fgrowth: Fast Growth Rates for Time Series and Panel Data

In collapse: Advanced and Fast Data Transformation

Fast Growth Rates for Time Series and Panel Data

Description

fgrowth is a S3 generic to compute (sequences of) suitably lagged / leaded, iterated and compounded growth rates, obtained with via the exact method of computation or through log differencing. By default growth rates are provided in percentage terms, but any scale factor can be applied. The growth operator G is a parsimonious wrapper around fgrowth, and also provides more flexibility when applied to data frames.

Usage

fgrowth(x, n = 1, diff = 1, ...)
      G(x, n = 1, diff = 1, ...)

## Default S3 method:
fgrowth(x, n = 1, diff = 1, g = NULL, t = NULL, fill = NA,
        logdiff = FALSE, scale = 100, power = 1, stubs = TRUE, ...)
## Default S3 method:
G(x, n = 1, diff = 1, g = NULL, t = NULL, fill = NA, logdiff = FALSE,
  scale = 100, power = 1, stubs = .op[["stub"]], ...)

## S3 method for class 'matrix'
fgrowth(x, n = 1, diff = 1, g = NULL, t = NULL, fill = NA,
        logdiff = FALSE, scale = 100, power = 1,
        stubs = length(n) + length(diff) > 2L, ...)
## S3 method for class 'matrix'
G(x, n = 1, diff = 1, g = NULL, t = NULL, fill = NA, logdiff = FALSE,
  scale = 100, power = 1, stubs = .op[["stub"]], ...)

## S3 method for class 'data.frame'
fgrowth(x, n = 1, diff = 1, g = NULL, t = NULL, fill = NA,
        logdiff = FALSE, scale = 100, power = 1,
        stubs = length(n) + length(diff) > 2L, ...)
## S3 method for class 'data.frame'
G(x, n = 1, diff = 1, by = NULL, t = NULL, cols = is.numeric,
  fill = NA, logdiff = FALSE, scale = 100, power = 1, stubs = .op[["stub"]],
  keep.ids = TRUE, ...)

# Methods for indexed data / compatibility with plm:

## S3 method for class 'pseries'
fgrowth(x, n = 1, diff = 1, fill = NA, logdiff = FALSE, scale = 100,
        power = 1, stubs = length(n) + length(diff) > 2L, shift = "time", ...)
## S3 method for class 'pseries'
G(x, n = 1, diff = 1, fill = NA, logdiff = FALSE, scale = 100,
  power = 1, stubs = .op[["stub"]], shift = "time", ...)

## S3 method for class 'pdata.frame'
fgrowth(x, n = 1, diff = 1, fill = NA, logdiff = FALSE, scale = 100,
        power = 1, stubs = length(n) + length(diff) > 2L, shift = "time", ...)
## S3 method for class 'pdata.frame'
G(x, n = 1, diff = 1, cols = is.numeric, fill = NA, logdiff = FALSE,
  scale = 100, power = 1, stubs = .op[["stub"]], shift = "time", keep.ids = TRUE, ...)

# Methods for grouped data frame / compatibility with dplyr:

## S3 method for class 'grouped_df'
fgrowth(x, n = 1, diff = 1, t = NULL, fill = NA, logdiff = FALSE,
        scale = 100, power = 1, stubs = length(n) + length(diff) > 2L,
        keep.ids = TRUE, ...)
## S3 method for class 'grouped_df'
G(x, n = 1, diff = 1, t = NULL, fill = NA, logdiff = FALSE,
  scale = 100, power = 1, stubs = .op[["stub"]], keep.ids = TRUE, ...)

