geks: GEKS index

In gpindex: Generalized Price and Quantity Indexes

GEKS index

Description

Calculate an inter-temporal GEKS price index over a rolling window, as described in chapter 7 of Balk (2008), by Ivancic et al. (2011), and in chapter 10 of the CPI manual (2020).

Usage

geks(f)

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
)

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.
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.

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.

Note

Like back_period(), if multiple prices correspond to a period-product pair, then the back price at a point in time is always the first price for that product in the previous period. Unlike a bilateral index, however, duplicated period-product pairs can have more subtle implications for a multilateral index.

References

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

ILO, IMF, OECD, Eurostat, UN, and World Bank. (2020). Consumer Price Index Manual: Theory and Practice. 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.

See Also

GEKSIndex() in the indexNumR package for an implementation of the GEKS index with more options.

Other price-indexes: index_weights(), price_indexes

Examples

price <- 1:6
quantity <- 6:1
period <- rep(1:3, 2)
product <- rep(letters[1:2], each = 3)

tornqvist_geks(price, quantity, period, product)

tornqvist_geks(price, quantity, period, product, window = 2)

# 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)

gpindex documentation built on Nov. 15, 2023, 9:06 a.m.