Podstawy modelowania ekonomicznego

Podstawy modelowania ekonomicznego

Poznaj podstawy EViews, wiodącego oprogramowania ekonometrycznego, i zapoznaj się z obsługą danych, programowaniem i modelowaniem regresji. Ten praktyczny kurs obejmuje analizę klasycznego modelu regresji liniowej (CLRM), testy diagnostyczne i techniki udoskonalania modelu.

Zapisz się tutaj
Zapisz się tutaj
190,00 GBP
Gwarancja bezpiecznej i pewnej realizacji transakcji
1 dzień
Online za pośrednictwem 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

  • Introduction to EViews software.

  • Understanding the concept of a "workfile" and an "object" in EViews.

  • Data handling and organization within EViews.

  • Introduction to EViews databases.

  • Session 2: Further Exploration of EViews Basics

Programming and Series Transformations:

  • Brief introduction to programming in EViews.

  • Series transformations and their applications.

  • Data description techniques, including creating, editing, freezing, and exporting graphs.

  • Descriptive statistics and hypothesis testing in EViews.

  • Session 3: Classical Linear Regression Model (CLRM) I

Preliminary Theory for Univariate Regression

  • Understanding the Classical Linear Regression Model (CLRM).

  • Assumptions underlying CLRM.

  • Ordinary Least Squares (OLS) estimation in EViews.

  • Regression statistics and their interpretation.

  • Session 4: Classical Linear Regression Model (CLRM) II

Misspecification Analysis:

  • Review of CLRM and its assumptions.

  • Diagnostic tests in EViews for identifying misspecification problems.

  • Stability tests for assessing the robustness of regression models.

  • Solutions to misspecification problems in regression analysis.

  • Introduction to the General-to-Specific (GETS) approach in model selection.

Day 2:

Session 1
  • Comparing estimators for static panel models for your research question 
  • Testing for serial correlation
Session 2: Dynamic Panel Models
  • The Arello Bond estimator and post-estimation diagnostic test 
  • The Blundell Bond estimator and post estimation diagnostic tests
  • Case study: the determinants of bank risk-taking in European banks.

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.

Dostarczone przez

  • https://timberlake.co/media/iopt/blog/Lorenzo_trapani.webp

    Prof Lorenzo Trapani

    University of Pavia and Honorary Professor at the University of Leicester School of Business

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