IndexNumR

An R package for computation of index numbers

IndexNumR provides a set of functions for computing various bilateral and multilateral indices. It is designed to compute price or quantity indices over time. Bilateral indices include Laspeyres, Paasche, Fisher, Tornqvist, Sato-Vartia, Walsh, CES, geometric Laspeyres and geometric Paasche as well as elementary indices Dutot, Carli, Harmonic mean, CSWD and Jevons. All of these bilateral indices can be computed as period-on-period, fixed-base or chained.

Multilateral indices can be computed in the time series context using the GEKS methodology, and updating is provided via the window, movement, half or mean splice methods. The GEKS method is computed using either the Fisher or Tornqvist superlative index number methods.

The package also provides functions to compute measures of dissimilarity between time periods, which can be used to choose the linking period for chained indices.

A sample dataset is included called CES_sigma_2, which is a dataset containing prices and quantities on four products over twelve periods.

To install the latest Github version of the package, you will first need remotes installed,

install.packages("remotes")

then use the following R commands,

remotes::install_github("grahamjwhite/IndexNumR")  
library(IndexNumR)  

Or to include the vignette,

remotes::install_github("grahamjwhite/IndexNumR", build_vignettes = TRUE)  
library(IndexNumR) 

Examples

To estimate a simple chained Laspeyres price index using the CES_sigma_2 dataset,

priceIndex(CES_sigma_2,pvar = "prices",qvar = "quantities",pervar = "time",prodID = "prodID", indexMethod = "laspeyres", output = "chained")

A GEKS index with mean splicing and an 11 period window is estimated as follows,

GEKSIndex(CES_sigma_2, pvar = "prices", qvar = "quantities", pervar = "time", prodID = "prodID", indexMethod = "tornqvist", window=11, splice = "mean")

More examples are contained in the package vignette.

vignette("indexnumr", package = "IndexNumR")