Model Identification

Model identification is a process used in statistics and data analysis to ensure that a mathematical model accurately describes the data it represents. Essentially, it involves determining whether a proposed model can be reliably estimated from available data. If a model is "identified," it means there is enough information to estimate its parameters uniquely, leading to meaningful predictions or insights. If a model is not identified, it may result in multiple interpretations and unreliable results. This process is crucial for building trustworthy models in various fields, including economics, engineering, and social sciences.