Working Paper: NBER ID: w23782
Authors: Nicholas Bloom; Charles I. Jones; John Van Reenen; Michael Webb
Abstract: In many growth models, economic growth arises from people creating ideas, and the long-run growth rate is the product of two terms: the effective number of researchers and their research productivity. We present a wide range of evidence from various industries, products, and firms showing that research effort is rising substantially while research productivity is declining sharply. A good example is Moore's Law. The number of researchers required today to achieve the famous doubling every two years of the density of computer chips is more than 18 times larger than the number required in the early 1970s. Across a broad range of case studies at various levels of (dis)aggregation, we find that ideas — and in particular the exponential growth they imply — are getting harder and harder to find. Exponential growth results from the large increases in research effort that offset its declining productivity.
Keywords: research productivity; economic growth; Moore's Law; agricultural productivity; healthcare innovation
JEL Codes: O30; O40
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Increased research effort (I23) | Declining research productivity (D29) |
| Number of researchers (C90) | Declining research productivity (D29) |
| R&D spending (O32) | Declining research productivity (D29) |
| Declining research productivity (D29) | Stable overall growth rates (O40) |
| Declining research productivity in semiconductors (L63) | Declining research productivity in agriculture and pharmaceuticals (L65) |