The Impact of Health Investment on Industrial Structure: "Spillover" or "Crowding Out"?-Evidence From Emerging Market Countries.

Using national dynamic panel data from 21 emerging markets between 1999 and 2020 and bidirectional fixed effect and threshold regression methods, this paper evaluated the impact of health investment on industrial structure upgrading from two aspects of economic output and economic structure. The results showed that: (1) public health investment and private health investment have a crowding out effect on the added value of primary and secondary industries, and the crowding out effect of public health investment is greater than that of private health investment; (2) Public health investment and private health investment have a spillover effect on the added value of the tertiary industry, and the spillover effect of public health investment is greater than that of private health investment; (3) Both public and private health investment contribute to the transfer of the labor force to the tertiary industry, and tests showed the baseline regression results were robust and reliable; (4) The relationship between health investment and industrial structure upgrading was non-linear. As per capital GDP increases, the inhibition effect of public health investment on industrial structure upgrading gradually weakens whilst the promotion effect of private health investment on industrial structure upgrading gradually increases. The results of this study clarify how health investment affects industrial structure, and offers new guidance for health investment policy formulation in emerging market countries.

The Effect of Urbanization on Population Health: Evidence From China.

This paper explores the relationship between urbanization rate and death incidence by applying panel threshold regression model to the inland provinces of China. The empirical results highlight that there is a nonlinear single threshold effect between urbanization and population health indicators. In China's inland provinces, the negative impact of urbanization on death rate is reduced when per capita GDP exceeds the threshold, that is, the positive impact of urbanization on population health is significantly weakened. Similarly, this result can also be applied to the north provinces, while there is a no threshold effect in south. These asymmetric effects are strongly related to geographical location, historical background, economic development conditions, and health policies. Therefore, in the urbanization process, while promoting the steady development of population urbanization, the government should also increase health investment to improve the system and mechanism, formulate policies to raise health awareness, protect residents' health and reduce the waste of health resources.

Crowding-Out or Crowding-In: Government Health Investment and Household Consumption.

This paper explores the relationship of government health investment and household consumption by applying a panel fixed effects model and Sobel-Goodman mediation tests to inland Chinese provinces. The empirical results highlight that government health investment has a crowding-in effect and can thus promote household consumption. Furthermore, the promotion effect on non-medical health consumption is greater than that on medical health consumption. The promotion effect of government health investment on rural household consumption is higher than that on urban household consumption, and the promotion effect on household consumption for northern provinces is higher than that in southern provinces. This heterogeneous effect is closely related to the difference between urban and rural development; and the economic levels of the northern and South regions. The mediation tests found that government health investment mainly promotes regional economic growth, and then increases household consumption. In the economic and social development process, the government should implement more effective medical and health care measures to increase social medical and health investment to improve the consumption level of households.