Additive Models and Marginal Effects

Additive models have been proven to be very useful as they naturally generalize the linear regression model and allow for an interpretation of marginal changes, i.e. for the effect of one variable on the mean function m(●) when holding all others constant. This kind of model structure is widely used in both theoretical economics and in econometric data analysis. The standard text of Deaton & Muellbauer (1980) provides many examples in microeconomics for which the additive structure provides interpretability. In econometrics, additive structures have a desirable statistical form and yield many well known economic results. For instance, an additive structure allows us to aggregate inputs into indices; elasticities or rates of substitutions can be derived directly. The separability of the input parameters is consistent with decentralization in decision making or optimization by stages. In summary, additive models can easily be interpreted.