There are some literatures that I find very frustrating, and the empirical growth literature is among them. The initial idea to take a production function to see the contribution of labor and capital to the average growth rate of an economy and then also to compare this way differences in income levels was initially very instructive, in particular because it highlighted how total factor productivity was important. It went all downhill from there, as people started wildly regressing whatever they could get their hands on across countries, mostly with poor data. TFP can be influenced by many things, and there is no way one can identify anything without applying some structure, even with good data.
Gino Gancia, Andreas Müller and Fabrizio Zilibotti use a model to distinguish the contributions of factors (labor, human capital and physical capital), barriers to technology adoptions and technology inadequate for local conditions. The results are interesting, too. Removing these barriers would increase per capita income by 24% in the OECD and 36% elsewhere. And given that a model was estimated, it can be used for various scenario analyses. For example, they find that globalization increases skill premia and thus world income disparities, but this can be reversed by coupling trade liberalization with a reinforcement of intellectual property rights. These latter results are somewhat counterintuitive, but are justified by the fact that with stronger IP rights, there can be a transfer of technology to the South.