Description

Download and Tidy Data from the Reserve Bank of Australia.

Description

Download up-to-date data from the Reserve Bank of Australia in a tidy data frame. Package includes functions to download current and historical statistical tables (<https://www.rba.gov.au/statistics/tables/>) and forecasts (<https://www.rba.gov.au/publications/smp/forecasts-archive.html>). Data includes a broad range of Australian macroeconomic and financial time series.

README.md

cran.r-project.org

readrba

Get data from the Reserve Bank of Australia in a tidy tibble!

Installation

Install from CRAN using:

install.packages("readrba")

Or install the development version from GitHub:

remotes::install_github("mattcowgill/readrba")

Examples

library(ggplot2)
library(dplyr)
library(readrba)

Quick examples

With just a few lines of code, you can get a data series from the RBA and visualise it!

Here’s the unemployment rate:

unemp_rate <- read_rba(series_id = "GLFSURSA") 

unemp_rate %>%
  ggplot(aes(x = date, y = value)) +
  geom_line() +
  theme_minimal() +
  labs(title = "Unemployment rate (actual)")

And you can also easily get the RBA’s public forecasts - from 1990 to present - and visualise those. Here’s every public forecast of the unemployment rate the RBA has made over the past three decades:

unemp_forecasts <- rba_forecasts() %>%
  filter(series == "unemp_rate")

unemp_forecasts %>%
  ggplot(aes(x = date, 
             y = value, 
             group = forecast_date, 
             col = forecast_date)) +
  geom_line() +
  theme_minimal() +
  labs(title = "Unemployment rate (RBA forecasts)")

Reading RBA data

There primary function in {readrba} is read_rba().

Here’s how you fetch the current version of a single RBA statistical table: table G1, consumer price inflation using read_rba():

cpi_table <- read_rba(table_no = "g1")

The object returned by read_rba() is a tidy tibble (ie. in ‘long’ format):

head(cpi_table)
#> # A tibble: 6 × 11
#>   date       series          value frequency series_type units source pub_date  
#>   <date>     <chr>           <dbl> <chr>     <chr>       <chr> <chr>  <date>    
#> 1 1922-06-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2024-08-01
#> 2 1922-09-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2024-08-01
#> 3 1922-12-31 Consumer price…   2.7 Quarterly Original    Inde… ABS /… 2024-08-01
#> 4 1923-03-31 Consumer price…   2.7 Quarterly Original    Inde… ABS /… 2024-08-01
#> 5 1923-06-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2024-08-01
#> 6 1923-09-30 Consumer price…   2.9 Quarterly Original    Inde… ABS /… 2024-08-01
#> # ℹ 3 more variables: series_id <chr>, description <chr>, table_title <chr>

You can also request multiple tables. They’ll be returned together as one tidy tibble:

rba_data <- read_rba(table_no = c("a1", "g1"))

head(rba_data)
#> # A tibble: 6 × 11
#>   date       series          value frequency series_type units source pub_date  
#>   <date>     <chr>           <dbl> <chr>     <chr>       <chr> <chr>  <date>    
#> 1 2013-07-03 Australian dol… 37899 Weekly    Original    $ mi… RBA    2024-08-16
#> 2 2013-07-10 Australian dol… 35106 Weekly    Original    $ mi… RBA    2024-08-16
#> 3 2013-07-17 Australian dol… 32090 Weekly    Original    $ mi… RBA    2024-08-16
#> 4 2013-07-24 Australian dol… 39592 Weekly    Original    $ mi… RBA    2024-08-16
#> 5 2013-07-31 Australian dol… 41286 Weekly    Original    $ mi… RBA    2024-08-16
#> 6 2013-08-07 Australian dol… 37974 Weekly    Original    $ mi… RBA    2024-08-16
#> # ℹ 3 more variables: series_id <chr>, description <chr>, table_title <chr>


unique(rba_data$table_title)
#> [1] "A1 Reserve Bank Of Australia - Balance Sheet"
#> [2] "G1 Consumer Price Inflation"

