# Intolerable nuisances: some laboratory evidence on survivor curve shapes

## Author

Listed:
• Ciril Bosch-Rosa

() (Colegio Universitario de Estudios Financieros
Technische Universität Berlin)

• Christina Aperjis

(Power Auctions)

• Daniel Friedman

(University of California Santa Cruz)

• Bernardo A. Huberman

(HP Labs)

## Abstract

Abstract The fraction of a user population willing to tolerate nuisances of size x is summarized in the survivor curve S(x); its shape is crucial in economic decisions such as pricing and advertising. We report a laboratory experiment that, for the first time, estimates the shape of survivor curves in several different settings. Laboratory subjects engage in a series of six desirable activities, e.g., playing a video game, viewing a chosen video clip, or earning money by answering questions. For each activity and each subject we introduce a chosen level $$x \in [x_{\min }, x_{\max }]$$ x ∈ [ x min , x max ] of a particular nuisance, and the subject chooses whether to tolerate the nuisance or to switch to a bland activity for the remaining time. New non-parametric techniques provide bounds on the empirical survivor curves for each activity. Parametric fits of the classic Weibull distribution provide estimates of the survivor curves’ shapes. The fitted shape parameter depends on the activity and nuisance, but overall the estimated survivor curves tend to be log-convex. An implication, given the model of Aperjis and Huberman (SSRN, doi: 10.2139/ssrn.1672820 , 2011), is that introducing nuisances all at once will generally be more profitable than introducing them gradually.

## Suggested Citation

• Ciril Bosch-Rosa & Christina Aperjis & Daniel Friedman & Bernardo A. Huberman, 2017. "Intolerable nuisances: some laboratory evidence on survivor curve shapes," Experimental Economics, Springer;Economic Science Association, vol. 20(3), pages 601-621, September.
• Handle: RePEc:kap:expeco:v:20:y:2017:i:3:d:10.1007_s10683-016-9501-4
DOI: 10.1007/s10683-016-9501-4
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## References listed on IDEAS

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### JEL classification:

• C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
• D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
• L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms

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