42469 - Quantitative Methods for Development Analysis

Academic Year 2023/2024

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Local and Global Development (cod. 5912)

Learning outcomes

Students will acquire knowledge concerning basic statistical techniques, main statistical inference techniques and basic sampling theory. Such knowledge is applied to problems arising from the analysis of economic development e growth, analysis of income, productivity, consumption and labour market. More in detail, the student will be able to : interpreting reports and casa studies produced by international agencies and research institutions, public and private boards working on cooperation projects; carrying out the statistical analysis requested to prepare reports on specific problems and Countries; participating and contributing in the activities of technical teams analysing real problems.

Course contents

The course is organized in lectures and seminars, as detailed in the following program.

Lectures (24 hours) aim to introduce students to the core tenets of the discipline.

Seminars (16 hours) aim to provide occasions for in-depth discussions of class materials and exercises.

Students are required to carefully read the assigned material before the session and - in the case of seminars - active participation through presentations of existing scholarship and case studies will also be expected.

Basic knowledge requested: basic descriptive statistics and inference (see recommended readings in the section Testi)

I Principles and methods of measurement and statistical analysis
  • Correlation analysis.
  • Dependence analysis, regression analysis: specification of the model and tests; Estimation (Ordinary least squares), estimation properties, tests.
  • Spatial analysis, Moran Test, spatial regression models.
  • Measuring and analysing welfare, poverty and income inequality.

II. Measuring and analysing specific phenomena (chosen from):

  • More about measuring and analysing welfare, poverty and income inequality.
  • More about spatial data analysis an spatial regression models.


Extra material will be provided by the teacher.

Teaching material available on the web.

Reference distribution list: rossella.bernardini.sleg

S. Borra, A. Di Ciaccio, Statistica, metodologie per le scienze economiche e sociali (III edizione)Mc Graw-Hill Education2015.

14.7; 6.8, 6.9, 16, 17, 18.6.

References to basic knowledge:

S. Borra, A. Di Ciaccio, Statistica, metodologie per le scienze economiche e sociali (III edizione)Mc Graw-Hill Education2015.

11, 12, 13, 14.

Teaching methods

In the first part lectures (ex-catedra) concerns probability, statistical inference and sampling methods; in the second one the topics are presented also showing case studies and carrying out seminars.

Assessment methods

Written exam

The final examination is in the form of a written test consisting of 2 exercises and 2 both theoretical and empirical questions; exam time: 50 minutes; it is not allowed to consult books or class notes.

During the final test, each candidate will be asked to show a document with a picture.

For students attending the course
A group work is planned for a topic that focuses on some of the content of the course (the material is partly provided by the teacher).
The group work: (max 6 students) involves (i) a case study (real data, to be completed at the first official exam) (ii) a classroom presentation of a paper (by the end of the course, 20/30 minutes). Group work evaluation can lead to an increase in the final evaluation from 0 to a maximum of 4 points.

Written intermediate exam if required by the students attending the course. In this case, the results obtained in the first partial test will only contribute to the final evaluation if the student completes the second partial test in the first planned written text.

Teaching tools

Slides and teaching materials - exercises and examples - concerning lectures are prepared by the teacher and available on line (via Reference distribution list).

Topics are presented using pc and video-projector.

Office hours

See the website of Rosa Bernardini Papalia


No poverty Reduced inequalities

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