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Mastering Quantitative Methods for Business and Economics

Econometrics and Operations Research

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The Master’s programme in Econometrics and Operations Research consists of two tracks: Econometrics and Operations Research. Directly from the start of the master you choose one of these tracks.

Each track offers three distinct specializations that allow you to focus your expertise in your chosen field.

Econometrics Track

The Econometrics track focuses on the development and application of advanced statistical and econometric methods for analyzing complex data. This track integrates mathematics, statistics, computer science, and knowledge of businesses to provide you with the tools needed to extract meaningful insights from data across various domains including economics, marketing, pricing, revenue management, finance, risk management, and climate science. The track offers three specializations:

  • Econometrics and Data Science: Master state-of-the-art techniques in econometrics and data science for analyzing large-scale datasets
  • Financial Econometrics: Develop expertise in analyzing financial markets and risk using advanced econometric methods
  • Climate Econometrics: Apply in-depth quantitative techniques to address climate-related challenges

Operations Research Track

The Operations Research track emphasizes the development and application of mathematical methods for analyzing and optimizing business processes. This track combines mathematics, computer science, and business studies to help you solve complex decision-making problems. Choose from three specializations:

  • Quantitative Logistics: Focus on optimizing transport networks and supply chains
  • Financial Engineering: Master the mathematical techniques needed for financial optimization and risk management
  • Business Engineering and Data-Driven Decision Making: Learn to optimize business processes using advanced analytical methods

Each specialization consists of:

  • Core courses that provide fundamental knowledge in your chosen field
  • Specialized courses that deepen your expertise in specific areas
  • Elective courses that allow you to broaden your knowledge
  • A master’s thesis where you apply your knowledge to solve a complex problem

Our courses combine theoretical foundations with practical applications, ensuring you develop both a deep understanding and hands-on experience. Through case studies, programming assignments, and research projects, you’ll learn to apply advanced methods to real-world challenges.

The academic year is divided into six periods, allowing for focused, intensive learning in each course. The programme begins in September and can be completed in one year of full-time study.

The start date of this programme is September 1st.

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Saturday 8 March 2025

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Which specialisation do you choose?

Find out what the different possibilities are within the master's programme

Summary

In today’s data-rich world, organizations face increasingly complex challenges that require deep statistical analysis and modeling. How can we extract meaningful insights from massive datasets? What methods help us understand causal relationships in business decisions? How can we combine classical statistical approaches with data science methods to solve real-world problems?

Our Econometrics and Data Science specialization prepares you to answer these questions and more, offering a unique blend of econometric methods and theory with modern data science applications. Unlike traditional data science programmes, we focus on understanding the underlying mechanisms of statistical and data science methods, teaching you not just how to apply these techniques, but also why they work and what to do when they don’t.

Why Choose Econometrics and Data Science?

We combine deep econometric foundations with modern data science methods. Our unique approach teaches you not just how to apply techniques, but why they work and what to do when they don’t – making you a more versatile and effective data scientist.

  • Master both classical econometric theory and modern data science methods
  • Develop a deep understanding of statistical foundations beyond surface-level applications
  • Learn advanced causal inference techniques for business decision-making
  • Apply your skills to real-world data and business cases
  • Combine theoretical understanding with practical applications in data science

Curriculum

The specialization features five core courses, two electives and a thesis that build your expertise:

  • Advanced Econometrics
  • Multivariate Econometrics
  • Big Data Statistics
  • Causal Inference and Machine Learning
  • Case Study in Econometrics and Data Science
  • Thesis MSc EOR - Econometrics
  • Two electives

Please consult the Study Guide for more information

Summary

How can we model and predict financial market behavior? What statistical methods help us understand and manage financial risks? How can we use econometric techniques to value complex financial instruments? These are the kinds of questions you’ll learn to answer in our Financial Econometrics specialization.

This specialization combines econometric theory, methods and data science with theoretical and practical applications in finance, preparing you to tackle complex financial challenges using advanced quantitative methods. This specialization consistently produces graduates who excel in various roles across the financial sector.

Why Choose Financial Econometrics?

This specialization stands at the intersection of advanced econometrics, data science and finance, offering a depth of quantitative expertise that sets us apart from traditional finance programmes. We combine comprehensive statistical methods with a strong understanding of to prepare you for the most demanding quantitative roles in finance.

