Linear regression

TBD

Interactions

• 8.3 Interactions between Independent Variables | Introduction to Econometrics with R

Fixed effects

• 10.3 Fixed Effects Regression | Introduction to Econometrics with R

R

Regression implementations

Regressions in R

The two most widely used R packages for regression analysis are fixest and lfe.

fixest is more actively maintained, while lfe is an older package.

fixest::feols()

lfe::felm()

From documentation:

The formula specification is a response variable followed by a four part formula.

• The first part consists of ordinary covariates.
• The second part consists of factors to be projected out.
• The third part is an IV-specification.
• The fourth part is a cluster specification for the standard errors.

I.e. something like y ~ x1 + x2 | f1 + f2 | (Q|W ~ x3+x4) | clu1 + clu2 where y is the response, ⁠x1,x2⁠ are ordinary covariates, ⁠f1,f2⁠ are factors to be projected out, Q and W are covariates which are instrumented by x3 and x4, and ⁠clu1,clu2⁠ are factors to be used for computing cluster robust standard errors. Parts that are not used should be specified as 0, except if it's at the end of the formula, where they can be omitted. The parentheses are needed in the third part since | has higher precedence than ~. Multiple left hand sides like y|w|x ~ x1 + x2 | f1+f2 | ... are allowed.