2018
DOI: 10.2139/ssrn.3303308
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Counterfactual Analysis With Artificial Controls: Inference, High Dimensions and Nonstationarity

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Cited by 15 publications
(17 citation statements)
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“…Yet, we remain somewhat cautious about our results in Fig. 4 due to the non-stationarity caveats raised by Masini and Medeiros (2019) and the unavailability of climatic data. Thus, we cannot completely discount the possibility that our results, while robust and significant, could be plagued by oversized tests of no intervention effects or, unlikely as it may seem, mediated by extreme climatic events coinciding with the lockdown.…”
Section: Resultsmentioning
confidence: 81%
See 1 more Smart Citation
“…Yet, we remain somewhat cautious about our results in Fig. 4 due to the non-stationarity caveats raised by Masini and Medeiros (2019) and the unavailability of climatic data. Thus, we cannot completely discount the possibility that our results, while robust and significant, could be plagued by oversized tests of no intervention effects or, unlikely as it may seem, mediated by extreme climatic events coinciding with the lockdown.…”
Section: Resultsmentioning
confidence: 81%
“…Another concern arises from the inspection of the time series used as outcome variables. Indeed, as reported by Masini and Medeiros (2019), the SCM suffers from issues of over-rejection of the null hypothesis of no effect when the data are nonstationary, as is the case for the daily count of fire observations (Fig. 3).…”
Section: Methodsmentioning
confidence: 83%
“…(2.2) is defined as: where is the number of days in the estimation window, and is the penalty parameter. Theoretical justification for the use of LASSO to estimate the parameters in this setup with trends can be found in Masini and Medeiros (2021) .…”
Section: Methodsmentioning
confidence: 99%
“…3.Although the synthetic control method (SCM) is different from the panel data approach (Wan et al, 2018), the time-series nature of the data has been ignored in the SCM literature. Masini and Medeiros (2019) argued that, when the data are nonstationary, the use of the SCM, inferential procedures to evaluate the effects of the intervention, can be misleading. As Bai et al (2014) insisted, the panel data approach might be better.…”
mentioning
confidence: 99%