Fundamentals of Economic Modelling

Fundamentals of Economic Modelling

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190,00 €
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1 Day
Online via Teams
EViews

Overview

This introductory course is designed to provide a comprehensive foundation in EViews, one of the most powerful and user-friendly econometric software tools. Participants will gain essential skills in data handling, programming, and regression modelling while learning to effectively apply the Classical Linear Regression Model (CLRM) for econometric analysis.

Through hands-on practice and interactive sessions, this course empowers participants to confidently use EViews for data analysis and modeling tasks. Whether you’re a beginner or seeking to refresh your skills, this course will equip you with the tools to conduct rigorous econometric analysis and prepare for more advanced applications.

How It Works
What You’ll Learn
  • Key EViews concepts like "workfile" and "object."
  • Efficient data organization, handling, and series transformations.
  • Programming basics and graphical data visualization in EViews.
  • Fundamentals of the Classical Linear Regression Model (CLRM), including OLS estimation.
  • Diagnostic testing, misspecification analysis, and stability testing.
  • Application of the General-to-Specific (GETS) approach for model refinement.
Course Highlights
  • Comprehensive Coverage: From fundamental concepts to advanced dynamic models.
  • Practical Learning: Real-world case studies and hands-on exercises with Stata.
  • Expert Insights: Gain clarity on complex topics like endogeneity and serial correlation.
  • Interactive Format: Live Q&A sessions to address individual questions and challenges.
Who Should Attend?

By the end of the course, participants will have a solid foundation in modelling non-stationary variables, equipping them with the skills needed to analyze complex time series data effectively.

Agenda

Non-Stationarity I - Unit Roots

Introduction to EViews
Programming and Series Transformations:
Preliminary Theory for Univariate Regression
Misspecification Analysis:
Day 2:

Session 1
Session 2: Dynamic Panel Models

Prerequisites

  • No prior knowledge of EViews required
  • Basic Regression and Statistics knowledge

Terms

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Temporary, time limited licences for the software(s)  used in the course will be provided. You are required to install the software provided prior to the start of the course.
  • Payment of course fees required prior to the course start date.
  • Registration closes 1-calendar day prior to the start of the course.

 

  • 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
  • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
  • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

 

The number of attendees is restricted. Please register early to guarantee your place.

Delivered By

Student Testimonials

Giovanni's delivery is fantastic; makes great connections between new and prior knowledge and focuses on the key strengths and limitations of the discussed methods. Excellent course design that builds on the Introductory Machine Learning course and knowledge acquired in the PhD Econometrics sequences of courses. This is all nicely supplemented by detailed Stata code with explanations and sample datasets. 

Georgi Boichev

A student on our

Excellent course and great explanations on ML techniques and applications from Giovanni ! I leanred so much including the coding and applications plus the fundamentals of ML.

Marco Delprado

A student on our

The 'Advanced Machine Learning (AML)' experience was excellent for trying to gain more experience in Statistics using links Python and STATA.  

I'm not a Statistician! However, Giovanni managed to link the 'Fundamentals of Machine Learning (FML) ' to 'Advanced Machine Learning' in his usual excellent way. When starting the AML, for me I am pleased that the FML was a tremendous help and allowed me to use my mathematical knowledge for Physics and Science. I'm looking forward to Giovanni's next course (using large datasets) and his book.

Linking my knowledge of mathematics (from Science and Engineering) to Statistics. I do hope it is leading towards becoming better at 'Medical Statistics' that require very large datasets...and a big thank you to Giovanni!

William Ware

A student on our

Very well organized, very useful and relevant content, looking forward to joining future events!

Hebatallah Nashaat

A student on our

As always great service and real good courses. In addition, thanks to Professor Cerulli for making himself understood in the best way.

David Pineda

A student on our

The delivery of this course was exceptionally well done. It really helped me to appreciate the concepts as well as the practical applications in Stata. If you are new to this topic, this will provide a good introduction to complex issues.

Very easy to communicate, all emails contained all the information necessary. I think that the course was very well structured and organized. The tutor provided a number of codes that were extremely helpful for understanding. Overall, very useful and easy to follow!

I highly appreciated Professor Giovannu Cerulli course. The classes notes are very clear   and well prepared with an extensive coverage of the course subjects. And they are simultanesouly quite objective by focusing on the most important contents. Professor Giovannu Cerulli lectures are very didatic which greately helps the easily assimilation of the   corespondent knowledge. Furthermore, the course materials are quite   comprehensive and they englobe not only the classes notes, but also the referenced papers as well as data and Stata programs to estimate the models in this software. All in all, I greatly recommend this   course, as it really amazingly speeds up the acquaintance of the underlying theory and appied aplication in a very short period of time.

I found the Stata Summer School 2021 very useful and interesting. The course was perfectly structured and organised, with a good progression during the week. The instructors presented the topics covered in an easy and understandable way. There were room for questions and answers when needed. Materials shared for the course were tidy and informative, and I am sure I will use them frequently. This course was arranged online, which in my opinion worked very well. I believe the course delivered as promised and according to information found online when I signed up for the course. Easy to purchase/sign up for the course. User friendly. Quick and timely response.

Very efficient in terms of communication and delivery. Provides a very comprehesnive applied knowledge of stata. I would definitely recommend others to buy from them.

I went UK University of Cambridge for a summer school with Timberlake, it was excellent.

It was a great course and I thoroughly enjoyed it. Many of my fellow participants were eager to share their ideas. I thought the course could help further many people in a similar stage to my career!