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:

1. Introduction to Econometrics:

• Definition and scope of econometrics

• Basic concepts and principles

• Role of econometrics in economic analysis

1. Statistical Foundations:

• Probability and distribution theory

• Hypothesis testing and confidence intervals

• Regression analysis fundamentals

1. Simple and Multiple Regression Models:

• Model specification and interpretation

• OLS (Ordinary Least Squares) estimation

• Assumptions and diagnostics

1. Violations and Remedies:

• Multicollinearity, heteroscedasticity, and autocorrelation

• Methods to address model violations

• Robust regression techniques

1. Advanced Topics in Econometrics:

• Instrumental variables

• Time-series analysis

• Panel data models

1. 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.

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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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