Pre-master Econometrics and Management Science

The pre-master Econometrics and Management Science prepares you for one of the specialisations within our MSc in Econometrics and Management Science.

The pre-master programme is taught in two languages. Please note that students who obtained their Bachelor's degree in the Netherlands can only participate in the English taught pre-master programme when the bachelor degree programme was taught entirely in English.

This pre-master is designed for students with a background in econometrics and operations research, economics and mathematics, quantitative economics, (applied) mathematics, statistics or industrial engineering that do not qualify for direct admission to any of the specialisations within the MSc in Econometrics and Management Science. Applicants with a Bachelor's degree in Economics, Business Economics or Business Administration need to have a quantitative specialisation (such as a minor or major in econometrics, operations research or decision analysis) in order to apply.

Courses in Programming

In the pre-master programme you can opt for FEB21011S Introduction to Programming or FEB22012 Programming. We advise all pre-master students to take Programming, and strongly recommend this in case you’re planning to choose the master specialisation Operations Research and Quantitative Logistics. We now first give an overview of both courses and then explain how to obtain prerequisite knowledge for the course Programming that you might be lacking.

Introduction to Programming (FEB21011S)

Introduction to Programming covers the fundamental concepts of imperative programming languages:

  • variables
  • elementary data-types
  • methods
  • arrays
  • for-loops, while-loops, and if-statements

The course also provides a brief and very basic introduction to object-oriented programming.

Programming (FEB22012 or FEB22012X)

Programming covers object-oriented programming in much more depth. It explains the following concepts:

  • inheritance and polymorphism
  • class hierarchies
  • exceptions
  • the collections framework

Preparing for Programming (FEB22012)

If you have prior experience with a strongly and statically typed language, such as C, C++, C#, Pascal or Java and have a very basic grasp of how to write a simple class, you should be able to follow the Programming course without any problems.

If you have prior experience with a weakly and/or dynamically typed language, such as Python, Javascript, MATLAB, R, Perl, Ruby, or PHP and are familiar with loops, if-statements and functions/methods, you are mostly good to go for the Programming course, although it is strongly encouraged to study static typing (e.g. all variables are declared with their type) and variable scope (e.g. a variable is not automatically available everywhere, depending on where you define it). This makes the transition to Java a lot more smooth.

If you don't have any prior programming experience, it is encouraged to follow and make the exercises of the free online Java course by the University of Helsinki (part 1-7) or watch the recommended part of the MOOC JAVA for Complete Beginners on Youtube before taking the Programming course. On the GitHub page linked below, you can find exactly which parts should be followed, and also two short exercises to assess your understanding of the material.

Preparation Exercises on GitHub

In any case, if you intend to follow Programming, it is encouraged to try and make the assignments at Preparation Exercises Programming for the Pre-master Econometrics and Management Science on GitHub and read up on some explanation or examples if you struggle.

  • De Take-Off is het introductieprogramma voor alle nieuwe  studententen aan Erasmus School of Economics. De Take-Off vindt plaats op maandag 31 augustus 2020. Tijdens dit introductie evenement maak je kennis met je studie, je medestudenten en de faculteit. Het programma bestaat onder meer uit een studie introductie en een uitleg over de systemen.

    Lees meer

    Introduction to Programming (minor and pre-master)

    The course starts by introducing the fundamental data types and operations. After that, control statements, i.e., decision and repetition, are presented. Then, methods, as computations consisting of multiple steps, are given. Lists and arrays, representing data structures storing multiple values, are depicted next. Last, the main concepts of object-oriented programming paradigm, i.e., class and instance, are described.

    Meanwhile, students are expected to roll up their sleeves and acquire hands-on experience with the Java programming language. For this purpose, programming assignments will have to be completed by the students using a popular Integrated Development Environment (IDE). Students will develop an algorithmic way of thinking by implementing solutions for elementary computational problems in Econometrics.

