Магистратура
2021/2022
Микроэконометрика качественных данных
Лучший по критерию «Полезность курса для Вашей будущей карьеры»
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Статус:
Курс по выбору (Экономика и экономическая политика)
Направление:
38.04.01. Экономика
Кто читает:
Департамент прикладной экономики
Где читается:
Факультет экономических наук
Когда читается:
1-й курс, 4 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Преподаватели:
Шелунцова Мария Александровна
Прогр. обучения:
Экономика и экономическая политика
Язык:
английский
Кредиты:
3
Контактные часы:
40
Course Syllabus
Abstract
● This course is devoted to binary choice models that are central in applied econometrics. We deal with the situation when the potential outcomes are discrete, i.e. the presence or absence of some quality of the object in question. It might also be the decision of an individual to perform or not to perform any action. The scope of application of these models is very wide. Classical examples are the problems of forecasting companies' defaults, employment equations, modeling the level of education, and many other problems of identifying the determinants of a certain choice and predicting its probability. In addition, we consider models with truncated dependent variable. The course includes Tobin and Heckman models that enables us to deal with truncated samples and selection bias. The course is applied in nature. Analysis of course’s topics is based on numerical examples. At the seminars, students use statistical software, i.e. STATA.
Learning Objectives
- The main goal of the course is to explore methods of analyzing microeconomic data. This includes estimating binary choice models and truncated regression models on the basis of statistical software package. Students will know the areas of application of the studied models, as well as the methods of checking the adequacy of these models with real data. Prerequisites are probability theory, statistics and econometrics.
Expected Learning Outcomes
- Students should be able to estimate and interpret probit and logit models as well as marginal effects.
- Students should be able to estimate multinominal logit and probit models
- Students should be able to estimate Tobit and Selection models
- Students should be able to use weighted least squares method to estimate probability under various assumptions about the distribution of random errors.
- Students should know when to apply Minimum Chi-square method and how to interpret the results.
Course Contents
- Binary choice models
- Ordered choice models
- System of binary choice equations with correlated errors
- Truncated and censored regression models
- Multiple choice models
Assessment Elements
- Individual home task
- Final written exam for 80 minutesExam will be carried out in LMS. Students must have personal computer with internet access to download individual tasks. Exam will be in an open book format.
- Individual home task
- Final written exam for 80 minutesExam will be carried out in LMS. Students must have personal computer with internet access to download individual tasks. Exam will be in an open book format.
Interim Assessment
- 2021/2022 4th module0.3 * Final written exam for 80 minutes + 0.7 * Individual home task
Bibliography
Recommended Core Bibliography
- Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics : Methods and Applications. New York, NY: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=138992
Recommended Additional Bibliography
- A. Colin Cameron, & Pravin K. Trivedi. (2010). Microeconometrics Using Stata, Revised Edition. StataCorp LP. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.tsj.spbook.musr