How to Perform VAR-IRF Analysis in Stata, Part 2 - Tutorial Dissertation

🔒 More advanced videos with Datasets (Excel) + Stata Do-files available as Members-Only - Join P.E.R.S here:    / @cruncheconometrix   P.E.R.S Full List:    • Members-only videos   VAR and Impulse Response Functions Part 2 - Stata 13 Tutorial for MSc Dissertation | UK, US, Canada | Stata Time Series Are you writing your MSc Economics, Finance, Banking or PhD dissertation using VAR and Impulse Response Functions in Stata 13 - #var #irf #impulseresponse #innovations #shocks - Part 1? You are in the right place. What do you understand by impulse response function? It explains the reaction of an endogenous variable to one of the innovations; describes the evolution of the variable of interest along a specified time horizon after a shock in a given moment; it is an essential tool in empirical causal analysis and policy effectiveness analysis; tracks the impact of a variable on othe... In this complete Stata 13 tutorial Part 1, I show you VAR and Impulse Response Functions Part 1. Learn to interpret the impulse response function in Stata using a three-variable VAR model. Master your time series analysis workflow. This tutorial continues our series on VAR model Stata applications. It is designed for students and researchers who have already completed the preliminary steps of testing for stationarity, determining the optimal lag length, and estimating a basic VAR model. If you are comfortable with those foundational tasks, this session focuses on the next analytical phase. We will walk through the specific steps required to generate and discuss results from an impulse response function. By the end of this video, you will know how to apply these techniques to your own data sets, ensuring your Stata econometrics work is accurate and technically sound. This guide assumes you have your model estimated and ready for interpretation. Subscribe for weekly Stata econometrics breakdowns, and comment below if you need help with a specific part of your time series analysis. 0:00 Setting Up the VAR Model in Stata 1:24 Executing the VAR Basic Command 2:44 Interpreting Impulse Response Graphs 6:57 Diagnostic Testing and Model Stability WHO THIS IS FOR: MSc, MBA, PhD Economics, Finance, Banking, Financial Economics, Monetary Economics students in UK (Warwick, Manchester, Leeds, Birmingham, Glasgow, Edinburgh, LSE), US, Canada, Australia, EU using VAR and Impulse Response Functions - IRF - Part 2 - advanced - Stata 13 time series. OFFICIAL LINKS & COMMUNITY: 🌐 Website: https://cruncheconometrix.com 🛒 Data Shop: https://cruncheconometrix.com/view/da... 🎓 Members-Only:    • Members-only videos   ⭐ Join Membership:    / @cruncheconometrix   👥 Facebook:   / cruncheconometrix   💼 LinkedIn:   / cruncheconometrix   🔔 Subscribe: https://www.youtube.com/c/CrunchEcono... FAQ: Q: What is difference between orthogonalized IRF and generalized IRF? A: Orthogonalized IRF OIRF - ordering matters - Cholesky ordering - e.g., var GDP FDI vs var FDI GDP different IRF if variables correlated - need theory justify ordering - e.g., more exogenous first - Generalized IRF GIRF - ordering invariant - no need ordering - more robust - similar to orthogonalized with correct ordering - preferred if no theory for ordering. Q: What is cumulative IRF? A: Cumulative IRF COIRF - shows cumulative effect over horizon - e.g., cumulative GDP response to FDI shock over 10 periods =0.5 - FDI shock increases GDP cumulatively 0.5 over 10 periods - long-run cumulative effect - policy - long-run - vs OIRF shows period-by-period response - e.g., response 0.05 at period1, 0.08 at period2 - COIRF sums over horizon - long-run. #VAR #IRF #ImpulseResponse #Part2 #Innovations #Shocks #VectorAutoregressive #Econometrics #Stata13 #TimeSeries #MScDissertation #UKUniversities #ImpulseResponseFunction #PhDResearch #DissertationHelp #StataTimeSeries #CrunchEconometrix #CausalAnalysis #PolicyAnalysis #AdvancedIRF