Research Methodology - Economics

Introduction

This course is a graduate level introduction to Econometrics.

Course content

I Data Management

• Traditional data (time series and panel data)
• Big data
• Data reduction

II Time series – Stationary and non-stationary univariate time series

• White noise, moving average, autoregressive models
• Forecasting
• Deterministic and stochastic trends, unit roots, structural change
• Applications

III Vector autoregression (VAR) methodology

• Structural VARs specification and estimation
• Identification, impulse responses, variance decomposition
• Spurious regression and log run economic relationships
• Applications

IV Panel data analysis

• Difference in difference methodology
• Fixed effects
• Applications

V Introduction to information search strategies

• Acquaintance with methods for information, harvesting and search techniques
• Know what a critical literature review is and how this type of articles may be searched for and used
• Critical evaluation of sources

VI Setting up an econometric project

• Research ethics, data handling, specification, modeling, policy analysis