You can also retrieve data based on the unique RBA time series identifier(s). For example, to getch the consumer price index series only:

cpi_series <- read_rba(series_id = "GCPIAG")
head(cpi_series)
#> # A tibble: 6 × 11
#>   date       series          value frequency series_type units source pub_date  
#>   <date>     <chr>           <dbl> <chr>     <chr>       <chr> <chr>  <date>    
#> 1 1922-06-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2024-08-01
#> 2 1922-09-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2024-08-01
#> 3 1922-12-31 Consumer price…   2.7 Quarterly Original    Inde… ABS /… 2024-08-01
#> 4 1923-03-31 Consumer price…   2.7 Quarterly Original    Inde… ABS /… 2024-08-01
#> 5 1923-06-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2024-08-01
#> 6 1923-09-30 Consumer price…   2.9 Quarterly Original    Inde… ABS /… 2024-08-01
#> # ℹ 3 more variables: series_id <chr>, description <chr>, table_title <chr>

unique(cpi_series$series_id)
#> [1] "GCPIAG"

The convenience function read_rba_seriesid() is a wrapper around read_rba(). This means read_rba_seriesid("GCPIAG") is equivalent to read_rba(series_id = "GCPIAG").

By default, read_rba() fetches the current version of whatever table you request. You can specify the historical version of a table, if it’s available, using the cur_hist argument:


hist_a11 <- read_rba(table_no = "a1.1", cur_hist = "historical")

head(hist_a11)
#> # A tibble: 6 × 11
#>   date       series          value frequency series_type units source pub_date  
#>   <date>     <chr>           <dbl> <chr>     <chr>       <chr> <chr>  <date>    
#> 1 1994-06-01 Australian dol… 13680 Weekly    Original    $ mi… RBA    2023-05-05
#> 2 1994-06-08 Australian dol… 13055 Weekly    Original    $ mi… RBA    2023-05-05
#> 3 1994-06-15 Australian dol… 13086 Weekly    Original    $ mi… RBA    2023-05-05
#> 4 1994-06-22 Australian dol… 12802 Weekly    Original    $ mi… RBA    2023-05-05
#> 5 1994-06-29 Australian dol… 13563 Weekly    Original    $ mi… RBA    2023-05-05
#> 6 1994-07-06 Australian dol… 12179 Weekly    Original    $ mi… RBA    2023-05-05
#> # ℹ 3 more variables: series_id <chr>, description <chr>, table_title <chr>

Browsing RBA data

Two functions are provided to help you find the table number or series ID you need. These are browse_rba_tables() and browse_rba_series(). Each returns a tibble with information about the available RBA data.

browse_rba_tables()
#> # A tibble: 127 × 5
#>    title                              no    url   current_or_historical readable
#>    <chr>                              <chr> <chr> <chr>                 <lgl>   
#>  1 RBA Balance Sheet                  A1    http… current               TRUE    
#>  2 Monetary Policy Changes            A2    http… current               TRUE    
#>  3 Monetary Policy Operations – Curr… A3    http… current               TRUE    
#>  4 Holdings of Australian Government… A3.1  http… current               TRUE    
#>  5 Securities Lending Repurchase and… A3.2  http… current               TRUE    
#>  6 Foreign Exchange Transactions and… A4    http… current               TRUE    
#>  7 Daily Foreign Exchange Market Int… A5    http… current               TRUE    
#>  8 Banknotes on Issue by Denomination A6    http… current               TRUE    
#>  9 Detected Australian Counterfeits … A7    http… current               TRUE    
#> 10 Assets of Financial Institutions   B1    http… current               TRUE    
#> # ℹ 117 more rows

browse_rba_series()
#> # A tibble: 4,369 × 8
#>    table_no series        series_id series_type table_title cur_hist description
#>    <chr>    <chr>         <chr>     <chr>       <chr>       <chr>    <chr>      
#>  1 A1       Australian G… ARBALDOG… Original    A1 Reserve… current  Australian…
#>  2 A1       Australian d… ARBAAASTW Original    A1 Reserve… current  Australian…
#>  3 A1       Australian d… ARBAAASTW Original    A1 Reserve… histori… Australian…
#>  4 A1       Capital and … ARBALCRFW Original    A1 Reserve… current  Capital an…
#>  5 A1       Capital and … ARBALCRFW Original    A1 Reserve… histori… Capital an…
#>  6 A1       Deposits (ex… ARBALDEPW Original    A1 Reserve… histori… Deposits (…
#>  7 A1       Deposits of … ARBALDOO… Original    A1 Reserve… current  Deposits o…
#>  8 A1       Exchange set… ARBALESBW Original    A1 Reserve… current  Exchange s…
#>  9 A1       Exchange set… ARBALESBW Original    A1 Reserve… histori… Exchange s…
#> 10 A1       Gold and for… ARBAAGFXW Original    A1 Reserve… current  Gold and f…
#> # ℹ 4,359 more rows
#> # ℹ 1 more variable: frequency <chr>