    Lees meer

    Programmeren

    • Week 1: Opfrissen Object-geörienteerd programmeren met Java
    • Week 2: Werken met interfaces
    • Week 3: Werken met inheritance
    • Week 4: Werken met datastructuren uit de Collections API
    • Week 5-6: Libraries, moderne Java features
    • Week 7: Samenvatting, andere programmeertalen (geen tentamenstof)

    Lees meer

    Discrete and continuous random variables, moment generating functions, discrete and continuous joint distributions, independence , conditional distributions, conditional expectations, variance, covariance, functions of random variables, transformation methods, Central Limit Theorem, stochastic convergence.

    Lees meer

    A typical phenomenon in empirical research is the wish to make statements about an unobservable population on the basis of an observed sample. The course Statistics aims to facilitate the construction of statistical statements about the population on the basis of a random sample. The statements may concern statistical estimates or statistical hypothesis tests.

    Moreover, the statistical statements are typically accompanied by information concerning the level of (un)certainty. In this course, the construction of "good" estimators and "good" tests in parametrical statistical models is considered. In particular, we will focus on the construction of method of moments estimators, maximum likelihood estimators, (uniformly) most powerful tests and likelihood ratio tests.

    Lees meer

    Van week tot week:

    1. Analysis of Unconstrained Problems
    2. Unconstrained Optimisation Methods
    3. Derivative-Free Optimisation
    4. Optimization with Sampling
    5. Analysis of Constrained Problems
    6. Constrained Optimisation Methods
    7. Distributed Optimisation

    Lees meer

    1. Discrete-time Markov chains
    2. Exponential distribution and the Poisson process
    3. Continuous-time Markov chains
    4. Basic queuing theory (M/M/c and variants)
    5. Gaussian processes (Brownian motion and others)

    (with applications in econometrics and operations research)

    Lees meer

    Het vakgebied econometrie wordt gekenmerkt door een combinatie van economische vraagstellingen, gebruik van empirische gegevens, toepassing van statistische en wiskundige methoden, en gebruik van software om modellen te schatten en te evalueren. Al deze onderwerpen komen uitgebreid aan de orde in de hoorcolleges en worden geoefend bij de sommencolleges en in de practica.

    • Hoorcollege en sommencollege: Inleiding econometrie, vraagstellingen, modellen, methoden. Het lineaire regressiemodel (enkelvoudig en meervoudig), methode van kleinste kwadraten, toetsen. Niet-lineaire modellen, maximale aannemelijkheid, enige asymptotische theorie van schatten en toetsen. De modellen en methoden worden gemotiveerd vanuit economische toepassingen en toegepast in praktische voorbeelden. De benodigde econometrische methoden maken intensief gebruik van eerdere vakken uit het programma, met name statistiek, lineaire algebra en analyse.
    • Practicum: Opgaven over theorie en toepassingen. Voorts wordt enige malen een computer-practicum gehouden, waar econometrische technieken worden toegepast met het pakket EViews.

    Lees meer

    Dit vak geeft een inleiding in de theorie en technieken van de lineaire programmering. Behandeld worden:

    • Modelleren van lineaire programmeringsproblemen
    • Oplossen van lineaire programmeringsproblemen
    • Primale en duale (gereviseerde) simplex methode
    • Dualiteitstheorie
    • Gevoeligheidsanalyse
    • Netwerk simplex methode

    Lees meer

    By means of practical case studies, attention will be given to the four different major tracks within the bachelor econometrics programme:

    • Students participate only in the case that fits with the profile of their pre-master programme
    • Different computer packages will be used
    • Presenting of research findings

    Lees meer

    Tijdreeksanalyse is het vakgebied dat zich bezighoudt met het modelleren van sequentiele waarnemingen van economische variabelen, zoals maandelijkse werkloosheidcijfers.
    Een dergelijk model kan worden gebruikt voor het doen van voorspellingen en voor het inschatten van mogelijke gevolgen van beleid.
    Centraal staat hierbij de dynamische samenhang tussen economische ontwikkelingen (bijv. trends, seizoeninvloeden, conjunctuurcycli).

