Quantifying Domestic Violence in Times of Crisis

Dan Anderberg, Helmut Rainer and Fabian Siuda

No 8593, CESifo Working Paper Series from CESifo

Abstract: We propose a model that (i) provides an algorithm for measuring temporal variation in domestic violence incidence based on internet search activity and (ii) makes precise the conditions under which this measure yields less biased estimates of the domestic violence problem during periods of crisis than traditional, police-recorded crime measures. Analyzing the COVID-19 lockdown in Greater London, we find a 40 percent peak increase in our internet search-based domestic violence index, 7-8 times larger than the increase in police recorded crimes and much closer to the increase reported by victim support charities in relation to helpline calls.

Keywords: COVID-19; domestic violence; police-recorded crime; internet search data; signal-to-noise (search for similar items in EconPapers)
JEL-codes: I18 J12 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Working Paper: Quantifying domestic violence in times of crisis (2020)
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