Arguments

x	a numeric vector / time series, (time series) matrix, data frame, 'indexed_series' ('pseries'), 'indexed_frame' ('pdata.frame') or grouped data frame ('grouped_df').
n	integer. A vector indicating the number of lags or leads.
diff	integer. A vector of integers > 1 indicating the order of taking growth rates, e.g. diff = 2 means computing the growth rate of the growth rate.
g	a factor, GRP object, or atomic vector / list of vectors (internally grouped with group) used to group x. Note that without t, all values in a group need to be consecutive and in the right order. See Details of flag.
by	data.frame method: Same as g, but also allows one- or two-sided formulas i.e. ~ group1 or var1 + var2 ~ group1 + group2. See Examples.
t	a time vector or list of vectors. See flag.
cols	data.frame method: Select columns to compute growth rates using a function, column names, indices or a logical vector. Default: All numeric variables. Note: cols is ignored if a two-sided formula is passed to by.
fill	value to insert when vectors are shifted. Default is NA.
logdiff	logical. Compute log-difference growth rates instead of exact growth rates. See Details.
scale	logical. Scale factor post-applied to growth rates, default is 100 which gives growth rates in percentage terms. See Details.
power	numeric. Apply a power to annualize or compound growth rates e.g. fgrowth(AirPassengers, 12, power = 1/12) is equivalent to ((AirPassengers/flag(AirPassengers, 12))^(1/12)-1)*100.
stubs	logical. TRUE (default) will rename all computed columns by adding a prefix "LnGdiff." / "FnGdiff.", or "LnDlogdiff." / "FnDlogdiff." if logdiff = TRUE.
shift	pseries / pdata.frame methods: character. "time" or "row". See flag for details.
keep.ids	data.frame / pdata.frame / grouped_df methods: Logical. Drop all identifiers from the output (which includes all variables passed to by or t using formulas). Note: For 'grouped_df' / 'pdata.frame' identifiers are dropped, but the "groups" / "index" attributes are kept.
...	arguments to be passed to or from other methods.

Details

fgrowth/G by default computes exact growth rates using repeat(diff) ((x[i]/x[i-n])^power - 1)*scale, so for diff > 1 it computes growth rate of growth rates. If logdiff = TRUE, approximate growth rates are computed using log(x[i]/x[i-n])*scale for diff = 1 and repeat(diff-1) x[i] - x[i-n] thereafter (usually diff = 1 for log-differencing). For further details see the help pages of fdiff and flag.

Value

x where the growth rate was taken diff times using lags n of itself, scaled by scale. Computations can be grouped by g/by and/or ordered by t. See Details and Examples.

See Also

flag/L/F, fdiff/D/Dlog, Time Series and Panel Series, Collapse Overview

Examples

## Simple Time Series: AirPassengers
G(AirPassengers)                      # Growth rate, same as fgrowth(AirPassengers)
G(AirPassengers, logdiff = TRUE)      # Log-difference
G(AirPassengers, 1, 2)                # Growth rate of growth rate
G(AirPassengers, 12)                  # Seasonal growth rate (data is monthly)

head(G(AirPassengers, -2:2, 1:3))     # Sequence of leaded/lagged and iterated growth rates

# let's do some visual analysis
plot(G(AirPassengers, c(0, 1, 12)))
plot(stl(window(G(AirPassengers, 12), # Taking seasonal growth rate removes most seasonal variation
                1950), "periodic"))


## Time Series Matrix of 4 EU Stock Market Indicators, recorded 260 days per year
plot(G(EuStockMarkets,c(0,260)))                    # Plot series and annual growth rates
summary(lm(L260G1.DAX ~., G(EuStockMarkets,260)))   # Annual growth rate of DAX regressed on the
                                                    # growth rates of the other indicators

## World Development Panel Data
head(fgrowth(num_vars(wlddev), 1, 1,                    # Computes growth rates of numeric variables
             wlddev$country, wlddev$year))              # fgrowth requires external inputs..
head(G(wlddev, 1, 1, ~country, ~year))                  # Growth of numeric variables, id's attached
head(G(wlddev, 1, 1, ~country))                         # Without t: Works because data is ordered
head(G(wlddev, 1, 1, PCGDP + LIFEEX ~ country, ~year))  # Growth of GDP per Capita & Life Expectancy
head(G(wlddev, 0:1, 1, ~ country, ~year, cols = 9:10))  # Same, also retaining original series
head(G(wlddev, 0:1, 1, ~ country, ~year, 9:10,          # Dropping id columns
       keep.ids = FALSE))

collapse documentation built on Nov. 13, 2023, 1:08 a.m.