  • Master advanced econometric and data science techniques for modeling financial markets and risk
  • Develop expertise in time series analysis, data science and financial modeling
  • Apply high-level statistical methods to real financial data
  • Gain hands-on experience with practical financial applications
  • Learn to solve complex financial problems using econometric methods

Additional Admission Requirements

This specialization has additional admission requirements for applying. You can find all admission requirements for this programme on the Admission Page.

Curriculum

The specialization features five core courses, two electives and a thesis that build your expertise:

  • Advanced Econometrics
  • Multivariate Econometrics
  • Time Series Models
  • Advanced Financial Econometrics
  • Financial Econometrics Case Study
  • Thesis MSc EOR - Econometrics
  • Two electives

Please consult the Study Guide for more information

Summary

How can we forecast extreme weather events using data science techniques? What is the impact of climate change on economies and societies in an increasingly interconnected world? How are financial markets affected by the implications of disasters?

Climate change is one of the most pressing issues of the 21st century, affecting people, economies, and the environment globally. As the Intergovernmental Panel on Climate Change (IPCC) emphasizes the complexities of the climate system, the need for advanced quantitative analysis has never been greater. Climate change presents one of the most complex data challenges of our time.

Our unique Climate Econometrics specialization equips you with advanced quantitative methods to analyze climate data, model environmental impacts, and support evidence-based decision-making in climate policy and business strategy.

Why Choose Climate Econometrics?

As the first programme in the Netherlands to combine advanced econometrics with climate science, we offer a unique opportunity to apply advanced quantitative methods to one of the world’s most pressing challenges. Through our collaboration with the Institute for Environmental Studies (IVM), you’ll learn to analyze complex climate data and model environmental impacts with unmatched precision.

  • Learn cutting-edge methods specifically designed for climate data analysis
  • Collaborate with leading climate scientists at VU’s Institute for Environmental Studies
  • Master advanced techniques for modeling complex climate systems
  • Apply econometric expertise to pressing environmental challenges
  • Develop solutions for climate-related economic and business problems

Additional Admission Requirements

This specialization has additional admission requirements for applying. You can find all admission requirements for this programme on the Admission Page.

Curriculum

The specialization features five core courses that build your expertise:

  • Advanced Econometrics
  • Multivariate Econometrics
  • Climate Data Science (New)
  • Climate Econometrics Case Study (New)
  • Big Data Statistics or Time Series Models
  • Thesis MSc EOR - Climate Econometrics (In collaboration with Institute for Environmental Studies)
  • Two electives

Please consult the Study Guide for more information

Summary

How can organizations efficiently distribute their services in an increasingly interconnected world? What quantitative methods can improve supply chain performance? How can we optimize complex logistics networks while maintaining sustainability? These are the kinds of challenges you’ll learn to solve in our Quantitative Logistics specialization.

This specialization combines advanced operations research techniques with deep logistics expertise, preparing you to optimize complex supply chains and distribution networks. It equips you with both the mathematical foundations and practical tools needed to excel in the rapidly evolving field of quantitative logistics.

Why Choose Quantitative Logistics?

In an increasingly connected world, optimizing logistics and supply chains requires advanced mathematical approaches. This specialization combines advanced operations research techniques with practical logistics expertise, preparing you to design and implement efficient solutions for complex distribution networks.

  • Master optimization methods for complex supply chain challenges
  • Develop strong computational and mathematical modeling skills
  • Design novel solutions for complex logistics problems
  • Create sustainable and efficient distribution networks
  • Apply advanced analytics to real-world logistics challenges

Additional Admission Requirements

This specialization has additional admission requirements for applying. You can find all admission requirements for this programme on the Admission Page.

Curriculum

The specialization features four core courses, three electives and a thesis that build your expertise:

  • Combinatorial Optimization
  • Optimization and Learning via Stochastic Gradient Search
  • Operations Research Case
  • Optimization and Multiagent Systems
  • Thesis MSc EOR - Operations Research
  • Three electives

Please consult the Study Guide for more information

Summary

How can we create and price complex financial products in today’s expanding markets? What quantitative methods help us optimize investment portfolios and manage risks? How can we use simulation-based techniques to evaluate complex derivatives? These are the kinds of questions you’ll learn to answer in our Financial Engineering specialization.

