Estimating demand elasticities using nonlinear pricing

• Autores: Christina Dalton
• Localización: International journal of industrial organization, ISSN 0167-7187, Vol. 37, Nº. 1, 2014, págs. 178-191
• Idioma: inglés
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• Resumen

  • Nonlinear pricing is prevalent in industries such as health care, public utilities, and telecommunications. However, this pricing scheme introduces bias into estimating elasticities for welfare analysis or policy changes. I develop a local elasticity estimation method that uses nonlinear price schedules to isolate consumers' expenditure choices from selection and simultaneity biases. This method improves over previous approaches by using commonly-available observational data and requiring only a single general monotonicity assumption. Using claims-level data on health insurance with two nonlinearities, I am able to measure two separate elasticities, and find that elasticity declines from - 0.26 to- 0.09 by the second nonlinearity. These estimates are then used to calculate moral hazard deadweight loss. This method enables estimation of many policies with nonlinear pricing which previous tools could not address.