Erica has been working to build, distribute, and strengthen the GAUSS universe since 2012. She is an economist skilled in data analysis and software development. She has earned a B.A. and MSc in economics and engineering and has over 15 years combined industry and academic experience in data analysis and research.
The preliminary econometric package for Time Series and Panel Data Methods has been updated and functionality has been expanded in this first official release of tspdlib 1.0. The tspdlib 1.0 package includes functions for time series unit root tests in the presence of structural breaks, time series and panel data unit root tests in the [...]
Introduction GAUSS packages provide access to powerful tools for performing data analysis. This guide covers all you need to know to get the most from GAUSS packages including: What is a GAUSS package Where to find GAUSS packages What is included in GAUSS packages How to use GAUSS packages What is a GAUSS package? A [...]
Introduction The latest Discrete Choice Analysis Tools 2.1.0 is now available for release. If you own Discrete Choice 2.0 the update is available for free. New features include tools for computing: Average marginal effects (AME) Marginal effects at the mean (MEM). Change Log Added ability to compute average marginal effects. Added error checking for variable [...]
Introduction The posterior probability distribution is the heart of Bayesian statistics and a fundamental tool for Bayesian parameter estimation. Naturally, how to infer and build these distributions is a widely examined topic, the scope of which cannot fit in one blog. We can, however, start to build a better understanding of sampling by examining three [...]
Introduction We use regression analysis to understand the relationships, patterns, and causalities in data. Often we are interested in understanding the impacts that changes in the dependent variables have on our outcome of interest. Marginal effects measure the impact that an instantaneous unit change in one variable has on the outcome variable while all other [...]
Introduction In this blog, we examine one of the fundamentals of panel data analysis, the one-way error component model. Today we will: Explain the theoretical one-way error component model. Consider fixed effects vs. random effects. Estimate models using an empirical example. The theoretical one-way error component model The one-way error-component model is a panel data [...]
Introduction When policy changes or treatments are imposed on people, it is common and reasonable to ask how those people have been impacted. This is a more difficult question than it seems at first glance. In order to truly know how those individuals have been impacted, we need to consider how those individuals would be [...]
Introduction GAUSS includes a plethora of tools for creating publication-quality graphics. Unfortunately, many people fail to use these tools to their full potential. Today we unlock five advanced GAUSS hacks for building beautiful graphics: Using HSL, HSLuv, and Colorbrewer color palettes. Controlling graph exports. Changing the plot canvas size. Annotating graphs with shapes, text boxes, [...]
Introduction In this blog, we extend last week's analysis of unit root testing with structural breaks to panel data. We will again use the quarterly current account to GDP ratio but focus on a panel of data from five countries: United States, United Kingdom, Australia, South Africa, and India. Using panel data unit roots tests [...]
Introduction In this blog, we examine the issue of identifying unit roots in the presence of structural breaks. We will use the quarterly US current account to GDP ratio to compare results from a number of unit root test found in the GAUSS tspdlib library including the: Zivot-Andrews (1992) unit root test with a single [...]
