Inflation Adjustment for Historical Currency Values

Convert historical monetary values into their present-day equivalents using bundled CPI (Consumer Price Index) and GDP deflator data sourced from the World Bank Development Indicators. Supports British pounds (GBP), Australian dollars (AUD), US dollars (USD), Euro (EUR), Canadian dollars (CAD), Japanese yen (JPY), Chinese yuan (CNY), Swiss francs (CHF), New Zealand dollars (NZD), Indian rupees (INR), South Korean won (KRW), Brazilian reais (BRL), and Norwegian krone (NOK). Currency codes and country names are both accepted as input.

inflateR

A technical working paper for this package can be found here.

Adjust monetary values for inflation across 13 currencies and 60+ years. Convert historical prices to today's money, calculate inflation rates, or reverse the calculation to find what a modern amount would have been worth in the past. Uses both CPI and GDP deflator indices from the World Bank.

Getting consistent, comparable inflation data across multiple countries and many decades is harder than it sounds. Each country has its own national statistics agency, its own methodology, and its own publication format. The World Bank Development Indicators solve this by aggregating data from national sources into a single, consistently formatted dataset - with the World Bank handling source reconciliation. All series are rescaled to 2020 = 100 for consistency across currencies.

Installation

install.packages("inflateR")

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

inflateR has no runtime dependencies and requires no API key or internet connection. All data is bundled directly inside the package.

CPI vs GDP deflator - which should I use?

inflateR provides two methods for adjusting monetary values across time. Choosing between them depends on what you're adjusting.

Use CPI (adjust_inflation, historical_value) for:

• Wages and salaries - "What would a £30,000 salary in 1990 be worth today?"
• Everyday prices - "What is £12 from 1963 worth in today's money?"
• Household budgets and cost of living comparisons
• Retail prices, rents, consumer spending

CPI tracks the price of a fixed basket of goods and services that a typical household buys. It's the most intuitive measure for anything a person earns or spends.

Use GDP deflator (adjust_real, historical_real) for:

• GDP figures - "How does UK GDP in 1980 compare to today in real terms?"
• Government expenditure - "What would the 2000 defence budget be worth today?"
• Business investment and capital expenditure
• Any macroeconomic aggregate you want to compare across time

The GDP deflator covers all goods and services produced in the economy - not just the consumer basket. It updates automatically (no fixed basket) and excludes imported goods, making it more appropriate for economy-wide comparisons.

When in doubt: if you're talking about something a person earns, buys, or pays for - use CPI. If you're talking about a number from a national accounts table - use the GDP deflator.

Functions

inflateR provides six functions: four adjustment functions in two symmetric pairs, plus inflation_rate() and list_currencies():

library(inflateR)

# CPI: adjust a historical value to today's money
adjust_inflation(amount, from_year, currency, to_year = NULL, round = 2)

# CPI: convert a present value back to a historical year
historical_value(amount, to_year, currency, from_year = NULL, round = 2)

# GDP deflator: adjust a historical value to today's money
adjust_real(amount, from_year, currency, to_year = NULL, round = 2)

# GDP deflator: convert a present value back to a historical year
historical_real(amount, to_year, currency, from_year = NULL, round = 2)

# Calculate cumulative or annualised inflation rate
inflation_rate(from_year, to_year = NULL, currency, annualise = FALSE)

# See all supported currencies and data coverage
list_currencies()

All four adjustment functions accept the same currency codes and country names and are exact inverses within each pair.

Arguments

Examples

CPI: adjusting everyday values

# What is £12 from 1963 worth today?
adjust_inflation(12, 1963, "GBP")
#> [1] 256.43

# What is $50 USD from 1980 worth today?
adjust_inflation(50, 1980, "USD")
#> [1] 190.33

# What is AUD 100 from 1990 worth today?
adjust_inflation(100, 1990, "AUD")
#> [1] 241.39

# Adjust to a specific year rather than today
adjust_inflation(100, 1970, "GBP", to_year = 2000)
#> [1] 872.45

# What would £100 today have been worth in 1963?
historical_value(100, 1963, "GBP")
#> [1] 4.68

# What would USD 1000 in 2020 have been worth in 1990?
historical_value(1000, 1990, "USD", from_year = 2020)
#> [1] 504.80

GDP deflator: adjusting macroeconomic values

# UK GDP was roughly £500bn in 1990 - what is that in today's terms?
adjust_real(500e9, 1990, "GBP")
#> [1] 1214415929203

