In RCTs we generally worry about “spillovers” i.e. the control group is affected by the treatment. Usually this is in the opposite direction: for example, in an RCT of cash transfers we might be worried that control households will benefit from the spending of treatment households. This violates one of the core assumptions of RCTs and means that we can’t estimate the true treatment effect.
But I have not seen the opposite effect (control group suffers from treatment group’s advantages) and I do not think development economists think about it a lot. Usually this is not an issue because the experiment should be designed to minimize spillovers of any kind, positive or negative—for example, randomizing at the village level so that treatment and control villages have basically separate economies.
There is indeed some evidence that human capital interventions can have their impact significantly attenuated via general equilibrium effects. For example, in one of the first empirical investigations of this issue, the benefits from an education expansion in India were significantly attenuated once spill-overs were accounted for (Khanna 2022) . Such general equilibrium effects could either take the form of the classic signalling arguments about education or by other mechanisms, such as decreasing the marginal returns to human capital leading to the control group’s investment being lower relative to a counterfactual with no treatment (think of a production function with diminishing marginal products). For a more detailed exposition of general equilibrium’s relevance, see Acemoglu (2010).
Additionally, in the context of cash transfers you cite, you might be interested to know that some RCTs in that area have found negative spill-overs within treated villages (e.g., Haushofer and Shapiro 2018), although the mechanisms are not totally clear. In fact, the existing evidence led GiveWell to believe that cash transfers’ spill-overs were negative in expectation when they last reviewed the evidence.
In RCTs we generally worry about “spillovers” i.e. the control group is affected by the treatment. Usually this is in the opposite direction: for example, in an RCT of cash transfers we might be worried that control households will benefit from the spending of treatment households. This violates one of the core assumptions of RCTs and means that we can’t estimate the true treatment effect.
But I have not seen the opposite effect (control group suffers from treatment group’s advantages) and I do not think development economists think about it a lot. Usually this is not an issue because the experiment should be designed to minimize spillovers of any kind, positive or negative—for example, randomizing at the village level so that treatment and control villages have basically separate economies.
There is indeed some evidence that human capital interventions can have their impact significantly attenuated via general equilibrium effects. For example, in one of the first empirical investigations of this issue, the benefits from an education expansion in India were significantly attenuated once spill-overs were accounted for (Khanna 2022) . Such general equilibrium effects could either take the form of the classic signalling arguments about education or by other mechanisms, such as decreasing the marginal returns to human capital leading to the control group’s investment being lower relative to a counterfactual with no treatment (think of a production function with diminishing marginal products). For a more detailed exposition of general equilibrium’s relevance, see Acemoglu (2010).
Additionally, in the context of cash transfers you cite, you might be interested to know that some RCTs in that area have found negative spill-overs within treated villages (e.g., Haushofer and Shapiro 2018), although the mechanisms are not totally clear. In fact, the existing evidence led GiveWell to believe that cash transfers’ spill-overs were negative in expectation when they last reviewed the evidence.