The hierarchical credibility model is a model that can accommodate more than one risk factor. This model can better describe the condition of a complex insurance data. Hypothetical mean is used as a quantity to be used for a benchmark of premium calculation. The process of estimating value of hypothetical mean can be done by using the orthogonal projection on one of Hilbert spaces that contains a linear combination of past observations. The estimation of hypothetical mean is a function of structural parameters of the model, which are estimated directly from the data. If the estimation of structural parameters that defines the variance on the upper levels of the hierarchical structure is zero, then that next structural parameters can still be counted with the limit. The methods that can be used to estimate these structural parameters are the Ohlsson method and Buhlmann-Gisler method. In this research, the estimation of hypothetical mean using the hierarchical credibility model and the Buhlmann-Straub model are compared. The result is there is a difference between the usage of both methods when applied on the hierarchical credibility model compared to the Buhlmann-Straub model and the estimation with the hierarchical credibility model defines the situation more realistically.
