ECONOMIC STATISTICS

Single discipline educational activity

Course Sheet

Academic Year of enrolment:

2016/2017

Optional/Mandatory:

Compulsory

Degree:

Bachelor's Degree Programme in ECONOMICS AND MANAGEMENT

Disciplinary Sector:

Statistics for Economics

Credits:

Programme Year:

Professor and Collaborators:

GONANO Maria Giovanna

Hours of classroom activity:

Prerequisites:

basic knowledge of descriptive statistics and inferential analysis

AF code:

40003442

Assessment Methods

Verification of learning:

The exam consists of both written and oral examinations. The written examination will take place in the computer lab and cover theory and practice. It will take about 2 hours. The theoretical-pratical tests will be articulated in the resolution of elementary exercises through the use of the sofware application available in the computer lab of Disea (STAT - LibreOffice Calc). The proposed exercises will concern the application to elementary cases of the principles and methods of analysis learned during the course.
The written examination one can be done as a partial examination concerning topics from the first part of the course and a final written one focusing on the contents of the second part. Each of them will take about 1 hour. The student is required to get a sufficient score in both examinations separately.

The exam (written and oral examinations) will cover the whole course’s program and the exercises will consist of simple applications of the principles and methodologies illustrated during the lectures.
To obtain the minimal score, the student must prove adequate understanding of the general principles of information extraction from data and of economic statistics and her ability to use in practice at least some of the statistical methodologies and data mining techniques.
Obtaining the maximum score will require full understanding of principles and mastery of all analytical instruments introduced during the course.

Teaching period

Second semester

Objectives

The course provides students with the basic tools for the study of quantitative economic and business phenomena, with particular attention to the methodological aspects of collecting, processing, analyzing and forecasting data, in particular economic and business data. Students will learn knowledge on the main economic data available. These data play a key role in the decision-making process of economic policies. Statistical methodologies concern the analysis of the relationship between economic phenomena, the univariate analysis of time series in the economic field, the interpretation and comparison between statistics data.
At the end of the course the student will have acquired:
1. KNOWLEDGE AND ABILITY TO UNDERSTAND: knowledge on the main economic-business data for the analysis of the quantitative phenomenon, ability to understand the appropriate statistical tools for the analysis of the economic phenomenon.
2. ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING: ability to recognize and apply the basic tools to carry out the study of the phenomenon, to analyse and interpret the results of the statistical analysis.
3. SELF JUDGEMENT: ability to recognize whether the statistical method applied is used appropriately for the study of the phenomenon.
4. COMMUNICATION SKILLS: ability to provide right interpretations and good analysis of the results using appropriate statistical terminology.
5. LEARNING SKILLS: it encourages in-depth study of the statistical methodologies proposed in the context of advanced specialized courses.

Contents

1. Official statistics. ISTAT: consumer price index, methodological note. ISTAT: Labour Force Survey, methodological note.
2. The linear regression model. Descriptive analysis: ordinary least squares method, the coefficient of determination. Inferential analysis: parameters, least squares estimates and estimators, standard assumptions for the linear regression model, hypothesis tests on the coefficients.
3. The multivariate linear regression model: model with two independent variables, model with k independent variables. Partial regression coefficients. Partial correlation coefficients. Dummy variables.
4. Univariate time series analysis. Decomposition model. Trend, seasonality and cycle. Simple and weighted moving average. Additive and multiplicative model. Seasonality and seasonal coefficients. Trend estimate with analytical method.
5. Interpretation and comparison between data. Statistical ratio. Index numbers (simple and composed)

Recommended Bibliography

P. Newbold, W.L. Carlson, B. Thorne, Statistica, Pearson University 2nd ed.,2010.
T. Di Fonzo, F. Lisi, Serie storiche economiche, Carocci ed., 2010.
R. Guarini, F. Tassinari, Statistica Economica, Il Mulino, Bologna, 2000.
E. Giovannini, Le statistiche economiche, Il Mulino, Bologna, 2006.
Any other teaching material will be made available through the course’s web page.

Teaching Methods

Academic lectures (54 hours) and laboratory classes (18 hours) for exercises and implementation of the principles and methodologies by means of computer software.

Contacts/More Information

1) Readiness to offer individual assistance (e.g. explanations during office hours) also in English to incoming students.
2) Availability of supporting material and bibliographic references in English.
3) Readiness to accept examination of incoming students also in English.

Office hours are posted on www.edisea.uniss.it.

Contacts:
- Maria Giovanna Gonano – email: mggonano@uniss.it – phone: 079/213032

ECONOMIC STATISTICS

Course year: 2

Course year: 3

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ECONOMIC STATISTICS