grattan (version 1.5.2.5)

lf_inflator: Labour force inflators

Description

Labour force inflators

Usage

lf_inflator_fy(labour_force = 1, from_fy = "2012-13", to_fy,
  useABSConnection = FALSE, allow.projection = TRUE, use.month = 1L,
  forecast.series = c("mean", "upper", "lower", "custom"),
  forecast.level = 95, lf.series = NULL)
lf_inflator(labour_force = 1, from_date = "2013-06-30", to_date,
  useABSConnection = FALSE)

Arguments

labour_force

A numeric vector.

from_fy

Financial year of labour_force.

to_fy

Financial year for which the labour force is predicted.

useABSConnection

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. The internal data was updated on 2017-08-16.

allow.projection

Logical. Should projections be allowed?

use.month

An integer (corresponding to the output of data.table::month) representing the month of the series used for the inflation.

forecast.series

Whether to use the forecast mean, or the upper or lower boundaries of the prediction intervals.

forecast.level

The prediction interval to be used if forecast.series is upper or lower.

lf.series

If forecast.series = 'custom', a data.table with two variables, fy_year and r. The variable fy_year consists of all financial years between the last financial year in the (known) labour force series and to_fy inclusive. The variable r consists of rates of labour force growth assumed in each fy_year, which must be 1 in the first year (to connect with the original labour force series).

from_date

The date of labour_force.

to_date

Dates as a character vector.

Value

The relative labour force between to_date and for_date or to_fy and from_fy, multiplied by labour_force.

Details

lf_inflator is used on dates. The underlying data series is available every month.

Examples

# NOT RUN {
lf_inflator_fy(labour_force = 1, from_fy = "2012-13", to_fy = "2013-14")

library(data.table)
# Custom 1% growth over 2017-18 -> 2018.19
lf_inflator_fy(from_fy = "2017-18",
               to_fy = "2018-19",
               forecast.series = "custom", 
               lf.series = data.table(fy_year = c("2017-18", "2018-19"),
                                      r = c(0, 0.01)))
# }
# NOT RUN {
lf_inflator(labour_force = 1, from_date = "2013-06-30", to_date = "2014-06-30")
# }