# 32173 - Applied Econometrics

### SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.    ## Learning outcomes

Students will learn the econometric methods used in applied research and the skills to perform their own empirical research using different econometric packages and software. Particularly, students will be able: - to use linear regression model in different contexts and to critically evaluate its principal economic applications; - to learn the basic methods of time series and dynamical models; - to acquire knowledge of the basic techniques of cross sections and panel data.

## Course contents

Part 1

Introduction to the linear regression model.

Examples of interest.

Interpretation and use of regression coefficients.

Compact matrix representation.

Distinction between cross-section data and time series data.

Distinction between the classic linear regression model and the generalized linear regression model.

Estimation problem: OLS estimation and properties of the estimator.

Diagnostic analysis of a linear regression model: main tests.

Testing restrictions on the parameters.

Endogenous regressors: introduction to the IV estimator.

Part 2

A brief review of the linear regression model.

• Review of the basic underlying assumptions of the linear regression model.
• Specification Testing
• Violations of the independence and identically distributed error assumption
• Time series and cross sectional models with heterogeneous units.

Introduction to Nonparametric Models

• Local smoothing methods
• Curse of dimensionality
• Kernel regression
• The semi-parametric partially linear regression model.

Introduction to Time Series Models

• Models with Lagged Dependent Variables
• Models with Trends
• AR and MA Models
• Introduction to models with integrated data I(1)
• Spurious regression
• Co-integration

Introduction to Panel data Models

• Simple Random Effects Model
• Fixed Effects Model

Slides provided by the teacher

Verbeek, M. (2000), Modern econometrics, Wiley.

Classes and labs

## Assessment methods

The ultimate goal of the exam is to verify that the students have achieved the following basic targets:

• knowledge of the basic econometric models which can be applied in the environmental context;

• the ability to distinguish between the application of the classic and generalized linear regression model;

• undestanding when the OLS estimator can not be applied for the specific problem at hand, and the knowlede of the IV estimator as alternative;

• testing general linear restrictions on the parameters of the model;

• the main topics of time series econometrics and panel models.

The exam is written and a grade of the form xx/30 is given.

Students are supposed to do theoretical exercises but also discuss practical cases based on estimation outputs which refer to real markets.

Further information may be found at the link "Teaching" at http://www.rimini.unibo.it/fanelli

## Teaching tools

Labs and use of econometric packages: Gretl (or Stata)