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Como textos prprios da dcada 40/50, h alguns comentrios machistas e eu, mesmo colocando em perspectiva a poca em que foram escritos, no posso deixar de comentar

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synth2 cigsale lnincome age15to24 retprice beer /// cigsale(1988) cigsale(1980) cigsale(1975), /// trunit(3) trperiod(1989) xperiod(1980(1)1988) /// nested allopt The key options are: trunit(3) treated unit is California (state == 3) trperiod(1989) treatment begins in 1989 xperiod(1980(1)1988) average covariates over 19801988 for matching nested use nested optimization (outer V-weights, inner W-weights) allopt try multiple starting values to avoid local optima Pre-treatment fit Fitting results in the pretreatment periods: Treated Unit: California Treatment Time: 1989 Number of Control Units = 38 Root Mean Squared Error = 1.75567 Number of Covariates = 7 R-squared = 0.97434 The synthetic control explains 97.4% of the pre-treatment variation in Californias cigarette sales (R-squared = 0.974), with a Root Mean Squared Error (RMSE) of just 1.76 packs per capita