Re: [R] Interpreting coefficient in selection and outcome Heckman models in sampleSelection

Dear Marinella Implementing a function in the sampleSelection package that calculates marginal effects is still on my to-do list but I probably won't implement it soon, because I have many other things with higher priority. Sorry! However, you are invited to implement this feature in the

[R] Interpreting coefficient in selection and outcome Heckman models in sampleSelection

Dear Arne, I have just read the exchange of messages with Mark Bulling.I was wondering if you have discovered/developed a function to calculate the marginal effects of the selection and outcome equations (sampleSelection). Thank you Marinella [[alternative HTML version deleted]]

Re: [R] Interpreting coefficient in selection and outcome Heckman models in sampleSelection

Hi Mark! On Sun, Jan 3, 2010 at 9:08 PM, Mark Bulling mark.bull...@googlemail.com wrote: Hi there Within sampleSelection, I'm trying to calculate the marginal effects for variables that are present in both the selection and outcome models. For example, age might have a positive effect on

Re: [R] Interpreting coefficient in selection and outcome Heckman models in sampleSelection

Hi Mark, why do you need that? If your task is to estimate how much your y changes if x change, why not use simple OLS? (Well, right, you should be able to use sampleSelection as well). It shouldn't probably be hard to compute it -- it is just OLS marginal effect + som kind of derivative of

Re: [R] Interpreting coefficient in selection and outcome Heckman models in sampleSelection

Hi Ott The reason for calculating would be to add context to the OLS estimates (from the probit) - e.g. a 1 year increase in age might increase the dependent variable by 1 unit, but given that the selection model is based on a subset of the full data set, if the probability of reaching the

[R] Interpreting coefficient in selection and outcome Heckman models in sampleSelection

Hi there Within sampleSelection, I'm trying to calculate the marginal effects for variables that are present in both the selection and outcome models. For example, age might have a positive effect on probability of selection, but then a negative effect on the outcome variable. i.e.