Taking Stock

This chapter ends our investigation of neoclassical growth models. It also opens the way for the analysis of endogenous technological progress in the next part of the book. The models presented in this chapter are, in many ways, more tractable and easier than those in earlier chapters.

its variants. Consequently, the debate about the measurement of total factor productivity has important implications for what types of models we should use for thinking about world economic growth and cross-country income differences.

The discussion in this chapter has also revealed another important tension. Chapters 3 and 8 demonstrated that the neoclassical growth model (or the simpler Solow growth model) have difficulty in generating the very large income differences across countries that we observe in the data. Even if we choose quite large differences in cross-country distortions (for example, eightfold differences in effective tax rates), the implied steady-state differences in income per capita are relatively modest. As noted before, this observation has generated a large literature that seeks reasonable extensions of the neoclassical growth model in order to derive more elastic responses to policy distortions or other differences across countries. The models presented in this chapter, like those that we will encounter in the next part of the book, suffer from the opposite problem. They imply that even small differences in policies, technological opportunities or other characteristics of societies will lead to permanent differences in long-run growth rates. Consequently, these models can explain very large differences in living standards from small policy, institutional or technological differences. But this is both a blessing and a curse. Though capable of explaining large cross-country differences, these models also predict an ever-expanding world distribution, since countries with different characteristics should grow at permanently different rates. The relative stability of the world income distribution in the postwar era is then a challenge to the baseline endogenous growth models.

Nevertheless, there is more to understanding the nature of the growth process and the role of technological progress than simply looking at the postwar data. First, as illustrated in Chapter 1, the era of divergence is not the past 60 years, but the 19th century. Therefore, it is equally important to confront these models with historical data. Second, a major assumption of most endogenous growth models is that each country can be treated in isolation. This “each country as an island” approach is unlikely to be a good approximation to reality in most circumstances, and much less so when technology is endogenous. Most economies do not generate their own technology by R&D or other processes, but partly import or adopt these technologies from more advanced nations (or from the world technology frontier). Consequently, a successful mapping of the theories to data requires us to enrich these theories and abandon the “each country as an island” assumption. I discuss the number of approaches that incorporate technology flows across countries and international trade linkages later in the book. But the next part will follow the established literature and develop the models of endogenous technological progress without paying much attention to cross-country knowledge flows.

11.6.