# What would $1 trillion of US government spending in 2000 be worth in 2020?
adjust_real(1e12, 2000, "USD", to_year = 2020)
#> [1] 1428890000000

# Reverse: what would today's UK GDP of £2.5 trillion have been in 1990 terms?
historical_real(2.5e12, 1990, "GBP")
#> [1] 1028928849648

Inflation rates

# Cumulative US inflation from 2000 to 2020
inflation_rate(2000, 2020, "USD")
#> [1] 0.5030

# Annualised UK inflation from 1990 to 2020
inflation_rate(1990, 2020, "GBP", annualise = TRUE)
#> [1] 0.0248

Vectorised amounts

# Adjust multiple amounts at once
adjust_inflation(c(100, 500, 1000), 2000, "GBP", to_year = 2020)
#> [1]  161.56  807.80 1615.61

# Full precision (no rounding)
adjust_inflation(100, 2000, "USD", to_year = 2020, round = NULL)
#> [1] 150.303...

Metadata

# See all supported currencies
list_currencies()
#>    currency                      country cpi_start cpi_end deflator_start deflator_end
#> 1       GBP               United Kingdom      1960    2025           1960         2025
#> 2       AUD                    Australia      1960    2025           1960         2025
#> ...

Country names work too (case-insensitive)

adjust_inflation(12, 1963, "Australia")   #> 218.09
adjust_inflation(12, 1963, "switzerland") #> 48
adjust_real(500e9, 1990, "United Kingdom") #> 1263091626371

Data

All data is sourced from the World Bank Development Indicators and bundled inside the package. All indices are rescaled so that 2020 = 100.

Coverage is not uniform at the recent end. Every series runs to 2025 except US CPI, which the World Bank has not yet published beyond 2024, so adjust_inflation() with currency = "USD" rejects a 2025 target year and names 2024 as the limit. The US GDP deflator does reach 2025, so adjust_real() is unaffected. Brazil starts at 1990: rebasing to 2020 = 100 pushes the hyperinflation years before that below the resolution of the stored index, and those years are dropped rather than shipped as zeros.

CPI datasets (indicator: FP.CPI.TOTL)

GDP deflator datasets (indicator: NY.GDP.DEFL.ZS)

Macroeconomic quirks

• Tax shocks - Australia (GST, 2000) and Canada (GST, 1991) both saw one-time price level jumps that appear in the CPI data but are really structural tax changes. Comparisons spanning these years will reflect the tax shift, not just underlying inflation.
• Japan's deflation - Japan had near-zero or negative inflation from roughly 1995 to 2020. Adjustments within this window will be very small, and in some years prices actually fell.
• China's CPI coverage - World Bank CPI data for China begins in 1986. The GDP deflator series begins in 1960 but the early years span significant structural change. Both series are internationally comparable but may not capture the full experience of price changes during China's reform era.
• Euro proxy - The World Bank does not publish an aggregated Euro area series for either CPI or GDP deflator. Germany is used as a proxy for both, which reflects the monetary anchor of the Eurozone but will understate the inflation experience of southern European countries in the 1970s and 1980s.
• Annual figures only - All values are annual averages. Month-to-month volatility is smoothed out.

Why do my results differ slightly from other calculators?

Inflation adjustment requires converting 12 monthly CPI observations into a single yearly figure. The CPI in January vs December of the same year can differ by 1-2%, so how that conversion is done matters more than which tool you use.

• Annual vs monthly CPI. inflateR (and most online calculators like the Minneapolis Fed) uses the annual average CPI: the mean of all 12 monthly values for a year. The BLS's own calculator lets you pick specific months, which can shift results by 1-2% depending on your choice. This is the biggest source of differences between calculators.
• Index level vs percentage change. inflateR uses the World Bank's CPI index level (FP.CPI.TOTL), published rounded to 2 decimal places. Other tools may use the annual percentage change series (FP.CPI.TOTL.ZG), which retains more decimal places and is compounded year by year. Both come from the same underlying national CPI data. The rounding difference is tiny: $100,000 from 2020 to 2024 gives $121,200 with inflateR vs $121,204 with a compounding approach, a gap of $4 (0.003%).

Related packages

Issues

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

Keywords

inflation adjustment, CPI, consumer price index, GDP deflator, purchasing power, real prices, nominal to real, price index, cost of living, World Bank, historical prices, inflation rate, deflation, currency adjustment, international inflation, R package, macroeconomics, economics data