Predicts the inflation of hourly rates of pay, between two financial years.
wage_inflator(wage = 1, from_fy = NULL, to_fy = NULL,
useABSConnection = FALSE, allow.projection = TRUE,
forecast.series = c("mean", "upper", "lower", "custom"),
forecast.level = 95, wage.series = NULL,
accelerate.above = 100000L)
The amount to be inflated (1 by default).
(character) a character vector with each element in the form "2012-13" representing the financial years between which the CPI inflator is desired.
If both from_fy
and to_fy
are NULL
(the default), from_fy
is set to the previous financial year and to_fy
to the current financial year, with a warning. Setting only one is an error.
Should the function connect with ABS.Stat via an SDMX connection? If FALSE
(the default), a pre-prepared index table is used. This is much faster and more reliable (in terms of errors), though of course relies on the package maintainer to keep the tables up-to-date.
If the SDMX connection fails, a message is emitted (not a warning) and
the function contines as if useABSConnection = FALSE
.
The internal data was updated on 2019-05-20 to 2019-Q1.
If set to TRUE
the forecast
package is used to project forward, if required.
Whether to use the forecast mean, or the upper or lower boundaries of the prediction intervals. A fourth option custom
allows manual forecasts to be set.
The prediction interval to be used if forecast.series
is upper
or lower
.
If forecast.series = 'custom'
, how future years should be inflated.
The future wage series can be provided in two ways:
(1) a single value, to be the assumed rate of wage inflation in years beyond the known series, or
(2) a data.table
with two variables, fy_year
and r
. If (2),
the variable fy_year
must be a vector of all financial years after the last financial year in the (known) wage series and the latest to_fy
inclusive.
The variable r
consists of rates of wage growth assumed in each fy_year
.
An integer setting the threshold for 'acceleration'.
When the maximum length of the arguments exceeds this value, calculate each unique value individually
then combine. Set to 100,000 as a rule of thumb beyond which calculation speeds benefit
dramatically. Can be set to Inf
to disable acceleration.
The wage inflation between the two years.
# NOT RUN {
# Wage inflation
wage_inflator(from_fy = "2013-14", to_fy = "2014-15")
# Custom wage inflation
wage_inflator(from_fy = "2016-17",
to_fy = "2017-18",
forecast.series = "custom",
wage.series = 0.05)
# }
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