We propose inference procedures for partially identified population features for which the population identification region can be written as a transformation of the Aumann expectation of a properly defined set valued random variable (SVRV). An SVRV is a mapping that associates a set (rather...

This paper illustrates how the use of random set theory can benefit partial identification analysis. We revisit the origins of Manski’s work in partial identification (e.g., Manski (1989, 1990)) focusing our discussion on identification of probability distributions and conditional expectations...

Electric vehicle (EV) battery costs have declined by more than 90% over the past decade. This study investigates the role of learning-by-doing (LBD) in driving this reduction and its interaction with two major government policies - consumer EV subsidies and local content requirements. Leveraging...

This paper examines the impact of industrial policies (IPs) on innovation in the global automobile industry. We compile the first comprehensive dataset linking global IPs with patent data related to the auto industry from 2008 to 2023. We document a major shift in policy focus: by 2022, nearly...