The effect of health on economic growth: a meta-regression analysis

Abstract

The main objective of this study is to examine the effect of health on economic growth based on 719 estimates obtained from 64 studies from all over the world. We find evidence of a publication bias towards a positive estimated effect of health on economic growth. After accounting for heterogeneity of the estimates, we show that health has a genuine positive effect on economic growth. Less developed countries seem to enjoy a higher effect of health on growth driven by the ongoing economic–demographic transition in those countries. The variation of the health effect on economic growth is also influenced by the available data, estimation procedure, model specification, publication channel, and country characteristics in each study. Studies that do not account for endogeneity seem to create an upward bias. Studies with more comprehensive variables seem to increase the estimated effect of health on growth. A higher number of years of compulsory education, longer working experience, and more favourable environmental conditions also increase the effect size. Overall, our results confirm the key role of the health factor in explaining economic growth across countries.

Yield effects of agricultural cooperative membership in developing countries: A meta‐analysis

“…The standard approach to dealing with this problem is to convert the estimated yield effects to a partial correlation coefficient, or PCC (Ogundari 2022;Ogundari & Bolarinwa 2018;Xue et al 2020). The PCC is a scale-free metric, providing a unified interpretation across different studies (Anwar & Mang 2022;Ogundari & Bolarinwa 2018;Ridhwan et al 2022). It is calculated using the following equation:…”

“…Two approaches can potentially be used to check whether there exists the presence of publication bias in meta-analysis: funnel plots and the funnel asymmetry test (Hong et al 2021;Ogundari & Bolarinwa 2018;Ridhwan et al 2022;Xue et al 2021). The funnel plot is a scatterplot of studyspecific effect sizes on the x-axis against a measure of study precision such as standard errors or inverse standard errors (in our case) on the y-axis.…”

“…previous studies(Anwar & Mang 2022;Duan et al 2020;Ogundari 2022;Ridhwan et al 2022;Xue et al 2021), we employ two weighted least squares (WLS) estimators to address this problem: WLS-Fixed Effects (FE) and WLS-Random Effects (RE).2 The WLS-FE model assumes that there is a single underlying true effect and the reason for different estimates across studies is solely due to sampling error. The corresponding weight is given by the inverse of the variance of the estimated effect, that is, 1∕[𝑆𝐸(𝑃𝐶𝐶 𝑖 ) 2 ] (Xue et al 2021).…”

What Will Be the Impact of the COVID-19 Pandemic on the Human Capital and Economic Growth? Evidence from Eurozone

“…In the other hands, a reverse causation from health and economic growth tests heavily on the work elaborated by Romer (1986) and Lucas (1988), which developed a theoretical model emphasizing the role of human capital in stimulating economic growth. Regarding the effect of health on economic growth, Ridhwan et al (2022) affirmed that health affects economic growth directly by increasing labor productivity and decreasing the costs of illnesses. In fact, healthy individuals also indirectly impact economic growth by having a healthy family, which may subsequently create healthier future generations (Fortune Ganda, 2022).…”

Dampak Health Capital Terhadap Pertumbuhan Ekonomi: Pembuktian Dari Negara Terpilih Di Asia Tenggara Dengan Pendekatan Model Autoregressive Distributed Lag (Ardl)

“…Tanpa kondisi kesehatan yang baik, ekonomi kehilangan kemampuannya untuk mengembangkan produktivitas yang kompetitif, yang selanjutnya dapat menghambat pertumbuhan ekonomi (Ridhwan et al, 2022). Menurut (Yıldırım et al, 2020) kesehatan merupakan pilihan karena merupakan sumber dari manfaat yang juga terkait langsung dengan tingkat kekayaan dan pendapatan secara individu.…”