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Health systems and healthcare have undergone significant progress and change in recent years. The cost of healthcare and health spending have dramatically increased due to these problems on a global scale. But it cannot be sustained. Governments have therefore been looking for measures to lower the price of services in the health sector. In this respect, the major goal of the study was to identify the determinants of health expenditure in Southeast Asia, taking into account ten out of eleven countries.. It was found that GDP per capita and the inflation rate (GDP deflator) were the most important factors affecting health expenditure in Southeast Asia (p < 0.05) and also, that school enrollment rate (tertiary level), unemployment rate and age dependency ratio had not statically significant effect on health expenditure (p > 0.05). This research is intended to focus on socioeconomic factors, therefore there may be other important factors that influence health expenditure that are not captured in the analysis. Thus, it is suggested that the following studies should also take a wider perspective into account. KEYWORDS: Health expenditure; GDP; educational level; inflation; unemployment; age dependent; urbanization
https://tailieuluatkinhte.com/ FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS -*** - ECONOMETRICS REPORT THE SOCIOECONOMIC DETERMINANTS OF HEALTH EXPENDITURE IN SOUTHEAST ASIAN COUNTRIES FROM 2000 TO 2020 Group: Class: KTEE318 Lecturer: PhD Đinh Thị Thanh Bình Hanoi – 6/ 2023 ABSTRACT Health systems and healthcare have undergone significant progress and change in recent years The cost of healthcare and health spending have dramatically increased due to these problems on a global scale But it cannot be sustained Governments have therefore been looking for measures to lower the price of services in the health sector In this respect, the major goal of the study was to identify the determinants of health expenditure in Southeast Asia, taking into account ten out of eleven countries It was found that GDP per capita and the inflation rate (GDP deflator) were the most important factors affecting health expenditure in Southeast Asia (p < 0.05) and also, that school enrollment rate (tertiary level), unemployment rate and age dependency ratio had not statically significant effect on health expenditure (p > 0.05) This research is intended to focus on socioeconomic factors, therefore there may be other important factors that influence health expenditure that are not captured in the analysis Thus, it is suggested that the following studies should also take a wider perspective into account KEYWORDS: Health expenditure; GDP; educational level; inflation; unemployment; age dependent; urbanization TABLE OF CONTENT ABSTRACT INTRODUCTION CHAPTER I: LITERATURE REVIEW 1.1 Health expenditure 1.2 Determinants of health expenditure CHAPTER II: METHODOLOGY & MODEL SPECIFICATION 11 2.1 Methodology 11 2.1.1 Data sources 11 2.1.2 Data processing 11 2.1.3 Deriving the model .11 2.2 Theoretical model specification 13 2.2.1 Specifying the theoretical model 13 2.2.2 Variable specification 13 2.2.3 Theoretical relationship between variables 14 2.3 Data description .16 CHAPTER III: QUANTITATIVE ANALYSIS 20 3.1 Model selection: fixed effect model (FE) and random effect model (RE) 20 3.2 Regression model .21 3.3 Diagnosing the problems of the model 22 3.3.1 E(u|X) = 22 3.3.2 Multicollinearity 22 3.3.3 Normality of u .23 3.3.4 Heteroskedasticity .23 3.3.5 Autocorrelation 24 3.4 Correcting model .25 3.5 Hypothesis test 25 3.6 Result analysis 26 3.6.1 Statistical meaning of the regression coefficient 26 3.6.2 The model’s coefficient of determination 27 3.6.3 Interpretation of the estimated results obtained 28 CONCLUSION 30 REFERENCES 31 APPENDIX 33 INTRODUCTION Importance of the study Health is one of the most important indicators of human development and spending upon it makes a man physically and mentally fit The development of society associates with the increasing concern for health in general In the wake of COVID 19 pandemic, spending for better health was obviously incremental, these spending attributes to the term called “health expenditure” To achieve sustainable development, a country needs to optimize their health expenditure, not only the government's fund for public health but also citizen’s private health expenditure Developed countries have successfully implemented the system to evaluate their total health expenditure, so that they can easily supply enough medical infrastructures that satisfy their demand There are a lot of previous research that points out the importance of health infrastructure as well as the determinants that affect the level of health infrastructure in different countries The results are much similar, however, in our research, we will focus on socioeconomic forces instead of merely economic or social aspects Moreover, we want to discover the driving determinants that lead to the change in total spending for health in Southeast Asian countries so that they can help the authorities to have information about future health infrastructure and also help achieve other economic goals Objects and Scope The object of this research is to answer the question: “What are the determinants of health expenditure in Southeast Asian countries” To evaluate the relationship between some socioeconomic factors and total health expenditure, we use the panel data of 10 Southeast Asian countries from 2000 2020 This range of data helps us have an overall look at the variation of health expenditure across different aspects during different time Structure of the research Our research contains main chapter: Chapter 1: Literature review: The review of previous research about health expenditure that helps us to determine the variables that should be included in the model Chapter 2: Methodology & Model specification ● The specification of model used and methodology to derive the model and data ● The overall outlook at the relationship between independent variables Chapter 3: Quantitative analysis: The regression result and model implication CHAPTER I: LITERATURE REVIEW 1.1 Health expenditure According to the World Health Organization (WHO), health expenditure includes all expenditures for the provision of health services, family planning activities, nutrition activities and emergency aid designated for health, but it excludes the provision of drinking water and sanitation Our research uses per capita total expenditure on health - This indicator is defined as the per capita total expenditure on health, expressed at the average exchange rate for that year in US$ It shows the total expenditure on health relative to the beneficiary population, expressed in US$ to facilitate international comparisons These indicators reflect government and total expenditure on health resources, access and services, including nutrition, in relation to government expenditure, the country's wealth, and the population Although increasing health expenditure is associated with better health outcomes, especially in low-income countries, there is no 'recommended' level of spending on health The larger the per capita income, the greater the expenditure on health Some countries, however, spend appreciably more than