    De voornaamste onderwerpen die in dit vak aan bod komen zijn:

    • Theorie van stationaire processen
    • Lineaire tijdreeksmodellen (ARIMA)
    • De keus van de dynamische structuur van een tijdreeksmodel
    • Schatten van modelparameters
    • Evaluatie van tijdreeksmodellen
    • Omgaan met bijzondere waarnemingen (uitschieters)
    • Voorspelmethoden
    • Niet-lineaire tijdreeksmodellen

    Lees meer

    Studenten kiezen een specialisatie uit onderstaande lijst van specialisaties:

    The course is primarily theoretical. In this course we use a lot of linear algebra and see its connection with statistics. After the univariate statistics studied in the previous courses, we move to multivariate statistical methods. We start with the geometry of multivariate samples. Then we generalize the univariate methods to multivariate setting. And finally, we study several techniques, which are useful in practice. 

    Learning goals

    • De student maakt kennis met de multivariaat normale verdeling.
    • De student leert enkele confirmatieve multivariate technieken, die gebruik maken van de multivariaat normale verdeling, toe te passen.
    • De student leert de basis van principale componenten en factoranalyse.

    Lees meer

    Na een algemene inleiding in de micro-economie zal de aandacht uitgaan naar de keuzetheorie. Uitgangspunt is dat economische handelingen doelgericht zijn: de beperkte middelen die een subject voorhanden heeft worden zodanig gebruikt dat een bepaalde doelstelling bereikt wordt. Dit algemene uitgangspunt wordt op de handelingen van de consument en producent toegepast. Vervolgens komt het functioneren van markten aan de orde. Ook zal een begin worden gemaakt met het analyseren van strategische interactie met behulp van de speltheorie.

    Lees meer

    De volgende simulatietechnieken worden behandeld:

    • Inleiding simulatiemodel
    • Vertalen complexe econometrische en besliskundige problemen in een simulatiemodel
    • Simulatiemodel validatie
    • Inleiding random generatoren
    • Methoden voor het genereren van realisaties van kansvariabelen
    • Discrete event simulatie
    • Monte Carlo methode
    • Statistische analyse van de uitkomsten van simulatie-experimenten
    • Simulatie optimalisatie

    Let wel: Het hoorcollege zal in het Engels worden gegeven.

    Lees meer

    Het college is een vervolg op het college Econometrie 1 en bestaat uit de volgende onderwerpen:

    • Modellen met heteroskedasticiteit en seriecorrelatie
    • Modellen met endogene regressoren
    • Modellen voor kwalitatieve data (logit, probit, multinomiaal)

    Na dit college heeft de student kennis van de theorie over diverse uitbreidingen van het lineaire model (waaronder: heteroskedasticiteit, seriecorrelatie, endogeniteit). Daarnaast heeft de student kennis van modellen voor keuzegedrag (logit, probit, multinomiale variabelen).

    De student kan de theorie ook daadwerkelijk toepassen in de praktijk, en heeft ook ervaring met het zelf analyseren van economische data met behulp van Eviews.

    Lees meer

    The course is primarily theoretical. In this course we use a lot of linear algebra and see its connection with statistics. After the univariate statistics studied in the previous courses, we move to multivariate statistical methods. We start with the geometry of multivariate samples. Then we generalize the univariate methods to multivariate setting. And finally, we study several techniques, which are useful in practice. 

    Lees meer

    Micro-economie (econometrie)

    Na een algemene inleiding in de micro-economie zal de aandacht uitgaan naar de keuzetheorie. Uitgangspunt is dat economische handelingen doelgericht zijn: de beperkte middelen die een subject voorhanden heeft worden zodanig gebruikt dat een bepaalde doelstelling bereikt wordt. Dit algemene uitgangspunt wordt op de handelingen van de consument en producent toegepast. Vervolgens komt het functioneren van markten aan de orde. Ook zal een begin worden gemaakt met het analyseren van strategische interactie met behulp van de speltheorie.

