An examination of the Breitung Test, used for testing unit roots or stationarity in panel data sets. The Breitung Test assumes a balanced panel with the null hypothesis of a unit root.
A comprehensive overview of the disturbance term, its significance in statistical and econometric models, historical context, types, key applications, examples, related terms, and more.
An in-depth look at Durbin's Test for identifying first-order serial correlation in errors with a lagged dependent variable.
Endogeneity is the condition where an explanatory variable in a regression model correlates with the error term, leading to biased and inconsistent estimates.
A comprehensive examination of exogenous variables, their significance in econometrics, examples, types, applications, and the importance in economic modeling.
An in-depth look at the Feasible Generalized Least Squares Estimator (FGLS) in econometrics, its historical context, key concepts, mathematical formulations, and practical applications.
A detailed examination of the Glejser Test, a statistical method to detect heteroscedasticity by regressing the absolute values of residuals on independent variables.
The Goldfeld–Quandt Test is a statistical method used to detect heteroscedasticity in regression models by dividing the data into two subgroups and comparing the variances of the residuals.
Heteroscedasticity occurs when the variance of the random error is different for different observations, often impacting the efficiency and validity of statistical models. Learn about its types, tests, implications, and solutions.
An in-depth look at Instrumental Variables, their usage, importance, mathematical formulations, applications, and examples in various fields.
An in-depth look into Instrumental Variables (IV) and their role in addressing endogeneity in statistical models.
The J-TEST is used in the context of the Generalized Method of Moments (GMM) to test the validity of overidentifying restrictions. It assesses if the instrumental variables are correctly specified and consistent with the model.
Exploring the multiple definitions and applications of the kernel in mathematics, econometrics, and game theory.
Nested models in econometrics are models where one can be derived from another by imposing restrictions on the parameters. This article explains nested models, providing historical context, key concepts, mathematical formulation, and more.
An in-depth look into the Probit Model, a discrete choice model used in statistics and econometrics, its historical context, key applications, and its importance in predictive modeling.
An in-depth look at the Random Effects model in panel data regression, explaining its significance, key concepts, applications, and related terms.
A comprehensive overview of the Ramsey Regression Equation Specification Error Test (RESET), including historical context, methodology, examples, and applications in econometrics.
Two-Stage Least Squares (2SLS) is an instrumental variable estimation method used in econometrics to address endogeneity issues. It involves two stages of regression to obtain consistent parameter estimates.
The Wald Test is a statistical method used to test restrictions on unknown parameters in a model using the maximum likelihood estimation.
White's Test is used to test the null hypothesis of homoscedasticity against the alternative of heteroscedasticity in a regression model.
Serial correlation, also known as autocorrelation, occurs in regression analysis involving time series data when successive values of the random error term are not independent.
Comprehensive guide on Multicollinearity covering its definition, types, causes, effects, identification methods, examples, and frequently asked questions. Understand how Multicollinearity impacts multiple regression models and how to address it.