This specialization combines advanced operations research techniques with deep financial expertise, preparing you to tackle complex financial challenges using advanced mathematical methods. This specialization bridges the gap between finance and operations research, equipping you with the tools needed to excel in quantitative finance roles.

Why Choose Financial Engineering?

We bridge the gap between mathematical optimization and financial markets, providing you with the advanced quantitative tools needed to solve complex financial challenges. This specialization uniquely combines operations research techniques with financial expertise, preparing you for specialized roles in quantitative finance.

  • Master advanced optimization techniques for financial applications
  • Develop expertise in pricing complex financial products
  • Apply operations research methods to financial problems
  • Learn high-level computational methods for implementation
  • Gain practical experience with portfolio optimization and risk management

Additional Admission Requirements

This specialization has additional admission requirements for applying. You can find all admission requirements for this programme on the Admission Page.

Curriculum

The specialization features four core courses, three electives and a thesis that build your expertise:

  • Combinatorial Optimization
  • Optimization and Learning via Stochastic Gradient Search
  • Operations Research Case
  • Optimization and Multiagent Systems
  • Thesis MSc EOR - Operations Research
  • Three electives

Please consult the Study Guide for more information

Summary

How can organizations make better decisions using data and mathematical optimization? What quantitative methods can improve business processes and strategy? These are the kinds of questions you’ll learn to answer in our Business Engineering and Data-Driven Decision Making specialization.

This specializaton combines advanced operations research methods with business engineering principles, preparing you to optimize complex business processes and drive data-informed decisions. Business engineering represents the intersection of business strategy and technical development, using mathematical models and frameworks to design and optimize processes that drive growth and performance. In today’s fast-developing business world, decision-making has become increasingly data-driven, requiring the integration of data analytics, statistics, and predictive modeling with process optimization. This specialization bridges the gap between mathematical optimization and business strategy, equipping you with the tools needed to help organizations make informed, objective, and measurable decisions that optimize outcomes.

Why Choose Business Engineering and Data-Driven Decision Making?

Modern business decisions require advanced quantitative analysis and optimization. This specialization combines operations research methods with business strategy, preparing you to transform complex business challenges into data-driven solutions that drive organizational success.

  • Transform business challenges into mathematical models
  • Develop expertise in data-driven decision making
  • Master process optimization techniques for business applications
  • Apply operations research methods to strategic business problems
  • Create solutions through business case studies and projects

Curriculum

The specialization features five core courses, two electives and a thesis that build your expertise:

  • Combinatorial Optimization
  • Optimization and Learning via Stochastic Gradient Search
  • Operations Research Case
  • Optimization and Multiagent Systems
  • AI for Data Driven Decision Making
  • Thesis MSc EOR - Operations Research
  • Two electives

  • Econometrics and Data Science

    Summary

    In today’s data-rich world, organizations face increasingly complex challenges that require deep statistical analysis and modeling. How can we extract meaningful insights from massive datasets? What methods help us understand causal relationships in business decisions? How can we combine classical statistical approaches with data science methods to solve real-world problems?

    Our Econometrics and Data Science specialization prepares you to answer these questions and more, offering a unique blend of econometric methods and theory with modern data science applications. Unlike traditional data science programmes, we focus on understanding the underlying mechanisms of statistical and data science methods, teaching you not just how to apply these techniques, but also why they work and what to do when they don’t.

    Why Choose Econometrics and Data Science?

    We combine deep econometric foundations with modern data science methods. Our unique approach teaches you not just how to apply techniques, but why they work and what to do when they don’t – making you a more versatile and effective data scientist.

    • Master both classical econometric theory and modern data science methods
    • Develop a deep understanding of statistical foundations beyond surface-level applications
    • Learn advanced causal inference techniques for business decision-making
    • Apply your skills to real-world data and business cases
    • Combine theoretical understanding with practical applications in data science

    Curriculum

    The specialization features five core courses, two electives and a thesis that build your expertise:

    • Advanced Econometrics
    • Multivariate Econometrics
    • Big Data Statistics
    • Causal Inference and Machine Learning
    • Case Study in Econometrics and Data Science
    • Thesis MSc EOR - Econometrics
    • Two electives

    Please consult the Study Guide for more information

  • Financial Econometrics

    Summary

    How can we model and predict financial market behavior? What statistical methods help us understand and manage financial risks? How can we use econometric techniques to value complex financial instruments? These are the kinds of questions you’ll learn to answer in our Financial Econometrics specialization.

