67730 - Econometrics

Course Unit Page

SDGs

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

Quality education Gender equality Reduced inequalities

Academic Year 2021/2022

Learning outcomes

The course provides an elementary but comprehensive introduction to the practice of econometrics for cross-sectional data, useful to correctly interpret estimates and develop simple empirical projects. By the end of the course the student will have adequate knowledge of linear and some non linear (logit, probit) regression models for the analysis of cross-sectional data and he/she will be able to understand under what conditions linear regression model estimates have a causal interpretation. All regression models will be illustrated starting from the discussion of a recent micro-economic application. Examples will be analyzed in detail through lab-session, where students will be able to practice at the computer with real data and learn the basic skills to perform empirical work using free-available software (GRETL). Students will develop data analysis competencies and critical thinking. At the end of the course we will devote some time to discuss under which assumptions one draw conclusions on the causal relationship between phenomena, using regression results (eg does education causes increases in earnings? does breastfeeding increase children IQ? does media bias affect voting behaviour?).

Course contents

1a. What is Econometrics?
Steps in Empirical Economic Analysis
The Structure of Economic Data (Cross-Sectional Data, Time Series Data,Pooled Cross Sections,Panel or Longitudinal Data)
A Comment on Data Structures; Causality and the Notion of Ceteris Paribus in Econometric Analysis
1b. Review of some basics (random variable,distribution of a random variable, conditional and unconditional moments –mean and
variance-;population, parameters and random sampling; hypothesis testing)

1c. Introduction to software (GRETL http://gretl.sourceforge.net/ and STATA) and practical illustration of concepts in 1a, 1b

2. The Simple Linear Regression Model: theory and applications with GRETL in the lab

empirical applications: modelling sales; evaluating the effect of promotions

3. The Multiple Linear Regression Model: theory and applications with GRETL or STATA in the labempirical applications: modelling sales; evaluating the effect of promotions

4. Introduction to Maximum Likelihood estimation

empirical applications: frauds in the "Wheel of Fortune" game; testing whether the 'difficulty' of academic exams is constant across rounds

5. Logit and Probit Models: theory and applications with GRETL in the lab

empirical application: modelling the choice between two brands

5. Extra (Topic lecture): Causality in Microeconometrics: examples

Additional empirical applications will be covered. Some applications are taken from the books in the reference list.

Teaching material on computer lab exercises will be made available to students (also using the e-learning Platform https://elearning-cds.unibo.it/)

Readings/Bibliography

Teaching material is based on selected material from the books listed below

Stock, J. H. and Watson, M. W. (2009) Introduction to Econometrics, 3e

Wooldridge, J. (2016) Introductory Econometrics: A Modern Approach, 6e

R. C. Hill, W. E. Griffiths, G. C. Lim, (2011) Principles of Econometrics (4th edition, International Student Version), Wiley

Joshua Angrist and Jörn-Steffen Pischke (2009) Mostly Harmless Econometrics: an empiricist's companion

Joshua Angrist and Jörn-Steffen Pischke (2015) Mastering 'Metrics: The Path from cause to effect

Franses, P.H. and Paap, R. (2007) Quantitative Methods for Marketing Research

 

All these should be available  (at least in previous edition) from the University libraries. You can check availability from

http://sol.unibo.it/SebinaOpac/Opac?sysb=

 

Teaching methods

Lectures involve the presentation of theoretical and applied issues of the various econometric methods. Applications are discussed in class and replicated during the computer laboratory session using GRETL or STATA.

Self-evaluation on-line tests will be made available through the e-learning platform https://elearning-cds.unibo.it/

The course consists of 60 hours. There will be a class lecture (3 hours) and a computer lab practice (3 hours) each week. Overall, there will be 10 lectures in class (30 hours) and 10 lectures in the lab (30 hours) but laboratory will be concentrated toward the end of the course.

Software GRETL (available for free from the web): http://gretl.sourceforge.net/

Software STATA: available for students of the Department of Economics (CAMPUS license) and at the Computer Lab of the School of Economics and Management.

I will experimentally adopt innovative teaching tools (such as peer instruction; see link with reference) using adequate techical support during lectures  relying for instance on free available software such as Pingo (https://pingo.upb.de/) and Kahoot! (https://kahoot.com/).  Students do not need to install the software ahead but need to have a device (mobile phone or laptop) who can access internet during the lectures in which this approach will be implemented.

In addition, peer education  requires a great deal of investment from students as students have to read the textbook before coming to class.

 

As concerns the teaching methods of this course unit, all students must attend Module 1, 2 [https://www.unibo.it/en/services-and-opportunities/health-and-assistance/health-and-safety/online-course-on-health-and-safety-in-study-and-internship-areas] on Health and Safety online

Assessment methods

1 hour written exam (30 points final exam or 15+15 intermediate exams) with open and multiple choice questions on theory and pratcical exercises using GRETL. The exam will be held in the computer lab. Each exam will have a minum of 3 and a maximum of 10 questions. Points awarderd for corrected answers to each question will be available.

Students can either take the exam at the end of the course on the full program or take two intermediate exams. If the student fails on at least one of the intermediate exams, he will have to take the full exam: there are no re-takes for intermediate exams

The final exam mark is the sum of the two intermediate exams' marks. The final mark ranges between 0 and 32; each intermediate exam is worth between 0 and 16 points (the range of points awarded for each question will be updated accordingly). To pass the final exam, both intermediate exam marks should be higher than 7 and their sum should be at least 18: eg. one fails, if his score is 7+7=14; one passes if the score is 7+11=18.

Since there are no re-takes for the intermediate exams, a student who fails the first or second intermediate exam, will have to take the full final exam.

Students with final number of points 32 qualify for getting the mark 30 cum laude. 30 cum laude could be awarded to students scoring between 30 and 32 points.

According to the indications of the council of the School of Economics and Management, the indications on the graduation of the grade are reported.

• <18 insufficient

• 18-23 sufficient

• 24-27 good

• 28-30 excellent

• 30 cum laude  excellent with praise (honors)

In the event of substantial restrictions due to the Covid-19 pandemic, the assessment methods might have to be adapted to online exam session and might be reviewed accordingly, giving prior notice to students. The topics tested (theory arguments and practical exercises with software) remain confirmed even in the case of different examination modes.

Teaching tools

Slides, teaching material , practice in the lab.

Self-evaluation on-line tests will be made available through the e-learning platform https://elearning-cds.unibo.it/

Lectures involve the presentation of theoretical and applied issues of the various econometric methods. Applications are discussed in class and replicated during the computer laboratory session using GRETL or STATA.

The course consists of 60 hours. There will be a class lecture (3 hours) and a computer lab practice (3 hours) each week. Overall, there will be 10 lectures in class (30 hours) and 10 lectures in the lab (30 hours) but laboratory will be concentrated toward the end of the course.

Software GRETL (available for free from the web): http://gretl.sourceforge.net/

Software STATA: available for students of the Department of Economics (CAMPUS license) and at the Computer Lab of the School of Economics and Management.

Links to further information

http://web.mit.edu/jbelcher/www/TEALref/Crouch_Mazur.pdf

Office hours

See the website of Margherita Fort