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Methods

case uses modern econometric methods and a multitude of data sources to analyse university degrees using the context of a specific study programme. We differentiate between different countries, universities, types of degrees, subject categories and graduating years.


This data is used to generate the case score in a two-step process: First, we compare the GPA of a degree with the distribution of GPAs, meaning we determine how hard it is to reach a particular GPA. In a second step, we combine this information with the performance levels of the students in different programmes at different universities. The relative weighting of these two factors is based, among other sources, on our own data collections in which the educational and employment biographies of hundreds of thousands of students are compared.


We use two different categories of models: either a global model, or a model which has been designed specifically for degrees in a particular country. Currently, we use specific natonal models for Germany, United Kingdom, Spain, Italy, Portugal, China, India and the US. This list is being expanded on continuously. The database on which the case algorithm is based within a country is also regularly expanded. As a result, but also due to changes in the methodology, the scores produced by case may change slightly in the future. Grade distributions are smoothed using a weighted moving average that includes a lag of up to three years. This smoothes out short-term fluctuations and enables the analysis of degrees that will be obtained in the future.

Local Grade Comparison

The assessment of the relative performance within a study program is based on the estimated grade distribution in the graduation year in the respective subject at the specific university. The vertical axis indicates the frequency of a specific grade. In Germany, for example, GPAs in the range between 2.0 and 3.0 are most common, which is why the highest point in the figure can often be found there. The figure represents a probability density function that is based on the actual local grade distribution. To make the data continuous, a piece-wise cubic polynomial is used if necessary to interpolate between grade steps.


A degree with an, in absolute terms, rather average GPA, which was acquired at a university with a very strict grading standard, will usually be rated better than the absolute GPA would suggest. The indicator used here is how frequently better grades have been awarded. A placement in the top 4% of the local grade distribution would accordingly be rated higher than a placement in the top 68%.


The local grade comparison of grades is not available for degrees from all countries. This can happen due to legal reasons that do not allow the output of program-specific grade distributions or because only average grades / standard deviations are available for a certain country, for which a graphical representation would not be helpful. In such cases, however, grading information is still included in the calculation of the case Global Score, case Country Score and the case Subject Score. In some cases, such as when the global model is used, no grade distributions are available for the specific combination of university, subject and year. In such cases, we use general grade distributions for the university system of the respective country and make adjustments according to the degree, subject and university, if possible. In these cases, we do not show local grade distribution graphs within the results.

case Subject Score

The case Subject Score allows for a comparison of degrees obtained in the same study field in the the respective country, but at different university. In contrast to the local grade comparison, this measure takes more than just the relative grade into consideration. In order to create comparability, the different capabilities of the students at different universities are taken into account. Among other things, data on the intelligence and personality of students in the particular study programme, their previous educational biography, performance in admission tests / procedures, information from university rankings, data on university transfers and the course of study, as well as later labour market indicators are used.


The curve compares a degree to all other degree types earned at different universities in the same study field. The further to the right a degree is positioned, the better the assessment of that degree relative to others within that subject area. Results are shown as percentiles. A degree could for example be among the top 10% of all degrees earned in mechanical engineering in the US.


This score is only available for countries for which we have a specific national model.

case Country Score

The case Country Score allows a precise comparison between all university degrees in the respective country. For this purpose, the approach used for the case Subject Score is expanded to include university degrees obtained in different subject categories.


The figure presents the case score of a degree, relative to other degrees, irrespective of their subject area. Therefore, the curve is identical for all degrees. This graphical representation can be interpreted in the same way as in the case of the local grades: Points to the left of the value of the degree represent weaker scores, points to the right of the degree represent better scores. The curve itself is based on millions of data points, which are graphically represented using a kernel density function.

case Global Score

The case Global Score allows a comparison between all university degrees worldwide. The interpretation is similar to the case Country Score, but with all university degrees worldwide as the comparison group. Differences between the two scores result from the different performance levels of students in different countries, for example due to educational migration.

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