Econometrics of Risk: Theoretical and Methodological Foundations of Econometric Analysis of Risks

Abstract

Econometrics is the integration of economic theory, mathematical statistics, and empirical data, and in the insurance sector it is often regarded as the science of forecasting future outcomes based on historical information. In insurance, econometric methods are used to analyze and predict risks, losses, and financial indicators through mathematical and statistical models. This field lies at the intersection of econometrics and insurance practice, providing analytical tools for managing uncertainty and supporting evidence-based decision-making. Since insurance operations are inherently based on uncertainty, econometric analysis enables insurers to estimate future losses, calculate appropriate premium levels, and maintain financial solvency. Risk refers to the deviation of actual outcomes from expected results and, unlike uncertainty, can be measured and quantified. The insurance sector is a fundamental component of the modern digital economy, contributing to economic stability through risk distribution and financial protection mechanisms. This study examines the nature of risk factors affecting the insurance sector and explores their evaluation through econometric methods. The research analyzes the influence of macroeconomic and microeconomic indicators on insurance market performance using multivariate regression models. The findings indicate that inflation, gross domestic product, interest rates, and loss frequency significantly affect risk levels and the financial stability of insurance institutions.