Бакалавриат
2026/2027
Эконометрика
Статус:
Курс обязательный (Международная программа по бизнесу и экономике)
Кто читает:
Департамент экономики
Где читается:
Санкт-Петербургская школа экономики и менеджмента
Когда читается:
3-й курс, 1, 2 модуль
Охват аудитории:
для всех кампусов НИУ ВШЭ
Язык:
английский
Кредиты:
4
Контактные часы:
84
Course Syllabus
Abstract
This module is a basic course of scientific econometrics for students of the third year of economic study programmes. The module deals with applying statistical methods for analysis of economic data and empirical testing of causal relationships. The main focus is placed on correct formulation of research questions, choice of an empirical model for testing, parameter estimation and interpretation of obtained results.
Throughout the course teaching is conducted using real data. Substantial part of tutorials deals with data preparation, econometric analysis and presentation of reproduceable research results using R language. Prerequisites for the course are basic knowledge of mathematical analysis, probability theory and statistics.
Learning Objectives
- -
- The course teaching is conducted using real data. Substantial part of tutorials deals with data preparation, econometric analysis and presentation of reproduceable research results using R language. Prerequisites for the course are basic knowledge of mathematical analysis, probability theory and statistics.
Expected Learning Outcomes
- formulate research questions and testable hypotheses based on general economic theory
- choose econometric methods suitable to the research question, data structure and conditions for causal inference identification
- prepare, process and analyse real economic data according to modern standards of empirical research
- construct and evaluate econometric models, interpret their results
- critically analyse limitations of models and threats to internal and external validity of the research
- conduct reproduceable econometric analysis using R language, including code writing, producing tables and graphs suitable for presentation of research results
Course Contents
- 1. Introduction to econometrics and causal inference
- 2. Probability theory and statistics recap.
- 3. Simple linear regression
- 4. Multiple linear regression
- 5. Statistical conclusions and hypothesis testing in regression analysis
- 6. Non-linear regression specifications
- 7. Regression model diagnostics and study validity
- 8. Panel data
- 9. Instrumental variables method
- 10. Binary choice models
Assessment Elements
- Midterm test
- Group Empirical ProjectStudents complete the project in groups, and the final grade is awarded on the basis of an oral presentation (defence). Both the overall quality of the project and each group member's individual contribution to the final work are taken into account. Members of the same project group may therefore receive different grades. Timely completion of individual interim tasks (compliance with the deadline schedule) is also taken into account.
- Final Examination
Interim Assessment
- 2026/2027 2nd module0.4 * Final Examination + 0.25 * Group Empirical Project + 0.35 * Midterm test
