- Docente: Lucio Picci
- Credits: 8
- SSD: SECS-P/02
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Forli
- Corso: Second cycle degree programme (LM) in International Politics and Economics (cod. 5702)
Learning outcomes
The course provides an overview of some of the most widely used quantitative methods for social sciences and economics, with an emphasis on regression analysis. The general linear regression model is considered at length, together with some of its incarnations and extensions. These include: the instrumental variables method, models for discrete random variables, models for panel data, and models for time series data. The course has an applied orientation. Examples draw heavily from the political sciences, and are analyzed using the R programming language. At the end of the course, diligent students will be able to apply the methods considered, using R, and to correctly interpret the results of their analyses.
Course contents
PLEADE NOTE: The updated version of the syllabus, and all relevant material for this course, is available here:
https://sites.google.com/view/quantitativemethods/
The course provides an overview of some of the most widely used quantitative methods for the social sciences, with an emphasis on regression analysis. The course begins with a "crash course" in introductory statistics. Then the theory of estimation and inference is considered, followed by the analysis of several incarnations of the multiple regression model.
The course has an applied orientation. Examples draw heavily from political science, and are analyzed using the software R. At the end of the course, diligent students will be able to apply the methods considered, using R, and to correctly interpret the results of their analyses.
Please note: this course follows the course in Data Analysis.
Readings/Bibliography
- The main textbook is: Stock, James and Mark W. Watson. 2014. Introduction to Econometrics. 3rd updated edition. Pearson (indicated in what follows as [SW])
Also relevant is: Ray C. Fair. 2012. Predicting Presidential Elections and Other Things. 2nd. edition. Stanford University Press (The PDF file of the first edition is: avialable online [http://www.google.com/url?q=http%3A%2F%2Ffairmodel.econ.yale.edu%2Frayfair%2Fpdf%2Fvote.pdf&sa=D&sntz=1&usg=AFQjCNH5SF8-FqeeRIYSELV1oqJ0oPEDWg] ). A copy is available at the Central library.
Teaching methods
Lectures, partly online.
Assessment methods
The final grade will be based on one midterm exam (30%), one final exam (30%), and one R project (read the instructions here ), which will contribute to 40% of the final grade.
Teaching tools
R, R Studio.
Office hours
See the website of Lucio Picci