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June 20, 2011 2:17 am

Methodology: A thorough look at the figures

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The Financial Times inaugural masters in finance rankings cover the top international programmes in the field.

Two rankings have been produced: one of pre-experience programmes, those that are aimed at students who are yet to enter the labour market.

The other is of post-experience degrees, which require participants to have some professional grounding.

Masters in financial engineering programmes, which tend to have a greater emphasise on quantitative skills, have not been included.

The rankings are intended to give a thorough assessment of the programmes included and an insight into the schools that teach them and the alumni.

They are compiled using data from two sets of online surveys.

The first set of surveys is completed by the schools themselves and the second by alumni who graduated three years previously.

Graduates surveyed in 2011 were from the class of 2008.

For a programme to be considered for inclusion in the ranking, the FT requires a response rate of 20 per cent of alumni, with a minimum of 20 responses for schools with fewer than 100 alumni in the graduating class.

For the pre-experience ranking, data from alumni questionnaires are used to determine the rankings in six of the 16 criteria, from “salary today”, which is calculated in US dollars, to “placement success rank” and “international mobility rank”.

The following process is applied to salary data to calculate the salary figures presented in “salary today (US$)” column.

To start with, salary figures supplied by alumni working in the non-profit and public service sectors, or who are still full-time students, are excluded.

Purchasing Power Parity (PPP) rates, supplied by the International Monetary Fund, are then used to convert the remaining salary data to US dollar PPP equivalent figures.

PPP rates are currency conversion rates that are applied to iron out differences in purchasing power between currencies.

In this way, alumni salary data can be standardised and compared. After this conversion has been completed, the very highest and lowest salaries are excluded before the average is calculated for each school.

The remaining 10 criteria: “employed at three months (%)” to “international board (%)”, “international course experience rank”, “languages” and “faculty with doctorates (%)”, are calculated using data from business school questionnaires.

The calculations for the post-experience ranking are the same with two exceptions.

First, a salary increase is also calculated, based on the rise in salary reported by alumni.

This is the percentage difference in earnings three years after graduation, compared with before the degree.

Second, the languages criterion is omitted, because none of the participating post-experience programmes require students to study an additional language as part of the degree.

After all calculations have been applied to the data for each of the criteria, the results are ranked using Z-scores on a column-by-column basis.

That is, for each criterion in the table, a separate set of Z-scores is calculated. Z-scores take into account the differences between each school and the spread of scores between the top and bottom school.

The Z-scores in each field are then multiplied by the column weights (see table key) and these results are added to give a final score for each school.

This final score is presented as the school’s overall rank.

All the criteria that contribute to the final ranking have underlying Z-scores, but in the table the data are presented as US$ equivalents, ranks, percentages, or, in the case of languages, the number of additional languages required on graduation.

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Table key

Note: weights are in brackets (pre-experience), [post-experience]

Salary today US$ (20) [20]: An average of salaries three years after graduation. The figure is based on purchasing power parity equivalence

Percentage salary increase (n/a) [20]: The difference in earnings three years after graduation, as a percentage of the pre-masters salary

Value for money rank (5) [3]: Calculated using alumni salaries three years after graduation and course costs. The length of the course is also taken into consideration

Careers rank (10) [7]: The career status of alumni three years after graduation. Progression is measured according to seniority and the size of company in which they are employed

Aims achieved % (5) [3]: The extent to which alumni fulfilled their goals or reasons for doing a degree

Placement success rank (5) [3]: Alumni who used the careers service at their business school were asked to rank its effectiveness

Employed at three months % (5) [3]: The percentage of the most recent graduating class in employment three months after graduation. The figure in brackets shows the percentage of the class the school provided data for

Women faculty % (3) [3]: Percentage of female faculty

Women students % (3) [3]: Percentage of female students

Woman board % (1) [2]: Percentage of female members of the advisory board

International faculty % (5) [5]: Percentage of faculty whose citizenship differs from their country of employment

International students % (5) [5]: Percentage of students whose citizenship differs from the country in which they are studying

International board % (2) [3]: Percentage of the board whose citizenship differs from the country in which the business school is based

Faculty with doctorates % (6) [6]: Percentage of faculty with a doctoral degree.

International mobility rank (10) [7]: A measure based on changes in the country of employment of alumni between graduation and today

International course experience rank (10) [7]: Weighted average of four criteria that measure international exposure during the masters programme

Languages (5) [n/a]: Number of languages required on graduation from the masters programme

Course length (months): The length of the masters programme

Company internships (%): The percentage of the last graduating class that completed company internships as part of the masters degree

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