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Managing the demand volatility of a municipal service system during a slow-onset disaster


Local governments encounter substantial difficulties when it comes to maintaining service provision during extended crises like droughts or pandemics. These crises exhibit fluctuating impacts over time and are accompanied by changing requirements from the population. This research aims to explore the impact of notable volatility in service demands on the productivity of public service systems during slow-onset disasters. The paper uses econometric time series analysis for empirically assessing the irregular and conditional variation in daily service demand caused by slow-onset disasters. The model is applied to and tested on publicly available government service data from New York City’s 311 non-emergency service system during the COVID-19 pandemic. 

Key words: Public service systems, 311, Productivity, Time Series.

ey words : public service systems; 311; productivity; theory of swift even flow; time Series, GARCH

Annualized rolling volatility patterns of Bronx County non-emergency call groups