Organization Name / Organize By
Indepth Research Institute
Organizing/Related Departments
Training Department
Organization Type
Organization
WorkshopCategory
Both (Technical & Non Technical)
WorkshopLevel
All (State/Province/Region, National & International)
Related Industries
Research/Science
Social Sciences
Finance
Economics
Accounting/Financial/Banking/Insurance
This course is designed to provide participants with a comprehensive understanding of time series analysis and econometric modeling using Stata.
It will equip the participants with the skills to work with time series data, including stationarity testing, ARIMA modeling, cointegration analysis, vector autoregression (VAR), and volatility modeling.
With hands-on exercises and real-world data applications, participants will learn to apply Stata's powerful time series features to analyze and forecast economic and financial data.
Course Duration
5 Days
Who Should Attend
- Economists,
- Financial analysts,
- Statisticians,
- Researchers,
- Data scientists
- Professionals in economic forecasting, financial analysis, and data-driven decision-making.
Personal Impact
- Master advanced time series modeling techniques using Stata.
- Gain practical experience in analyzing and interpreting time series data.
- Enhance your ability to develop accurate economic and financial forecasts.
Organizational Impact
- Improve organizational forecasting and decision-making capabilities.
- Apply robust time series analysis methods to identify trends and assess risks.
- Strengthen organizational strategies using advanced econometric models.
Course Objectives
- Understand the key principles of time series data analysis and econometrics.
- Conduct unit root tests, estimate ARIMA models, and analyze cointegration relationships.
- Build and interpret VAR models, impulse response functions, and forecast variance decomposition.
- Use Stata to model and forecast time series data effectively.
- Apply advanced econometric techniques to real-world economic and financial datasets.
Course Outline
Module 1: Introduction to Time Series Data and Stata Basics
- Overview of time series data and Stata’s time series capabilities
- Importing, managing, and manipulating time series data in Stata
- Understanding stationarity and non-stationarity
- Practical Exercise: Data management and stationarity testing in Stata
Module 2: ARIMA and SARIMA Modeling
- Introduction to autoregressive integrated moving average (ARIMA) models
- Identifying ARIMA models using autocorrelation and partial autocorrelation functions
- Estimating ARIMA models and performing diagnostics
- Forecasting with ARIMA and SARIMA models
- Case Study: Building an ARIMA model for financial time series data
Module 3: Cointegration and Error Correction Models
- Concept of cointegration and its significance in time series analysis
- Estimating and interpreting cointegrated models
- Building vector error correction models (VECM)
- Practical Exercise: Cointegration testing and VECM estimation in Stata
Module 4: Vector Autoregression (VAR) and Impulse Response Functions
- Introduction to VAR modeling for multivariate time series
- Estimating VAR models and interpreting results
- Impulse response functions and variance decomposition
- Case Study: VAR model application in economic forecasting
Module 5: Volatility Modeling and GARCH Models
- Introduction to volatility and ARCH/GARCH models
- Estimating and interpreting GARCH models for time series volatility
- Practical Exercise: GARCH model estimation and volatility forecasting in Stata
- Real-life Project: Time series modeling and forecasting using real-world economic data
Related Courses
- Financial Econometrics Using Stata Training Course
- EViews — Advanced Time Series Econometrics Training Course
- Performance Based Budgeting Training Course
- Introduction to Econometric Modelling With Ox Metrics 8 Training Course
- Post Pandemic Economic Recovery Training Course
- Machine Learning Using Stata Training Course
Course Administration Details
Methodology
The instructor-led trainings are delivered using a blended learning approach and comprises presentations, guided sessions of practical exercise, web-based tutorials, and group work.
Our facilitators are seasoned industry experts with years of experience, working as professionals and trainers in these fields.
All facilitation and course materials will be offered in English. Therefore, the participants should be reasonably proficient in English.
Accreditation
Upon successful completion of this training, participants will be issued an IRES certificate certified by the National Industrial Training Authority (NITA).
Training Venue
The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments, and lunch.
All participants will additionally cater to their travel expenses, visa application, insurance, and other personal expenses.
In addition to our virtual training, we conduct training in Kenya (Nairobi, Mombasa, Kisumu, Nakuru, and Naivasha) and in the following locations:
- Dubai - United Arab Emirates
- Cairo - Egypt
- Johannesburg, Pretoria, and Cape Town - South Africa
- Zanzibar, Dar-es-Salaam, and Arusha - Tanzania
- Kigali - Rwanda
- Accra - Ghana
- Kampala - Uganda
Accommodation and Airport Transfer
Upon request, we can arrange accommodation and airport transfer.
For reservations and bookings, kindly contact us at:
Tailor-Made Program
Upon request, this training can also be customized to suit the needs of you or your institution.
You can have it delivered at our IRES Training Centre or a convenient location.
For further inquiries, please contact us at:
Address/Venue
IRES Training Centre
Tala Road, Off Kiambu Road Runda-Nairobi
Pin/Zip Code : 00100