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The purpose of this paper is to provide a better understanding of the driving forces and structural changes of China as a market provider for Korea. This paper gives the answers for the following questions: How do China’s final demands trigger the growth of its imports from Korea? And what’s the impact of China’s final demands on the import in different industries?

Based on the Multi-Regional Input-Output model and World Input-Output Table database, this paper constructs the non-competitive imports input-output (IO) table of China to Korea. According to this table, we can calculate the induced imports coefficient and comprehensive induced import coefficients of China’s four final demands for imports from Korea in the 56 industries in China.

Among the four driving forces, the strongest one is changes in inventories and valuables. The impact of final consumption expenditure and fixed capital formation is much lower than that of changes in inventories and valuables, but they have a broader impact for the 56 industries. This paper finds out the China’s import induction of the final demands to Korea peaked in 2005 and 2010 and decreased greatly in 2014, so the position of China as market provider for Korea will no longer rise substantially, contrarily it will be in a steady state.

First, this paper constructs the non-competitive IO table to analyze the market provider issues between two countries and provides practical ways and methods for studies on the issues of imports and market provider. Second, this paper investigates the different roles of four final demands on driving force of China as market provider for Korea and the structural changes of China as a market provider for Korea among 56 industries from 2000 to 2014.

This paper aims to investigate the efficiency implications of belonging to a strategic hospital alliance (SHA) and measuring the effects over capacity utilization of such agreements in a Mexican healthcare context.

Data Envelopment Analysis (DEA) is the nonparametric methodology used, which supports both objectives. Technological gaps ratios are calculated by using DEA-metafrontier approach to compare efficiency between SHA members and a hospital’s control group. Also, hospital capacity utilization ratios are used as the maximum rate of output possible from fixed inputs in a frontier setting using directional distance functions. Data were collected from an alliance called Consorcio Mexicano de Hospitales in México, which has 29 general private hospitals and a group of 47 hospitals with same characteristics from a database made by the Instituto Nacional de Estadística y Geografía for year 2014.

The results indicate that efficiency is better at hospitals that belong to an alliance; it also shows an improvement of installed capacity management for hospital alliances in México.

The results can be useful for both private health organization managers and regulators themselves to adopt management practices that may end up having a favorable impact on cost and prices containment. Additionally, there are no previous studies neither in Mexico nor in Latin America that analyze the impact of strategic hospitality alliances on the efficiency and utilization of the capacity of private hospitals.

Este documento tiene como objetivo investigar las implicaciones de pertenecer a una alianza hospitalaria estratégica (AHE) en la eficiencia, así como cuantificar los efectos sobre la utilización de la capacidad de dichos acuerdos en el contexto mexicano de atención médica.

El Análisis Envolvente de Datos (DEA) es la metodología no paramétrica utilizada para lograr ambos objetivos. Las brechas tecnológicas se estiman empleando meta-fronteras calculadas mediante modelos DEA, comparando la eficiencia entre los miembros de la AHE y un grupo de control de hospitales. El nivel de utilización de la capacidad hospitalaria se calcula, utilizando funciones direccionales de distancia, a partir del máximo output alcanzable a partir de la dotación de inputs fijos. Los datos fueron obtenidos de la alianza Consorcio Mexicano de Hospitales en México, integrada por 29 hospitales privados generales, y de un grupo de 47 hospitales con las mismas características obtenidos de una base de datos del Instituto Nacional de Estadística y Geografía para el año 2014.

adosLos resultados indican que los niveles de eficiencia son superiores en los hospitales pertenecientes a la alianza, así como una mejor gestión de la capacidad instalada en la alianza hospitalaria en México.

Los resultados pueden ser útiles tanto para los administradores de las organizaciones de salud privadas como para los reguladores, de forma que puedan adoptar prácticas de gestión con un impacto favorable en la contención de costos y precios. Asimismo, no existen estudios previos ni en México ni en América Latina que analicen el impacto de las alianzas estratégicas hospitalarias en la eficiencia y la utilización de la capacidad de los hospitales privados.

This article investigates the relative impact which marketing growth strategies have on profit performance as opposed to strategic debt utilisation, asset management, and margin management. A structural equation approach is used to assess which areas deserve the greatest attention in the process of making strategic decisions. Implications for management and future research are offered.

We compare two approaches to measuring inequity in the health distribution. The first is the concentration index. The second is the calculation of the inequality in an overall measure of individual well-being, capturing both the income and health dimensions. We introduce the concept of equivalent income as a measure of well-being that respects preferences with respect to the trade-off between income and health, but is not subjectively welfarist since it does not rely on the direct measurement of happiness. Using data from a representative survey in France, we show that equivalent incomes can be measured using a contingent valuation method. We present counterfactual simulations to illustrate the different perspectives of the approaches with respect to distributive justice.

This chapter attempts to study the long-term determinants of public and private healthcare expenditure in Hong Kong, by employing time series data over the period from 1990 to 2017. We find that income is not a determinant of either public or private spending per capita on healthcare services. Rather, a higher proportion of elderly will raise public expenditure on health and private spending even more. The share of children within the population will conversely decrease both public and private spending. Results also show that the rising density of doctors decreases both public and private per capita healthcare spending, showing that the supplier-induced demand problem is not an issue in Hong Kong.

This article aims to relate investments in human capital to the United Nations Sustainable Development Goals (UN SDGs), and examine the spending levels necessary to achieve high performance in related SDG sectors for Azerbaijan.

