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Обычная версия сайта
2023/2024

Использование и анализ панельных данных в социальных науках

Лучший по критерию «Новизна полученных знаний»
Статус: Маго-лего
Когда читается: 3 модуль
Охват аудитории: для своего кампуса
Язык: английский
Кредиты: 3
Контактные часы: 36

Course Syllabus

Abstract

The course “Panel data: Analysis and Applications for the Social Sciences” aims to provide students with the theoretical background and practical skills in conducting panel data analysis. The first part of the course gives an overview of multiple regression models. The second part of the course focuses on the methodological tools necessary to succeed in handling panel data, namely, regression models with interaction terms and exploratory longitudinal data analysis. The third part covers fixed-effects and random-effects models. Lectures provide students with the theoretical foundations of panel data analysis. Practical sessions develop data analysis and data visualization skills. Students use RStudio for statistical analysis. At the practical sessions, students discuss the key approaches to handling panel data and illustrate them with different examples from social science research, in particular, economic sociology. Students are given datasets from original studies to replicate the findings and change the model specifications if needed.
Learning Objectives

Learning Objectives

  • The course aims to provide students with the theoretical background and practical skills in conducting panel data analysis. Specifically, the learning objectives are as follows: to enable students to choose appropriate models for panel data analysis; to develop data manipulation and visualization skills; to enable students to implement linear panel models in RStudio
  • The course aims to provide students with the theoretical background and practical skills in conducting panel data analysis. Specifically, the learning objectives are as follows:  to enable students to choose appropriate models for panel data analysis  to develop data manipulation and visualization skills  to enable students to implement linear panel models in RStudio
Expected Learning Outcomes

Expected Learning Outcomes

  • By the end of the course students are expected to apply fixed- and random- effects models to analyze panel data, to interpret the results, to have data visualization skills and skills in implementing the afore-mentioned methods by using RStudio in the context of panel data analysis. Students will learn the advantages and limitations of different approaches to panel data analysis. This knowledge will help students choose a set of appropriate statistical tools to test their research hypotheses.
Course Contents

Course Contents

  • Introduction. Linear regression analysis
  • Interaction terms in regression analysis
  • Fixed-effects models
  • Random-effects models VS Fixed-effects models
Assessment Elements

Assessment Elements

  • non-blocking Home Assignment 2
  • non-blocking Home Assignment 1
  • non-blocking Quiz 1
  • non-blocking Quiz 2
  • non-blocking Seminar Activity
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • 2023/2024 3rd module
    0.4 * Exam + 0.1 * Home Assignment 1 + 0.1 * Home Assignment 2 + 0.15 * Quiz 1 + 0.15 * Quiz 2 + 0.1 * Seminar Activity
Bibliography

Bibliography

Recommended Core Bibliography

  • Charles N. Halaby. (2003). Running Head: Panel Models Panel Models in Sociological Research: Theory into Practice. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.72A0015F
  • Анализ панельных данных и данных о длительности состояний, учебное пособие, Нац. исслед. ун-т Высшая школа экономики, 373 с., Ратникова, Т. А., Фурманов, К. К., 2014

Authors

  • SALNIKOVA DARIA VYACHESLAVOVNA