Data, Economic Modeling, and Forecasting with Stata
49mBeginner2021-02-25
Authors

Jason Schenker
Economist, Finance Expert, Futurist, Speaker, and Author
Course details
Working with data is an important part of many jobs, and in the future, it will be important for even more. In this course, financial forecaster Jason Schenker teaches important fundamentals about data, economic modeling basics, and how to forecast with Stata. He guides you through building univariate and multivariate linear regression models in Stata, as well as interpreting statistical outputs, and the importance of data modeling iteration. Jason also discusses critical statistics used in forecasting, like the mean, standard error, standard deviation, coefficients, independent variables, and confidence intervals, and highlights critical data risks and best practices like how correlation does not equal causation. Jason also shares the importance of good data, big data, and managing risks when building forecasting models, and finishes with an introduction to some advanced topics in statistics and econometrics.
Skills covered
StataCorporate FinanceData VisualizationFinance and AccountingLimited SeriesData ScienceBusiness Analysis and StrategyBusiness Software and Tools
Concepts
Introduction
- Be prepared for the data jobs of the future
Overview
- Purpose of modeling in Stata
- The value of good data and good big data
Modeling Basics
- Statistics and econometrics
- Univariate and multivariate linear regression models
- Correlation is not causation
- Overly tight model fit
- Models are always wrong
Screencap Basics in Stata
- Overview and enter data
- Data preparation and selection
- Inputting data
- Mean and summary statistics
- Standard deviation and SE
- Correlation
- Key output validity measures
- Univariate model
- Multivariate model
- Appling univariate model to forecast
- Saving and files
Advanced Topics
- Advanced topics
Conclusion
- Next steps