Applied Time Series Econometrics

The course deals with how empirical analyzes are performed using time series data, which models and methods are relevant to various issues, and how empirical models can be used to give predictions. Empirical work with applications in financial economics and macroeconomics will be discussed. Assessments of what are good empirical approaches for different types of time series analyzes are emphasized.

Knowledge

You learn

• how researchers design empirical studies using time series data in financial economics and applied macroeconomics, including the formulation of econometric models and the use of different methods.
• how to evaluate models and choose between different models
• how empirical models can be used to give predictions and how the prediction properties can be evaluated

Skills

You should

• be able to understand the challenges of conducting empirical analyzes using time series data
• be familiar with different models and methods that are relevant for different types of time series analyzes
• be familiar with how different models can be used to give predictions
• be able to apply models and methods in own analyzes using time series data

General competence

You should be able to

• read and understand reports and research articles that make use of models and methods discussed in the course
• reveal problems and shortcomings in academically weak analyzes within topics dealt with in the course
• use the course content as a basis for their own independent academic work, such as the master's thesis

4 hours of organized learning activities each week.

Compulsory activity: Approved term paper(s) / exercise(s) / student presentations. Specific requirements will be announced at the beginning of the term, and an independent econometric work will be included. Compulsory activity must not be re-completed when repeating the exam.