Denny, KevinKevinDenny2010-11-262010-11-262009-07200909http://hdl.handle.net/10197/2606I show a simple back-of-the-envelope method for calculating marginal effects in binary choice and count data models. The approach suggested here focuses attention on marginal effects at different points in the distribution of the dependent variable rather than representative points in the joint distribution of the explanatory variables. For binary models, if the mean of the dependent variable is between 0.4 and 0.6 then dividing the logit coefficient by 4 or multiplying the probit coefficient by 0.4 should be moderately accurate.57832 bytesapplication/pdfenMarginal effectsBinary choiceCount dataMathematical modelsMathematical statisticsWorking Paperhttps://creativecommons.org/licenses/by-nc-sa/1.0/