Overview
This course is part five of a five-part EViews training series running throughout 2024.
You will find links for all other courses in the series below:
Course 1: EViews Basics
Course 2: Atheoretical Models in EViews
Course 3: Models for Non-Stationarity Variables in EViews
Course 4: Volatility Models and Panel Data Models
This comprehensive course delves into advanced topics in data analysis, focusing on two key aspects: Models for Panel Data and Models for Discrete Choice. Participants will gain a nuanced understanding of panel data dynamics and discrete choice modelling, equipping them with valuable skills for informed decision-making in various fields. The course combines theoretical insights with practical applications in EViews, offering hands-on exercises and interactive sessions to reinforce learning.
Course Highlights
- Fixed vs Random Effects
- Dynamic Panels
- Taxonomy of Discrete Choice Models
- Estimation techniques for Discrete Choice Models
Upon the course's completion, all attendees will receive a certificate of attendance as proof of professional development.
Agenda
Level: Intermediate / Advanced
Learning ratio: 50% Practical; 50% Theory
Sessions 1 & 2: Models for Panel Data
Fixed vs Random Effects:
- Overview of Panel Data and its relevance in various disciplines.
- Recognizing the benefits of utilizing panel data for analysis.
- In-depth exploration of the differences between fixed and random effects models.
- Practical applications and considerations for choosing the appropriate model.
Dynamic Panels:
- Understanding (short) dynamic panel data.
- The Arellano-Bond estimator.
Sessions 3 & 4: Models for discrete choice
Taxonomy of Discrete Choice Models:
- Overview of discrete choice models and their significance in decision-making. Exploring different types of discrete choice models.
- Understanding the characteristics and applications of each model type with real-world examples.
Estimation Techniques for Discrete Choice Models:
- Methods for estimating parameters in discrete choice models.
- Practical considerations and challenges in the estimation process.
Forecasting in Discrete Choice Models
- Utilizing discrete choice models for predictive analytics.
- Forecasting techniques and applications in decision-making.
Prerequisites
Models for Panel Data in EViews
- Prior knowledge of EViews and its programming language
- Basic knowledge of of Probit / Logit models
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Terms & Conditions
- 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.
- Delegates are provided with temporary licences for the principal software package(s) used in the delivery of the course. It is essential that these temporary training licenses are installed on your computers 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 more than 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.