    This specialization combines econometric theory, methods and data science with theoretical and practical applications in finance, preparing you to tackle complex financial challenges using advanced quantitative methods. This specialization consistently produces graduates who excel in various roles across the financial sector.

    Why Choose Financial Econometrics?

    This specialization stands at the intersection of advanced econometrics, data science and finance, offering a depth of quantitative expertise that sets us apart from traditional finance programmes. We combine comprehensive statistical methods with a strong understanding of to prepare you for the most demanding quantitative roles in finance.

    • Master advanced econometric and data science techniques for modeling financial markets and risk
    • Develop expertise in time series analysis, data science and financial modeling
    • Apply high-level statistical methods to real financial data
    • Gain hands-on experience with practical financial applications
    • Learn to solve complex financial problems using econometric methods

    Additional Admission Requirements

    This specialization has additional admission requirements for applying. You can find all admission requirements for this programme on the Admission Page.

    Curriculum

    The specialization features five core courses, two electives and a thesis that build your expertise:

    • Advanced Econometrics
    • Multivariate Econometrics
    • Time Series Models
    • Advanced Financial Econometrics
    • Financial Econometrics Case Study
    • Thesis MSc EOR - Econometrics
    • Two electives

    Please consult the Study Guide for more information

  • Climate Econometrics

    Summary

    How can we forecast extreme weather events using data science techniques? What is the impact of climate change on economies and societies in an increasingly interconnected world? How are financial markets affected by the implications of disasters?

    Climate change is one of the most pressing issues of the 21st century, affecting people, economies, and the environment globally. As the Intergovernmental Panel on Climate Change (IPCC) emphasizes the complexities of the climate system, the need for advanced quantitative analysis has never been greater. Climate change presents one of the most complex data challenges of our time.

    Our unique Climate Econometrics specialization equips you with advanced quantitative methods to analyze climate data, model environmental impacts, and support evidence-based decision-making in climate policy and business strategy.

    Why Choose Climate Econometrics?

    As the first programme in the Netherlands to combine advanced econometrics with climate science, we offer a unique opportunity to apply advanced quantitative methods to one of the world’s most pressing challenges. Through our collaboration with the Institute for Environmental Studies (IVM), you’ll learn to analyze complex climate data and model environmental impacts with unmatched precision.

    • Learn cutting-edge methods specifically designed for climate data analysis
    • Collaborate with leading climate scientists at VU’s Institute for Environmental Studies
    • Master advanced techniques for modeling complex climate systems
    • Apply econometric expertise to pressing environmental challenges
    • Develop solutions for climate-related economic and business problems

    Additional Admission Requirements

    This specialization has additional admission requirements for applying. You can find all admission requirements for this programme on the Admission Page.

    Curriculum

    The specialization features five core courses that build your expertise:

    • Advanced Econometrics
    • Multivariate Econometrics
    • Climate Data Science (New)
    • Climate Econometrics Case Study (New)
    • Big Data Statistics or Time Series Models
    • Thesis MSc EOR - Climate Econometrics (In collaboration with Institute for Environmental Studies)
    • Two electives

    Please consult the Study Guide for more information

  • Quantitative Logistics

    Summary

    How can organizations efficiently distribute their services in an increasingly interconnected world? What quantitative methods can improve supply chain performance? How can we optimize complex logistics networks while maintaining sustainability? These are the kinds of challenges you’ll learn to solve in our Quantitative Logistics specialization.

    This specialization combines advanced operations research techniques with deep logistics expertise, preparing you to optimize complex supply chains and distribution networks. It equips you with both the mathematical foundations and practical tools needed to excel in the rapidly evolving field of quantitative logistics.

    Why Choose Quantitative Logistics?

    In an increasingly connected world, optimizing logistics and supply chains requires advanced mathematical approaches. This specialization combines advanced operations research techniques with practical logistics expertise, preparing you to design and implement efficient solutions for complex distribution networks.

