In a previous post I described the evidence that pointed me toward the two big questions that guided me when I was building models of growth: Why has the rate of growth been speeding up over time? Why have so many poor countries failed to take advantage of the potential for rapid catch-up growth? A sign of a good mathematical model is that once you understand it, you can state the answer it suggests very simply.

The bar I set for a model is that it should yield answers we believe to questions that matter. For a model of growth, the two questions that matter most are: Speeding-up: Why has the rate of growth at the technological frontier been increasing over time? Missed Opportunities: Why have so many countries that start from far behind the frontier failed to achieve rapid catch-up growth?

In The Great Escape, Angus Deaton concludes by saying that he is “cautiously optimistic” about the future. In his review of the book, David Leonhardt captured its real spirit: “Deaton’s central message is deeply positive, almost gloriously so.” Deaton has made many contributions that make him such a great choice for today’s prize. (See here, here, and here.) I take special satisfaction from the validation it provides to Deaton’s optimism, which I would describe as careful, not cautious.

The oral tradition at the University of Chicago attributed the observation that “sloppy writing reflects sloppy thinking” to Milton Friedman. Of course, it echoes George Orwell’s claim that “the slovenliness of our language makes it easier for us to have foolish thoughts.” Neither Friedman’s word “reflects” nor Orwell’s phrase “makes it easier” go far enough. The right verb is “produces.” Clear writing produces clearer thoughts. Sloppy writing produces sloppier thoughts. This is a natural consequence of the fact that anything stored in connections between neurons is part of a biochemical and electrical dynamic feedback loop.

To me, one of the ways in which my 1990 paper, Endogenous Technological Change, was a step forward relative to the first round models of endogenous growth was the explicit distinction that it allowed between the stock of human capital H and the stock of knowledge A. To be sure, this was a very small step. In the model, they interacted the simplest possible way. Human capital H was an input that could be used to produce new knowledge A.