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Estimating demand elasticities using nonlinear pricing

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  • Dalton, Christina M.

Abstract

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.

Suggested Citation

  • Dalton, Christina M., 2014. "Estimating demand elasticities using nonlinear pricing," International Journal of Industrial Organization, Elsevier, vol. 37(C), pages 178-191.
  • Handle: RePEc:eee:indorg:v:37:y:2014:i:c:p:178-191
    DOI: 10.1016/j.ijindorg.2014.08.007
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Michael Gerfin & Boris Kaiser & Christian Schmid, 2015. "Healthcare Demand in the Presence of Discrete Price Changes," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1164-1177, September.
    2. Herr, A. & Suppliet, M., 2011. "Co-Payment Exemptions and Reference Prices: an Empirical Study of Pharmaceutical Prices in Germany," Health, Econometrics and Data Group (HEDG) Working Papers 11/18, HEDG, c/o Department of Economics, University of York.
    3. Minke Remmerswaal & Jan Boone & Michiel Bijlsma & Rudy Douven, 2017. "Cost-Sharing Design Matters: A Comparison of the Rebate and Deductible in Healthcare," CPB Discussion Paper 367, CPB Netherlands Bureau for Economic Policy Analysis.
    4. Bijlsma, Michiel & Boone, Jan & Douven, Rudy & Remmerswaal, Minke, 2017. "Cost-Sharing Design Matters: A Comparison of the Rebate and Deductible in Healthcare," CEPR Discussion Papers 12507, C.E.P.R. Discussion Papers.
    5. Patrick Bajari & Christina Dalton & Han Hong & Ahmed Khwaja, 2014. "Moral hazard, adverse selection, and health expenditures: A semiparametric analysis," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 747-763, December.
    6. Kairies-Schwarz, Nadja & Harrison, Glenn W. & Han, Johann, 2018. "Deductibles and Health Care Utilization: An Experiment on the Role of Forward-Looking Behavior," Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181588, Verein für Socialpolitik / German Economic Association.
    7. Remmerswaal, Minke & Boone, Jan & Bijlsma, Michiel & Douven, R.C.M.H., 2017. "Cost-Sharing Design Matters : A Comparison of the Rebate and Deductible in Healthcare," Discussion Paper 2017-039, Tilburg University, Tilburg Law and Economic Center.
    8. Haizhen Lin & Daniel W. Sacks, 2016. "Intertemporal Substitution in Health Care Demand: Evidence from the RAND Health Insurance Experiment," NBER Working Papers 22802, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Elasticity; Nonlinear; Health insurance; Moral hazard;

    JEL classification:

    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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