ECN430 Empirical Methods and Applications in Macroeconomics and Finance
In empirical macroeconomics and finance we are investigating dynamic relationships between variables. This course will discuss methods for inference and forecasting in dynamic models in macroeconomics and finance, including:
- regression with panel data;
- identification and instrumental variables;
- estimation and forecasting in dynamic models in macroeconomics and finance;
- estimation and evaluation of structural econometric models;
- volatility clustering and conditional heteroscedasticity;
- non-linear models.
This course presents empirical methods and discusses applications in macroeconomics and finance. The course gives students a solid basis for practical empirical analysis in macroeconomics and finance. The course is especially suitable for students who write on an empirical master thesis in macroeconomics and finance.
Students work on a practical empirical project, and the result will be presented towards the end of the course.
At the end of the course students should achieve the following goals:
- be familiar with practical econometric methods in modern macroeconomics and finance
- apply their econometrics knowledge both to analyze and write about quantitative problems
- estimate and evaluate econometric models and analyze empirical questions in macroeconomic and finance;
- use software to handle data and to do econometric analyses;
- formulate and answer a research question in macro-econ. and finance
- write a term-paper where econometrics is used
- presentation of research ideas and the content of their own term-paper
From Fall 2015 the following prerequisites will apply:
Students taking this course are expected to have knowledge about econometrics similar to that covered in one of the courses BUS444, ECN402, ECO403 or FIE401 at NHH. That means: multiple regression analysis, testing and inference, heteroskedasticity and serial correlation, instrumental variables estimation.
Requirements for course approval
The final grade will be based on empirical assignments (50%) and term paper (50%).
Grading scale A - F.
STATA or other software (R, Matlab)
Selected chapters from various textbooks and scientific empirical papers. A full reading list will be announced at the beginning of the course.
Spring. Offered spring 2019
Gernot Doppelhofer, Department of Economics.