Бакалавриат
2021/2022![Learning Objectives](/f/src/global/i/edu/objectives.svg)
![Course Contents](/f/src/global/i/edu/sections.svg)
![Assessment Elements](/f/src/global/i/edu/controls.svg)
![Interim Assessment](/f/src/global/i/edu/intermediate_certification.svg)
![Bibliography](/f/src/global/i/edu/library.svg)
Эконометрика
Статус:
Курс обязательный
Направление:
01.03.02. Прикладная математика и информатика
Где читается:
Факультет компьютерных наук
Когда читается:
3-й курс, 1-4 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
7
Контактные часы:
120
Course Syllabus
Abstract
The Elements of Econometrics is an introductory full year course for the 3-rd year students of the Double Degree programme of NRU HSE and the University of London. The course is taught in English and finally examined by the University of London international programme, or by HSE final exam.
The stress in the course is done on the essence of statements, methods and approaches of econometric analysis. The conclusions and proofs of basic formulas and models are given which allows the students to understand the principles of econometric theory development. The main attention is paid to the economic interpretations and applications of the econometric models. The first part of the course is devoted to the cross-section econometrics; the second part – to the time series and panel data econometrics. Prerequisites: Statistics, Mathematical Methods or Mathematics for Economists, Introduction to Economics
Learning Objectives
- The students get in the course basic knowledge and skills of econometric analysis and its application in Economics. They should be able to: - apply econometric methods to the investigation of economic relationships and processes; - verify economic facts, theories and models with real data; - evaluate the quality of statistical and econometric analysis; - do and evaluate forecasting for time series and cross section data; - understand econometric methods, approaches, ideas, results and conclusions met in economic books and articles.
- The students should understand essential differences between the time series and cross section data and those specific econometric problems met in the work with these types of data (measurement errors, endogeneity, autocorrelation, non-stationarity and others), as well as with panel data, and apply the appropriate econometric methods (instrumental variables, maximum likelihood estimation, models of dynamic processes, etc.).
- The students should get the skills of construction and development of linear regression models, get acquainted with some non-linear models and special methods of econometric analysis and estimation (binary choice models, non-linear least squares, maximum likelihood estimation), understanding the area of their application in economics.
- The methods and models should be mastered practically on real economic data sets with modern econometric software.
Course Contents
- Introduction to Econometrics
- Simple Linear Regression Model (SLR) with Non-stochastic Explanatory Variables. OLS estimation
- Multiple Linear Regression Model (MLR): two explanatory variables and k explanatory variables
- Variables Transformations in Regression Analysis
- Dummy Variables
- Linear Regression Model Specification
- Heteroscedasticity
- Stochastic Explanatory Variables. Measurement Errors. Instrumental Variables
- Simultaneous Equations Models
- Maximum Likelihood Estimation
- Binary Choice Models, Limited Dependent Variable Models
- Modelling with Time Series Data. Dynamic Processes Models
- Autocorrelated disturbance term
- Time Series Econometrics: Nonstationary Time Series
- Panel Data Models
Assessment Elements
- Home assignments Semester 1
- October mid-termThe students sit two mid-term written exams in October and in March, first semester written exam in December, and University of London International programme exam (or HSE final exam) in May. October and December exams include multiple choice and free response parts. March and May exams are free response (open questions) exams.
- December examThe exam may be carried out online via distance learning platforms. In 2021-2022, December exam and the University of London (or HSE final) exam have a status of exam in the Curriculum with possible retakes, while October and March mid-term exams have a status of Control Paper (with no retakes).
- March Mid-termThe students sit two mid-term written exams in October and in March, first semester written exam in December, and University of London International programme exam (or HSE final exam) in May. October and December exams include multiple choice and free response parts. March and May exams are free response (open questions) exams.
- Final examThe exam may be carried out online via distance learning platforms. In 2021-2022, December exam and the University of London (or HSE final) exam have a status of exam in the Curriculum with possible retakes, while October and March mid-term exams have a status of Control Paper (with no retakes).
- Applied essay
- Bonus for course activities
- Home assignments Semester 2
Interim Assessment
- 2021/2022 2nd moduleG=0.25*Goct+0.5*Gdec+0.25*Gha1 ha1 – home assignments in semester; Goct, Gdec - the grades for October mid-term and December exam out of 100.
- 2021/2022 4th moduleG=0.3*(0.25*Goct+0.5*Gdec+0.25*Gha1)+0.2*Gmarch+0.1*Gha2+Gessay+0.4Gfin+Gbonus In the second semester the applied essay is set with the bonus points out of 10. As a rule, the applied essay will be required to be presented and defended by the author.
Bibliography
Recommended Core Bibliography
- Dougherty, C. (2016). Introduction to Econometrics. Oxford University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.oxp.obooks.9780199676828
- Introduction to econometrics, Dougherty, C., 2011
Recommended Additional Bibliography
- Econometric analysis, Greene, W. H., 2003
- Wooldridge, J. M. . (DE-588)131680463, (DE-576)298669293. (2006). Introductory econometrics : a modern approach / Jeffrey M. Wooldridge. Mason, Ohio [u.a.]: Thomson/South-Western. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.250894459