ECONOMIC STATISTICS

Università degli Studi
"G. d'Annunzio"

Chieti - Pescara

Single discipline educational activity

Course Sheet

Course code:

000100L

Academic Year of enrolment:

2016

Year of supply:

2017/2018

Type of Course:

Characterising

Degree:

Course of 2nd Cycle Degree in ECONOMICS AND COMMERCE

Disciplinary Sector:

Statistics for Economics

Location:

PESCARA

Credits:

Programme Year:

Professor and Collaborators:

POSTIGLIONE PAOLO

Cycle:

Second semester

Hours of classroom activity:

Individual study hours:

153

Prerequisites:

The knowledge of Basic Statistics is requested.

Objectives

The course aims to provide to the students with the basic knowledge of some statistical methodologies useful for economic analysis. It wants to help students to familiarize with the open source statistics package R.

Contents

Content: 1. Basic concepts of probability and statistical inference. Discrete and continuous random variables. Expected values, variability. Point estimation. Confidence intervals. Hypothesis test. 2. R statistical software. 3. Basic concepts of linear algebra: vectors and matrices; Determinant and inverse of a matrix. 4. The linear regression model Simple linear regression. Multiple linear regression. Inference. Eteroschedasticity and Autocorrelation. Dummy variables. Instrumental variables. 5. The linear regression model and R. Study cases. 6. The logistic regression model. Definitions. Parameter Estimation and Interpretation. 7. The logistic regression model and R.
8. Principal Component Analysis. Solutions of the problem. Interpretation.
9. principal Component Analysis and R.
10. Regression analysis for spatial data.

Recommended Bibliography

- Course slides. - PICCOLO D. (2010). Statistica. Edizioni Il Mulino. (Cap. 14 pagg.491-501; 520-526; Cap. 15 pagg. 548-557, 560-561, 567-577, Cap. 16 pagg. 585-591; Cap. 17 pagg. 607-620; Cap. 18 pagg. 669-673, 677-678; Cap. 19 pagg. 731-737, Cap. 22; Cap. 23.).
FABBRIS L. (1997). Statistica Multivariata. Analisi esplorativa dei dati. McGraw-Hill. (Cap.5 pagg. 163-171; 177-185).
-Stock JH,‎ Watson MW (2016),
Introduzione all'econometria. Pearson
(Cap. 4,5,6,7,12,17,18)

Methods of Provision

Conventional

Evaluation methods

Verification of learning:

The exam is written and oral. The written exam will consist of theoretical questions and empirical exercises. The exam will cover the entire program, with particular attention to the use of the R software. Students will also have to prepare and discuss a regression (linear or logistic) analysis, carried out with R, concerning a real case study (data sets can be found on internet). This report must be sent to the Professor at least one week before the examination date. Further information can be found on the Professor's website: http://www.unich.it/~postigli/Home.html

Contacts/More Information

E-mail: postigli@unich.it Professor's website: http://www.unich.it/~postigli/Home.html In the first semester the Professor sees students only by appointment (postigli@unich.it). In the second semester, the office hours for students is scheduled for Wednesday from 2 pm to 4 pm, studio DEC 2 ° floor, Viale della Pineta, 4.

Other courses

Course year: 1

BUSINESS INFORMATION SYSTEMS
6 Credits - Characterising
ECONOMY OF NETWORKS AND INNOVATION
9 Credits - Characterising
COMPUTER LANGUAGES FOR STATISTICS
6 Credits - Related/Supplementary
INFORMATION SYSTEMS
6 Credits - Related/Supplementary
OPERATIONAL RESEARCH
6 Credits - Related/Supplementary

Course year: 2

ADVANCED MACROECONOMICS
9 Credits - Characterising
ECONOMIC STATISTICS
9 Credits - Characterising
LINEAR MODELS
6 Credits - Characterising
STATISTICAL METHODS FOR ECONOMIC ANALYSIS
9 Credits - Characterising
TIME SERIES ANALYSIS
9 Credits - Characterising
ORGANIZATION AND PLANNING TOURISM
9 Credits - Elective Course
URBAN AND REGIONAL GEOGRAPHY
9 Credits - Elective Course

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ECONOMIC STATISTICS