Template-Type: ReDIF-Paper 1.0
Author-Name: Elias Bouacida
Author-Name-First: Elias
Author-Name-Last: Bouacida
Author-Name: Daniel  Martin
Author-Name-First: Daniel 
Author-Name-Last: Martin
Title: Predictive Power in Behavioral Welfare Economics
Abstract: When choices are inconsistent due to behavioral biases, there is a theoretical debate about whether the structure of a model is necessary for providing precise welfare guidance based on those choices. To address this question empirically, we use standard data sets from the lab and field to evaluate the predictive power of two “model-free” approaches to behavioral welfare analysis. We find they typically have high predictive power, which means there is little ambiguity about what should be selected from each choice set. We also identify properties of revealed preferences that help to explain the predictive power of these approaches.
Creation-Date: 2020
File-URL: http://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/lums/economics/working-papers/LancasterWP2020_008.pdf
File-Format: application/pdf
Number: 296961902
Classification-JEL: I30, C91, D12
Keywords: Welfare economics, behavioral economics, predictive power, revealed preferences
Handle: RePEc:lan:wpaper:296961902