR forecast for 2027-28 borrowing in October 2024 vs March 2026?
oct_2024 <- get_efo_fiscal(vintage = "October 2024")
mar_2026 <- get_efo_fiscal(vintage = "March 2026")

oct_2024[oct_2024$series == "Net borrowing" & oct_2024$fiscal_year == "2027-28", ]
mar_2026[mar_2026$series == "Net borrowing" & mar_2026$fiscal_year == "2027-28", ]

# Or pin once and let every subsequent EFO call use that vintage
obr_pin("October 2024")
get_efo_fiscal()                  # uses October 2024
get_efo_economy("inflation")      # also uses October 2024
obr_unpin()

# Find which EFO was current on a given date
obr_as_of("2024-12-15")
#> [1] "October 2024"

welfare <- get_welfare_spending()
# Working-age incapacity spending, last 10 years
ic <- welfare[welfare$series == "Working-age incapacity benefits spending" &
              welfare$year >= "2014-15", ]
ic
#>        year                                      series value
#>     2014-15 Working-age incapacity benefits spending  1.44
#>     2015-16 Working-age incapacity benefits spending  1.33
#>     ...
#>     2023-24 Working-age incapacity benefits spending  1.78
#>     2024-25 Working-age incapacity benefits spending  2.02
#>     2025-26 Working-age incapacity benefits spending  2.16

# Number of people on incapacity benefits
cases <- get_incapacity_caseloads()
cases[cases$series == "Share of working age population", ]
#>  2008-09   Share of working age population  6.80
#>  ...
#>  2023-24   Share of working age population  6.82

Incapacity benefit spending and caseloads have risen sharply since the pandemic - a key driver of welfare reform debate in 2025.

# All tax measures scored from 2025-26 onwards
pmd <- get_policy_measures(type = "tax", since = "2025-26")

# Filter to measures from a specific event, ordered by 2025-26 effect
oct24 <- pmd[grepl("October 2024", pmd$event) &
             pmd$fiscal_year == "2025-26", ]
oct24 <- oct24[order(-oct24$value_mn), ]
head(oct24[, c("measure", "head", "value_mn")])

The PMD covers every measure scored at a UK fiscal event: 1970 onwards for tax, 2010 onwards for spending. Combine search = and since = to pull a thematic time series, e.g. all alcohol-duty measures since 2010.

get_policy_measures(type = "tax", search = "alcohol", since = "2010-11")

obr_fiscal_rules()

Returns the three Charter for Budget Responsibility rules in force (stability rule, investment rule, welfare cap), with their target metric, direction of pass, and the source Charter version. Numerical headroom is not shipped as a constant because it changes at every fiscal event; derive it from get_efo_fiscal() or consult the EFO press release for the relevant vintage.

proj <- get_pension_projections()

# Central demographic projection: pension spending rises from 5% to 7.7% of GDP
central <- proj[proj$scenario_type == "Demographic scenarios" &
                proj$scenario == "Central projection", ]
head(central[, c("fiscal_year", "pct_gdp")], 5)
#>   fiscal_year pct_gdp
#>       2023-24    4.56
#>       2024-25    4.95
#>       2025-26    5.06
#>       2026-27    5.13
#>       2027-28    5.05

tail(central[, c("fiscal_year", "pct_gdp")], 5)
#>   fiscal_year pct_gdp
#>       2069-70    7.73
#>       2070-71    7.82
#>       2071-72    7.77
#>       2072-73    7.66
#>       2073-74    7.65

The OBR's central projection has the state pension rising from 4.6% of GDP today to 7.7% by 2073-74 as the UK population ages. The FSR also publishes scenarios for higher/lower life expectancy and different triple-lock uprating assumptions.

The Public Finances Databank is accessed via a stable URL that the OBR keeps pointed at the latest file. The Historical Official Forecasts Database, EFO, WTR, and FSR functions all use a dynamic URL resolver that probes the OBR's recent fiscal events (most recent first) and uses whichever URL is live, so the package automatically picks up new editions without a code change.

If the resolver cannot find a live URL (for example because of a temporary network outage, or because the OBR has moved to an unfamiliar slug pattern), it falls back to the last-known-good URL and emits an explicit warning rather than failing silently. The returned obr_tbl always records the URL that was actually used, so any analysis carries its own audit trail.

The OBR publishes on a roughly predictable schedule: the EFO twice a year (March and October/November), the FSR each summer, the WTR annually. The package's fallback URLs are refreshed at each release; check the NEWS for the current fallback edition.

Please report bugs or requests at https://github.com/charlescoverdale/obr/issues.

Office for Budget Responsibility, OBR, UK fiscal forecasts, economic forecasts, GDP forecast, inflation forecast, public finances, government borrowing, fiscal policy, UK budget, R package