    • Master optimization methods for complex supply chain challenges
    • Develop strong computational and mathematical modeling skills
    • Design novel solutions for complex logistics problems
    • Create sustainable and efficient distribution networks
    • Apply advanced analytics to real-world logistics challenges

    Additional Admission Requirements

    This specialization has additional admission requirements for applying. You can find all admission requirements for this programme on the Admission Page.

    Curriculum

    The specialization features four core courses, three electives and a thesis that build your expertise:

    • Combinatorial Optimization
    • Optimization and Learning via Stochastic Gradient Search
    • Operations Research Case
    • Optimization and Multiagent Systems
    • Thesis MSc EOR - Operations Research
    • Three electives

    Please consult the Study Guide for more information

  • Financial Engineering

    Summary

    How can we create and price complex financial products in today’s expanding markets? What quantitative methods help us optimize investment portfolios and manage risks? How can we use simulation-based techniques to evaluate complex derivatives? These are the kinds of questions you’ll learn to answer in our Financial Engineering specialization.

    This specialization combines advanced operations research techniques with deep financial expertise, preparing you to tackle complex financial challenges using advanced mathematical methods. This specialization bridges the gap between finance and operations research, equipping you with the tools needed to excel in quantitative finance roles.

    Why Choose Financial Engineering?

    We bridge the gap between mathematical optimization and financial markets, providing you with the advanced quantitative tools needed to solve complex financial challenges. This specialization uniquely combines operations research techniques with financial expertise, preparing you for specialized roles in quantitative finance.

    • Master advanced optimization techniques for financial applications
    • Develop expertise in pricing complex financial products
    • Apply operations research methods to financial problems
    • Learn high-level computational methods for implementation
    • Gain practical experience with portfolio optimization and risk management

    Additional Admission Requirements

    This specialization has additional admission requirements for applying. You can find all admission requirements for this programme on the Admission Page.

    Curriculum

    The specialization features four core courses, three electives and a thesis that build your expertise:

    • Combinatorial Optimization
    • Optimization and Learning via Stochastic Gradient Search
    • Operations Research Case
    • Optimization and Multiagent Systems
    • Thesis MSc EOR - Operations Research
    • Three electives

    Please consult the Study Guide for more information

  • Business Engineering and Data-Driven Decision Making

    Summary

    How can organizations make better decisions using data and mathematical optimization? What quantitative methods can improve business processes and strategy? These are the kinds of questions you’ll learn to answer in our Business Engineering and Data-Driven Decision Making specialization.

    This specializaton combines advanced operations research methods with business engineering principles, preparing you to optimize complex business processes and drive data-informed decisions. Business engineering represents the intersection of business strategy and technical development, using mathematical models and frameworks to design and optimize processes that drive growth and performance. In today’s fast-developing business world, decision-making has become increasingly data-driven, requiring the integration of data analytics, statistics, and predictive modeling with process optimization. This specialization bridges the gap between mathematical optimization and business strategy, equipping you with the tools needed to help organizations make informed, objective, and measurable decisions that optimize outcomes.

    Why Choose Business Engineering and Data-Driven Decision Making?

    Modern business decisions require advanced quantitative analysis and optimization. This specialization combines operations research methods with business strategy, preparing you to transform complex business challenges into data-driven solutions that drive organizational success.

    • Transform business challenges into mathematical models
    • Develop expertise in data-driven decision making
    • Master process optimization techniques for business applications
    • Apply operations research methods to strategic business problems
    • Create solutions through business case studies and projects

    Curriculum

    The specialization features five core courses, two electives and a thesis that build your expertise:

    • Combinatorial Optimization
    • Optimization and Learning via Stochastic Gradient Search
    • Operations Research Case
    • Optimization and Multiagent Systems
    • AI for Data Driven Decision Making
    • Thesis MSc EOR - Operations Research
    • Two electives

Change your future with the Econometrics and Operations Research programme

Change your future with the Econometrics and Operations Research programme

On completing this Master’s programme, you will be a highly sought-after candidate in all types of businesses. As a graduate, depending on your chosen track and specialization, you can start working at a number of businesses and institutions. From conducting active research in the field of econometrics to understanding supply chain management; or from analysing Big Data to improving marketing strategies using data science, you will have the quantitative skills needed in the job market of today and the future.

Explore your future prospects
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