Employing data from the World Bank, the empirical approach undertaken in this study relies on peer analysis by examining spending levels for nations exhibiting similar income levels and geographical proximity to Azerbaijan.

This study estimates that total spending in education would need to increase by 0.4 percentage points of GDP by 2030, while total spending in health would need to increase by 5.9 percentage points of GDP by 2030 for Azerbaijan.

This study contributes to the literature by conducting an empirical analysis in which other nations can emulate in measuring their relative progress on human capital investments and related UN SDGs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0137

This study investigates the impact of total health expenditure on life expectancy in a panel of 43 African countries from 2000 to 2018.

The dynamic panel generalized method of moments (GMM) estimation method developed by Arellano and Bond (1991) is used in this study. This approach generates estimates that are heteroskedasticity and autocorrelation consistent, as well as controls for unobserved time-invariant country-specific effects and eliminates any endogeneity in the panel model.

The results reveal that health expenditure on its own has a positive significant influence on life expectancy. However, health expenditure via the moderating effect of government effectiveness reduces life expectancy. The authors also observe that school enrollment and the level of economic activity significantly drive life expectancy.

The study is limited to 43 out of 54 African countries, and it covers a period of 18 years: 2000 to 2018.

The authors argue that larger health expenditure will aid in improving the life expectancy rate in Africa. However, in practice, this would be difficult given the needs of other priority sectors.

Since most developing countries' health expenditures are small, a policy option is that healthcare services should be subsidized such that the poorest people can also access them.

The study differs from the previous attempts, and with this, the authors contribute significantly to the literature. First, to the best of the authors’ knowledge, the authors are unaware of any study considering the role of government effectiveness as a moderating factor in investigating the effect of health expenditure on life expectancy in the African context. Thus, the authors fill a yawning gap in the literature. Second, the authors employ a recent dataset with larger sample size. Finally, to address the problem of endogeneity and simultaneity bias, the authors use the system GMM technique.

The unresolved crisis scenario and a prolonged COVID-19 pandemic increased social inequalities, mainly affecting the most vulnerable groups to access health services. The data in Pakistan show that health coverage benefits less than half of the population and a weak health system forces households to finance their health with out-of-pocket expenses. Therefore, it is a pending task to guarantee universal health coverage and design sustainable and inclusive policies to finance and provide health services. This study aims to offer a unique solution for health financing to Pakistan.

This study uses the VECM model by employing the data from Pakistan to indicate sustainable policies for health financing.

The results of this research show that direct taxes have a positive impact on public health expenditure; on the contrary, indirect taxes have a negative impact; it also confirms the importance of considering the direct tax based on high-income quintiles to guarantee equality and Access to health for all that contributes to human development.

This article leads to the design of a new health system that will be useful for improving the health of Pakistan by presenting a solution to enhance health financing. Meanwhile, Pakistan will experience better conditions in the face of health crises.

Improving health financing through the equality approach can provide public access to the health system and strengthen the positive effects of the health system on socio-economic relations.

This paper provides a unique solution for the ministry of health of Pakistan, International organisations and national authorities to reach a high level of health coverage without any cost to the financial system and increase the cost of living of the Pakistani people.

1. Increase efficient health financing by integrating health coverage programmes.

2. Implementing direct taxes based on income quintiles improves health equality.

3. Indirect tax policies will not positively contribute to health financing.

4. Improving health financing efficiency decreases health inequality.

Increase efficient health financing by integrating health coverage programmes.

Implementing direct taxes based on income quintiles improves health equality.

Indirect tax policies will not positively contribute to health financing.

Improving health financing efficiency decreases health inequality.

The study aims to compare India's public health expenditure at the international and state levels. The paper also empirically examines the regional disparities in NRHM spending across the 21 selected states of India.

The tools of absolute β-and σ-convergence are used in the analysis to test the regional convergence. The average annual growth rate across the states is the dependent variable for β-convergence, and time is the second dependent variable but is used for s-convergence. In contrast, the initial value of NRHM expenditure and the coefficient of variation of NRHM expenditure are used as independent variables, respectively. Descriptive statistics are also used for the study. The data are annual and cover the panel from 2007 to 2020.

The study attests to the hypothesis of β-and σ-convergence for the selected states in the period mentioned. The observed convergence in NRHM expenditure is due to the shift in the government's attention from the non-high focus high focus states to high states through the national rural health mission policy. The coefficient of variation across the states also shows a declining trend and provides the robustness of the σ-convergence.

As far as the literature is concerned, none of the existing studies examines the convergence of a public health expenditure scheme like the National Rural Health Mission across the Indian states by applying the techniques of β-and σ-convergence. The novelty of the study is using the newly updated dataset and validating the convergence hypotheses in the National Rural Health Mission expenditure case.

The purpose of this study is to first assess how the US healthcare financing system is influenced by income variation. Then, it examines whether or not the impact of income variation is asymmetric.

For the analyses of this paper, the autoregressive distributed lag (ARDL) model is implemented to a data set covering the period from 1960 to 2018.

The results provide evidence that major funding sources of aggregate healthcare expenditure (HCE) respond differently to changes in income. The results also imply that the effect of income is not always symmetric.

Many studies have attempted to identify the relationship between income and HCE. A common feature of past studies is that they have only focused on aggregate HCE, while one might be interested in knowing how major funders of aggregate HCE would be affected by changes in income. Another common feature of past studies is that they have assumed that the relationship between income and HCE is symmetric.