Econometrics: Big Data Business Analytics
The Amsterdam School of Economics' Master’s in Econometrics provides a balanced and rigorous training in the quantitative analysis of problems in economics and finance. You will become fluent in the application of advanced mathematical and statistical methods, supported by modern software packages such as E-Views and Matlab. The multidisciplinary one-year programme consists of advanced courses in both mathematical economics and econometrics.
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The programme in brief
To fully grasp the new phenomenon of Big Data, the Big Data Business Analytics track provides you with the skills, expertise and techniques that are required to apply robust statistical methods, to be used in exploring all topics, research and issues relevant to the discipline. Study the correlations between data flows for predictive purposes and apply game theory to social media and the internet. The multidisciplinary character of the programme is reflected in the wide range of courses you can take, such as: General Equilibrium Theory, Micro-Econometrics, Financial Mathematics for Insurance, and Quantitative Marketing.
Many of the lecturers in the programme are researchers at one of the ten research programmes of UvA Economics and Business. Benefit from a programme that covers both the knowledge and skills required for practitioners and for a career in research – designed in cooperation with leading specialists in Big Data. The ASE’s affiliation with a number of internal and external economics-related research institutes enriches the research and career opportunities for students in the Master’s programme.
The Big Data Business Analytics track of the master Econometrics is a one-year programme of 60 ECTS credits (1 ECTS credit = 0.5 US credits). The academic year runs from September to the middle of July and is divided into two semesters, each with three periods. Refer to the academic calendar for exact dates.
The curriculum for the Master’s in Econometrics is quite demanding, with classes taking up 12-15 hours a week on average. An additional 25 hours are required for class preparation, homework, debates, casework and computer time.
In the first semester, you'll be given a solid basis in econometrics with several core courses for students of all tracks. General Equilibrium Theory teaches you to formulate the general equilibrium model and understand its basic properties, and critically evaluate underlying model assumptions and implications. Through Advanced Econometrics 1 and 2, you’ll obtain a deep understanding of econometric theory, practice and inference by using a variety of advanced techniques. The theoretical background and economic applications of Game Theory trains you in the ability to model interactive decision-making situations using game-theoretic techniques, and compute and characterise their equilibrium outcomes.
You'll also take one elective and one track-defining course, Machine Learning for Econometrics. Understand the principles of machine learning at an advanced level and acquire the skills to apply machine learning to complex problems in the real world.
During the first part of the second semester, you'll focus on your specialisation track in three electives. In the track-defining course Quantitative Marketing, you analyse relevant marketing questions and learn to apply quantitative techniques for making data driven marketing decisions. Financial Econometrics covers topics such as non-linear time series, volatility models, and the pricing of complex derivatives.
For your electives, you have a wide range of options. Study operations research, for example, or privacy law and ethics. Part two of the semester will be spent on completing a thesis in one of four specialised areas of expertise. A research staff member from the Department of Quantitative Economics will supervise your work.
In total it is possible to choose 25 EC as electives in the master's curriculum. 15 EC must be chosen from the following list of master courses in econometrics:
- Bounded Rationality (5 EC)
- Financial Econometrics (5 EC)
- Micro-Econometrics (5 EC)
- Non-linear Economic Dynamics (5 EC)
- Stochastic Calculus (5 EC)
- Machine Learning for Econometrics (5 EC)
- Quantitative Marketing (5 EC)
For the Big Data Business Analytics track the courses Machine Learning for Econometrics and Quantitative Marketing need to be chosen from this list, leaving one choice of a course from this list. The remaining 10 EC may be chosen from the master's courses of the Amsterdam School of Economics and Finance (not including Derivatives). If preferred, other master's courses, for example those offered by the Amsterdam Business School, or computer science or mathematics courses, can also be chosen. For these courses, permission from the Board of Examiners is required. The Board of Examiners will contact the programme director for a recommendation in these cases.
Your Master’s thesis is your graduation piece of work and it will be supervised by one of the researchers in Department of Quantitative Economics. Your thesis must add to the existing body of scientific knowledge to an appropriate extent and it may be written during an internship at a firm.
Internships and exchange
Students who have completed the curriculum of the Big Data Business Analytics track will have the possibility of doing an internship or go on exchange. This especially gives international students a unique opportunity to experience the Dutch labour market.