R Under development (unstable) (2024-02-26 r85990 ucrt) -- "Unsuffered Consequences"
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> library(lfe)
Loading required package: Matrix
> options(lfe.threads = 1, digits = 5, warn = 1)
> set.seed(6320)
> x <- rnorm(1000, mean = 200)
> x2 <- rnorm(length(x))
> x3 <- rexp(length(x))
> ## create individual and firm
> id <- factor(sample(200, length(x), replace = TRUE))
> firm <- factor(sample(200, length(x), replace = TRUE))
> shoe <- factor(sample(200, length(x), replace = TRUE))
> shirt <- factor(sample(200, length(x), replace = TRUE))
> ## effects
> id.eff <- rnorm(nlevels(id))
> firm.eff <- rnorm(nlevels(firm))
> shoe.eff <- rnorm(nlevels(shoe))
> shirt.eff <- rnorm(nlevels(shirt))
> ## left hand side
> y <- x + 0.25 * x2 + 0.5 * x3 + id.eff[id] + firm.eff[firm] + shoe.eff[shoe] + shirt.eff[shirt] + rnorm(length(x))
> 
> ## estimate
> est <- felm(y ~ x + x2 + x3 | id + firm + shoe + shirt)
> cat("Components:", nlevels(est$cfactor), "largest:", sum(est$cfactor == "1"), "\n")
Components: 1 largest: 1000 
> ## extract the group fixed effects
> ## verify that id and firm coefficients are 1
> opt <- options(scipen = 8, warn = 1)
> 
> for (ef in c("ln", "ref", "zm", "zm2")) {
+   fe <- getfe(est, ef = ef)
+   ## merge back
+ 
+   ideff <- fe[paste("id", id, sep = "."), "effect"]
+   firmeff <- fe[paste("firm", firm, sep = "."), "effect"]
+   shoeeff <- fe[paste("shoe", shoe, sep = "."), "effect"]
+   shirteff <- fe[paste("shirt", shirt, sep = "."), "effect"]
+   if (ef %in% c("zm", "zm2")) {
+     icpt <- fe[paste("icpt", 1:nlevels(est$cfactor), sep = "."), "effect"][est$cfactor]
+     print(summary(lm(y ~ x + x2 + x3 + ideff + firmeff + shoeeff + shirteff + icpt - 1), digits = 8))
+   } else {
+     print(summary(lm(y ~ x + x2 + x3 + ideff + firmeff + shoeeff + shirteff - 1), digits = 8))
+   }
+ }
Warning in is.estimable(ef, obj$fe) :
  non-estimable function, largest error 0.02 in coordinate 35 ("id.35")
Warning in getfe.kaczmarz(obj, se, ef = ef, bN = bN, robust = robust, cluster = cluster,  :
  Supplied function seems non-estimable

Call:
lm(formula = y ~ x + x2 + x3 + ideff + firmeff + shoeeff + shirteff - 
    1)

Residuals:
   Min     1Q Median     3Q    Max 
-1.581 -0.270  0.000  0.278  1.752 

Coefficients:
         Estimate Std. Error t value Pr(>|t|)    
x        1.036709   0.000257  4036.0   <2e-16 ***
x2       0.244033   0.014252    17.1   <2e-16 ***
x3       0.530698   0.014396    36.9   <2e-16 ***
ideff    1.000000   0.010495    95.3   <2e-16 ***
firmeff  1.000000   0.010924    91.5   <2e-16 ***
shoeeff  1.000000   0.010992    91.0   <2e-16 ***
shirteff 1.000000   0.011527    86.8   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.441 on 993 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.96e+07 on 7 and 993 DF,  p-value: <2e-16


Call:
lm(formula = y ~ x + x2 + x3 + ideff + firmeff + shoeeff + shirteff - 
    1)

Residuals:
   Min     1Q Median     3Q    Max 
-1.581 -0.270  0.000  0.278  1.752 

Coefficients:
         Estimate Std. Error t value Pr(>|t|)    
x        1.036709   0.000381  2718.6   <2e-16 ***
x2       0.244033   0.014252    17.1   <2e-16 ***
x3       0.530698   0.014396    36.9   <2e-16 ***
ideff    1.000000   0.010489    95.3   <2e-16 ***
firmeff  1.000000   0.010925    91.5   <2e-16 ***
shoeeff  1.000000   0.010992    91.0   <2e-16 ***
shirteff 1.000000   0.011527    86.8   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.441 on 993 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.96e+07 on 7 and 993 DF,  p-value: <2e-16


Call:
lm(formula = y ~ x + x2 + x3 + ideff + firmeff + shoeeff + shirteff + 
    icpt - 1)

Residuals:
   Min     1Q Median     3Q    Max 
-1.581 -0.270  0.000  0.278  1.752 

Coefficients:
         Estimate Std. Error t value Pr(>|t|)    
x          1.0367     0.0145   71.58   <2e-16 ***
x2         0.2440     0.0143   17.11   <2e-16 ***
x3         0.5307     0.0144   36.85   <2e-16 ***
ideff      1.0000     0.0105   95.21   <2e-16 ***
firmeff    1.0000     0.0109   91.49   <2e-16 ***
shoeeff    1.0000     0.0110   90.92   <2e-16 ***
shirteff   1.0000     0.0115   86.71   <2e-16 ***
icpt       1.0000     0.4240    2.36    0.019 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.441 on 992 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.59e+07 on 8 and 992 DF,  p-value: <2e-16


Call:
lm(formula = y ~ x + x2 + x3 + ideff + firmeff + shoeeff + shirteff + 
    icpt - 1)

Residuals:
   Min     1Q Median     3Q    Max 
-1.581 -0.270  0.000  0.278  1.752 

Coefficients:
         Estimate Std. Error t value Pr(>|t|)    
x          1.0367     0.0145   71.58   <2e-16 ***
x2         0.2440     0.0143   17.11   <2e-16 ***
x3         0.5307     0.0144   36.85   <2e-16 ***
ideff      1.0000     0.0105   95.21   <2e-16 ***
firmeff    1.0000     0.0109   91.49   <2e-16 ***
shoeeff    1.0000     0.0110   90.92   <2e-16 ***
shirteff   1.0000     0.0115   86.71   <2e-16 ***
icpt       1.0000     0.4569    2.19    0.029 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.441 on 992 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.59e+07 on 8 and 992 DF,  p-value: <2e-16

> options(opt)
> 
> proc.time()
   user  system elapsed 
   1.25    0.10    1.34