    Lees meer

    Finance (econometrie)

    • De tijdswaarde van geld en geschikte disconteringsvoet. 
    • De rol van arbitrage in finance.
    • De waardebepaling van obligaties en aandelen.
    • Marktefficientie en de financiele markt als informatieverwerker.
    • Risico en rendementsmodellen
    • Portefeuille theorie

    Lees meer

     

    De volgende simulatietechnieken worden behandeld:

    • Inleiding simulatiemodel
    • Vertalen complexe econometrische en besliskundige problemen in een simulatiemodel
    • Simulatiemodel validatie
    • Inleiding random generatoren
    • Methoden voor het genereren van realisaties van kansvariabelen
    • Discrete event simulatie
    • Monte Carlo methode
    • Statistische analyse van de uitkomsten van simulatie-experimenten
    • Simulatie optimalisatie

    Let wel: Het hoorcollege zal in het Engels worden gegeven.

    Lees meer

    Het college is een vervolg op het college Econometrie 1 en bestaat uit de volgende onderwerpen:

    • Modellen met heteroskedasticiteit en seriecorrelatie
    • Modellen met endogene regressoren
    • Modellen voor kwalitatieve data (logit, probit, multinomiaal)

    Na dit college heeft de student kennis van de theorie over diverse uitbreidingen van het lineaire model (waaronder: heteroskedasticiteit, seriecorrelatie, endogeniteit). Daarnaast heeft de student kennis van modellen voor keuzegedrag (logit, probit, multinomiale variabelen).

    De student kan de theorie ook daadwerkelijk toepassen in de praktijk, en heeft ook ervaring met het zelf analyseren van economische data met behulp van Eviews.

    Lees meer

    The course is primarily theoretical. In this course we use a lot of linear algebra and see its connection with statistics. After the univariate statistics studied in the previous courses, we move to multivariate statistical methods. We start with the geometry of multivariate samples. Then we generalise the univariate methods to multivariate setting. And finally, we study several techniques, which are useful in practice. 

    Lees meer

    Na een algemene inleiding in de micro-economie zal de aandacht uitgaan naar de keuzetheorie. Uitgangspunt is dat economische handelingen doelgericht zijn: de beperkte middelen die een subject voorhanden heeft worden zodanig gebruikt dat een bepaalde doelstelling bereikt wordt. Dit algemene uitgangspunt wordt op de handelingen van de consument en producent toegepast. Vervolgens komt het functioneren van markten aan de orde. Ook zal een begin worden gemaakt met het analyseren van strategische interactie met behulp van de speltheorie.

    Lees meer

    The objective of the course will be to demonstrate the benefits of using a systematic and analytical approach to decision-making in marketing. 

    Lees meer

    Het college is een vervolg op het college Econometrie 1 en bestaat uit de volgende onderwerpen:

    • Modellen met heteroskedasticiteit en seriecorrelatie
    • Modellen met endogene regressoren
    • Modellen voor kwalitatieve data (logit, probit, multinomiaal)

    Na dit college heeft de student kennis van de theorie over diverse uitbreidingen van het lineaire model (waaronder: heteroskedasticiteit, seriecorrelatie, endogeniteit). Daarnaast heeft de student kennis van modellen voor keuzegedrag (logit, probit, multinomiale variabelen).

    De student kan de theorie ook daadwerkelijk toepassen in de praktijk, en heeft ook ervaring met het zelf analyseren van economische data met behulp van Eviews.

    Lees meer

    De combinatorische optimalisering houdt zich bezig met het vinden van een optimale oplossing uit een eindige verzameling van toegelaten oplossingen. Omdat volledige enumeratie van deze verzameling vaak onpraktisch is door het zeer grote aantal toegelaten oplossingen, probeert men gericht te zoeken naar een optimale oplossing door gebruik te maken van de aanwezige structuur. In dit college worden oplossingsmethoden voor combinatorische optimaliseringsproblemen behandeld. Technieken die worden behandeld zijn:

    • Branch-and-bound
    • Lagrange relaxatie
    • Maximum stroom algoritme
    • Hongaarse methode
    • Dynamisch programmeren

    Lees meer

    Micro-economie (econometrie)

    Na een algemene inleiding in de micro-economie zal de aandacht uitgaan naar de keuzetheorie. Uitgangspunt is dat economische handelingen doelgericht zijn: de beperkte middelen die een subject voorhanden heeft worden zodanig gebruikt dat een bepaalde doelstelling bereikt wordt. Dit algemene uitgangspunt wordt op de handelingen van de consument en producent toegepast. Vervolgens komt het functioneren van markten aan de orde. Ook zal een begin worden gemaakt met het analyseren van strategische interactie met behulp van de speltheorie.

