FORECASTING mutuato
ANALISI E PREVISIONI ECONOMICHE
| A.Y. | Credits |
|---|---|
| 2021/2022 | 8 |
| Lecturer | Office hours for students | |
|---|---|---|
| Giorgio Calcagnini | On appointment by email |
| Teaching in foreign languages |
|---|
|
Course with optional materials in a foreign language
English
This course is entirely taught in Italian. Study materials can be provided in the foreign language and the final exam can be taken in the foreign language. |
Assigned to the Degree Course
| Date | Time | Classroom / Location |
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| Date | Time | Classroom / Location |
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Learning Objectives
The course aims at providing students with methodological tools to analyse relationships between macroeconomics and economic activity at firm level. Indeed, any microeconomic decision (i.e., new products, fixed investment, etc.) depends upon the state of the current and future state of the economy (domestic or worldwide). Attending the class will improve students' analytical abilities together with their ability to synthetize information by means of down-to-earth applications.
Program
1. Definitions and methods of forecasting
2. Statistcal sources and economic analysis
3. Forecasting by means of quantitative methods: single-equation methods
4. Forecasting by means of quantitative methods: time series methods
5. Real-world applications
Bridging Courses
Basic knowledge of Statistics, Microeconomics, Macroeconomics, Marketing and Business Management will help students to learn and apply forecasting methods to real-world problems.
Learning Achievements (Dublin Descriptors)
At the end of the course, students will be able to manage the acquired techniques to forecast and build scenarios concerning different economic actors and sectors: consumers, firms, industry associations and governments.
Knowledge and Understanding: at the end of the semester students are expected to know multiple forecasting methods by means of which they will be able to build senarios. Futher, they will learn how to find information from several statistical sources and how to manage it by means of statistcal software.
Applying Knowledge and Understanding: students will be able to make forecasts by means of quantitative methods and to evaluate their efficacy.
Making Judgements: students will be able to analyze information to solve several types of problems, to choose the most appropriate method and to evaluate the soundness of found solutions.
Communication Skills: students will learn how to present results from their analyses by means of short reports and graphics. They will learn to work together and present their scenario.
Learning Skills: students will be able to apply technical knowledge acquired in other courses and integrate them with skills that they will learn during this course.
Teaching Material
The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it
Supporting Activities
Teaching materials will be made available through the Forecasting Blended-Learning page at https://blended.uniurb.it/moodle/
Teaching, Attendance, Course Books and Assessment
- Teaching
Lectures & computer lab supplementary work.
- Attendance
Highly suggested
- Course books
1. Jennifer Castle, Michael Clements and David Hendry, (2019) Forecasting: An Essential Introduction, Yale University Press ISBN: 9780300244663 (https://yalebooks.yale.edu/book/9780300244663/forecasting).
2. Professor's notes are avilable at https://blended.uniurb.it
- Assessment
Final is a written test (3 exercises) taken at the computer lab for 1 and 1/2 hours. Each exercise covers one of the main class topics: a) model estimation (OLS) by means of Gretl; b) traditional time series (exponential smoothing and moving average methods) by Excel; c) ARIMA models by means of Gretl. Each exercise has three questions and each answer you get right is worth three points. Up to six point are assigned on the classwork clarity.
- Disability and Specific Learning Disorders (SLD)
Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.
To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.
Additional Information for Non-Attending Students
- Teaching
There are no changes in the conditions for non-attending students
- Attendance
There are no changes in the conditions for non-attending students
- Course books
There are no changes in the conditions for non-attending students
- Assessment
There are no changes in the conditions for non-attending students
- Disability and Specific Learning Disorders (SLD)
Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.
To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.
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