I don’t agree with the conclusion of this piece, but I like this line:
“… they use something based on natural language (because what else is there?) …”
I do agree with this piece:
There is always an alternative.
The Economist on the Big Data Honeymoon: “Economists are prone to fads, and the latest is machine learning”.
I like its discussion of the ebb and flow of our favorite methods, but I think they miss something here:
Before, economists would try to predict things using only a few inputs. With machine learning, the data speak for themselves; the machine learns which inputs generate the most accurate predictions.
Non-structural, statistical time-series forecasting (factor VARs anyone?) is nothing new. The way more interesting application of machine learning for economists is to measure concepts that were previously out of our reach and to use such new data in our causal studies. See, for example, here or here.