Page 146 - GHES-2-4

Global Health Economics and
Sustainability
Silver economy and long-term care

= 0.9613). According to these results, the econometric Table 2. Least squares test results
model was analyzed under the RE model, revealing that
the independent variables had a good explanatory power Dependent Independent Coefficient Significance
variable
variable
on the dependent variable; however, multicollinearity,
cross-sectional dependence, and autocorrelation LEAB 2.168702 0.0000
problems persisted in the model. Therefore, the new LTCFE LEO65 −0.543117 0.0338*
model was re-estimated under the AR(1) model, and AR (1) 0.978071 0.0000
no multicollinearity, cross-sectional dependence, or Diagnostic test results: Breusch–Pagan LM=0.0265*; Pesaran scaled
autocorrelation problem (at a 1% significance level) were LM=0.0447*; Durbin Watson=1.926913; Skewness Value=0.508116;
2=
2=
found. According to the least squares results in Table 2, a Kurtosis Value=5.658287; R 0.99; Adjusted R 0.99. * denotes a 5%
significance level; variables are used in logarithmic form in the analysis.
1% increase in the LEAB increased LTCFE by 2.1%, while Abbreviations: LTCFE: Expenditures on long-term care facilities;
a 1% increase in the LEO65 decreased LTCFE by 0.54%. LEAB: Life expectancy at birth; LEO65: Life expectancy at 65 years and
Furthermore, diagnostic tests showing the validity of least over.
squares analyses confirm the suitability of the econometric
model established in the research. Table 3. Unit root test results
At this stage, the augmented Dickey-Fuller Fisher Chi- Variables Augmented Dickey‑Fuller Level
square test, which is a unit root test, was done to determine Fisher Chi‑square test
whether the variables were stationary (Levin et al., 2002). LTCFE 0.0000* I (0)
In these tests, the null hypothesis indicates the presence LEAB 0.0002* I (0)
of a unit root, and the alternative hypotheses indicate the LEO65 0.0000* I (0)
absence of a unit root. Table 3 shows that all variables were *1% significance level.
stationary at the 1% significance level. Abbreviations: LTCFE: Expenditures on long-term care facilities;
Causality analysis is a technique used to explain the LEAB: Life expectancy at birth; LEO65: Life expectancy at 65 years and
causal relationship between two variables. It evaluates over.
whether the lagged values of the other variable (for example, Table 4. Dumitrescu Hurlin panel causality test results
the X variable) in a relationship contribute to explaining
t
the current value of one of the variables (for example, the Y t Null hypothesis W‑Stat. ZbarStat Prob. Decision
variable) (Granger, 1969). This study used the DH causality LEO65 ≠|> LTCFE 4.08902 2.45029 0.0143* LEO65→LTCFE
method to determine the causal relationship between LTCFE ≠|> LEO65 2.98160 0.73955 0.4596 LEAB→LTCFE
the variables. Panel causality analyses developed by LEAB ≠|> LTCFE 4.02408 2.34998 0.0188*
Dumitrescu and Hurlin (2012) do not require testing the LTCFE ≠|> LEAB 2.94350 0.68071 0.4961
cointegration relationship between variables; they provide
more effective and consistent results in cases of horizontal LEAB ≠|> LEO65 2.14428 0.55108 0.5816
cross-section dependence and take heterogeneity and LEO65 ≠|> LEAB 2.27707 0.34536 0.7298
short time dimension into account (Tang et al., 2009). The *5% significance level.
results obtained in the analysis revealed unidirectional Abbreviations: LTCFE: Expenditures on long-term care facilities;
causality relationships of LEAB and LEO65 with LTCFE. LEAB: Life expectancy at birth; LEO65: Life expectancy at 65 years and
over.
According to this result, changes in LEAB and LEO65
unilaterally affected LTCFE. Table 4 presents the results. 65 years and over (Colombo et al., 2011). In addition,
the global long-term care industry was projected to
4. Discussion reach a market value of $1.6 trillion, with an annual
Elderly populations in OECD countries are increasing growth rate of 8.5% between 2021 and 2027 (Ugalmugle
because of high life expectancy and declining fertility rates. & Swain 2021). The need for long-term care also means
While the share of the population aged 65 years and over in increased health expenditures. A study examining the
these countries averaged <9% in 1960, it increased to 17% in expenditures per patient during the 60 months before
2015 and is expected to reach 28% by 2050 (OECD, 2017). death calculated total long-term care expenditure
The aging of the population brings a significant as USD48, 319, of which USD27, 217 belonged to
increase in the number of individuals with diseases institutional care services and USD21, 102 to home
requiring long-term care, such as chronic and mental care services (Teraoka et al., 2021). French et al. (2017)
disorders. The demand for long-term care is considered determined that health expenditure per capita in the
age-related and mostly demanded by individuals aged past 12 months of life was USD80,000 in the United

Volume 2 Issue 4 (2024) 5 https://doi.org/10.36922/ghes.3298