Mishra, U. S. | Search bioRxiv

bioRxiv2026

Variability and persistence in inflation reshape human population dynamics by amplifying sensitivity and eroding demographic buffering

Inflation affects human fertility and survival; persistent inflation can translate into fluctuations in annual population growth rate. Existing studies have yet to systematically examine inflations impact on long-term growth rates across populations. Here, we examine whether high inflation variance and autocorrelation amplify long-term growth rates sensitivity to inflation, across 32 countries over 1971-2024. Additionally, we examine the effect of increasing inflation variance and autocorrelation on humans capacity for demographic buffering, i.e., reducing the temporal variance in vital rates most sensitive to growth. First, we construct inflation-dependent matrix population models using a hierarchical Bayesian framework. We then calculate the stochastic sensitivity and elasticity of population growth rate to inflation to quantify demographic buffering across a variance-autocorrelation parameter space. We find that the stochastic sensitivities of the growth rate increase with inflations variance and autocorrelation. However, we do not find support for the expected adverse effects of inflation variance and autocorrelation on humans capacity to buffer against inflation. Our framework provides a valuable tool for examining the impact of resource uncertainty on life history strategies in stochastic environments. We discuss how our framework can be extended to study the resource-dependent population dynamics within variable environments and across the tree of life.

ecology↗

bioRxiv2024

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 (p) 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 walking inflation compared to lower level of inflation, such as creeping 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.

animal behavior and cognition↗