would be expected from their income levels, and some appreciably less When a government attributes proportionately less of its total expenditure on health, this may indicate that health, including nutrition, is not regarded as a priority 1.2 Determinants of health expenditure In the wake of COVID–19 pandemic, the huge increases in health expenditure around the world have forced the countries to emphasize the issues related to health Health expenditure is affected by economic factors (income, out – of – pocket expenditure, health financing, etc.), but it is affected by sociodemographic factors (population, age, location, etc.) as well Within the scope of our research, we focus on the relationship between social economic factors and total health expenditure Yetim et al (2020) conducted the research to figure out the predictors of health expenditure in OECD using panel ordinary least square regression (OLS) analysis which covers the period of 2000 – 2017 The result from the logarithms model indicated that education level had a statistically significant and positive effect on health expenditure Another finding of the analysis was that inflation also impacted total health expenditure in a negative way, a higher inflation rate refers to decreasing purchasing power Some other factors such as unemployment rate and age dependency ratio were found to have insignificant impact on health expenditure In the study of Bedado et al (2022), they revealed a significant association between advancing age and urban residency with a higher likelihood of incurring health expenditures By using the cross-sectional study and the logistic regression analysis, the authors concluded that individuals residing in urban areas exhibited a substantially higher probability, approximately four times greater, of incurring out-ofpocket healthcare expenditures compared to their counterparts residing in rural areas In addition, their study pointed out that individuals aged 31–49 years old had significantly higher odds, approximately 2.58 times greater, of bearing out-of-pocket healthcare expenditures compared to participants younger than 31 years old Similar results were also obtained by Matteo et al (1998), Lopreite and Zhu, (2020) But these two papers mainly focused on the group aged above 65 Using a pooled time-series cross-section data set for Canada's provinces over the period 1965–1991, Matteo has estimated that the convergence of two factors, namely the decline in the new Canada Health and Social Transfer and the increasing proportion of the population aged 65 and above, signifies that the issue of provincial health care expenditures is set to remain a formidable challenge within the policy landscape as older adults generally require more extensive and specialized care Moreover, with the use of Bayesian-VAR (B-VAR) models, Lopreite and Zhu have computed the relatively strong relationship between the number of people aged 65 or over and the number of people aged from to 14 and health expenditure per capita in China Age and urban regions again have been proven as effective factors in determining health expenditures (Samadi et al., 2013) By employing panel data econometrics methods, the research findings indicated a negative association between healthcare expenditures and the proportion of individuals under 15 years old and above 65 years old in the long term, as well as urbanization in the short term If a country has a higher proportion of individuals in these age gaps, it is generally regarded as having a healthier population Consequently, such countries tend to exhibit lower healthcare expenditures compared to nations with a less healthy population In contrast to the findings of Samadi, Tian et al (2018)’s research has led to a different conclusion Using data over the period 1990–2012 and applying an instrumental variable quantile regression method for a dynamic panel model, this study suggested that the relationship between the growth of the aging population and healthcare expenditure is not consistently constant Instead, the impact of older populations on healthcare spending depends on the specific stage of per capita health expenditure growth in a particular region or area This implies that the influence of aging populations on healthcare expenditure varies and is contingent upon the developmental phase of healthcare spending in each context Regarding the factor of the unemployment rate, Braendle and Colombier (2016) have revealed a significant positive relationship toward the growth of public healthcare expenditure Unemployment serves as a significant indicator of the prevailing socioeconomic conditions, providing valuable insights into the broader context in which public healthcare expenditure evolves Using dynamic panel estimation methods to analyze the period 1970–2012 the research concluded that because the likelihood of illness is generally higher among the unemployed, including unemployment in the study allows for an examination of its impact on healthcare expenditure growth In terms of GDP growth, both Hitiris and Posnett (1992) and Jakovljevic et al., 2020 have validated the significance of Gross Domestic Product (GDP) as a factor influencing healthcare expenditure Using panel regression analysis, Jakovljevic has estimated that the actual increase in Gross Domestic Product (GDP) had a noteworthy and measurable adverse impact on the current healthcare expenditure represented as a percentage of GDP, per capita healthcare expenditure in Purchasing Power Parity (PPP) using constant 2011 international USD, and individual out-of-pocket expenditure (OOPS) per capita in PPP international USD The growth of real GDP is demonstrated to have a significant and detrimental impact solely on the current healthcare expenditure as a percentage of GDP and per capita healthcare expenditure in constant 2010 USD, both statistically and economically McKinsey estimated that the annual US national health expenditure is likely to be $370 billion higher by 2027 due to the impact of inflation compared with pre pandemic projections The report by OECD in January 2023 found that spending on health jumped by almost 1% of GDP across OECD countries, on average, during the pandemic as governments stepped in to cover unexpected public health and treatment costs The crisis highlighted the need for further investments to strengthen health system resilience in the face of new shocks – estimated to be 1.4% of pre-pandemic GDP, on average across OECD It also concluded that Russia’s war in Ukraine has added to already rising energy costs with inflationary pressures across much of the OECD This has repercussions for the cost of health care, as well as the ability to maintain service levels and address the backlog of care due to the pandemic Turgut et al (2017) analyzed the relationship between total health expenditure and inflation rates It revealed that health expenditure growth rate has a statistically positive effect on the inflation rate and is also higher than the inflation rates Health expenditures vary significantly across countries and over time within countries The variation across countries has been attributed to differences in demographics, life expectancy, infant mortality, socio-economic environment and the structure of health care systems (Payne et al., 2015)