    Lees meer

    Finance (econometrie)

    • De tijdswaarde van geld en geschikte disconteringsvoet. 
    • De rol van arbitrage in finance.
    • De waardebepaling van obligaties en aandelen.
    • Marktefficientie en de financiele markt als informatieverwerker.
    • Risico en rendementsmodellen
    • Portefeuille theorie

    Lees meer

    De volgende simulatietechnieken worden behandeld:

    • Inleiding simulatiemodel
    • Vertalen complexe econometrische en besliskundige problemen in een simulatiemodel
    • Simulatiemodel validatie
    • Inleiding random generatoren
    • Methoden voor het genereren van realisaties van kansvariabelen
    • Discrete event simulatie
    • Monte Carlo methode
    • Statistische analyse van de uitkomsten van simulatie-experimenten
    • Simulatie optimalisatie

    Let wel: Het hoorcollege zal in het Engels worden gegeven.

    Lees meer

  • The Take-Off is the introduction programme for all new students at Erasmus School of Economics. The Take-Off will take place on Monday, 31 August 2020. During the Take-Off you will meet your fellow students, get acquainted with our study associations and learn all the ins and outs of your new study programme, supporting information systems and life on campus and in the city.

    Read more

    The course starts by introducing the fundamental data types and operations. After that, control statements, i.e., decision and repetition, are presented. Then, methods, as computations consisting of multiple steps, are given. Lists and arrays, representing data structures storing multiple values, are depicted next. Last, the main concepts of object-oriented programming paradigm, i.e., class and instance, are described.
    Meanwhile, students are expected to roll up their sleeves and acquire hands-on experience with the Java programming language. For this purpose, programming assignments will have to be completed by the students using a popular Integrated Development Environment (IDE). Students will develop an algorithmic way of thinking by implementing solutions for elementary computational problems in Econometrics.

    Read more

    • Week 1: Refresh Object-oriented programming Java
    • Week 2: Working with interfaces
    • Week 3: Working with inheritance
    • Week 4: Working with datastructes from the Collections API
    • Week 5-6: Libraries, modern Java features
    • Week 7: Summary, other programming languages (no exam material)

    Read more

    Discrete and continuous random variables, moment generating functions, discrete and continuous joint distributions, independence , conditional distributions, conditional expectations, variance, covariance, functions of random variables, transformation methods, Central Limit Theorem, stochastic convergence.

    Read more

    A typical phenomenon in empirical research is the wish to make statements about an unobservable population on the basis of an observed sample. The course Statistics aims to facilitate the construction of statistical statements about the population on the basis of a random sample. The statements may concern statistical estimates or statistical hypothesis tests. Moreover, the statistical statements are typically accompanied by information concerning the level of (un)certainty. In this course, the construction of "good" estimators and "good" tests in parametrical statistical models is considered. In particular, we will focus on the construction of method of moments estimators, maximum likelihood estimators, (uniformly) most powerful tests and likelihood ratio tests.

    Read more

    From week to week:

    1. Analysis of Unconstrained Problems
    2. Unconstrained Optimization Methods
    3. Derivative-Free Optimization
    4. Optimization with Sampling
    5. Analysis of Constrained Problems
    6. Constrained Optimization Methods
    7. Distributed Optimization

    Read more

    (1) Discrete-time Markov chains
    (2) Exponential distribution and the Poisson process
    (3) Continuous-time Markov chains
    (4) Basic queueing theory (M/M/c and variants)
    (5) Gaussian processes (Brownian motion and others)

    (with applications in econometrics and operations research)

    Read more

    Econometrics is characterized by the combination of economic research questions, use of empirical data, application of statistical and mathematical methods, and the use of software to estimate and evaluate models. All these topics are extensively discussed in the lectures and practised in the tutorials.

