MikroModelle

MikroModelle, or micro-models, are small-scale representations used to study complex systems by modeling individual units and their interactions rather than the system as a whole. They focus on micro-level behavior and heterogeneity, enabling the emergence of aggregate phenomena from simple rules.

They complement macro models by capturing distributional properties, networks, and decision making under uncertainty.

Common approaches include agent-based models, microsimulation, and other forms of microscale econometric or statistical models. Data sources include microdata from censuses, surveys, or administrative records. Calibration aligns model parameters with observed micro-level patterns; validation checks if emergent macro-level outcomes resemble real-world data.

Applications include economics for labor markets and consumer choice, epidemiology for disease spread, urban planning for transportation and land use, and social science for diffusion of innovations.

Limitations include data intensity, computational demands, sensitivity to assumptions, and challenges in validation. Transparency and reproducibility depend on model documentation, and ethical considerations may arise when using individual-level data.