BOJ

Stefan Angrick

2022-01-04

The BOJ package provides an R interface to Bank of Japan statistics, specifically the flat files available on the BOJ Time-Series Data portal.

Import data

To import data, first load the package:

library("BOJ")

Next, run the get_boj_datasets() function to obtain a list of available data sets:

datasets <- get_boj_datasets()
datasets
## # A tibble: 17 × 3
##    desc                                    name     url                         
##    <chr>                                   <chr>    <chr>                       
##  1 "Corporate Goods Price Index (CGPI)"    cgpi_m_… https://www.stat-search.boj…
##  2 "Producer Price Index using chain-weig… cgpiren… https://www.stat-search.boj…
##  3 "Services Producer Price Index (SPPI)"  sppi_m_… https://www.stat-search.boj…
##  4 "Wholesale Services Price Index"        sppi_q_… https://www.stat-search.boj…
##  5 "Input-Output Price Index of the Manuf… iopi_m_… https://www.stat-search.boj…
##  6 "Flow of Funds"                         fof      https://www.stat-search.boj…
##  7 "Flow of Funds (with name of time-seri… fof2_en  https://www.stat-search.boj…
##  8 "TANKAN"                                co       https://www.stat-search.boj…
##  9 "TANKAN (Fixed Investment and Software… colease  https://www.stat-search.boj…
## 10 "Balance of Payments "                  bp_m_en  https://www.stat-search.boj…
## 11 "Regional Balance of Payments (quarter… regbp_q… https://www.stat-search.boj…
## 12 "International Investment Position (Qu… qiip_q_… https://www.stat-search.boj…
## 13 "International Investment Position (Ca… iip_cy_… https://www.stat-search.boj…
## 14 "BIS International Locational Banking … bis1-1_… https://www.stat-search.boj…
## 15 "BIS International Locational Banking … bis1-2_… https://www.stat-search.boj…
## 16 "BIS International Consolidated Bankin… bis2-1_… https://www.stat-search.boj…
## 17 "BIS International Consolidated Bankin… bis2-2_… https://www.stat-search.boj…

The function returns a tibble data frame listing the available data sets. The column url can be used as input for the function get_boj() which downloads, parses and imports the corresponding data.

To import monthly-frequency data on Japan’s Services Producer Price Index, run:

sppi <- get_boj(datasets$url[(datasets$name == "sppi_m_en")])
sppi
## # A tibble: 42,247 × 5
##    code              desc                  struc                 date  obs_value
##    <chr>             <chr>                 <chr>                 <chr>     <dbl>
##  1 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…      99.6
##  2 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…      99.7
##  3 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…     100. 
##  4 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…     100  
##  5 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…     100. 
##  6 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…     100  
##  7 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…     100. 
##  8 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…     100. 
##  9 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…      99.9
## 10 PRCS15_5200000000 Services Producer Pr… [Services Producer P… 2015…      99.9
## # … with 42,237 more rows

To plot the data using ggplot2, run the following:

library("dplyr")
library("ggplot2")
library("zoo")

sppi_plot <- subset(sppi, code %in% c("PRCS15_5200000000", "PRCS15_5200010001",
                                      "PRCS15_5200010002", "PRCS15_5200010003",
                                      "PRCS15_5200010004", "PRCS15_5200010005",
                                      "PRCS15_5200010006", "PRCS15_5200010007"))
sppi_plot <- mutate(sppi_plot, date = as.Date(as.yearmon(date, format = "%Y%m")))
sppi_plot <- mutate(sppi_plot, struc = gsub("^Major group/ ", "", struc))
sppi_plot <- subset(sppi_plot, !is.na(obs_value))

ggplot(sppi_plot, aes(x = date, y = obs_value)) +
  geom_line(aes(colour = struc)) +
  labs(x = "Date", y = "Services Producer Price Index (2015 base)") +
  theme(legend.title = element_blank())

Note that BOJ data sets come with a number of different time formats. The zoo package (e.g. as.yearmon()) should be able to parse most formats.

Note

This package is in no way officially related to or endorsed by the Bank of Japan. It was inspired by the BIS R package. Please don’t abuse the BOJ’s servers with unnecessary calls.