Instrumental variables (IV) is a method used in econometrics and statistics to estimate causal relationships between variables in the presence of endogeneity, or when the relationship between variables is confounded by unobserved factors. IVs are used to address issues such as omitted variable bias, measurement error, and reverse causality. In IV analysis, researchers identify variables that are correlated with the endogenous variable of interest but are not directly related to the outcome variable. These variables are then used as instruments to help isolate the causal effect of the endogenous variable on the outcome. The strength of an IV is measured by its relevance to the endogenous variable and its independence from the error term in the regression model. IV analysis is commonly used in fields such as economics, social sciences, and epidemiology to estimate the impact of policies, interventions, or treatments on outcomes of interest. It is a valuable tool for researchers when randomization or controlled experiments are not possible or ethical to conduct.