Human populations with low survival at advanced ages and postponed fertility reduce long-term growth in high inflation environments

Temporal variability in inflation can lead to important fluctuations in the long-term growth rate of human populations via their differential impacts on vital rates like survival and fertility. However, historically, demographic studies have overlooked this time-dependent relationship. Here, we test whether human populations have higher stochastic population growth rates when exposed to lower levels of inflation. We also examine if lower survival rates at older ages (>60 years) and fertility rates at the later reproductive years (>30 years) among populations exposed to higher inflation rates determine their expected lower long-term growth rate compared to those exposed to lower inflation rates. To explore the impact of variability in inflation on vital rates response, we develop a quantitative pipeline with four steps, and parameterise it with high-resolution economic and demographic data across 76 countries from 1971-2021. The four steps are (1) defining treatment groups based on levels of trend inflation (creeping inflation (0-3%), walking inflation (3-10%), galloping inflation (10-50%), and hyperinflation (>50%)) among which the stochastic population growth rates will be compared; (2) constructing matrix population models for each environmental state under every treatment. The environmental states for each treatment are defined on the basis of the duration of inflation (e.g., 0, 2, 4, six years or above); (3) estimating the stochastic population growth rate for each treatment by considering a Markovian environment dictated by the long-term frequency (f) and temporal autocorrelation (ρ) of the treatment; and (4) decomposing the differences in the population growth rate between treatments into contributions from environmental variability and vital rate differences between environments to test how vital rates impact on population growth under varying environmental scenarios. In agreement with our hypothesis, we find that the stochastic population growth rate at lower levels of inflation is systematically higher than that at a higher level of inflation at all stationary frequencies and temporal autocorrelation of the inflation environment. Moreover, the disadvantage in survival at older ages (>60 years) and fertility at ages >30 years led to the lower stochastic growth rate among populations exposed to higher level of inflation such as creeping inflation compared to higher level of inflation, such as walking inflation. Our framework explicitly links human population performance and inflation environment by describing nonlinear feedback between inflation, human survival, fertility, population growth, and its age structure. We discuss the potential of our approach to study the life-history strategies and population dynamics of a wide range of drivers of environmental variability.