 For both practical and ethical reasons, it is often hard to experiment in economics (though, as discussed in section 4.5, far from impossible). But with some ingenuity and with far greater enthusiasm for experimentation than had been the case previously, economists are experimenting much more frequently both in the laboratory and in the field. In addition, as a substitute for experimentation, or as a way of stretching the limits on experimentation, economists in recent years have become very enthusiastic about so-called “instrumental variable” techniques. For example, merely examining the correlation between economic growth and development aid, even controlling for other factors known to influence economic growth is unlikely to reveal the causal influence of aid on growth, because aid may reciprocally depend on growth and well as many factors that are hard to measure that also influence growth. These problems can be to some extent circumvented if economists can find an “instrumental” variable x upon which aid depends that influences growth (if at all) only by its influence on aid and which is probabilistically independent of all other determinants of growth. In that case, one can use the effect of x on growth to estimate the effect of aid on growth. Instrumental variable techniques, policy experimentation, and reliance on “natural experiments” have become widespread, though they bring with them new problems extrapolating experimental results to the target population (Deaton 2010; Cartwright and Hardie 2013).