Course Details

STATISTICAL METHODS FOR BUSINESS

GS1071

Course
STATISTICAL METHODS FOR BUSINESS
Code
GS1071
Academic Year
2024/2025
Curriculum Year
2023/2024
Degree Programme
ECONOMICS AND MANAGEMENT
Curriculum
A29 - MANAGEMENT
Course coordinator
-
Lecturers
Credits
10
Lecture Hours
60
Scientific Disciplinary Sector (SSD)
SECS-S/03 - Statistics for Economics
Course Type
Single-subject learning activity
Course Delivery
OPZ - Opzionale
Year
2
Teaching period
Primo Semestre
Campus
ALESSANDRIA
Teaching language
Italian
Course Contents
The course focuses on the application of statistical methods for causal inference estimation applicable to the evaluation of public programs and policies, and to the evaluation of strategic business choices. The course is divided into a theoretical module and an application module which involves the use of the statistical software "STATA".
Reference Texts
Booklets prepared by the instructor and downloadable from the DIR web site (additional study material s also available in English)
Learning Outcomes
By the end of the course the students should be able to implement statistical models to generate empirical evidence to evaluate the causal impact of public programs and business strategic choices.
Prerequisites
In order to best understand the topics of the course it is advisable (but not mandatory) to have previously passed a statistics course.
Teaching Methods
In class lectures with powepoint slides and the use of statistical software packages (STATA) or datasheet programmes (EXCEL).
Additional Information
All the course material and information can be downloaded from the DIR section of the DIGSPES web site
Assessment Methods
Written test that requires the students to solve problems and/or case studies.
Detailed Syllabus
Part I
This part aims at teaching students how to develop the appropriate statistical models for producing empirical evidence on the impacts of public policies and programs and of business strategic choices.
List of topics:
1. How to use multiple regression models to evaluate the impacts of the strategic choices of the firms;
2. Analysis of business panel data: fixed effects estimators, first and long differencing;
3. Selection and omitted variable bias
4. Non-parametric estimators, diffference in difference techiniques;
5. Shift share analysis;
6. Evaluation designs with non-esperimental data;
7. Multiple regression analysis with qualitative information (binary dependent variables): probit and logit models

Part II
Estimation of the models of part I through the software STATA
Expected Learning Outcomes
The students are expected to be able to understand and apply the main statistical methods to empirically evaluate the effects of the strategic decisions of the firms. The students are also expected to posses the basic skills to programme the statistical analyses on the STATA software
Last update:09-09-2026 00:14:31