I am trying to estimate the elasticity of my outcome variable y with respect to income. y is censored at 0, and it is between 0 and almost one, which suggests the use of the Tobit model(under the usual assumption on residuals) . However, for the sake of simplicity, I am presenting OLS here my data for the variable y and income are reported below. I also include the log of income for reference, as I used it in the model (i.e. ln_income). input float(y ln_income income) .6291617 6.839435 933.9615 .9945465 7.655005 2111.1853 .9926049 6.69821 810.9529 0 7.633141 2065.5273 0 7.138404 1259.4164 0 8.019789 3040.534 .981214 6.830252 925.424 .8981348 6.331939 562.2459 .9946473 7.226309 1375.1375 0 5.830486 340.5242 0 -4.6051702 .01 I found this technical note: https://www.stata.com/stata14/fracti...utcome-models/ suggesting to use margins, dyex in the context of fractional regression given that the dependent variable is already a proportion and so is already on a percentage scale (same as mine). When I apply this regress prob_mod_sev income [pw=wt] margins [pw=wt], dyex(income) I get --------------------------------------------------------------------------------- | Delta-method | dy/ex std. err. t P>|t| [95% conf. interval] ----------------+---------------------------------------------------------------- income | -.0018123 .0004174 -4.34 0.000 -.0026304 -.0009943 --------------------------------------------------------------------------------- Differently from the technical note, in my case, the elasticity is computed with margins, dydx because the independent variable of interest appears in log (i.e. ln_income), so it is already on a percentage scale regress prob_mod_sev ln_income [pw=wt] margins [pw=wt], dydx(ln_income) which gives me: ------------------------------------------------------------------------------------ | Delta-method | dy/dx std. err. t P>|t| [95% conf. interval] -------------------+---------------------------------------------------------------- ln_income | -.0238224 .0002898 -82.20 0.000 -.0243904 -.0232544 ------------------------------------------------------------------------------------ SO I have two main concerns: 1. how to reconcile the two results that in principle should be the same (or at least scaled by 100, not by 10 for sure) and which one should I trust? 2. with reference to the second model: how to interpret the elasticity given my context? so a 1% increase in income would bring a reduction in y by 0.02% or 2%. And with reference to the first? Thanks in advance for any help you can provide on this Anna