Data Analytics Blog - Page 2 of 7

Dec 23 by Erica Posted in Time Series, User Interface

Preparing and Cleaning FRED data in GAUSS

In today’s blog, we look at how to save time and reduce errors using GAUSS’s new data management tools. Using the quarterly real GDP dataset from the FRED database we explore GAUSS’s new data management tools. In particular, we examine how to:

Deal with irregular dataset headers.
Change variable names.
Filter dates and change the date display.

Dec 08 by aptech Posted in Releases, Video

Easy and Fast Data Management in GAUSS 21

The new dataframes and interactive data management tools in GAUSS 21 will make your work more enjoyable and save you hours of time. Learn more about the latest features including:

New dataframes that handle strings, categories, and dates with ease.
Interactive data filtering.
Easy to manage date displays.
Interactive management of categorial variables.
Auto-generated code.

Tagged in data management

Oct 15 by Erica Posted in Econometrics, Programming

Maximum Likelihood Estimation in GAUSS

Maximum likelihood is a fundamental workhorse for estimating model parameters with applications ranging from simple linear regression to advanced discrete choice models. Today we learn how to perform maximum likelihood estimation with the GAUSS Maximum Likelihood MT library using our simple linear regression example. We’ll show all the fundamentals you need to get started with maximum likelihood estimation in GAUSS including:

How to create a likelihood function.
How to call the maxlikmt procedure to estimate parameters.
How to interpret the results from maxlikmt.

Tagged in maximum likelihood, programming

Oct 01 by Erica Posted in Econometrics, Panel data

Panel Data Stationarity Test With Structural Breaks

Reliable unit root testing is an important step of any time series analysis or panel data analysis. However, standard time series unit root tests and panel data unit root tests aren’t reliable when structural breaks are present. Because of this, when structural breaks are suspected, we must employ unit root tests that properly incorporate these breaks. Today we will examine one of those tests, the Carrion-i-Silvestre, et al. (2005) panel data test for stationarity in the presence of multiple structural breaks.

Tagged in structural breaks, unit root

Sep 21 by Erica Posted in Econometrics, Programming

Beginner's Guide To Maximum Likelihood Estimation

Maximum likelihood is a widely used technique for estimation with applications in many areas including time series modeling, panel data, discrete data, and even machine learning. In today’s blog, we cover the fundamentals of maximum likelihood including:

The basic theory of maximum likelihood.
The advantages and disadvantages of maximum likelihood estimation.
The log-likelihood function.
Modeling applications.

Aug 31 by Mark Harris Posted in Econometrics

Anchoring Vignettes and the Compound Hierarchical Ordered Probit (CHOPIT) Model

Self-assessments are a common survey tool but, they can be difficult to analyze due to bias arising from systematic variation in individual reporting styles, known as reporting heterogeneity. Anchoring vignette questions combined with the Compound Hierarchical Ordered Probit (CHOPIT) model, allows researchers to address this issue in survey data (King et al. 2004). This methodology is based on two key identifying assumptions:

Response consistency (RC)
Vignette equivalence (VE)

In today’s blog we look more closely the fundamental pieces of this modeling technique including the:

Typical data set up.
Hierarchical Ordered Probit Model (HOPIT).
Anchoring vignettes.
Likelihood and identifying assumptions used for estimation.

Tagged in survey data

Aug 04 by aptech Posted in Graphics

How to Create Tiled Graphs in GAUSS

Placing graphs next to each other can be a great way to present information and improve data visualization. Today we will learn how to create tiled graphs in GAUSS with the easy-to-use plotLayout procedure.

We will work through two simple examples where you will learn:

How to created tiled layouts which are uniform and layouts with graphs of different sizes.
Which graph types can be used with plotLayout.
How to clear your tiled graph layouts.

Jul 17 by aptech Posted in Best Practices, Programming

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.

Jun 11 by Erica Posted in Econometrics, Programming

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.

May 26 by Erica Posted in Time Series

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.

Tagged in cointegration, unit root

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