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Reducing pharmaceutical reimbursement price risk to lower national health expenditures without lowering R&D incentives

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  • Hiroshi Nakamura

    (Keio University)

  • Naohiko Wakutsu

    (Nagoya City University)

Abstract

In Japan, higher reimbursement drug prices give pharmaceutical firms stronger R&D incentives, but they also increase the financial burden on national health insurance and patients. Considering the severe financial situation that the government faces, analyzing how to achieve lower national health expenditures without lowering pharmaceutical firms’ existing R&D incentives is important. In this research, we investigate the effect of reducing the reimbursement price risk that pharmaceutical firms face on their R&D incentives. Theoretically, the presence of output price risks reduces risk-averse firms’ R&D incentives. Therefore, to the extent that pharmaceutical firms exhibit risk aversion, if creating guidelines, accelerating information disclosure and/or enabling public–private dialogue can reduce reimbursement price risks, then maintaining or even increasing R&D incentives is possible, even if the level of reimbursement drug prices is reduced. Specifically, we address (1) by how much a given level of reimbursement price risk reduces pharmaceutical firms’ R&D incentives; (2) by how much reimbursement drug prices can be reduced, keeping pharmaceutical firms’ R&D incentives constant, if one can successfully remove the risk; and (3) how the magnitude of the impact changes with the degree of price risk that firms face and with the level of their risk aversion. To this end, a hypothetical new branded drug is constructed from actual data on the Japanese drug market. Assuming that a pharmaceutical firm is an expected-utility maximizer, that the firm’s instantaneous utility function is in the form of the constant-relative-risk-aversion utility function and that its R&D incentives are quantified by the standard discounted cash flow valuation, we use simulations to compute the certainty equivalent and risk premium associated with various degrees of price risk and risk aversion. Referring to the empirical literature on risk preference, we set the parameter value for the level of relative risk aversion of a pharmaceutical firm to 3.0 and that for the discount rate to 0.08. The following results emerged. (1) In the presence of a 20% price risk regarding a reimbursement price of 100 (i.e., ranging from 80 to 120), a pharmaceutical firm’s certainty equivalent is 96.0. Hence, in the presence of a 20% price risk, a risky reimbursement drug price of 100 is equivalent to a sure reimbursement drug price of 96.0. (2) In the presence of a 20% price risk regarding a reimbursement price of 100, the price premium is 4.0. Therefore, by increasing the predictability of future prices, the reimbursement price may decrease by 4.0, while the firm’s R&D incentives remain unchanged. (3) The magnitude of the impact increases at an increasing rate with the degree of price risk and increases at a decreasing rate with the level of risk aversion.

Suggested Citation

  • Hiroshi Nakamura & Naohiko Wakutsu, 2019. "Reducing pharmaceutical reimbursement price risk to lower national health expenditures without lowering R&D incentives," International Journal of Economic Policy Studies, Springer, vol. 13(1), pages 75-88, January.
  • Handle: RePEc:spr:ijoeps:v:13:y:2019:i:1:d:10.1007_s42495-018-0002-7
    DOI: 10.1007/s42495-018-0002-7
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    1. Z. Bar‐Shira & R.E. Just & D. Zilberman, 1997. "Estimation of farmers' risk attitude: an econometric approach," Agricultural Economics, International Association of Agricultural Economists, vol. 17(2-3), pages 211-222, December.
    2. Saha, Atanu, 1997. "Risk Preference Estimation in the Nonlinear Mean Standard Deviation Approach," Economic Inquiry, Western Economic Association International, vol. 35(4), pages 770-782, October.
    3. Hui Guo & Robert F. Whitelaw, 2006. "Uncovering the Risk–Return Relation in the Stock Market," Journal of Finance, American Finance Association, vol. 61(3), pages 1433-1463, June.
    4. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    5. Peter P. Wakker, 2008. "Explaining the characteristics of the power (CRRA) utility family," Health Economics, John Wiley & Sons, Ltd., vol. 17(12), pages 1329-1344, December.
    6. Pope, Rulon D. & LaFrance, Jeffrey T & Just, Richard E., 2007. "Agricultural Arbitrage and Risk Preferences," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt3tw1m1p0, Department of Agricultural & Resource Economics, UC Berkeley.
    7. Michel Normandin & Pascal St-Amour, 1998. "Substitution, risk aversion, taste shocks and equity premia," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 265-281.
    8. Tai-Hsin Huang & Tong-Liang Kao, 2006. "Joint estimation of technical efficiency and production risk for multi-output banks under a panel data cost frontier model," Journal of Productivity Analysis, Springer, vol. 26(1), pages 87-102, August.
    9. Luis Orea & Alan Wall, 2012. "Productivity and Producer Welfare in the Presence of Production Risk," Journal of Agricultural Economics, Wiley Blackwell, vol. 63(1), pages 102-118, February.
    10. Chavas, Jean-Paul & Holt, Matthew T, 1996. "Economic Behavior under Uncertainty: A Joint Analysis of Risk Preferences and Technology," The Review of Economics and Statistics, MIT Press, vol. 78(2), pages 329-335, May.
    11. Elie Appelbaum & Alan D. Woodland, 2010. "The Effects of Foreign Price Uncertainty on Australian Production and Trade," The Economic Record, The Economic Society of Australia, vol. 86(273), pages 162-177, June.
    12. Satyanarayan, Sudhakar, 1999. "Econometric tests of firm decision making under dual sources of uncertainty," Journal of Economics and Business, Elsevier, vol. 51(4), pages 315-325, July.
    13. Ralph S.J. Koijen, 2014. "The Cross-Section of Managerial Ability, Incentives, and Risk Preferences," Journal of Finance, American Finance Association, vol. 69(3), pages 1051-1098, June.
    14. Elie Appelbaum & Aman Ullah, 1997. "Estimation Of Moments And Production Decisions Under Uncertainty," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 631-637, November.
    15. Peter P. Wakker, 2008. "Explaining the characteristics of the power (CRRA) utility family," Health Economics, John Wiley & Sons, Ltd., vol. 17(12), pages 1329-1344.
    16. Pope, Rulon D. & LaFrance, Jeffrey T. & Just, Richard E., 2011. "Agricultural arbitrage and risk preferences," Journal of Econometrics, Elsevier, vol. 162(1), pages 35-43, May.
    17. Pierre‐André Chiappori & Monica Paiella, 2011. "Relative Risk Aversion Is Constant: Evidence From Panel Data," Journal of the European Economic Association, European Economic Association, vol. 9(6), pages 1021-1052, December.
    18. Rulon D. Pope & Richard E. Just, 1991. "On Testing the Structure of Risk Preferences in Agricultural Supply Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(3), pages 743-748.
    19. repec:bla:jfinan:v:59:y:2004:i:1:p:407-446 is not listed on IDEAS
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    More about this item

    Keywords

    Risk; Risk aversion; Drug price; R&D incentive; Simulation;
    All these keywords.

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health

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