Fitting a Public Health Index Model Based on Smart Data with an Emphasis on Population Aging and Retirement Age in Iran

Document Type : Original Article

Authors

1 PhD Student, Department of Economics, SR.C., Islamic Azad University, Tehran, Iran.

2 Professor, Department of Economics, SR.C., Islamic Azad University, Tehran, Iran.

Abstract
The aim of the study is to fit a public health index model based on smart data with an emphasis on population aging and retirement age in Iran. The study examines the fitting of the public health index model (life expectancy) considering retirement age and population aging in Iran during the years 1990 to 2024 using the quantile method (quartile regression). The present study is in the category of post-event research from the perspective of applied purpose and analytical-descriptive nature. First, reliability tests (PP) were conducted on the variables, which showed that the variables were stationary at the level of one after one order of difference. The results of the cointegration test also indicate the existence of at least one cointegration vector between the variables under study. The results of the quantile model estimation show that the retirement index has a negative and significant effect on the life expectancy index (health index) in the lower quartiles (25Q and 50Q), and the intensity of this negative effect increases as it moves towards the higher quartiles (75Q and 95Q). Also, factors such as public health expenditures, private health sector expenditures, capital formation, and literacy rate have a positive and significant effect on life expectancy, while the real exchange rate, inflation rate, and liquidity volume have a negative and significant effect on it. The impact of the retirement index, inflation rate, liquidity volume, and real exchange rate on the health index increases in the higher quartiles (75Q and 95Q).

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Subjects

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  • Receive Date 18 June 2025
  • Revise Date 26 July 2025
  • Accept Date 28 August 2025