Professor Mark Kelson

Causality@Exeter: Seminar Series - Assessing the impact of violence reduction units.

Open to University of Exeter staff and students

An Institute for Data Science and Artificial Intelligence seminar
Date1 March 2021
Time14:00 to 15:00
PlaceOnline

Join us for the first in this series of seminars looking at Causality research at Exeter.

Professor Mark Kelson - Department of Mathematics: Assessing the impact of violence reduction units

Understanding whether one thing causes another is a central goal of much of data science.  For example, understanding causal and effect relationships allows us to answer questions such as “Does this treatment harm or help patients?”  However, much of data science, machine learning and statistics is built on correlations.  This seminar series brings together researchers across the University working on and using causal analysis with the aims of understanding different approaches to causal analysis and developing new collaborations and methods.  Starting with University of Exeter experts in causal analysis, the seminars will expand to include external visitors. 

Register to attend the seminar here.


Abstract

Assessing the impact of violence reduction units

In summer 2019 the UK government announced 35 million in funding for violence reduction units in the 18 police boards with highest levels of violence in preceding years (regression to the mean klaxon). Violence reduction units are designed to tackle serious violence and its causes. The same police forces also received additional SURGE funding which has a specific focus on enforcement (contamination of the intervention group klaxon). Since then we have experienced the COVID-19 pandemic and associated lockdowns which are naturally expected to have influenced all kinds of behaviours, including crime (general how-should-we-handle-this klaxon). The Home Office would like to know how effective their investment has been. 

I have been involved (with external partners) in the evaluation of the effect of such funding. This endeavour involves many approaches, including difference in difference estimation, synthetic control groups, and divergent validity analysis. I will give an overview of my pathway into causal inference as well as giving a summary of the proposed approaches (no results will be presented as the project is due to finish in April).

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