Evaluating Innovation and Institutions for Tech-Trade: A Global Assessment in the Quest for Sustainable Economic Prosperity

Abstract

Sustainable economic prosperity lies in the production of technological products that use the latest technology and do not depend upon natural, non-renewable sources. Trade of such goods boosts the economy and diversifies its existing trade pattern. This study analyses various variables that contribute to high-tech exports. All countries of the world that have more than one per cent share of high-tech exports to manufactured products are taken from 2008 to 2021. A robust statistical method called Feasible Generalized Least Squares (FGLS-hetero) is used to deal with heteroscedasticity. To minimize the impact of outliers, quantile regression, and bootstrap quantile regression techniques are also used. The main purpose of using multiple regression techniques is to assess whether the sign and significance of the coefficient will change by change in estimation techniques. The findings reveal that innovation, access to information, strong institutions, and partnerships between universities and industries all play a significant role in boosting high-tech exports in all estimation techniques. Financial development has a significant direct impact on high-tech export in the case of simple linear regression and FGLS (hetero) but an insignificant positive impact in the case of quantile regression and bootstrap quantile regression.