Прикладная микроэконометрика

Бакалавриат 2021/2022

Статус: Курс по выбору (Совместная программа по экономике НИУ ВШЭ и РЭШ)

Направление: 38.03.01. Экономика

Кто читает: Отдел сопровождения учебного процесса в Совместном бакалавриате ВШЭ-РЭШ

Где читается: Факультет экономических наук

Когда читается: 3-й курс, 3, 4 модуль

Формат изучения: без онлайн-курса

Охват аудитории: для своего кампуса

Язык: русский

Кредиты: 6

Контактные часы: 64

Полная версия программы учебной дисциплины

Аннотация

The goal of this course is to familiarize you with a range of techniques used in applied microeconometrics and to practice conducting your own empirical research. The big concept of the class is causality, and we will learn how/when we can interpret a certain empirical relationship as causal. The emphasis in the course will be on issues that arise in working with data and practical considerations in using various econometric techniques rather than their theoretical underpinnings. We will also have several invited lectures. It is assumed that you already have a sufficient knowledge of the basic econometric theory.

Цель освоения дисциплины

The main objective of the course is to prepare the students to do research and to provide them with essential tools to start working on their Bachelor’s thesis towards their diploma.

Планируемые результаты обучения

Has a working knowledge of some of the main econometric tools helpful for understanding current empirical literature in economics
Has an understanding of how the theoretical concepts are treated in applied econometrics, and have enough computational skills and familiarity with econometric software to implement their own empirical research.

Содержание учебной дисциплины

Introduction to causal inference. Potential outcomes approach. Randomized Experiments. Randomized inference. Externalities.
Regression: agnostic and causal. Selection on observables. Omitted variable bias and bad controls. Matching. Propensity score methods. Synthetic controls.
Measurement error in cross-section and in panel. Panel data. Fixed-effects and Firstdifferences estimators. Fixed effects vs Random effects. Incidental parameters problem. Difference-in-differences estimator. Non-standard standard errors.
Instrumental Variables. Heterogeneity and Local Average Treatment Effect. Weak instruments.
Regression discontinuity design. Sharp vs Fuzzy.
Selection and count models

Элементы контроля

Home assignments
Midterm
25%
In-class final test
35%

Промежуточная аттестация

2021/2022 учебный год 4 модуль
0.25 * Midterm + 0.35 * In-class final test + 0.4 * Home assignments

Программа дисциплины