# collinearity: Collinearity diagnostics for 'fixest' objects In fixest: Fast Fixed-Effects Estimations

 collinearity R Documentation

## Collinearity diagnostics for `fixest` objects

### Description

In some occasions, the optimization algorithm of `femlm` may fail to converge, or the variance-covariance matrix may not be available. The most common reason of why this happens is colllinearity among variables. This function helps to find out which set of variables is problematic.

### Usage

```collinearity(x, verbose)
```

### Arguments

 `x` A `fixest` object obtained from, e.g. functions `femlm`, `feols` or `feglm`. `verbose` An integer. If higher than or equal to 1, then a note is prompted at each step of the algorithm. By default `verbose = 0` for small problems and to 1 for large problems.

### Details

This function tests: 1) collinearity with the fixed-effect variables, 2) perfect multi-collinearity between the variables, 4) perfect multi-collinearity between several variables and the fixed-effects, and 4) identification issues when there are non-linear in parameters parts.

### Value

It returns a text message with the identified diagnostics.

Laurent Berge

### Examples

```
# Creating an example data base:
set.seed(1)
fe_1 = sample(3, 100, TRUE)
fe_2 = sample(20, 100, TRUE)
x = rnorm(100, fe_1)**2
y = rnorm(100, fe_2)**2
z = rnorm(100, 3)**2
dep = rpois(100, x*y*z)
base = data.frame(fe_1, fe_2, x, y, z, dep)

# creating collinearity problems:
base\$v1 = base\$v2 = base\$v3 = base\$v4 = 0
base\$v1[base\$fe_1 == 1] = 1
base\$v2[base\$fe_1 == 2] = 1
base\$v3[base\$fe_1 == 3] = 1
base\$v4[base\$fe_2 == 1] = 1

# Estimations:

# Collinearity with the fixed-effects:
res_1 = femlm(dep ~ log(x) + v1 + v2 + v4 | fe_1 + fe_2, base)
collinearity(res_1)

# => collinearity with the first fixed-effect identified, we drop v1 and v2
res_1bis = femlm(dep ~ log(x) + v4 | fe_1 + fe_2, base)
collinearity(res_1bis)

# Multi-Collinearity:
res_2 =  femlm(dep ~ log(x) + v1 + v2 + v3 + v4, base)
collinearity(res_2)

```

fixest documentation built on April 1, 2022, 1:05 a.m.