Basics of GAUSS Procedures
GAUSS procedures are user-defined functions that allow you to combine a sequence of commands to perform desired tasks. In this blog, you will learn the fundamentals of creating and using procedures in GAUSS.
How To Create Dummy Variables in GAUSS
Dummy variables are a common econometric tool, whether working with time series, cross-sectional, or panel data. Unfortunately, raw datasets rarely come formatted with dummy variables that are regression ready.
In today’s blog, we explore several options for creating dummy variables from categorical data in GAUSS, including:
- Creating dummy variables from a file using formula strings.
- Creating dummy variables from an existing vector of categorical data.
- Creating dummy variables from an existing vector of continuous variables.
How to Interpret Cointegration Test Results
In this blog, we will explore how to set up and interpret cointegration results using a real-world time series example. We will cover the case with no structural breaks as well as the case with one unknown structural break using tools from the GAUSS tspdlib library.
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How to Interactively Create Reusable Graphics Profiles
Learn how to create reusable graphics profiles with a few clicks of your mouse.
How to Create a Simple Table with sprintf in GAUSS
Learn how to create a simple output table with variable names, parameter estimates and standard errors using sprintf in GAUSS.
The Basics of Optional Arguments in GAUSS Procedures
Optional input arguments can make your statistical computing more efficient and enjoyable. GAUSS version 20 added a new suite of tools to make it easy for you to add optional input arguments to your GAUSS procedures. This blog lays the foundation to start using optional arguments in your GAUSS programs.
A Guide to Conducting Cointegration Tests
Cointegration is an important tool for modeling the long-run relationships in time series data. If you work with time series data, you will likely find yourself needing to use cointegration at some point. This blog provides an in-depth introduction to cointegration and will cover all the nuts and bolts you need to get started.
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Advanced Search and Replace in GAUSS
You’re probably familiar with the basic find-and-replace. However, large projects with many files across several directories, require a more powerful search tool. The GAUSS Source Browser is the powerful search-and-replace tool you need. In this blog, you’ll learn more about using the advanced search-and-replace tools in GAUSS to effectively navigate and edit in projects with multiple files and directories.
Update Time Series Application Module TSMT
The latest Time Series MT (TSMT) 3.1.0 is now available for release. If you own TSMT 3.0 the update is available for free.
Introduction to the Fundamentals of Panel Data
Panel data, sometimes referred to as longitudinal data, is data that contains observations about different cross sections across time. Panel data exhibits characteristics of both cross-sectional data and time-series data. This blend of characteristics has given rise to a unique branch of time series modeling made up of methodologies specific to panel data structure. This blog offers a complete guide to those methodologies including the nature of panel data series, types of panel data, and panel data models.