Volume 3, Issue 4 (10-2018)                   hrjbaq 2018, 3(4): 245-253 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Golkhandan A. Testing the Hypothesis of Health Induced Demand in Iran Using the Bayesian Model Averaging. hrjbaq. 2018; 3 (4) :245-253
URL: http://hrjbaq.ir/article-1-265-en.html
Department of Economics, Faculty of Economics and Administrative, Lorestan University, Khorram Abad, Iran , (golkhandana@gmail.com)
Abstract:   (1085 Views)

Introduction: The number of physicians and hospital beds is one of the major factors affecting on health costs in the supply side, which is posited in the health economics issues called inductive demand hypothesis. According to this hypothesis, health care demand may be due to asymmetric information in health market, is influenced by the behavior of health suppliers. Therefore, the purpose of this study is to evaluation of inductive demand health hypothesis in Iran.
Materials and Methods: This study using time series data from 1979-2013 is paid to study effect of per capita the number physicians and per capita the number hospital beds on per capita health sector costs. To this purpose, the Bayesian averaging approach has been used. Also, the statistical analyzes were performed using the R software.
Results: Estimation of 40000 regressions and Bayesian averaging of coefficients shows that the effect of physician's per capita variable on per capita health sector costs with a probability of 0.49 and a coefficient of 0.20 is non- fragile and strong. However, the impact of the per capita the number hospital beds on the per capita health sector costs is fragile and meaningless.
Conclusions: The results of the research indicate that the health inductive demand hypothesis is confirmed for the number of physician, and rejected for the number of hospital beds; Therefore, policies and strategies that will lead to a reduction in physician induced demand in the country is essential.

Full-Text [PDF 600 kb]   (519 Downloads)    
Type of Study: Research | Subject: General
Received: 2018/09/4 | Revised: 2018/12/5 | Accepted: 2018/11/3 | ePublished ahead of print: 2018/11/3 | Published: 2018/12/4

1. Newhouse JP. Medical-care expenditure: a cross-national survey. J Human Resources. 1977;12(1):115-25.
2. Magazzino C, Mele M. The determinants of health expenditure in Italian regions. Inter J Economy & Finance 2012;4(3):61-72.
3. Sekimoto M, Ii M. Supplier-Induced Demand for Chronic Disease Care in Japan: Multilevel Analysis of the Association between Physician Density and Physician-Patient Encounter Frequency. Value Health Reg Issues. 2015;6:103-10. DOI: 10.1016/j.vhri.2015.03.010 PMID: 29698180
4. Khorasani E, Keyvanara M, Karimi S, Jafarian Jazi M. The Role of patients in induced demand from experts’ perception: A qualitative study. J Qualitat Res in Health Sci. 2014;2(4):336-45.
5. Shain M, Roemer MI. Hospital costs relate to the supply of beds. Mod Hosp. 1959;92(4):71-3 passim. PMID: 13644010
6. Roemer MI. Bed supply and hospital utilization: a natural experiment. Hospitals. 1961;35:36.
7. Panahi H, Salmani B, Nasibparast S. Inductive Effect of Physicians Number and Hospital Bed on Health Expenditures in Iran. Quarter J Apply Theory Economy. 2015;2(2):25-42.
8. Pauly M. Doctors and Their Workshops: Economic Models of Physician Behavior, 1980. University of Chicago Press.
9. Yuda M. Medical fee reforms, changes in medical supply densities, and supplier-induced demand: Empirical evidence from Japan. Hitotsubashi J Economy. 2013:79-93.
10. Nassiri A, Rochaix L. Revisiting physicians' financial incentives in Quebec: a panel system approach. Health Econ. 2006;15(1):49-64. DOI: 10.1002/hec.1012 PMID: 16167322
11. Hosoya K. Determinants of health expenditures: Stylized facts and a new signal. Modern Economy. 2014;5(13):1171.
12. Khani M. Evaluation of the Physicians Induced Demand: Case Study of Cesarean in Iran: Sharif University of Technology; 2012.
13. Filippini M, Masiero G, Moschetti K. Socioeconomic determinants of regional differences in outpatient antibiotic consumption: evidence from Switzerland. Health Policy. 2006;78(1):77-92. DOI: 10.1016/j. healthpol.2005.09.009 PMID: 16290129
14. Crivelli L, Filippini M, Mosca I. Federalism and regional health care expenditures: an empirical analysis for the Swiss cantons. Health Economics. 2006;15(5):535-41.
15. Varharami V. [Evaluation of the Physician Induced Demand]. J Healthcare Manage. 2010;2:3742.
16. Golkhandan A, Fatholahi E. [Offering and Testing a Model to Explain the Physician Induced Demand in Iran]. J healthcare manage. 2017;7(4):29-40.
17. Liu C, Maheu JM. Forecasting realized volatility: a Bayesian model‐averaging approach. J Apply Economy. 2009;24(5):709-33.
18. Draper D. Assessment and propagation of model uncertainty. J Royal Statistical Society Series B (Methodological). 1995:45-97.
19. Doppelhofer G, Miller RI, Sala-i-Martin X. Determinants of long-term growth: A Bayesian averaging of classical estimates (BACE) approach. American Economic Review. 2004;94(4):813-35.
20. Bilgel F, Tran KC. The determinants of Canadian provincial health expenditures: evidence from a dynamic panel. Applied Economics. 2013;45(2):201-12.
21. Rezaei S, Dindar A, Rezapour A. Health care expenditures and their determinants: Iran provinces (2006-2011). J Health Administration (JHA). 2016;19(63).
22. Ang JB. The determinants of health care expenditure in Australia. Applied Economics Letters. 2010;17(7):639-44.
23. Golkhandan A. Measuring the Impacts of Air Pollution on Health Costs in Iran. Health Res J. 2017;2(3):157-66.

Add your comments about this article : Your username or Email:

Send email to the article author

© 2020 All Rights Reserved | Health Research Journal

Designed & Developed by : Yektaweb