IQ IN THE PRODUCTION FUNCTION: EVIDENCE FROM IMMIGRANT EARNINGS

The cross-country growth literature (especially Sala-i-Martin 1997; Sala-i-Martin, Doppelhofer, and Miller 2004) has found that traditional education measures rarely have a robust relationship with growth and productivity--elementary education being a rare exception. By contrast, a new empirical growth literature (Jones and Schneider 2006; Lynn and Vanhanen 2002; Ram 2007; Weede 2004; Weede and Kampf 2002) has shown that a nation's average IQ has a remarkably robust relationship with its productivity (Figure 1). That a test designed by psychologists should have such a robust relationship with economic variables is a puzzle that demands explanation. For instance, Jones and Schneider showed that national average IQ was more robust than other human capital variables and was statistically significant at the 1% level in all 455 growth regressions that controlled for all 18 factors that passed Sala-i-Martin, Doppelhofer, and Miller's (2004) robustness tests. Of course, as with all the growth regression literature, a key difficulty is disentangling cause and effect. Thus, in this article, we run no growth regressions whatsoever. Instead, we perform a simple calibration of the IQ-productivity relationship based on widely agreed upon microeconomic parameters. That means we can directly estimate one causal channel running from cognitive ability to productivity. In the process, we learn the following: (1) If one knows the average IQ of a nation's citizens as estimated by Lynn and Vanhanen (2002, 2006), one can predict the average wages that immigrants from that country will earn upon their arrival in the United States--whether or not one controls for immigrant education and even if the test is completely visual rather than verbal. In other words, national average IQ predicts part of what Hendricks (2002) calls "unmeasured worker skill." (2) We find that a 1-point increase in national average IQ predicts 1% higher immigrant wages--precisely the value found repeatedly in microeconometric studies (note that by construction, 1 IQ point [approximately equal to] 1/15th of a standard deviation within any large national population). Together, Points 1 and 2 provide further evidence that cross-country IQ tests are valid predictors of worker productivity. (3) When IQ is added to the production function in the form implied by traditional, externality-free human capital theory, differences in national average IQ are quantitatively significant in explaining cross-country income differences. That said, our productivity accounting exercise does not resolve the puzzle of why high-IQ countries are 15 times richer than low-IQ countries. In a related vein, Hanushek and Kimko (2000) use national math and science test scores to verify that cognitive skills appear to matter more for groups than for individuals. Like us, they use immigrants to the United States as a way to test whether immigrants bring their home country productivity levels along with them when they immigrate to the United States. When they interpret their results within a Solow-type framework, they conclude that "the [cross-country] growth equation results are much larger than the corresponding results for individual earnings." In sum, our article rigorously explores the quantitative magnitude of the puzzle uncovered by Hanushek and Kimko (2000) and Hanushek and Woessman (2007). But by using IQ tests rather than other widely used math and science test scores, we can often double our sample size while simultaneously using the most widely analyzed, best understood form of cognitive test. We begin with an overview of the recent psychological literature on the validity of IQ tests and then proceed to our discussion of the link between IQ and immigrant wages. The discussion of IQ and immigrant wages yields a key parameter, [gamma], the IQ semi-elasticity of wages, which we use in our development accounting exercise. We then discuss the questions of reverse causality and trends in the IQ-productivity relationship over the past 40 yr and conclude by discussing how our results fit into the growth literature. …