geks: GEKS index

Description

Calculate a generalized inter-temporal GEKS price index over a rolling window.

Usage

geks(f, r = 0)
tornqvist_geks(
  p,
  q,
  period,
  product,
  window = nlevels(period),
  n = window - 1L,
  na.rm = FALSE
)
fisher_geks(
  p,
  q,
  period,
  product,
  window = nlevels(period),
  n = window - 1L,
  na.rm = FALSE
)
walsh_geks(
  p,
  q,
  period,
  product,
  window = nlevels(period),
  n = window - 1L,
  na.rm = FALSE
)

Value

geks() returns a function:

function(p, q, period, product, window = nlevels(period), n =
         window - 1, na.rm = FALSE){...}

This calculates a period-over-period GEKS index with the desired index-number formula, returning a list for each window with a named-numeric vector of index values.

tornqvist_geks(), fisher_geks(), and walsh_geks() each return a list with a named numeric vector giving the value of the respective period-over-period GEKS index for each window.

Arguments

f: A price index function that uses information on both base and current-period prices and quantities, and satisfies the time-reversal test. Usually a Törnqvist, Fisher, or Walsh index.
r: A finite number giving the order of the generalized mean used to average price indexes over the rolling window. The default uses a geometric mean.
p: A numeric vector of prices, the same length as q.
q: A numeric vector of quantities, the same length as p.
period: A factor, or something that can be coerced into one, that gives the corresponding time period for each element in p and q. The ordering of time periods follows the levels of period to agree with cut().
product: A factor, or something that can be coerced into one, that gives the corresponding product identifier for each element in p and q.
window: A positive integer giving the length of the rolling window. The default is a window that encompasses all periods in period. Non-integers are truncated towards zero.
n: A positive integer giving the length of the index series for each window, starting from the end of the window. For example, if there are 13 periods in window, setting n = 1 gives the index for period 13. The default gives an index for each period in window. Non-integers are truncated towards zero.
na.rm: Passed to f to control if missing values are removed.

References

Balk, B. M. (2008). Price and Quantity Index Numbers. Cambridge University Press.

IMF, ILO, Eurostat, UNECE, OECD, and World Bank. (2020). Consumer Price Index Manual: Concepts and Methods. International Monetary Fund.

Ivancic, L., Diewert, W. E., and Fox, K. J. (2011). Scanner data, time aggregation and the construction of price indexes. Journal of Econometrics, 161(1): 24--35.

Examples

Run this code

price <- 1:10
quantity <- 10:1
period <- rep(1:5, 2)
product <- rep(letters[1:2], each = 5)

cumprod(tornqvist_geks(price, quantity, period, product)[[1]])

# Calculate the index over a rolling window

(tg <- tornqvist_geks(price, quantity, period, product, window = 3))

# Use a movement splice to combine the indexes in each window

splice_index(tg, 2)

# ... or use a mean splice

splice_index(tg)

#---- Missing data ----

quantity[2] <- NA

# Use all non-missing data

fisher_geks(price, quantity, period, product, na.rm = TRUE)

# Remove records with any missing data

fg <- geks(balanced(fisher_index))
fg(price, quantity, period, product, na.rm = TRUE)

#---- Make a Jevons GEKS index ----

jevons_geks <- geks(\(p1, p0, ..., na.rm) jevons_index(p1, p0, na.rm))
jevons_geks(price, quantity, period, product)