42469 - Quantitative Methods for Development Analysis

Academic Year 2019/2020

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Local and Global Development (cod. 9200)

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

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

I Principles and methods of inference and sampling

  • Population and sample. Basic notions of probability. The random variable and main discrete and continous probability distributions. Principles of statistical inference. Point estimation and interval estimation. Sampling from finite populations, general features and simple random sampling. Test of hypothesis.
  • The simple regression analysis: specification of the model and tests; Estimation (Ordinary least squares), estimation properties, tests.

II. Measuring and analysing specific phenomena

  • Measuring and analysing welfare, poverty and income inequality.
  • Measuring and analysing production, productivity and human capital.

Readings/Bibliography

References

S. Borra e A. Di Ciaccio, Statistica, metodologie per le scienze economiche e sociali, McGraw-Hill, capitoli 8-14 (comprensivi della parte di allineamento delle conoscenze di base), 16 e 17.

Extra material will be provided by the teacher. 

Teaching material available on the web.

Reference distribution list: rossella.bernardini.sleg

 

References to basic knowledge:  

S. Borra, A. Di Ciaccio, Statistica, metodologie per le scienze economiche e sociali capitoli 1; 2; 4.1-4.4;4.7;4.8;5.1-5.4;6.1-6.5. Mc Graw-Hill. (oppure A. Di Ciaccio, S. Borra, Introduzione alla statistica descrittiva, Mc Graw - Hill).

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 3 exercises and 3 both theoretical and empirical questions; exam time: 1 h and half; 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 the classroom presentation by the end of the course (15-30 minutes). Group work evaluation can lead to an increase in the final evaluation from 0 to a maximum of 3 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

SDGs

No poverty Reduced inequalities

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