When there are non-additive, value-enhancing relationships across inputs, single-cause causal experiments can serve up misleading results

From Some dangers in estimating signaling and human capital premia by Tyler Cowen.

The trick is this: when there are non-additive, value-enhancing relationships across inputs, single-cause causal experiments can serve up misleading results. In fact, by cherry-picking your counterfactual you can get the return to signaling, or to human capital, to be much higher or lower. Usually one is working in a model where the implicit marginal causal returns to learning, IQ, signaling, and so on sum up to much more than 100%, at least if you measure them in this “naive” fashion. If you think of a career in narrative terms, IQ, learning, and signaling are boosting each others’ value with positive and often non-linear feedback. And insofar as these labor market processes have “gatekeepers,” it is easy for the marginal product of any one of these to run very high, again if you set up the right thought experiment.

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