    • Lectures and exercise lectures: Introduction to econometrics, research questions, methods. The linear regression model (simple and multiple), method of least squares, testing. Non-linear models, maximum likelihood, some asymptotic theory of estimation and testing. The models and methods are motivated by economic applications and applied in practical examples. The required econometric methods make intensive use of earlier courses in the programme, in particular statistics, matrix algebra and analysis.
    • Tutorials: Exercises on theory and applications. Further, some tutorials consist of computer sessions to apply econometric techniques by means of the software package EViews.

    Read more

    This course is an introduction in the theory and methods to solve linear programming problems. The topics of the course are:

    • Modeling and solving linear programming problems
    • Primal and dual (revised) simplex method
    • Duality theory
    • Sensitivity analysis
    • Network simplex method

    Read more

    By means of practical case studies, attention will be given to the four different major tracks within the bachelor econometrics programme:

    • Students participate only in the case that fits with the profile of their pre-master program
    • Different computer packages will be used
    • Presenting of research findings

    Read more

    Time series analysis concerns modelling sequential observations on economic variables, such as monthly unemployment figures. A suitable time series model can be used for making forecasts and for policy analysis. A key issue in developing a suitable model for time series concerns the dynamic features of economic variables, such as trends, seasonal fluctuations, and business cycles.

    The main topics covered in this course are:

    • Theory of stationary dynamic processes
    • Linear time series models (ARMA)
    • Model selection
    • Parameter estimation
    • Evaluating time series models
    • Handling special observations (outliers)
    • Forecasting methods and evaluation
    • Nonlinear time series models

    Read more

    Students choose one Specialisation from the specialisations listed below:

    The course is primarily theoretical. In this course we use a lot of linear algebra and see its connection with statistics. After the univariate statistics studied in the previous courses, we move to multivariate statistical methods. We start with the geometry of multivariate samples. Then we generalize the univariate methods to multivariate setting. And finally, we study several techniques, which are useful in practice. 

    Read more

    • The first part of the course deals with the theory of the consumer. Topics covered include consumer choice under certainty and uncertainty, and individual and market demand.
    • The second part focuses on the theory of the firm, and includes the topics of firm production and firm cost.
    • The last part of the course turns to market structures (monopoly, imperfect competition and perfect competition), to the joint analysis of firm and consumer behavior within a market (general equilibrium theory) and to factor markets.

    Read more

    The following simulation techniques will be covered:

    • Basic set-up of a Discrete-event simulation model
    • Formulating complex econometric and OR problems in a simulation model.
    • Model validation
    • Random number generators
    • Methods to generate realisations of random variables
    • Discrete event simulation
    • Monte Carlo method
    • Statistical analysis of simulation results

    Read more

    The lectures are a follow-up on the lectures in Econometrics 1. The following topics will be discussed:

    • Models with heteroskedasticity and/or serial correlation
    • Models with endogenous regressors
    • Models for limited dependent variables (logit, probit, multinomial)

    After this course the student will have practical and theoretical knowledge of various extensions of the linear model (among which: heteroskedasticity, serial correlation, endogeneity). The student will also have knowledge of models for limited dependent variables (logit model, probit model, multinomial).

    The student will be able to apply the theory in practice, and will also gain experience in the analysis of economic data using Eviews.

    Read more

    The course is primarily theoretical. In this course we use a lot of linear algebra and see its connection with statistics. After the univariate statistics studied in the previous courses, we move to multivariate statistical methods. We start with the geometry of multivariate samples. Then we generalize the univariate methods to multivariate setting. And finally, we study several techniques, which are useful in practice. 

    Read more

    Microeconomics

    • The first part of the course deals with the theory of the consumer. Topics covered include consumer choice under certainty and uncertainty, and individual and market demand.
    • The second part focuses on the theory of the firm, and includes the topics of firm production and firm cost.
    • The last part of the course turns to market structures (monopoly, imperfect competition and perfect competition), to the joint analysis of firm and consumer behavior within a market (general equilibrium theory) and to factor markets.

