42469 - Quantitative Methods for Development Analysis

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)

1 Principles and methods of inference and sampling

1.1. Population and sample. Basic notions of probability. The random variable and main discrete and continous probability distributions.

1.2 Principles of statistical inference. Point estimation and interval estimation and properties. Sampling from finite populations: general features and simple random sampling. Estimation of the population mean, ratios. Test of hypothesis. Test for means and ratios . Introduction to simple regression analysis; specification of the model and model hypothesis. Estimation -Ordinary least squares. R square and testing coefficients.

2. Measuring and analysing specific phenomena

2.1 Measuring and analysing welfare, poverty and income inequality.

2.2 Measuring and analysing production, productivity and human capital.

Readings/Bibliography

1. S. Borra e A. Di Ciaccio, Statistica, metodologie per le scienze economiche e sociali , McGraw-Hill, chapters 8-14, 16 and 17.

2. Guarini R., F. Tassinari, Statistica economica (sec. ed.), Il Mulino, Bologna 1996,  III and IV parts of the programme.

Other readings to deepen some specific topic and handouts will be given in the class.

References concerning basic knowledge requested:

S. Borra, A. Di Ciaccio, Statistica, metodologie per le scienze economiche e sociali capitoli 1-7, 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

Oral examination

Students attending lectures: written tests not compulsory carryed out in the lecture period could to define final evaluation. 

Students not-attending lectures: preliminary written test before oral examination.

Teaching tools

Slides and teaching materials - exercises and examples - concerning lectures are prepared by the teacher and available on line.

Topics are presented using pc and video-projector.

Office hours

See the website of Carlo Filippucci