TY  - JOUR
PY  - 2022//
TI  - Learning about spatial and temporal proximity using tree-based methods
JO  - Statistics, politics and policy
A1  - Levin, Ines
SP  - 73
EP  - 95
VL  - 13
IS  - 1
N2  - Learning about the relationship between distance to landmarks and events and phenomena of interest is a multi-faceted problem, as it may require taking into account multiple dimensions, including: spatial position of landmarks, timing of events taking place over time, and attributes of occurrences and locations. Here I show that tree-based methods are well suited for the study of these questions as they allow exploring the relationship between proximity metrics and outcomes of interest in a non-parametric and data-driven manner. I illustrate the usefulness of tree-based methods vis-à-vis conventional regression methods by examining the association between: (i) distance to border crossings along the US-Mexico border and support for immigration reform, and (ii) distance to mass shootings and support for gun control.<p />  <p>Language: en</p>
LA  - en
SN  - 2194-6299
UR  - http://dx.doi.org/10.1515/spp-2021-0031
ID  - ref1
ER  -