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1/3 Econ. readers asked if they can get hold of those magical night-vision goggles that tell us which causal effects in an econ. model are identifiable by OLS (and how). The answer is embarrassingly simple: Consider
Model 2 in p. 163 of ucla.in/2mhxKdO
Model 2 in p. 163 of ucla.in/2mhxKdO
2/3 Take any two variables, say Z_3 and Y. If you can
find a set S of observed variables (e.g., S={W_1,W_2}),
non-descendants of Z_3, that block all back doors paths from Z_3 to Y, you are done; the coefficient a in the regression Y = a*Z_3 + b1*W_1 +b2*W_2
gives you the right
find a set S of observed variables (e.g., S={W_1,W_2}),
non-descendants of Z_3, that block all back doors paths from Z_3 to Y, you are done; the coefficient a in the regression Y = a*Z_3 + b1*W_1 +b2*W_2
gives you the right
3/3 answer. A similar goggle works for a single
structural parameter (See page 84 of Primer ucla.in/2KYYviP). Duck soup. This re-begs the question whether the restricted notion of "reduced form" is still needed in 2019. @EconBookClub @lewbel #Bookofwhy.
structural parameter (See page 84 of Primer ucla.in/2KYYviP). Duck soup. This re-begs the question whether the restricted notion of "reduced form" is still needed in 2019. @EconBookClub @lewbel #Bookofwhy.
