Proportional Treatment Effects for Count Response Panel Data: Effects of Binary Exercise on Health Care Demand

2003 ◽  
pp. 117-132 ◽  
Author(s):  
Myoung-Jae Lee ◽  
Satoru Kobayashi
Keyword(s):  
Health Care ◽  
Panel Data ◽  
Treatment Effects ◽  
Response Panel ◽  
Health Care Demand ◽  
Count Response

scholarly journals Determinants of prepaid systems of healthcare financing: a worldwide country-level perspective

2021 ◽  
Author(s):  
Andrea M. Leiter ◽  
Engelbert Theurl
Keyword(s):  
Health Care ◽  
Panel Data ◽  
Health Care Financing ◽  
Value Added ◽  
The Elderly ◽  
Dynamic Panel Data ◽  
Individual Characteristics ◽  
Minor Importance ◽  
Data Set ◽  
Country Level

AbstractIn this paper we examine determinants of prepaid modes of health care financing in a worldwide cross-country perspective. We use three different indicators to capture the role of prepaid modes in health care financing: (i) the share of total prepaid financing as percent of total current health expenditures, (ii) the share of voluntary prepaid financing as percent of total prepaid financing, and (iii) the share of compulsory health insurance as percent of total compulsory prepaid financing. In the econometric analysis, we refer to a panel data set comprising 154 countries and covering the time period 2000–2015. We apply a static as well as a dynamic panel data model. We find that the current structure of prepaid financing is significantly determined by its different forms in the past. The significant influence of GDP per capita, governmental revenues, the agricultural value added, development assistance for health, degree of urbanization and regulatory quality varies depending on the financing structure we look at. The share of the elderly and the education level are only of minor importance for explaining the variation in a country’s share of prepaid health care financing. The importance of the mentioned variables as determinants for prepaid health care financing also varies depending on the countries’ socio-economic development. From our analysis we conclude that more detailed information on indicators which reflect the distribution of individual characteristics (such as income, family size and structure and health risks) within a country’s population would be needed to gain deeper insight into the decisive determinants for prepaid health care financing.

Aid Modalities and Budgetary Response: Panel Data Evidence

2007 ◽  
Vol 143 (4) ◽  
pp. 720-741 ◽  
Author(s):  
George Mavrotas ◽  
Bazoumana Ouattara
Keyword(s):  
Panel Data ◽  
Response Panel

Managing Health Care Demand

2000 ◽  
Vol 22 (5) ◽  
pp. 47
Author(s):  
Scott MacStruvic ◽  
Gary Montrose
Keyword(s):  
Health Care ◽  
Health Care Demand

scholarly journals Do You Have to Win It to Fix It? A Longitudinal Study of Lottery Winners and Their Health-Care Demand

2018 ◽  
Vol 4 (1) ◽  
pp. 26-50 ◽  
Author(s):  
Terence C. Cheng ◽  
Joan Costa-Font ◽  
Nattavudh Powdthavee
Keyword(s):  
Health Care ◽  
Longitudinal Study ◽  
Health Care Demand

scholarly journals Experiencia comparada europea y el reto de la descentralización sanitaria

2020 ◽  
Vol 32 (2) ◽  
pp. 841
Author(s):  
Carla Blázquez-Fernández ◽  
David Cantarero-Prieto ◽  
Marta Pascual-Sáez
Keyword(s):  
Health Care ◽  
Panel Data ◽  
Health Outcomes ◽  
Health Expenditure ◽  
Econometric Model ◽  
Fiscal Decentralization ◽  
Health Data ◽  
Panel Data Models ◽  
Demand And Supply ◽  
European Health

This paper analyzes the main characteristics of European health care decentralization models with special attention to the determinants of health outcomes and expenditures and proposes using panel data models, and data from OECD Health Data, an econometric model explaining their behaviour and evolution. The results show that income is the most important factor in explaining the volume of health expenditure both statically and dynamically, while other factors of demand and supply and the degree of decentralization or type of health system, despite also influence are less important. Instead, in health outcomes fiscal decentralization has a more mixed against other factors.

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