You can specify a search string to filter the tables or series, as in:

browse_rba_tables("inflation")
#> # A tibble: 3 × 5
#>   title                               no    url   current_or_historical readable
#>   <chr>                               <chr> <chr> <chr>                 <lgl>   
#> 1 Consumer Price Inflation            G1    http… current               TRUE    
#> 2 Consumer Price Inflation – Expendi… G2    http… current               TRUE    
#> 3 Inflation Expectations              G3    http… current               TRUE

RBA forecasts

The function rba_forecasts() provides easy access to all the RBA’s public forecasts of key economic variables since 1990. The function scrapes the RBA website to obtain the latest Statement on Monetary Policy forecasts.

rba_forecasts()
#> # A tibble: 7,070 × 8
#>    series_desc       forecast_date notes source value date       year_qtr series
#>    <chr>             <date>        <chr> <chr>  <dbl> <date>        <dbl> <chr> 
#>  1 CPI - 4 quarter … 1990-03-01    <NA>  JEFG     8.6 1990-03-01    1990. cpi_a…
#>  2 CPI - 4 quarter … 1990-03-01    <NA>  JEFG     7.6 1990-06-01    1990. cpi_a…
#>  3 CPI - 4 quarter … 1990-03-01    <NA>  JEFG     6.5 1990-09-01    1990. cpi_a…
#>  4 CPI - 4 quarter … 1990-03-01    <NA>  JEFG     6   1990-12-01    1990. cpi_a…
#>  5 CPI - 4 quarter … 1990-03-01    <NA>  JEFG     5.9 1991-03-01    1991. cpi_a…
#>  6 CPI - 4 quarter … 1990-03-01    <NA>  JEFG     6.2 1991-06-01    1991. cpi_a…
#>  7 Unemployment rate 1990-03-01    <NA>  JEFG     5.9 1989-12-01    1989. unemp…
#>  8 Unemployment rate 1990-03-01    <NA>  JEFG     6.3 1990-03-01    1990. unemp…
#>  9 Unemployment rate 1990-03-01    <NA>  JEFG     6.5 1990-06-01    1990. unemp…
#> 10 Unemployment rate 1990-03-01    <NA>  JEFG     6.7 1990-09-01    1990. unemp…
#> # ℹ 7,060 more rows

If you just want the latest forecasts, you can request them:

rba_forecasts(all_or_latest = "latest")
#> # A tibble: 148 × 8
#>    forecast_date date       series       value series_desc source notes year_qtr
#>    <date>        <date>     <chr>        <dbl> <chr>       <chr>  <chr>    <dbl>
#>  1 2024-08-01    2024-06-01 aena_change    6.6 Nominal (n… ABS (… Year…    2024.
#>  2 2024-08-01    2024-12-01 aena_change    3.8 Nominal (n… ABS (… Year…    2024.
#>  3 2024-08-01    2025-06-01 aena_change    4.3 Nominal (n… ABS (… Year…    2025.
#>  4 2024-08-01    2025-12-01 aena_change    4.1 Nominal (n… ABS (… Year…    2025.
#>  5 2024-08-01    2026-06-01 aena_change    4.1 Nominal (n… ABS (… Year…    2026.
#>  6 2024-08-01    2026-12-01 aena_change    3.6 Nominal (n… ABS (… Year…    2026.
#>  7 2024-08-01    2024-06-01 business_in…   1.4 Business i… ABS (… Year…    2024.
#>  8 2024-08-01    2024-12-01 business_in…   0.1 Business i… ABS (… Year…    2024.
#>  9 2024-08-01    2025-06-01 business_in…   2.2 Business i… ABS (… Year…    2025.
#> 10 2024-08-01    2025-12-01 business_in…   2.7 Business i… ABS (… Year…    2025.
#> # ℹ 138 more rows

Data availability

The read_rba() function is able to import most tables on the Statistical Tables page of the RBA website. These are the tables that are downloaded when you use read_rba(cur_hist = "current"), the default.

read_rba() can also download many of the tables on the Historical Data page of the RBA website. To get these, specify cur_hist = "historical" in read_rba().

