Use the formula("string") with felm() from the lfe package while also using fixed effects

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I'm trying to run a large regression formula that is created somewhere else as a long string. I also want to use "fixed effects" (individual specific intercepts).

Without fixed effects this works both in the lm() and in felm() functions:

library("lfe")
MyData <- data.frame(country = c("US","US","DE","DE"),
             y = rnorm(4),
             x = rnorm(4))

testformula <- "y ~ x"

lm(formula(testformula),
   data = MyData)

felm(formula(testformula),
     data = MyData)

There is also no problem with this kind of regression in felm() if I use country fixed effects:

felm(y ~ x | country,
     data = MyData)

However, when I try to combine both the formula() function and the fixed effects argument, I get an error:

felm(formula(testformula) | country ,
     data = MyData)

"Error in terms(formula(as.Formula(formula), rhs = 1), specials = "G") : 
Object 'country' not found"

I find this strange, separately, both of these arguments work. How can I use the formula() function in felm() and still work with the convenient fixed effects syntax of that function? I don't want to write the fixed effects into the formula because I want to rely on the within transformations of the lfe package.

p.s.: This works in plm() by the way so I'm guessing there is something odd in the felm() function or I input it badly.

library("plm")

plm(formula(testformula),
    data =  MyData,
    index = c("country"),
    model = "within",
    effect = "individual")
panel-data r
1 Answers

Since the fixed effects are part of the formula*, we can include them in the formula string.

fit1 <- felm(y ~ x | country, data=MyData)

testformula <- "y ~ x | country"
fit2 <- felm(formula(testformula), data=MyData)
fit2
#      x 
# 0.3382 

all.equal(fit1$coefficients, fit2$coefficients)
# [1] TRUE

*you can see this by the fact that function parameters in R are usually separated by commas

user_65740380
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