EC2020 - Elements of Econometrics at London School of Economics: A brief Overview
Explore the fundamental principles of econometrics in the EC2020 course at the London School of Economics. This comprehensive program is designed to equip students with the necessary tools and techniques to analyze economic data, make informed predictions, and understand the complex relationships within economic systems.
Syllabus:
Introduction to Econometrics:
Definition and scope of econometrics
Basic concepts and principles
Role of econometrics in economic analysis
Statistical Foundations:
Probability and distribution theory
Hypothesis testing and confidence intervals
Regression analysis fundamentals
Simple and Multiple Regression Models:
Model specification and interpretation
OLS (Ordinary Least Squares) estimation
Assumptions and diagnostics
Violations and Remedies:
Multicollinearity, heteroscedasticity, and autocorrelation
Methods to address model violations
Robust regression techniques
Advanced Topics in Econometrics:
Instrumental variables
Time-series analysis
Panel data models
Applications and Case Studies:
Real-world examples and applications
Empirical studies in economics
Practical implementation of econometric techniques
Why Choose EC2020 at LSE?
World-Class Faculty: Learn from renowned experts and scholars in the field of econometrics.
Cutting-Edge Curriculum: Stay updated with the latest advancements in econometric methods and applications.
Practical Application: Gain hands-on experience through case studies and real-world applications.
Networking Opportunities: Connect with fellow students and professionals in the field during workshops and seminars.
Career Opportunities: A solid foundation in econometrics opens doors to a variety of career paths, including economic research, financial analysis, policy evaluation, and more.
Enroll in EC2020 at LSE to unlock the door to a future in econometrics. Explore the intricacies of economic analysis and make informed decisions based on data-driven insights. Contact LSE admissions to secure your spot in this dynamic course.
Detailed Course Plan
Week 1-2: Introduction to Econometrics
Overview of econometrics and its role in economics
Basic concepts: population vs. sample, parameters vs. estimators
Types of data: cross-sectional, time series, panel data
Review of statistical concepts (probability, distributions)
Week 3-4: Simple Linear Regression
Introduction to simple linear regression
Estimation and interpretation of regression coefficients
Hypothesis testing and confidence intervals
Assumptions of the simple linear regression model
Week 5-6: Multiple Regression
Extension to multiple regression
Interpretation of multiple regression coefficients
Dummy variables and interactions
Model specification and interpretation
Week 7-8: Violations of OLS Assumptions
Detection and handling of violations of OLS assumptions
Heteroscedasticity, multicollinearity, and autocorrelation
Robust standard errors and remedial measures
Week 9-10: Model Evaluation and Selection
Goodness of fit measures (R-squared, adjusted R-squared)
Model selection criteria (AIC, BIC)
Cross-validation and out-of-sample prediction
Week 11-12: Time Series Analysis
Introduction to time series data
Autoregressive and moving average models
Stationarity and unit roots
Introduction to forecasting
Week 13-14: Panel Data Analysis
Introduction to panel data
Fixed effects and random effects models
Hausman test
Applications in economics
Week 15: Review and Exam Preparation
Comprehensive review of the course material
Practice problems and discussions
Exam preparation tips and strategies
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