Historical exchange rate tables

The historical exchange rate tables do not have table numbers on the RBA website. They can still be downloaded, using the following table numbers:

Table title	table_no
Exchange Rates – Daily – 1983 to 1986	ex_daily_8386
Exchange Rates – Daily – 1987 to 1990	ex_daily_8790
Exchange Rates – Daily – 1991 to 1994	ex_daily_9194
Exchange Rates – Daily – 1995 to 1998	ex_daily_9598
Exchange Rates – Daily – 1999 to 2002	ex_daily_9902
Exchange Rates – Daily – 2003 to 2006	ex_daily_0306
Exchange Rates – Daily – 2007 to 2009	ex_daily_0709
Exchange Rates – Daily – 2010 to 2013	ex_daily_1013
Exchange Rates – Daily – 2014 to 2017	ex_daily_1417
Exchange Rates – Daily – 2018 to 2022	ex_daily_1822
Exchange Rates – Daily – 2023 to Current	ex_daily_23cur
Exchange Rates – Monthly – January 2010 to latest complete month of current year	ex_monthly_10cur
Exchange Rates – Monthly – July 1969 to December 2009	ex_monthly_6909

Non-standard tables

read_rba() is currently only able to import RBA statistical tables that are formatted in a (more or less) standard way. Some are formatted in a non-standard way, either because they’re distributions rather than time series, or because they’re particularly old.

Tables that are not able to be downloaded are:

Table title	table_no	current_or_historical
Household Balance Sheets – Distribution	E3	current
Household Gearing – Distribution	E4	current
Household Financial Assets – Distribution	E5	current
Household Non-Financial Assets – Distribution	E6	current
Household Debt – Distribution	E7	current
Open Market Operations – 2012 to 2013	A3	historical
Open Market Operations – 2009 to 2011	A3	historical
Open Market Operations – 2003 to 2008	A3	historical
Individual Banks’ Assets – 1991–1992 to 1997–1998	J1	historical
Individual Banks’ Liabilities – 1991–1992 to 1997–1998	J2	historical
Treasury Note Tenders - 1989–2006	E4	historical
Treasury Bond Tenders – 1982–2006	E5	historical
Treasury Bond Tenders – Amount Allotted, by Years to Maturity – 1982–2006	E5	historical
Treasury Bond Switch Tenders – 2008	E6	historical
Treasury Capital Indexed Bonds – 1985–2006	E7	historical
Indicative Mid Rates of Australian Government Securities – 1992 to 2008	F16	historical
Indicative Mid Rates of Australian Government Securities – 2009 to 2013	F16	historical
Zero-coupon Interest Rates – Analytical Series – 1992 to 2008	F17	historical

Resolving network issues by manually setting the download method

Certain corporate networks restrict your ability to download files in an R session. On some of these networks, the "wininet" method must be used when downloading files. Users can specify the method that will be used to download files by setting the "R_READRBA_DL_METHOD" environment variable.

For example, the following code sets the environment variable for your current session:

Sys.setenv("R_READRBA_DL_METHOD" = "wininet")

You can add "R_READRBA_DL_METHOD" to your .Rprofile to have this persist across sessions.

If you have other issues using {readrba} in your corporate environment, I would appreciate you opening an issue on GitHub.

Issues and contributions

I welcome any feature requests or bug reports. The best way is to file a GitHub issue.

I would welcome contributions to the package. Please start by filing an issue, outlining the bug you intend to fix or functionality you intend to add or modify.

Disclaimer

This package is not affiliated with or endorsed by the Reserve Bank of Australia. All data is provided subject to any conditions and restrictions set out on the RBA website.

r-readrba

readrba

Installation

Examples

Quick examples

Reading RBA data

Browsing RBA data

RBA forecasts

Data availability

Historical exchange rate tables

Non-standard tables

Resolving network issues by manually setting the download method

Issues and contributions

Disclaimer

Version

License

Status

Source

Homepage

Platforms (77)

readrba

Installation

Examples

Quick examples

Reading RBA data

Browsing RBA data

RBA forecasts

Data availability

Historical exchange rate tables

Non-standard tables

Resolving network issues by manually setting the download method

Issues and contributions

Disclaimer

Version

License

Status

Source

Homepage

Platforms77 (77)

Platforms (77)