Quantifying domestic violence in times of crisis - Dan Anderberg; Helmut Rainer; Fabian Siudae (Institute for Fiscal Studies (IFS), 2020)
Recent contributions using police recorded calls-for-service and/or crime data to estimate impacts of COVID-19 lockdowns on the incidence of domestic violence (DV) have reported relatively modest effects. This may reflect a low reporting-propensity, exacerbated by the lockdown measures. Combining five years of daily Google Trends data for a set of DV-related search terms with daily data on DV crimes recorded by the London Metropolitan Police Service (MPS), we propose a method for generating a search-based DV-index, exploiting that both sets of data reflect the same inter-temporal variation in the (unobserved) DV incidence. Estimating the same model for the impact of lockdown on police-reported DV crimes and our search-based DV-index, we find a similar timing, but a substantially larger impact on the latter.
Keywords: J12; I18; 330; Coronavirus; COVID-19; domestic violence; police recorded crime; Google Trends; signal-to-noise