The aim of Thermoeconomic diagnosis is to identify malfunctioning components in energy systems and to quantify the impact on fuel consumption caused by each of them. The quantitative causality analysis is a method based on the linearization of the thermodynamic model of the system. The accuracy of the method is demonstrated by quantifying the error produced in the diagnosis of a large amount of points of a real example. Additionally, a formulation to combine this approach with thermoeconomic analysis has been developed. It allows to precisely quantify intrinsic and induced effects. Finally, the method is compared with two diagnosis approaches based on linear regression and neural networks.