ECN301 Econometric Methods

This course focuses on modern econometric methods for the utilization of and analysis using economic data - both cross-sectional and time-series data. The following topics are covered: estimation and testing of linear regression models with stochastic and possibly endogenous regressors, panel data models, models with limited dependent variables, models of sample selection, and time-series models for stationary or non-stationary processes, co-integration and error correction models, prediction and cross-validation.

Knowlegde

The student

• has detailed knowledge and understanding of econometric models and their assumptions
• has knowledge about different sources for economic data
• can distinguish between different types of economic data, and has knowledge about the key different models and estimators for each data type

Skills

Student

• can access different sources for economic data,
• can combine data from different sources
• can conduct independent econometric analysis of economic data
• can choose appropriate models and estimators for each type of economic data
• can conduct tests for the appropriateness of the chosen model and estimator
• can use Python and/or R for statistical analysis of economic data

General Competence

Student

• can can critically evaluate econometric analysis with respect to choice of model, method and interpretation of results
• can communicate empirical economic analysis and results including data sources, choice of model and estimator, results and policy implications, and
• know and understand current professional and ethical standards for analysis, documentation and reporting within economics.