Panel Vector Autoregression (PVAR) in STATA | When, Why & How to Run PVAR | Panel data

In this video, I explain Panel Vector Autoregression (PVAR) from both a theoretical and practical perspective. You will learn what a PVAR model is, when it should be used, and how to estimate and interpret it in STATA using real panel data. The tutorial covers: ✅ What is a PVAR model? ✅ When should you use PVAR? ✅ Key assumptions of PVAR ✅ Selecting the optimal lag length ✅ Estimating a PVAR model in STATA ✅ Testing model stability ✅ Interpreting Impulse Response Functions (IRFs) ✅ Forecast Error Variance Decomposition (FEVD) ✅ Understanding the output and interpreting the results This tutorial is ideal for researchers, PhD/MS students, economists, finance researchers, and anyone working with dynamic panel data. If you found this video helpful, please Like, Share, and Subscribe to support the channel and stay updated with future tutorials on Econometrics, STATA, AI tools for research, panel data analysis, time series analysis, Difference-in-Differences (DiD), GMM, PSM, and other advanced research methods. 📩 PS: The dataset and STATA do-file used in this tutorial are available upon request on: [email protected] #PVAR #STATA #Econometrics #PanelData #VectorAutoregression #IRF #FEVD #DynamicPanelData #GMM #ResearchMethods #DataAnalysis #PhD #Economics #Finance #STATATutorial #AcademicResearch