When I criticize the fad of RCTs in development (which I do occasionally), I often get the sarcastic response, “What should we do, go back to doing growth regressions?” The under-40 generation defend their fad, whatever its flaws, as at least better than the previous fad. It is conventional wisdom that development economics did far too many growth regressions and that theory was simplistic, empirical work was sloppy, and therefore nothing was learned. Moreover, it was argued that problems of pathways of causality both amongst the many potential covariates (the covariate “robustness” problem) and between covariates and growth (the “adequate identifying instruments” problem) would and even in principle could never be adequately resolved. In many ways, the rise in development of the RCT agenda of carefully controlled experiments to measure causal impacts of specific identifiable programs or “treatments” was a direct, allergic-type, reaction to the real and perceived negative excesses of growth research generally, and growth regressions in particular.
I argue, though, that we did learn two very important things from growth research, and these were learned from research in the strong sense that they changed people’s views from a previous view that was incorrect.
A doesn’t converge
One thing we did learn from growth research is that convergence in total factor productivity (TFP) was not common. This was learned from empirical growth research in the strong sense that most people doing development in the 1950s and 1960s thought there would be convergence in TFP.
It would not be a caricature of the Solow (1956) model and its aftermath in the 1950s and 1960s to conclude that American economic growth could usefully be decomposed into “factor accumulation” and “TFP.” Moreover, while formally people recognized TFP was residually measured and hence, strictly speaking, “a measure of our ignorance,” it was not uncommon to think of TFP growth as “technical progress.” I was taught in graduate school at MIT that the production function A represented “sets of blueprints” of what was technologically possible (subsuming organization into technology), and this set of the possible with science and technology (and organizational) advanced to account for a significant fraction of output-per-hour growth. Reading Robert J. Gordon’s magisterial 2016 book The Rise and Fall of American Growth, which still has as its centerpiece decompositions of growth, I am convinced this is still a productive way to think about American economic growth. It is demonstrably the case that during the twentieth century, science and technology created vast new possibilities (e.g., electricity, internal combustion engines, telephones, jet travel, air conditioning, improved medicine). Alfred Chandler and the business history school emphasize that new forms and practices of organizations (the rise of managerial capitalism) and professions led to the “scale and scope” that brought these potentials into everyday life.
If one understood “A” in the aggregate production function as codifiable technical knowledge—how medicines affect disease, how fertilizers affect plant growth, how to produce steel, how telephones transmit sound, etc.—then it was easy to think of A as a “public good” that was non-rival and non-excludable. In a post-colonialist world in which political sovereigns were interested in progress in their country (and maybe even the well-being of their people), it was easy to imagine that governments would have every incentive to bring this available knowledge to bear in promoting growth in their country. This was an obvious, and widely accepted, narrative of the two pre-World War II development successes: Russia and Japan. The idea of the “advantages of backwardness” was premised on the perfectly plausible notion that it must be easier to transplant, adopt, and adapt existing knowledge, already within the frontiers of technology and organizational practice, than to push the frontier.
In this intellectual context, everything about the “first generation” development research and practice is pretty clear. If A converges rapidly—because, after all, the knowledge of how penicillin and nitrogenous fertilizers and electricity work is “in the air,” like Jefferson’s metaphor of the light of a candle that all can benefit from—then the key constraint on convergence in incomes is the speed with which resources can be mobilized, from domestic and foreign savings, to invest in physical and human capital (and it is a complete myth that human capital was ever underacknowledged). The convergence of A with low K/L meant returns on K would be high and growth dynamics—the speed of convergence—would be determined by savings. Hence the famous 1954 Arthur Lewis quote:
The central problem in the theory of economic development is to understand the process by which a community which was previously saving, and investing, 4 or 5 per cent of its national income or less converts itself into an economy where voluntary saving is running income or less converts itself into an economy where voluntary saving is running at about 12 to 15 per cent of national income or more. This is the central problem because the central fact of economic development is rapid capital accumulation.
This implies that the goal of a development organization, say a bank, say a World Bank, should be to mobilize investible resources to augment domestic savings and perhaps transmit those savings via investment projects that would also transmit the knowledge of the technical frontier.
These ideas were so powerful in part because they were grounded in common sense and practical observation. Who could deny there had been technical progress? Before there weren’t cars, now there are cars. Before people died of diseases that are now easily treated. Who could deny that scientific knowledge was a public good (of course, the whole premise of protection of intellectual property like patents was that it was otherwise a public good)? Who could deny it was hard to mobilize savings when consumption levels were very low?
Good thing the fad of “growth research” came along and documented the facts. Bosworth and Collins (2003) (among many others) decomposed growth in output per person across lots of countries from 1960 to 2000 into TFP growth and factor accumulation. What was striking was that for most developing country regions (Latin America, Africa, Middle East), TFP had grown more slowly than in industrial countries: (measured) A was diverging. Even in relatively high-growth regions (East Asia excluding China, South Asia), the more rapid rates of growth were not due to convergence of A (it grew at 1 percent in these regions, exactly the industrial country rate) but faster factor accumulation.
Full Report attached
Report by Centre for Global Development