About the Stata Course

This course provides an introduction to the principles and practice of time series analysis and forecasting using Stata. Time series data, which is collected over time, is commonly encountered in fields such as finance, economics, engineering, and social sciences. The course is designed to teach students how to model and analyze time series data and how to make forecasts based on these models. The course is tailored for economics students (undergraduates, graduates, postgraduates) as the examples are based on real-world economic data. Throughout the course, we will see examples of monetary policy, fiscal policy, economic growth, money supply and demand, inflation, and other macroeconomic variables such as the consumer price index. 

The course covers the following topics:

• Introduction to time series data and its properties

• Stationarity and non-stationarity

• Mean Forecasting with univariate models (AR, MA, ARMA, ARIMA)

• Models for the Variance (Arch and Garch)

• Model selection and diagnostic checking

•  Multivariate Forecasting Models: Vector Autoregressive (VAR) Models

• Evaluation and forecast of models

• Advanced topics in time series analysis, including Dynamic Stochastic General Equilibrium (DSGE) Models

The course is taught using Stata software, a popular statistical package widely used in academic research and industry. Students will learn to use Stata to conduct data analysis, model estimation, diagnostic checking, and forecasting.

Prerequisites:

Students are expected to have basic knowledge of statistics, econometrics. Familiarity with the Stata software is NOT required as I will walk you through the necessary steps.

Learning Outcomes:

Upon completion of this course, students will be able to:

• Understand the properties and characteristics of time series data

• Choose appropriate models for time series data and make inferences based on these models

• Use Stata software to estimate and diagnose time series models

• Generate accurate forecasts and evaluate their performance

• Apply advanced time series techniques to real-world data problems. 

Final Notes and Big Thanks

The course is offered free of charge and aims to provide students with the necessary skills and knowledge to succeed in their academic and professional careers. However, students also have the option to purchase the material of the course: including complete Stata DO files, slides used in the videos, and datasets.

Purchasing these materials is entirely optional, but it provides learners with the opportunity to study at their own pace and support the creation of further content. By investing in these materials, learners can also demonstrate their appreciation for the instructor's efforts and contribute to the continued development of the course.

I am confident that the course content will provide you with valuable insights and practical skills that will help you succeed in your economic assignments, exams, thesis, and projects. I hope you find the course and material engaging and informative and that it assists you in achieving your educational goals. 

Best Regards,

Juan D'Amico - JDEconomics