Extracting Marginal Effects from Interaction Terms in an OLS Regression

Comrades,

I am trying to compute marginal effects for several interaction terms in two separate models--one based on a binary outcome (using a probit model) and one based on a continuous outcome (using OLS). I came across a really great blog post, from Vince Wiggins, that details a clever way of extracting marginal effects from interactions terms in non-linear models: http://www.stata.com/statalist/archi.../msg00301.html. This clarified things for my probit model.

Here is the trouble: I recently reviewed Richard Williams slides on marginal effects (http://www3.nd.edu/~rwilliam/stats/Margins01.pdf) and read that marginal effects in OLS regressions should be identical to the OLS coefficients themselves. When I compute marginal effects in my OLS model for variables that are not included in interactions, the marginal effects are equivalent to the analogous coefficients, as would be expected based on my reading of Richard's slides. However, when I compute marginal effects in my OLS model for any terms included in an interaction--as well as when I compute marginal effects for the interactions themselves using Vince Wiggins' method--I get a slightly different result than the OLS-based coefficients for each term.

Is this to be expected?

Cheers,
Francis