Happiness plays a critical role in determining public policies and increasing the welfare of society. Therefore, studies on measuring happiness and identifying the factors affecting happiness are very important to guide policy makers.  This study aims to identify the main determinants of happiness using annual data of 27 European countries for the period 2005-2022 and to demonstrate the validity of the model appropriate for the collected data. The indicators used in the study, which are likely to be explanatory of happiness levels, were selected in accordance with the theoretical literature and included in the models used. These indicators are macroeconomic variables such as unemployment, inflation, income inequality, government expenditures, and economic growth, in addition to those presented in the World Happiness Report (GDP, healthy life expectancy, social support, freedom of choice, generosity, perception of corruption, positive impact, negative impact). Depending on the structure and availability of the compiled data set, the main indicators affecting the happiness levels of countries were investigated with classical panel data models and panel quantile regression models. When all constructed models are compared, it is observed that the panel quantile regression model is more effective in determining the factors affecting happiness. One of the important findings of the study is that corruption perception, positive impact and growth variables, which are insignificant in classical panel data models, are significant at different quantile points. While inflation and income inequality variables are statistically insignificant at 75% and 50% quantile points, respectively, they are significant at other quantiles. These results show that panel quantile regression evaluates the determinants of happiness in a more detailed way in countries with different levels of happiness and aims to make an important contribution to the literature in terms of guiding policy decisions correctly.