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• W3134169144 abstract "The Rubin Causal Model (RCM) is a framework that allows to define the causal effect of an intervention as a contrast of potential outcomes. In recent years, several methods have been developed under the RCM to estimate causal effects in time series settings. However, none of these make use of ARIMA models, which are instead very common in the econometrics literature. In this paper, we propose a novel approach, C-ARIMA, to define and estimate the causal effect of an intervention in a time series setting under the RCM. We first formalize the assumptions enabling the definition, the estimation and the attribution of the effect to the intervention; we then check the validity of the proposed method with an extensive simulation study, comparing its performance against a standard intervention analysis approach. In the empirical application, we use C-ARIMA to assess the causal effect of a permanent price reduction on supermarket sales." @default.
• W3134169144 created "2021-03-15" @default.
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• W3134169144 date "2021-03-11" @default.
• W3134169144 modified "2023-09-27" @default.
• W3134169144 title "Estimating the causal effect of an intervention in a time series setting: the C-ARIMA approach" @default.
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• W3134169144 hasPublicationYear "2021" @default.
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