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Course Syllabus

Master 2023/2024

Data Analysis and Econometrics: Applications to Environmental Economics

Type: Compulsory course (Environmental Economics and Sustainable Development)
Area of studies: Economics
Delivered by: Faculty of World Economy and International Affairs
Where: Faculty of World Economy and International Affairs
When: 1 year, 2-4 module
Mode of studies: distance learning
Online hours: 24
Open to: students of one campus
Master’s programme: Environmental Economics and Sustainable Development
Language: English
ECTS credits: 9
Contact hours: 52

Course Syllabus

Full Syllabus

Abstract

Цель курса - не только дать студентам новые навыки как в области эконометрических инструментов, так и в их применении к современным экономическим проблемам, особенно в анализе проблем окружающей среды, но также теоретически изучить эконометрические методы и рассмотреть некоторые разделы эконометрики на прочной теоретической основе. В структуру курса также включен вывод основных свойств методов оценивания, но исключены доказательства наиболее аналитически сложных результатов. Основная цель изучения таких тем – четкое понимание эконометрических идей и предположений, при которых могут применяться эконометрические подходы. В то же время студенты должны получить навыки чтения и понимания наиболее передовых эконометрических статей.
Learning Objectives

Learning Objectives

  • The course aims to provide students with: knowledge on the fundamentals of econometrics and its application, knowledge and proficiency on the use of statistical package R for econometric analysis, practice in conducting data analysis and application of econometric tools in research and analytics, a range of quantitative methods of policy evaluation, examples of their application, problems that arise when evaluating programs and policies, directions of further development in the area of policy evaluation, practical exercises that can help in research and analytic activity.
Expected Learning Outcomes

Expected Learning Outcomes

  • Basic knowledge that will help you answer the following questions: • What is policy? • What would be the economic basis for your testimony? • Is there an objective theoretical justification for either policy? • How would you go about calculating the expected gains and losses from these proposed policies?
  • Have an ability to use computer software to perform statistical analysis on data (specifically, STATA).
  • Able to fit a logistic and linear regression model on a given dataset
  • Knows the main determinants of exchange rates, understands the role of expectations
  • Course gives opportunities to students to study how to apply econometrics and statistical software to model economic and financial processes, justify causal relations, find their main determinants and make forecasts.
Course Contents

Course Contents

  • Topic 1.1: OLS
  • Topic 1.2: Model Specification
  • Topic 1.3: Multicollinearity, Heteroskedasticity and Autocorrelation
  • Topic 1.4: Endogeneity and Instrumental Variables
  • Topic 2.1: Maximum Likelihood and Models with Limited Dependent Variables
  • Topic 2.2.: Time series econometrics. Univariate time series
  • Topic 2.3: Time series econometrics. Multivariate time series
  • Topic 2.4: Panel Data Analysis
  • Topic 3.1. Introduction. Randomization.
  • Topic 3.2. Propensity score matching
  • Topic 3.3. Difference-in-difference
  • Topic 3.4. Non-market valuation
  • Topic 3.5. Regression discontinuity.
  • Topic 3.6. Measuring distributional program effects
Assessment Elements

Assessment Elements

  • non-blocking Test on part 1
  • non-blocking Project Assignment
  • non-blocking Test on part 2
  • non-blocking Presentation on Part 3
  • non-blocking Test on Part 3
  • non-blocking Activity score
Interim Assessment

Interim Assessment

  • 2023/2024 3rd module
    0.3 * Project Assignment + 0.3 * Test on part 1 + 0.4 * Test on part 2
  • 2023/2024 4th module
    0.3 * Activity score + 0.3 * Presentation on Part 3 + 0.4 * Test on Part 3
Bibliography

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
  • Econometric analysis of panel data, Baltagi, B. H., 2005
  • Elhorst, J. P. (DE-588)171025091, (DE-576)131852809. (2014). Spatial econometrics : from cross-sectional data to spatial panels / J. Paul Elhorst. Heidelberg [u.a.]: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.396630170
  • Jeffrey M. Wooldridge. (2019). Introductory Econometrics: A Modern Approach, Edition 7. Cengage Learning.

Recommended Additional Bibliography

  • A guide to modern econometrics, Verbeek, M., 2008
  • Thornton, M., & Hashimzade, N. (2013). Handbook of Research Methods and Applications in Empirical Macroeconomics. Cheltenham: Edward Elgar Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=609451