Econometrics: Methods and Applications (Coursera)

Econometrics: Methods and Applications (Coursera)
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The course requires some basics of matrices, probability, and statistics, which are reviewed in the Building Blocks module.
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Econometrics: Methods and Applications (Coursera)
Do you wish to know how to analyze and solve business and economic questions with data analysis tools? Then Econometrics by Erasmus University Rotterdam is the right course for you, as you learn how to translate data into models to make forecasts and to support decision making.

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* What do I learn?

When you know econometrics, you are able to translate data into models to make forecasts and to support decision making in a wide variety of fields, ranging from macroeconomics to finance and marketing. Our course starts with introductory lectures on simple and multiple regression, followed by topics of special interest to deal with model specification, endogenous variables, binary choice data, and time series data. You learn these key topics in econometrics by watching the videos with in-video quizzes and by making post-video training exercises.

* Do I need prior knowledge?

The course is suitable for (advanced undergraduate) students in economics, finance, business, engineering, and data analysis, as well as for those who work in these fields. The course requires some basics of matrices, probability, and statistics, which are reviewed in the Building Blocks module. If you are searching for a MOOC on econometrics of a more introductory nature that needs less background in mathematics, you may be interested in the Coursera course “Enjoyable Econometrics” that is also from Erasmus University Rotterdam.

* What literature can I consult to support my studies?

You can follow the MOOC without studying additional sources. Further reading of the discussed topics (including the Building Blocks) is provided in the textbook that we wrote and on which the MOOC is based: Econometric Methods with Applications in Business and Economics, Oxford University Press. The connection between the MOOC modules and the book chapters is shown in the Course Guide – Further Information – How can I continue my studies.

* Will there be teaching assistants active to guide me through the course?

Staff and PhD students of our Econometric Institute will provide guidance in January and February of each year. In other periods, we provide only elementary guidance. We always advise you to connect with fellow learners of this course to discuss topics and exercises.

* How will I get a certificate?

To gain the certificate of this course, you are asked to make six Test Exercises (one per module) and a Case Project. Further, you perform peer-reviewing activities of the work of three of your fellow learners of this MOOC. You gain the certificate if you pass all seven assignments.

Have a nice journey into the world of Econometrics!

The Econometrics team


Syllabus


WEEK 1

Simple Regression


WEEK 2

Multiple Regression


WEEK 3

Model Specification


WEEK 4

Endogeneity


WEEK 5

Binary Choice


WEEK 6

Time Series


WEEK 7

Case Project

This Case Project is the final assignment of our MOOC. It is of an applied nature, and it asks you to answer practical questions by means of econometric methods. By doing the case, you will integrate various econometric methods and skills that were trained in our MOOC.


WEEK 8

OPTIONAL: Building Blocks

By studying this module, you get the required background on matrices, probability and statistics. Each topic is illustrated with simple examples, and you get hands-on training by doing the training exercise that concludes each lecture. Three lectures on matrices show you the basic terminology and properties of matrices, including transpose, trace, rank, inverse, and positive definiteness. Two lectures on probability teach you the basics of univariate and multivariate probability distributions, especially the normal and associated distributions, including mean, variance, and covariance. Finally, two lectures on statistics present you with the basic ideas of statistical inference, in particular parameter estimation and testing, including the use of matrix methods and probability methods.



MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Course Auditing
42.00 EUR
The course requires some basics of matrices, probability, and statistics, which are reviewed in the Building Blocks module.

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.