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i

Create, or interact variables with, factors

Description

Treat a variable as a factor, or interacts a variable with a factor. Values to be dropped/kept from the factor can be easily set. Note that to interact fixed-effects, this function should not be used: instead use directly the syntax fe1^fe2.

Usage

i(factor_var, var, ref, keep, bin, ref2, keep2, bin2, ...)

Arguments

`factor_var`	A vector (of any type) that will be treated as a factor. You can set references (i.e. exclude values for which to create dummies) with the `ref` argument.
`var`	A variable of the same length as `factor_var`. This variable will be interacted with the factor in `factor_var`. It can be numeric or factor-like. To force a numeric variable to be treated as a factor, you can add the `i.` prefix to a variable name. For instance take a numeric variable `x_num`: `i(x_fact, x_num)` will treat `x_num` as numeric while `i(x_fact, i.x_num)` will treat `x_num` as a factor (it's a shortcut to `as.factor(x_num)`).
`ref`	A vector of values to be taken as references from `factor_var`. Can also be a logical: if `TRUE`, then the first value of `factor_var` will be removed. If `ref` is a character vector, partial matching is applied to values; use "@" as the first character to enable regular expression matching. See examples.
`keep`	A vector of values to be kept from `factor_var` (all others are dropped). By default they should be values from `factor_var` and if `keep` is a character vector partial matching is applied. Use "@" as the first character to enable regular expression matching instead.
`bin`	A list of values to be grouped, a vector, or the special value `"bin::digit"`. To create a new value from old values, use `bin = list("new_value"=old_values)` with `old_values` a vector of existing values. It accepts regular expressions, but they must start with an `"@"`, like in `bin="@Aug\|Dec"`. The names of the list are the new names. If the new name is missing, the first value matched becomes the new name. Feeding in a vector is like using a list without name and only a single element. If the vector is numeric, you can use the special value `"bin::digit"` to group every `digit` element. For example if `x` represent years, using `bin="bin::2"` create bins of two years. Using `"!bin::digit"` groups every digit consecutive values starting from the first value. Using `"!!bin::digit"` is the same bu starting from the last value. In both cases, `x` is not required to be numeric.
`ref2`	A vector of values to be dropped from `var`. By default they should be values from `var` and if `ref2` is a character vector partial matching is applied. Use "@" as the first character to enable regular expression matching instead.
`keep2`	A vector of values to be kept from `var` (all others are dropped). By default they should be values from `var` and if `keep2` is a character vector partial matching is applied. Use "@" as the first character to enable regular expression matching instead.
`bin2`	A list or vector defining the binning of the second variable. See help for the argument `bin` for details (or look at the help of the function `bin`).
`...`	Not currently used.

Details

To interact fixed-effects, this function should not be used: instead use directly the syntax fe1^fe2 in the fixed-effects part of the formula. Please see the details and examples in the help page of feols.

Value

It returns a matrix with number of rows the length of factor_var. If there is no interacted variable or it is interacted with a numeric variable, the number of columns is equal to the number of cases contained in factor_var minus the reference(s). If the interacted variable is a factor, the number of columns is the number of combined cases between factor_var and var.

Author(s)

Laurent Berge

Examples

#
# Simple illustration
#

x = rep(letters[1:4], 3)[1:10]
y = rep(1:4, c(1, 2, 3, 4))

# interaction
data.frame(x, y, i(x, y, ref = TRUE))

# without interaction
data.frame(x, i(x, "b"))

# you can interact factors too
z = rep(c("e", "f", "g"), c(5, 3, 2))
data.frame(x, z, i(x, z))

# to force a numeric variable to be treated as a factor: use i.
data.frame(x, y, i(x, i.y))

#
# In fixest estimations
#

data(base_did)
# We interact the variable 'period' with the variable 'treat'
est_did = feols(y ~ x1 + i(period, treat, 5) | id + period, base_did)

# => plot only interactions with iplot
iplot(est_did)

# Using i() for factors
est_bis = feols(y ~ x1 + i(period, keep = 3:6) + i(period, treat, 5) | id, base_did)

# we plot the second set of variables created with i()
# => we need to use keep (otherwise only the first one is represented)
coefplot(est_bis, keep = "trea")

# => special treatment in etable
etable(est_bis, dict = c("6" = "six"))

#
# Interact two factors
#

# We use the i. prefix to consider week as a factor
data(airquality)
aq = airquality
aq$week = aq$Day %/% 7 + 1

# Interacting Month and week:
res_2F = feols(Ozone ~ Solar.R + i(Month, i.week), aq)

# Same but dropping the 5th Month and 1st week
res_2F_bis = feols(Ozone ~ Solar.R + i(Month, i.week, ref = 5, ref2 = 1), aq)

etable(res_2F, res_2F_bis)

#
# Binning
#

data(airquality)

feols(Ozone ~ i(Month, bin = "bin::2"), airquality)

feols(Ozone ~ i(Month, bin = list(summer = 7:9)), airquality)

fixest

Fast Fixed-Effects Estimations

v0.10.0

GPL-3

Authors

Laurent Berge [aut, cre], Sebastian Krantz [ctb], Grant McDermott [ctb] (<https://orcid.org/0000-0001-7883-8573>)

Initial release

i