id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-338024-8kq5nzv5	Lee, Sokbae	Sparse HP filter: Finding kinks in the COVID-19 contact rate()	2020-09-26		.txt	text/plain	7358	569	75	In this paper, we estimate the time-varying COVID-19 contact rate of a Susceptible-Infected-Recovered (SIR) model. To estimate a SIR-type model, Fernández-Villaverde and Jones (2020) allowed for a time-varying contact rate to reflect behavioral and policy-induced changes associated with social distancing. To extract the time-varying signal from the noisy measurements, we consider nonparametric trend filters that produce possibly multiple kinks in β t where the kinks are induced by government policies and changes in individual behavior. To document and monitor outbreaks of COVID-19, we propose to use piecewise constant contact growth rates using the piecewise linear trend estimates from the sparse HP filter. Table 1 reports the time-varying contact growth rates in the five countries that we investigate, using the sparse HP trend estimates. We have developed a novel method to estimate the time-varying COVID-19 contact rate using data on actively infected, recovered and deceased cases.	./cache/cord-338024-8kq5nzv5.txt	./txt/cord-338024-8kq5nzv5.txt