Кто читает:: Департамент экономики и анализа данных (Факультет экономики НИУ ВШЭ (Нижний Новгород))

Статус:: Курс обязательный

Когда читается:: 1-й курс, 1, 2 модуль

Преподаватель

Аистов Андрей Валентинович

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Abstract

As a result of studying the discipline, the student will be able to select a suitable approach for conducting empirical estimates in a particular practical scenario, accurately explain the benefits and drawbacks of the selected empirical model, identify the benefits and drawbacks of alternative approaches of performing empirical estimates that have been employed by other authors, and gain experience conducting empirical estimates on actual data. Features of the course are the illustration of theoretical material with examples of performing empirical estimates using computer programs and the acquisition by course participants of computer skills in econometric packages.

Learning Objectives

At the end of the course the student must have the general (universal) competence abbreviated in Russian as ``OPK--2.FIK''. It means being able to apply advanced instrumental methods of economic and financial analysis in applied and/or fundamental research in the field of financial relations, including the use of intelligent information and analytical systems.
Studying the course also contributes to the development of ``PK--2'' (Russian abbreviation) competence. It means being able to present the results of the research to the scientific community in the form of a report (presentation) and an article.

Expected Learning Outcomes

accurately explain benefits and drawbacks of selected empirical model
acquisition of computer skills in econometric packages
gain experience conducting empirical estimates on actual data
illustration of theoretical material with examples of performing empirical estimates using computer programs

Course Contents

Introduction
Inconsistency of the OLS estimator
The Instrumental Variables Estimator
Method of Moments

Assessment Elements

Activity
Activity

Interim Assessment

2025/2026 2nd module
Final grade for the course = max { Activity, Exam } , (1) where max is the largest of the two numbers, Activity or Exam. Activity is the result of rounding to the nearest integer value of the normalised sum of points accumulated by a student. Normalisation is implemented using a normalising multiplier, which equates the maximum total score in the educational group to 8.5. The sum of points is formed as follows. • During the classes, students ask questions, answer questions, and complete assignments. Activity in classes is stimulated by using a random number generator to call students to formulate questions and answers. • A student is given 1 point for the ability to ask a question, the correct answer, additions to the answers and similar activities that are useful for teaching and mastering educational material. • In case of missing a class in some day, a student can receive points for his detailed notes, additional materials, brief analytical reviews and essays, computer codes, presentations, etc., confirming that he has all the knowledge and practical skills that his classmates received during the class missed by the student. Additional points may be received for answering the instructor’s questions concerning materials of the class missed. The sum of points received by a student for the missed day of classes cannot exceed the maximum sum of points received by classmate present in the class that day. – The calendar day preceding the last class of the current course is the last day to submit the above-mentioned materials for missed classes. The Exam in (1) is exam score (an integer value). The maximum possible score is 10.1 To receive a score of 10, a student must demonstrate an excellent ability to complete any advanced assignment (marked with an asterisk) and explain the results obtained, or give a brilliant answer to a complex theoretical question have been offered during the classes. The assignment or question are selected randomly (using a random number generator). The time to prepare the answer is 10 minutes, during which students may use their own one-page A4 cheat sheet. The score is reduced by 1 for each of the following events: the student cannot complete a task or provides an incorrect solution or obtains an incorrect result or cannot correctly interpret the result or cannot explain the limitations of the applicability of the model. To receive a score lower than 10 during the exam, it is possible to receive points for the missed classes (see Activity) or classes with a small number of accumulated points. To do this, a student must retell the material from the classes in detail. This retelling must convincingly demonstrate the student’s mastery of the knowledge and practical skills other classmates were taught in those classes. The total score for the retelling cannot exceed the maximum of points received by classmate present in class. If a student is unable to answer a question on the subject matter, the student’s exam score will be reduced. Additional options for obtaining examination points are presented in Table 1.1 Table 1. Evaluation criteria Score Criterion 0–3 Scores 0–3 can be obtained using formula (1) 4 The student is able to successfully run on the computer all the scripts proposed by the teacher during the course 5 The student’s answer satisfies the above condition and the student explains the operation of all the commands contained in the scripts 6 The student’s answer meets the above condition and the student can modify the script to solve a similar problem with a different research question 7 The student’s answer meets the above conditions and the student provides details of the empirical models estimated using the above script, the results obtained, and the limitations imposed on the data generation process 8 The student’s answer satisfies the condition stated above and the student reasonably proposes another model that removes the limitations mentioned above 9 The student’s answer fulfils the above condition and the student discusses in detail all the empiri- cal models covered in the course that solve a similar problem, their advantages and disadvantages, gives recommendations for the choice of the optimal model, justifies the criteria for the choice of a model and suggests the development of the model to improve the quality of the result obtained Retake is carried out according to the rules of the Exam. The final grade is given according to formula (1).

Bibliography

Recommended Core Bibliography

A Guide to Modern Econometrics, 4th ed., 497 p., Verbeek, M., 2012
Verbeek, M. (2017). A Guide to Modern Econometrics (Vol. 5th edition). Hoboken, NJ: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1639496

Recommended Additional Bibliography

Econometric Analysis, 5th ed., 1026 p., Greene, W. H., 2003
Econometric Analysis, 7th ed., international edition, 1239 p., Greene, W. H., 2012
Greene, W. H. (2012). Econometric Analysis: International Edition : Global Edition (Vol. 7th ed., International ed). Boston: Pearson Education. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1417839
Greene, W. H. (2015). Econometric analysis. Slovenia, Europe: Prentice-Hall International. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.1BF5A5CA

Authors

Aistov Andrei Valentinovich

Магистерская программа «Финансы»

Econometrics