Analysing differences between scenarios

dc.contributor.authorHendry, David F.
dc.contributor.authorPretis, Felix
dc.date.accessioned2023-12-15T19:20:42Z
dc.date.available2023-12-15T19:20:42Z
dc.date.copyright2023en_US
dc.date.issued2023
dc.description.abstractComparisons between alternative scenarios are used in many disciplines, from macroeconomics through epidemiology to climate science, to help with planning future responses. Differences between scenario paths are often interpreted as signifying likely differences between outcomes that would materialise in reality. However, even when using correctly specified statistical models of the in-sample data generation process, additional conditions are needed to sustain inferences about differences between scenario paths. We consider two questions in scenario analyses: First, does testing the difference between scenarios yield additional insight beyond simple tests conducted on the model estimated in-sample? Second, when does the estimated scenario difference yield unbiased estimates of the true difference in outcomes? Answering the first question, we show that the calculation of uncertainties around scenario differences raises difficult issues, since the underlying in-sample distributions are identical for both ‘potential’ outcomes when the reported paths are deterministic functions. Under these circumstances, a scenario comparison adds little beyond testing for the significance of the perturbed variable in the estimated model. Resolving the second question, when models include multiple covariates, inferences about scenario differences depend on the relationships between the conditioning variables, especially their invariance to the interventions being implemented. Tests for invariance based on the automatic detection of structural breaks can help identify the in-sample invariance of models to evaluate likely constancy in projected scenarios. Applications of scenario analyses to impacts on the UK’s wage share from unemployment and agricultural growth from climate change illustrate the concepts.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipDavid F Hendry reports financial support was provided by Robertson Foundation. David F Hendry reports article publishing charges and travel were provided by University of Oxford Nuffield College. Financial support from the Robertson Foundation (grant 9907422), Institute for New Economic Thinking (grant 20029822), and Nuffield College is gratefully acknowledged.en_US
dc.identifier.citationHendry, D. F., & Pretis, F. (2023). Analysing differences between scenarios. International Journal of Forecasting, 39(2), 754-771. https://doi.org/10.1016/j.ijforecast.2022.02.004en_US
dc.identifier.urihttps://doi.org/10.1016/j.ijforecast.2022.02.004
dc.identifier.urihttp://hdl.handle.net/1828/15717
dc.language.isoenen_US
dc.publisherInternational Journal of Forecastingen_US
dc.subjectScenario analysisen_US
dc.subjectClimate changeen_US
dc.subjectForecastingen_US
dc.subjectScenario uncertaintyen_US
dc.subjectTime seriesen_US
dc.subjectInvarianceen_US
dc.titleAnalysing differences between scenariosen_US
dc.typeArticleen_US

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