Author: eclower

Unit Root Tests with Structural Breaks

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 [...]

The Basics of Quantile Regression

Introduction Classical linear regression estimates the mean response of the dependent variable dependent on the independent variables. There are many cases, such as skewed data, multimodal data, or data with outliers, when the behavior at the conditional mean fails to fully capture the patterns in the data. In these cases, quantile regression provides a useful [...]

Top five hotkeys to get more done in GAUSS

Introduction The GAUSS interface includes a number of often overlooked hotkeys and shortcuts. These features can help make programming more efficient and navigation seamless. In this blog I highlight my top five GAUSS hotkeys: Quickly view data symbols using Ctrl+E. Open floating command reference pages using Shift+F1. Toggle block comments on and off using Ctrl+/. [...]

Apples to Apples: The case for cluster-robust standard errors

Introduction Linear regression commonly assumes that the error terms of a model are independently and identically distributed (i.i.d). However, when datasets contain groups, the potential for correlated error terms within groups arises. Example: Weather shocks to apple orchards For example, consider a model of the supply of apples from various orchards across the United States. [...]

A Simple Test for Structural Breaks in Variance

Introduction Though many standard econometric models assume that variance is constant, structural breaks in variance are well-documented, particularly in economic and finance data. If these changes are not accurately accounted for, they can hinder forecast inference measures, such as forecast variances and intervals. In this blog, we consider a tool that can be used to [...]

Reading dates and times in GAUSS

Introduction Time series data with inconsistently formatted dates and times can make your work frustrating. Dates and times are often stored as strings or text data and converting to a consistent, numeric format might seem like a daunting task. Fortunately, GAUSS includes an easy tool for loading and converting dates and times – the date [...]

The Effects of Structural Breaks on GMM models

Introduction While structural breaks are a widely examined topic in pure time series, their impacts on panel data models have garnished less attention. However, in their forthcoming paper Chowdhury and Russell (2018) demonstrate that structural breaks can cause bias in the instrumental variable panel estimation framework. This work highlights that structural breaks shouldn't be limited [...]
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