Regression analyses should use more growth variables: ECB
Regression analyses should not prioritise simplicity at the expense of completeness, a European Central Bank paper published on Monday argues.
With as many as 145 different variables included in published growth regressions, the paper's author shows that the accuracy of partial coefficients within small models is often unclear. "The number of explanatory variables is so large because hundreds of theories have been developed to explain economic growth", he notes. As a result, analyses should
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