This paper aims to investigate the determinants of performance for insurance companies in Tunisia from 2004 to 2017. Namely, we consider three dimensions of determinants; those related to firms’ microenvironment, macroenvironment and meso or industry environment. The performance of insurance companies is measured using three criteria: Return On Assets (ROA), Return On Equity (ROE), and Combined Ratio. The independent variables are categorized into three groups: microeconomic variables (Firm Size, Financial leverage, Capital management risk, Volume of capital, and Age of the firm), meso-economic variables (Concentration ratio and Insurance Sector Size), and macroeconomic variables (Inflation, Unemployment, and Population Growth). The General Least Squares (GLS) regression technique is employed for the analysis. The study reveals that the financial performance of Tunisian insurance companies is positively influenced by firm size, capital amount, and risk capital management. On the other hand, it is negatively influenced by leverage level, industry size, concentration index, inflation, and unemployment. In terms of technical performance, the capital amount of the firm, industry size, age of the firm, and population growth have a positive impact. However, firm size, leverage, concentration index, and risk capital management negatively affect technical performance. This paper contributes to the existing literature by examining the determinants of performance specifically for insurance companies in Tunisia. Besides the classical proxies of performance, this paper has the originality of using the technical performance which is the most suitable for the case of Insurance companies.

The female labor force participation holds significant implications for various aspects of society, the economy, and individual lives. Understanding its significance involves recognizing the multifaceted impact of women’s participation in the workforce. In this context, the current study investigates the factors influencing the female labor force participation rate in Saudi Arabia while using a set of independent variables such as GDP growth, employment-to-population ratio, inflation, urban population growth, tertiary school enrollment, labor force with advanced education, fertility rate, and age dependency ratio, covering a period from 2000 to 2022. The results reveal that the employment-to-population ratio, inflation rate, urbanization, and age dependency ratio have positive and statistically significant impacts on the female labor force participation rate. This research offers valuable insights for formulating policies to foster female empowerment and overcome the obstacles that hinder their economic participation.