Matt Clancy | Searcharxiv

arXiv2026

The Geography of Private Sector Agricultural Innovation in the USA: Evidence from Patents

This paper develops a novel estimates of annual private sector agricultural R&D at the level of US states for the period 1976-2014. For each of five different agricultural subsectors, I allocate estimates of national private sector R&D across the 50 states by using the geographic distribution of inventors listed on contemporaneous US patents in the same agricultural subsector. These five subsectors comprise a large majority of total private sector agricultural R&D. I then use this new dataset to document three stylized facts about private sector agricultural R&D: it is highly correlated with the size of the state's agricultural economy (including over time, as well as in cross section), it is highly persistent, and is has become increasingly less concentrated over 1976-2014, though this last trend shows signs of reversing.

econ.GN↗

arXiv2023

The Returns to Science in the Presence of Technological Risk

Scientific and technological progress has historically been very beneficial to humanity but this does not always need to be true. Going forward, science may enable bad actors to cause genetically engineered pandemics that are more frequent and deadly than prior pandemics. I develop a quantitative economic model to assess the social returns to science, taking into account benefits to health and income, and forecast damages from new biological capabilities enabled by science. I set parameters for this model based on historical trends and forecasts from a large forecasting tournament of domain experts and superforecasters, which included forecasts about genetically engineered pandemic events. The results depend on the forecast likelihood that new scientific capabilities might lead to the end of our advanced civilization - there is substantial disagreement about this probability from participants in the forecasting tournament I use. If I set aside this remote possibility, I find the expected future social returns to science are strongly positive. Otherwise, the desirability of accelerating science depends on the value placed on the long-run future, in addition to which set of (quite different) forecasts of extinction risk are preferred. I also explore the sensitivity of these conclusions to a range of alternative assumptions.

econ.GN↗