Course Overview:
This specialized short professional online course is designed for academics, PhD students, and professors aiming to deepen their expertise in macroeconometric forecasting and analysis with a focus on policy applications. The course provides comprehensive training on the theoretical foundations, practical implementation, and policy relevance of macroeconometric models.
Course Objectives:
Understand the principles and techniques of macroeconometric forecasting.
Develop skills to construct and estimate macroeconometric models.
Apply macroeconometric models to analyze and forecast economic policies.
Utilize software tools such as EViews, Stata, and MATLAB for macroeconomic analysis.
Target Audience:
Academics in economics and related fields.
PhD students specializing in macroeconomics, econometrics, and economic policy.
Professors and researchers seeking to enhance their macroeconometric forecasting capabilities.
Course Structure: The course is structured into four intensive modules, each featuring lectures, readings, assignments, and practical exercises. Participants will engage with video lectures, interactive tutorials, and peer discussions.
Week 1: Fundamentals of Macroeconometric Forecasting
Introduction to macroeconomic forecasting and its importance.
Overview of macroeconometric models: structural and reduced-form models.
Week 2: Data Preparation and Model Specification
Data collection, cleaning, and transformation.
Specifying and calibrating macroeconometric models.
Readings:
"Macroeconomic Forecasting" by Steven N. Durlauf and Lawrence E. Blume.
"Forecasting, Structural Time Series Models and the Kalman Filter" by Andrew C. Harvey.
Week 3: Estimation Methods
Ordinary least squares (OLS) and maximum likelihood estimation (MLE).
Bayesian estimation techniques in macroeconometrics.
Week 4: Model Evaluation and Diagnostic Testing
Evaluating forecast accuracy: RMSE, MAE, and Theil’s U.
Diagnostic tests for model adequacy and stability.
Readings:
"Econometric Analysis" by William H. Greene.
"Time Series Analysis" by James D. Hamilton.
Week 5: Vector Autoregressions (VAR) and Cointegration
Introduction to VAR models and impulse response functions.
Cointegration and error correction models (ECM).
Week 6: Structural VAR (SVAR) and Dynamic Stochastic General Equilibrium (DSGE) Models
Identifying structural shocks in SVAR models.
Basics of DSGE models and their applications in policy analysis.
Readings:
"New Introduction to Multiple Time Series Analysis" by Helmut Lütkepohl.
"Structural Macroeconometrics" by David N. DeJong and Chetan Dave.
Week 7: Macroeconomic Policy Analysis
Using macroeconometric models for monetary and fiscal policy analysis.
Evaluating the impact of policy interventions on economic variables.
Week 8: Real-World Applications and Case Studies
Case studies on macroeconomic forecasting and policy analysis.
Presenting and discussing participant projects and findings.
Readings:
Selected articles from the Journal of Economic Perspectives and the Review of Economics and Statistics.
Relevant policy papers from central banks and international organizations.
Assignments:
Weekly problem sets and practical exercises.
Mid-term project involving the construction and estimation of a macroeconometric model.
Final Project:
Comprehensive macroeconomic forecasting and policy analysis project.
Presentation and peer review of the final project.
Certification:
Participants who complete all modules, assignments, and the final project will receive a certificate of completion.
Course Delivery:
The course will be delivered through a combination of pre-recorded video lectures, live Q&A sessions, interactive tutorials, and discussion forums.
All course materials, including readings, software guides, and lecture slides, will be available online.
Instructor:
The course will be led by a team of experienced economists and econometricians with extensive expertise in macroeconometric forecasting and policy analysis.
Enrollment:
Participants can enroll through the university’s online learning platform.
Enrollment will be open to individuals with a foundational knowledge in macroeconomics and econometrics.
By the end of this course, participants will have a robust understanding of macroeconometric forecasting techniques and be equipped with the skills to apply these methods to real-world economic policy analysis and forecasting.