Can we have growth when population is stagnant? Testing linear growth rate formulas and their cross-unit cointegration of non-scale endogenous growth models

We sub-divide scale-invariant fully or semi-endogenous growth models into six sub-categories for formulas relating steady-state growth rates of income per capita and the growth rate of the population depending on the properties of slopes and intercepts. We capture their steady-state relation by a long-term relation in panel vector-error-correction models for 16 countries, and estimate the 16 models simultaneously allowing successively for more heterogeneity. The slope and intercepts of the growth equations are positive in this setting under slope homogeneity but less significant or even negative when allowing for heterogeneity. Slopes are mostly non-positive. Intercepts are positive for a large majority of countries. Results therefore favour fully over semi-endogenous growth with and without slope homogeneity and allow for growth rate policies. The more frequent case is that long-run growth can remain positive if population stops growing. Analysis of cross-unit cointegration suggests that long-run results are internationally connected.

JEL Classification: C33, O47

Keywords: Endogenous growth, population growth, panel times series estimation