Spatial econometric analysis of health services in Turkey through the perspective of the health development indicator

Suna Tatlı

doi:10.15637/jlecon.8.4.14

Authors

Suna Tatlı Istanbul Rumeli University/TURKEY https://orcid.org/0000-0002-9894-934X

DOI:

https://doi.org/10.15637/jlecon.8.4.14

Keywords:

Health Economics, Spatial Health Econometrics, Health Development, Infant Mortality, Spatial Autoregressive Model

Abstract

Health-related parameters are critical as indicators of development, and as a result, governments allocate a sizable portion of their budgets to the health sector. The most fundamental variable considered an indicator of health development is the infant mortality rate, which was used as the dependent variable in this study. The data utilized in the study were compiled from the TURKSTAT web page and the TR Ministry of Health's health annuals, with the year 2019 serving as the reference point for access to all data. In the study, econometric analyses were performed while keeping the notion of contiguity in mind to reveal the factors healthily affecting the infant mortality rate at the NUTS 3 level, which encompasses all provinces in the TURKSTAT regional categorization. The distribution of infant mortality rates by provinces in Turkey was analyzed in this context, and it was discovered that there was a high degree of clustering between provinces. This clustering structure indicated the presence of a spatial relationship between provinces, and it was from this point of view that spatial econometric analysis of health services in Turkey was conducted. Analyzes were carried out using STATA and GeoDa package programs.

The diagnostic tests revealed the presence of spatial autocorrelation, necessitating the employment of the spatial autoregressive model (SAR Model) to explain the relationship between the variables. As a result, it was concluded that both the variables included in the study and the infant mortality rate in nearby locations have an effect on the infant mortality rate for each province.

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