Deze cursusinformatie geeft aan hoe het onderwijs zal verlopen bij pandemieniveau code geel en groen.
Als er tijdens het academiejaar aangepast wordt naar code oranje of rood, zijn er wijzigingen mogelijk o.a. in de gebruikte werk - en evaluatievormen.

# Introduction to econometrics

 Course Code : 1304TEWKWM Study domain: Statistics Academic year: 2020-2021 Semester: 1st semester Sequentiality: The student must have obtained a credit for the following courses: - 'Beschrijvende statistiek en kansrekenen' or 'Statistiek I' - 'Statistiek II' - 'Micro-economie' (or included in study programme) - 'Macro-economie' (or included in study programme) Contact hours: 60 Credits: 6 Study load (hours): 168 Contract restrictions: No contract restriction Language of instruction: English Exam period: exam in the 1st semester Lecturer(s) Sunčica VujićSofie Cabus

### 3. Course contents *

Introduction to Econometrics is designed as a first course in undergraduate econometrics. The goal of this course is to use statistical analysis, including the classical regression model, to estimate relevant economic parameters, predict economic outcomes, and test economic hypotheses using quantitative data; to understand the basic assumptions of the classical linear regression model, and identify and correct (if possible) any violations of these assumptions, such as autocorrelation, heteroscedasticity, and multicollinearity; to develop and maintain a working knowledge of econometrics that will provide a basic foundation for future study in econometrics and statistical techniques. The course is not theorem-proof driven, but emphasises motivation, understanding, implementation, and interpretation.

Part I. Introduction and Review

• Economic Questions and Data
• Review of Probability and Statistics

Part II. Fundamentals of Regression Analysis

• The Simple Linear Regression Model
• Hypothesis Tests and Confidence Intervals
• The Multiple Regression Model
• Further Inference in the Multiple Regression Model
• Nonlinear Regression Functions
• Assessing Studies Based on Multiple Regression

Part III. Further Topics in Regression Analysis

• Regression with a Binary Dependent Variable
• Instrumental Variables Regression