Abstract

Our main contribution in this paper consists of analyzing long-run interactions between health status and innovation in the form of R&D activities accounting for possible economic development. For this purpose, we are based on a sample of fifteen developed and fifteen developing countries across the world during the period 2000–2017. As the principal interest is on the long-run effect, it is not essential to be concerned about the variable lags through which innovation will impact health. Therefore, to get the asymptotically efficient long-run impact of innovation on health, we have introduced both dynamic OLS and fully modified OLS for developed countries. Further, we have employed a technique based on panel ARDL methods for developing countries which deals with the stationary series problem of different orders to monitor possible association between population health and innovation in the long-run horizon. Our empirical results support long- and short-run causality running from R&D activities to health in all developed countries, whereas the just-mentioned causality prevails only in the long-run in case of developing countries. Finally, to check the robustness of the said association, we have implemented neural network-based NARX technique to validate the prediction of health status on the basis of R&D activities, and eventually, NARX supports our hypothesis in case of long-run through back-propagation. Policy recommendation includes the encouragement of more R&D activities and R&D-related policy implementation in both developed and developing nations to opt for better health status.

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