Эконометрика: методы и применение

Магистратура 2019/2020

Статус: Курс по выбору (Управление в сфере науки, технологий и инноваций)

Направление: 38.04.02. Менеджмент

Кто читает: Департамент образовательных программ

Где читается: Институт статистических исследований и экономики знаний

Когда читается: 1-й курс, 4 модуль

Формат изучения: с онлайн-курсом

Преподаватели: Майснер Дирк

Прогр. обучения: Управление в сфере науки, технологий и инноваций

Язык: английский

Кредиты: 3

Контактные часы: 2

Full Syllabus

Abstract

The course introduces econometric tools to analyze and solve business and economic questions with data analysis tools. Econometrics is suitable 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. It includes simple and multiple regression, endogenous variables, binary choice data, and time series data tools. The course is provided by Econometric Institute Erasmus School of Business. The full outline is here https://www.coursera.org/learn/erasmus-econometrics

Learning Objectives

Ability to understand econometric analysis

Expected Learning Outcomes

Skills for linear regression, time series, econometrics, regression analysis

Course Contents

Simple Regression
Multiple Regression
Model Specification
Endogeneity
Binary Choice
Time Series
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.
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.

Assessment Elements

Essay
Final oral group examination
The Exam is planned as an ORAL GROUP EXAMINATION, online on ZOOM Platform. A Student should log in 20 minutes prior to Exam Session. Temporary internet breakdown is for up to 10 min. If longer - a written request to the course director, cc study office manager for further decision to reschedule the Exam for another date for examination: with different exam questions.

Interim Assessment

Interim assessment (4 module)
0.3 * Essay + 0.7 * Final oral group examination

Bibliography

Recommended Core Bibliography

Washington, S., Karlaftis, M. G., & Mannering, F. L. (2011). Statistical and Econometric Methods for Transportation Data Analysis (Vol. Second edition). Boca Raton, FL: Chapman and Hall/CRC. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1763415

Recommended Additional Bibliography

Harry Kelejian, & Gianfranco Piras. (2017). Spatial Econometrics. London, United Kingdom: Academic Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1465560

Course Syllabus