Post Covid-19 Pandemic Economic Growth With Human Capital As A Long Term Drive

Abstract

The latest direction in development economics research both at home and abroad is starting to reduce the use of convoluted analytical models. Using too many variables but with unclear causality will actually complicate the analysis and produce results that are not necessarily good and correct. There are quite a lot of scientific work findings that use dozens of variables, with statistically significant results, but if you examine the relationship many questions arise such as "How can x have a relationship with y?" or “Doesn't y affect x, and not vice versa?” or what is known as reverse causality. Causality between variables must be supported by a strong and in-depth theoretical basis—not to show that the increase in the number of giraffes in Australia affects Indonesia's GDP—and the existence of this relationship must be free from sources of bias.