Abstract
Firearm injury is a major public health crisis in the United States, where more than 200 people sustain a nonfatal firearm injury and more than 100 people die from it every day. To formulate policy that minimizes firearm-related harms, legislators must have access to spatially resolved firearm possession rates. Here, we create a spatiotemporal econometric model that estimates monthly state-level firearm ownership from two cogent proxies (background checks per capita and fraction of suicides committed with a firearm). From calibration on yearly survey data that assess ownership, we find that both proxies have predictive value in estimation of firearm ownership and that interactions between states cannot be neglected. We demonstrate use of the model in the study of relationships between media coverage, mass shootings, and firearm ownership, uncovering causal associations that are masked by the use of the proxies individually.
Original language | English (US) |
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Article number | 100546 |
Journal | Patterns |
Volume | 3 |
Issue number | 8 |
DOIs | |
State | Published - Aug 12 2022 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- General Decision Sciences
Keywords
- DSML3: Development/Pre-production: Data science output has been rolled out/validated across multiple domains/problems
- firearm ownership
- firearm violence
- spatial econometrics
- time series