Working with Index Numbers (original) (raw)

IndexNumberTools intends to ease the everyday work of users and producers of index numbers by providing functionalities like chain-linking, base shifting or computing pyp indices.

Installation

Getting started

We’ll work through an example using the Spanish GDP in current prices, which is preloaded as gdp_current, and the chain-linked volume (index), gdp_volume.

We can easily re-reference the volume series with [change_ref_year()](reference/change%5Fref%5Fyear.html).1

#> Time Series:
#> Start = 2008 
#> End = 2022 
#> Frequency = 1 
#>           2020      2010
#> 2008 104.90885 103.81798
#> 2009 100.95573  99.90596
#> 2010 101.05075 100.00000
#> 2011 100.40412  99.36010
#> 2012  97.52742  96.51331
#> 2013  96.13535  95.13571
#> 2014  97.59707  96.58224
#> 2015 101.56035 100.50430
#> 2016 104.52100 103.43417
#> 2017 107.54800 106.42969
#> 2018 110.12422 108.97913
#> 2019 112.28397 111.11642
#> 2020 100.00000  98.96018
#> 2021 106.68315 105.57383
#> 2022 113.27545 112.09758

We can also get the series at previous year prices from gdp_volume with [get_pyp()](reference/get%5Fpyp.html).2

Multiplying the volume series by the mean of the current prices series at the reference year (2020), we obtain the GDP in (chain-linked) constant prices.

ref_year_mean <- window(gdp_current,start = c(2020,1), end = c(2020,4)) |> mean()
gdp_constant <- ref_year_mean * gdp_volume / 100

By dividing the GDP in current prices by the GDP in constant prices, we derive the chain-linked implicit deflator of the GDP.

gdp_deflator <- gdp_current / gdp_constant * 100

Using [get_v_index()](reference/get%5Fv%5Findex.html) and chain-linking the result with [get_chain_linked()](reference/get%5Fchain%5Flinked.html), we get the chain-linked value indices.

Then, we can verify the identity V=P⋅QV = P\cdot Q, that is, the value index must equal the product of the price and volume indices.

dplyr::near(gdp_value, gdp_deflator * gdp_volume / 100) |> all()
#> [1] TRUE