Time series forecasting in stata - ARIMA Models Part 3

ARIMA time series in stata tutorial : "Time series forecasting in stata - ARIMA Models Part 3". In this tutorial video, we explore time series forecasting using ARIMA models in Stata. Specifically, we focus on forecasting the Consumer Price Index (CPI) in the USA. This is the final part of the tutorial, where we verify that the estimated model is a stable univariate process. We cover topics such as checking that the residuals are white noise, the ARMA process is covariance stationary, and that the ARMA process is invertible. The video walks through how to generate the errors of the model, generate a graph to visualize the residuals, and check whether the residuals are white noise using the Wald test. We also demonstrate how to check that the estimated ARMA process is covariance stationary using the roots graph. Finally, we show you how to forecast the ARIMA model by including more observations. Whether you're a beginner or an experienced data analyst, this video provides valuable insights and practical tips on how to perform time series forecasting using ARIMA models in Stata. So, if you're interested in forecasting the CPI or other time series data, this tutorial is a must-watch! 📣 Get the complete package for learning ARIMA models in Stata! Purchase the slides used in the video, along with the complete Stata Do File and Dataset at: https://jdeconomicstore.com/b/arimastata. 📈 You can also download the dataset for free and replicate the content of the video at https://www.jdeconomics.com/stata-tutorials/arima-models-in-stata. ✅ This video is part of a FREE STATA Course. See the full course outline at: https://www.jdeconomics.com/stata-tutorials ✅ Visit my website for all the content available: https://www.jdeconomics.com/ 📣 Tutorial is also available in EViews: https://www.youtube.com/watch?v=ukGJ0sLgbqI&list=PLsZ8kVwX52ZGXxJ-bqP-WmRBD2HytO4d4 📺 For more videos likes this, please subscribe: https://www.youtube.com/channel/UC5P21WGFO4WRUlAiGLcwymg?sub_confirmation=1 ✅ Is there any topic you would like me to cover? Do you have any research questions? Contact me at: 📧 [email protected] 📲 Follow me on social media for news, updates, discounts, tips and more! https://juandamico.start.page/ --------------------------------------------------------------------------------------------------------- This is the third and last video of ARIMA modelling in Stata. There are three Videos Total. One for each Step: Ensure to watch them all. 🌐Video 1: ARIMA models in STATA - Part 1: Identification Link: https://www.youtube.com/watch?v=pquD3OjeLFU&list=PLsZ8kVwX52ZEFZsVViYs60lf7idJuKKUO 🌐Video 2: ARIMA models in STATA - Part 2: Estimation Link: https://www.youtube.com/watch?v=mPDNH-rA4OQ&list=PLsZ8kVwX52ZEFZsVViYs60lf7idJuKKUO --------------------------------------------------------------------------------------------------------- 🕘 Timestamps: 👋 Introduction 0:00 📊 Overview of Step 3: 0:38 📊 Recap of our Arima Model 1:50 📊 Testing White Noise 2:14 📊 Checking for Covariance Stationarity 4:55 📊 Forecasting 5:48 --------------------------------------------------------------------------------------------------------- ✅ Interested in learning more? 🎬 Learn how to write your research paper in a fancy way in Latex with Overleaf: https://youtube.com/playlist?list=PLsZ8kVwX52ZGTCs7OsRPzweuqnJSiU76p 🎬 EViews related videos: https://youtube.com/playlist?list=PLsZ8kVwX52ZGXxJ-bqP-WmRBD2HytO4d4 --------------------------------------------------------------------------------------------------------- If you liked the video and would like more content, please support my channel subscribing! 👍Like and subscribe for more videos! ☕️ If you would like to show your appreciation and make a donation: 💳 https://paypal.me/JDEconomics?locale.x=en_US Thanks a lot!