    Read more

    Finance (econometrics)

    • The time-value of money and appropriate discount rate.
    • The role of arbitrage in finance
    • The value of bonds and stocks
    • Market efficiency and financial markets as information processor.
    • Risk and return models
    • Portfolio theory

    Read more

    The following simulation techniques will be covered:

    • Basic set-up of a Discrete-event simulation model
    • Formulating complex econometric and OR problems in a simulation model.
    • Model validation
    • Random number generators
    • Methods to generate realisations of random variables
    • Discrete event simulation
    • Monte Carlo method
    • Statistical analysis of simulation results

    Read more

    The lectures are a follow-up on the lectures in Econometrics 1. The following topics will be discussed:

    • Models with heteroskedasticity and/or serial correlation
    • Models with endogenous regressors
    • Models for limited dependent variables (logit, probit, multinomial)

    After this course the student will have practical and theoretical knowledge of various extensions of the linear model (among which: heteroskedasticity, serial correlation, endogeneity). The student will also have knowledge of models for limited dependent variables (logit model, probit model, multinomial).

    The student will be able to apply the theory in practice, and will also gain experience in the analysis of economic data using Eviews.

    Read more

    The course is primarily theoretical. In this course we use a lot of linear algebra and see its connection with statistics. After the univariate statistics studied in the previous courses, we move to multivariate statistical methods. We start with the geometry of multivariate samples. Then we generalize the univariate methods to multivariate setting. And finally, we study several techniques, which are useful in practice. 

    Read more

    • The first part of the course deals with the theory of the consumer. Topics covered include consumer choice under certainty and uncertainty, and individual and market demand.
    • The second part focuses on the theory of the firm, and includes the topics of firm production and firm cost.
    • The last part of the course turns to market structures (monopoly, imperfect competition and perfect competition), to the joint analysis of firm and consumer behavior within a market (general equilibrium theory) and to factor markets.

    Read more

    The lectures are a follow-up on the lectures in Econometrics 1. The following topics will be discussed:

    • Models with heteroskedasticity and/or serial correlation
    • Models with endogenous regressors
    • Models for limited dependent variables (logit, probit, multinomial)

    After this course the student will have practical and theoretical knowledge of various extensions of the linear model (among which: heteroskedasticity, serial correlation, endogeneity). The student will also have knowledge of models for limited dependent variables (logit model, probit model, multinomial).

    The student will be able to apply the theory in practice, and will also gain experience in the analysis of economic data using Eviews.

    Read more

    The objective of the course will be to demonstrate the benefits of using a systematic and analytical approach to decision-making in marketing. 

    Read more

    Combinatorial optimisation deals with finding an optimal solution from a finite set of feasible solutions. Since enumerating this set is practically infeasible in general, one tries to exploit the problem structure to find an optimal solution in a computationally efficient way. In this course, we develop techniques for combinatorial optimisation problems. These techniques include:

    • Branch-and-bound
    • Lagrangean relaxation
    • Maximum flow algorithm
    • Hongarian method
    • Dynamic programming

    Read more

    Microeconomics

    • The first part of the course deals with the theory of the consumer. Topics covered include consumer choice under certainty and uncertainty, and individual and market demand.
    • The second part focuses on the theory of the firm, and includes the topics of firm production and firm cost.
    • The last part of the course turns to market structures (monopoly, imperfect competition and perfect competition), to the joint analysis of firm and consumer behavior within a market (general equilibrium theory) and to factor markets.

    Read more

    Finance (econometrics)

    • The time-value of money and appropriate discount rate.
    • The role of arbitrage in finance
    • The value of bonds and stocks
    • Market efficiency and financial markets as information processor.
    • Risk and return models
    • Portfolio theory

    Read more

    The following simulation techniques will be covered:

    • Basic set-up of a Discrete-event simulation model
    • Formulating complex econometric and OR problems in a simulation model.
    • Model validation
    • Random number generators
    • Methods to generate realisations of random variables
    • Discrete event simulation
    • Monte Carlo method
    • Statistical analysis of simulation results

    Read more