TIME SERIES ANALYSIS
Understand and apply advanced time series methods using STATA and EViews. From ARIMA and structural breaks to VAR, VECM, and volatility models — this instructor-led course equips you with the tools to analyze and forecast real-world economic and financial data.
Overview
Applied Time Series Econometrics Analysis with STATA & EViews
This course delivers a comprehensive approach to time series econometrics through live classes and real data analysis. It combines theory with STATA & EViews applications to help researchers, analysts, and students interpret economic trends, test stationarity, model volatility, and run forecasting simulations.
Course Overview
Duration: 30–35 Hours | Mode: Instructor-led | Tools Covered: STATA & EViews
Schedule: Monday to Friday | 8:00 PM – 9:30 PM IST
Course Span: 5 Weeks
Next Batch: (Dates to be announced)
Global Timings: Participants from Europe, North America, South America, and Africa can request alternative slots.
Course Highlights
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Live Interactive Classes – Learn with instructor guidance using real economic datasets.
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Dual Software Training – Hands-on use of both STATA and EViews.
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Empirical + Theoretical Focus – Develop strong forecasting, modeling, and econometric skills.
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Data-Driven – Practical assignments with data from World Bank, IMF, Statista, NSSO & more.
What You’ll Learn
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Time Series Data Collection and Transformation
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Classical Trend, Seasonal, and Cyclical Analysis
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AR, MA, ARMA, ARIMA, SARIMA Models
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Structural Break Tests: Chow, Zivot-Andrews, Bai-Perron
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Co-integration using Engel-Granger, Johansen & Bounds Tests
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VAR, VECM, ARDL, SVAR, BVAR, and Markov Switching Models
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ARCH & GARCH Volatility Models
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Model Diagnostics for Stationarity, Normality, and Stability
This course is perfect for professionals and scholars aiming to build forecasting systems, test economic hypotheses, or evaluate policy over time.
Datasets Used
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World Bank Indicators
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IMF Macroeconomic Data
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NSSO Government Datasets
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Statista Macro Data
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Indian Economic Surveys
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Custom simulation datasets
References
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Applied Econometrics Time Series – Walter Enders, 3rd Edition
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Basic Econometrics – Damodar Gujarati, 5th Edition
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Theory of Econometrics – A. Koutsoyannis, 2nd Edition
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Econometrics by Example – D. Gujarati, 2nd Edition
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Fundamentals of Mathematical Statistics – S.C. Gupta & V.K. Kapoor, 20th Edition
Curriculum
- 12 Sections
- 40 Lessons
- 35 Hours
- 1. Time Series Data SourcesLearn to extract macroeconomic, financial, and institutional data from authentic global sources.5
- 2. Time Series Data ProcessingMaster essential transformations for time series data to make it ready for modeling and analysis.4
- 3. Classical Time Series AnalysisUnderstand long-term patterns, seasonal effects, and business cycles in time series.3
- 4. StationarityLearn to differentiate between trend and difference stationary series, and test for unit roots.4
- 5. Uni-variate Time Series ModelingBuild and forecast models using single-variable time series methods.4
- 6. Structural BreaksDetect breaks in economic relationships due to policy changes, crises, or events.3
- 7. Co-integrationExplore long-run equilibrium relationships between time series variables.3
- 8. Multi-variate Time Series ModelingMove beyond uni-variate analysis by building systems of interrelated time series.3
- 9. Advanced Multi-variate Time Series ModelingModel structural and regime-switching behavior in time series data.3
- 10. Diagnostic TestsEnsure your models are well-specified and assumptions are met.6
- 11. Volatility ModelingStudy conditional heteroscedasticity and model financial volatility using ARCH & GARCH frameworks.2
- 12. Software Application (STATA & EViews)Each concept includes hands-on implementation using real data in STATA and EViews. Includes replication of standard results from published studies and real-time policy data.0
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Course Features
- Lectures 40
- Quiz 0
- Duration 5 Weeks
- Skill level All levels
- Language English
- Students 279
- Assessments Yes