Can we have growth when population is stagnant? Testing linear growth rate formulas of non-scale endogenous growth models

Thomas Ziesemer*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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. Under slope homogeneity, the slope and intercepts of the growth equations are positive in this setting. However, allowing for heterogeneity there are two main groups of countries: those with non-positive slopes and positive intercepts are a large majority supporting fully endogenous growth; those with positive slopes and zero intercepts are a smaller group supporting semi-endogenous growth. 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.

Original languageEnglish
Pages (from-to)1502-1516
Number of pages15
JournalApplied Economics
Issue number13
Early online date15 Oct 2019
Publication statusPublished - 2020

JEL classifications

  • c33 - "Multiple or Simultaneous Equation Models: Models with Panel Data; Longitudinal Data; Spatial Time Series"
  • o47 - "Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence"


  • Endogenous growth
  • population growth
  • panel-time-series estimation
  • LONG

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