2017 Agricultural and Applied Economics Association Annual Meeting

Farmer Mac Economist Ryan Kuhns and fellow economists Kevin Patrick (USDA) and Jenny Ifft (Cornell University), will be presenting a paper on the use of machine learning to improve predictions of agricultural credit demand at the annual meeting of the Agricultural and Applied Economics Association Meeting in Chicago, IL on August 1st, 2017. The presentation will explain typical machine learning techniques and demonstrate the benefits of applying machine learning to data from the USDA Agricultural Resource Management Survey (ARMS) in order to predict whether or not a farm applied for new financing. Better predictions of farms desiring additional financing will allow agricultural finance industry participants to better understand the characteristics of their potential customers, while potentially informing policymakers of industry segments with greater loan demand and where credit constraints could potentially occur.

Additional Meeting Information: http://www.aaea.org/meetings/2017-aaea-annual-meeting

Date: July 30 - August 1, 2017
Location: Chicago, IL