The long-run relationship between per capita incomes and population size

Maya Eden (University of Zurich) and Kevin Kuruc (Population Wellbeing Initiative, University of Texas at Austin)

GPI Working Paper No. 29-2024

The relationship between the human population size and per capita incomes has long been debated. Two competing forces feature prominently in these discussions. On the one hand, a larger population means that limited natural resources must be shared among more people. On the other hand, more people means more innovation and faster technological progress, other things equal. We study a model that features both of these channels. A calibration suggests that, in the long run, (marginal) increases in population would likely lead to (marginal) increases in per capita incomes.

Other working papers

Critical-set views, biographical identity, and the long term – Elliott Thornley (Global Priorities Institute, University of Oxford)

Critical-set views avoid the Repugnant Conclusion by subtracting some constant from the welfare score of each life in a population. These views are thus sensitive to facts about biographical identity: identity between lives. In this paper, I argue that questions of biographical identity give us reason to reject critical-set views and embrace the total view. I end with a practical implication. If we shift our credences towards the total view, we should also shift our efforts towards ensuring that humanity survives for the long term.

Economic inequality and the long-term future – Andreas T. Schmidt (University of Groningen) and Daan Juijn (CE Delft)

Why, if at all, should we object to economic inequality? Some central arguments – the argument from decreasing marginal utility for example – invoke instrumental reasons and object to inequality because of its effects…

Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Rethink Priorities), Jojo Lee and Victor Yaneng Wang (Global Priorities Institute, University of Oxford)

The surrogate index method allows policymakers to estimate long-run treatment effects before long-run outcomes are observable. We meta-analyse this approach over nine long-run RCTs in development economics, comparing surrogate estimates to estimates from actual long-run RCT outcomes. We introduce the M-lasso algorithm for constructing the surrogate approach’s first-stage predictive model and compare its performance with other surrogate estimation methods. …