11398 - Statistical Models for Economic Behaviour

Learning outcomes

The course's goal is to provide for deep knowledge of problems and technical methods about estimation of statistical models describing micro-economic behaviour. Influence of data generating process on estimation strategy is highlighted referring to economic contexts of labour market and consumer behaviour. Students are required to have mastery of concepts and statistical methods concerning estimation multivariate linear models.

Course contents

1) Fundamental concepts and definitions (remind):

• Economic theories, models and measures; macro and micro models.
• Definition of utility function, rational choice, bounded rationality.
• Choices and uncertainty, the limited information problem.

 2) Main estimation methods (remind):

• Data generating process.
• Fundamental assumptions of the  classical linear model
• Estimation procedure when they are violated: Generalized Least Square, estimation of variance-covariance matrix.
• Maximum likelihood estimates, algorithms and software.

3) Market labour agents' behaviour:

• Analysis of the choices determinants: discrete binary and multiple choice models; probability estimates in presence of discrete dependent variables; non-linearity; Probit and Logit models.
• Analysis of spells: duration models; Logit models using panel data.

 4) Consumers' behaviour :

• Analysis of the choices determinants: estimation in presence of truncated and censored dependent variables, Tobit and double hurdle models;  Estimation in presence of selection bias: Heckmann and Amemya models.
• Analysis of purchasing process: estimation of purchasing and re-purchasing probability, estimation of time between two consecutive purchases.

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Readings/Bibliography

W.H. GREENE, Econometric Analysis, Mac Millan, London, Third Edition, 1997

Chap.: 6, 8, 9, 11, 12, 14, 19, 20.

Teaching methods

• Frontal lessons
• Guided case-studies
• Individual case-studies, checked during lessons

Assessment methods

Oral examination.

Teaching tools

In the classroom:

• Overhead Projector
• PC equipped with video projector

 In the teacher's internet site:

• Handouts and transparencies on-line
• Teaching material on-line

 e-mail address devoted to didactic help: infodrudi@stat.unibo.it

 

Links to further information

http://www2.stat.unibo.it/drudi/

Office hours

See the website of Ignazio Drudi