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PROGRAMMING COURSE: STATA
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PROGRAMMING COURSE: STATA
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Academic year 2023/2024
- Course ID
- SEM0184
- Teacher
- Marina Di Giacomo (Lecturer)
- Year
- 1st year
- Teaching period
- Second semester
- Type
- Other activities
- Credits/Recognition
- 3
- Course disciplinary sector (SSD)
- SECS-P/05 - econometrics
- Delivery
- Formal authority
- Language
- English
- Attendance
- Optional
- Type of examination
- Written
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Sommario del corso
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Course objectives
The course aims to introduce participants to the basic tools of two statistical softwares, Stata and Eviews, for analyzing economic and financial data.
The course provides an overview of the basic functions of the statistical sofwares and the application of these functions using real data examples.
The course has thus two main objectives:
- presentation of the software structure and philosophy;
-presentation of the potentialities of the softwares for analyzing data
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Results of learning outcomes
1. Knowledge
- Using digital tools to support data analysis.
- Identifying the econometric model that better fits the research question and the data available.
2. Skills
- Describing a database, determining an appropriate data analysis technique and performing analysis for generating tables, charts, and graphs.
- Performing regression analysis
3. Responsibility and Autonomy
- Students should be able to demonstrate and produce a database for research question
- Students should be able to develop and test hypothesis for particular research question
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Program
The syllabus is the following:
1. Introduction to Stata
2. Data management and graphical analysis
3. Regression and hypothesis testing in different contexts (OLS, GMM and IV, Logit and Probit, Tobit)
5. Applications of univariate time series analysis
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Course delivery
The course consists of 24 lecture hours given at the Computer Lab. Strong interaction between teacher and students is warmly encouraged.
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Learning assessment methods
The final exam consists of a written exam (1h) at the end of the course. The exam paper is structured in two parts ("Estimation" and "Time Series"). Scores sum up to 30/30
Suggested readings and bibliography
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Lecture notes and datasets will be available on the Moodle page of the course.
The Stata software is available following the instructions at this link:
https://www.unito.it/servizi/servizi-line/licenze-software-campus-di-ateneo
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