What is the var model? In this video, I show you How to estimate and interpret VAR models in Eviews - Vector Autoregression model. In order to do so, we will replicate Stock and Watson (2001) published paper entitled:"Vector Autoregressions". Learn to estimate a Monetary policy VAR in EViews. Please download the data set and paper provided below in the description of the video to replicate VAR in Eviews.

I hope you enjoy this time series var model step by step explanation!

✅ Buy Eviews Workfile Complete + SLIDES +Dataset (Includes the two VAR Videos material): [ Ссылка ]

📈 Download the dataset for free and replicate the content of the video:
[ Ссылка ]

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💡VAR model in Eviews:
✅ How to estimate and interpret VAR models in Eviews - Vector Autoregression model

✅ Objective of the video: The video first covers an overview of VAR models and then we estimate a VAR model in EViews. To cover the content, we replicate the var model set up in Stock and Watson (2001). Monetary policy VAR model in Eviews. By watching the two videos I uploaded, you will learn how to estimate and interpret VAR models in Eviews, select the appropriate lag length, check for VAR stability conditions and residuals, and perform the Granger causility Test.

✅ In the second Video, you will learn how to do impulse-response functions and obtain the Variance Decomposition in a var model in eviews.

🎬 VAR MODEL IN EVIEWS PART 2: [ Ссылка ]

📣 Please note: The Vector Autoregression model I estimate in EViews respects the estimation procedure by the authors, such as the Lag-lenght selection, the inclusion of a constant term, and the recursive order of the variables. For further details, please refer to the original paper.
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🕘 Timestamps:
🎬 In this video the following analysis is performed:
👋 Introduction 0:00
📊Overview of VAR models 0:17
📊 VAR models - Formal Representation 1:11
📊 VAR model example: Stock & Watson (2001): 2:44
📊 Stock and Watson : Formal representation: 3:36
📊 Estimating VAR model in Eviews: 4:01
📊 Lag-Length Criteria: 5:45
📊 VAR stability conditions: 8:15
📊 Residual Diagnostics: 9:47
📊 Granger Causality Test 12:02
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🗂Video Material:

📚Stock and Watson (2001) Paper: "Vector Autoregressions".
🌐 [ Ссылка ]

⚠ Disclaimer: the data was gathered from different data sources (i.e., Fred , World Data Bank, etc.). The data set is not the original used by the authors, reason why some estimates may differ in a minimal way.
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📚 Recommended Literature:

📚 Christopher Sims (1980): "Macroeconomics and Reality".
🌐[ Ссылка ]

📚Sims, Stock and Watson (1990): "Inference in Linear Time Series Models with some Unit Roots"
🌐[ Ссылка ]

📚 Granger (1969): "Investigating Causal Relations by Econometric Models and Cross-spectral Methods"
🌐[ Ссылка ]
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✅ Other Useful Links:

🎬 Unit Root Test Tutorial (Stationarity):
[ Ссылка ]

Interested in learning more?

🎬 Learn how to write your research paper in a fancy way in Latex with Overleaf: [ Ссылка ]

🎬 More EViews related videos:
[ Ссылка ]
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💬 Doubts or comments? Please leave your comment!

Thanks!

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