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The illusion of predictability: How regression statistics mislead experts

Emre Soyer and Robin Hogarth ()

International Journal of Forecasting, 2012, vol. 28, issue 3, 695-711

Abstract: Does the manner in which results are presented in empirical studies affect perceptions of the predictability of the outcomes? Noting the predominant role of linear regression analysis in empirical economics, we asked 257 academic economists to make probabilistic inferences based on different presentations of the outputs of this statistical tool. The questions concerned the distribution of the dependent variable, conditional on known values of the independent variable. The answers based on the presentation mode that is standard in the literature demonstrated an illusion of predictability; the outcomes were perceived to be more predictable than could be justified by the model. In particular, many respondents failed to take the error term into account. Adding graphs did not improve the inference. Paradoxically, the respondents were more accurate when only graphs were provided (i.e., no regression statistics). The implications of our study suggest, inter alia, the need to reconsider the way in which empirical results are presented, and the possible provision of easy-to-use simulation tools that would enable readers of empirical papers to make accurate inferences.

Keywords: Regression; Presentation formats; Probabilistic inference; Prediction; Graphics; Uncertainty (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:28:y:2012:i:3:p:695-711

DOI: 10.1016/j.ijforecast.2012.02.002

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