Contrasting Growth Theories: Ideas, Capital, and the Role of Firms

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Growth theory for EAs - reading list and summary, published by Karthik Tadepalli on September 12, 2024 on The Effective Altruism Forum.
Economic growth is a unique field, because it is relevant to both the global development side of EA and the AI side of EA. Global development policy can be informed by models that offer helpful diagnostics into the drivers of growth, while growth models can also inform us about how AI progress will affect society. My friend asked me to create a growth theory reading list for an average EA who is interested in applying growth theory to EA concerns. This is my list.
(It's shorter and more balanced between AI/GHD than this list) I hope it helps anyone who wants to dig into growth questions themselves.
These papers require a fair amount of mathematical maturity. If you don't feel confident about your math, I encourage you to start with Jones 2016 to get a really strong grounding in the facts of growth, with some explanations in words for how growth economists think about fitting them into theories.
Basics of growth
These two papers cover the foundations of growth theory. They aren't strictly essential for understanding the other papers, but they're helpful and likely where you should start if you have no background in growth.
Jones 2016
Sociologically, growth theory is all about finding facts that beg to be explained. For half a century, growth theory was almost singularly oriented around explaining the "Kaldor facts" of growth. These facts organize what theories are entertained, even though they cannot actually validate a theory - after all, a totally incorrect theory could arrive at the right answer by chance.
In this way, growth theorists are engaged in detective work; they try to piece together the stories that make sense given the facts, making leaps when they have to.
This places the facts of growth squarely in the center of theorizing, and Jones 2016 is the most comprehensive treatment of those facts, with accessible descriptions of how growth models try to represent those facts. You will notice that I recommend more than a few papers by Chad Jones in this list. That's because he is by far the best writer in the growth literature. His exposition of complex ideas and coverage of the big picture is just not matched by any other growth economist.
Jones 2005
While Jones 2016 focuses on the facts of growth, Jones 2005 is an overview of the most common kind of long-run growth model - the idea-based model. Historically, economists used models like the Solow model, in which growth came from accumulating capital. But capital-based models are basically incapable of predicting sustained long-run growth. The now-canonical Romer model made a breakthrough by refocusing growth on ideas. Unlike machines, ideas are infinitely reusable.
So if growth comes from creating new ideas, and ideas don't get used up, we can generate sustained long-run growth. This is another demonstration of the aesthetic of growth theory: theories are celebrated if they can match facts that economists think are important.
The idea-based growth model is way too canonical to leave off this list. But I personally think it is overrated by EAs and not necessarily applicable to the issues we care about (AI or global development). I include it because working through it will help you understand the mechanics of growth models more generally, including the more complicated ones covered below.
Growth theory for AI progress
The growth theory that focuses on AI progress builds off the canonical growth work listed above, but with important advances from it. Few papers really apply their framework directly to AI, so it's important to try and extrapolate what the model implies about AI. The three papers below are the ones whose frameworks I think are most applicable to thinking about AI ...