Goldfeld Quandt Test for Heteroscedasticity
The Goldfeld Quandt Test is used to detect the presence of heteroscedasticity in a regression model. This test was introduced by economists Arthur Goldfeld and Richard Quandt in the 1960s.…
The Goldfeld Quandt Test is used to detect the presence of heteroscedasticity in a regression model. This test was introduced by economists Arthur Goldfeld and Richard Quandt in the 1960s.…
The Breusch Pagan test for heteroscedasticity is sometimes also referred to as the BPG or Breusch Pagan Godfrey test. It is one of the most widely known tests for detecting…
The White test is one of the most commonly used statistical methods of detecting heteroscedasticity. It focuses on analysing the residuals from regression models to check for heteroscedasticity. Furthermore, the…
Heteroscedasticity is a situation where the variance of residuals is non-constant. Hence, it violates one of the assumptions of Ordinary Least Squares (OLS) which states that the residuals are homoscedastic…
The subject matter of Economics is broadly divided into two sub-fields: microeconomics and macroeconomics. Every topic, theory or application in Economics can be broadly classified into these two branches. Although…
Cointegration refers to the situation where the variables have a long-run or equilibrium relationship. Such variables move together over time and can be said to have a similar wavelength or…
If a non-stationary time series has to be differenced “d” times to make it stationary, that time series is integrated of order "d". In other words, the order of integration…
The Dickey Fuller Test is a unit root based test of stationarity. The unit root based tests focus on the coefficient associated with the first lag of the time series…
The ACF or Autocorrelation Function is one of the most widely used methods to check for stationarity of a time series. Moreover, it also gives valuable insights into the autoregressive…
The Random Walk Model is an example of a non-stationary time series. This model is often used to discuss as well as illustrate the concepts of stationarity, unit root process…
A time series is said to be stationary if its characteristics do not change with time. Moreover, a stationary time series can be identified as strictly stationary or weak stationary.…
The Three-Stage Least Squares or 3SLS is applied to simultaneous equation models. It is different from single equation methods like Indirect Least Squares (ILS) and 2SLS because it is applied…
The Indirect Least Squares (ILS) is a method used to estimate simultaneous equation models that are exactly identified. Moreover, it is a single equation method because it is applied to…
A simultaneous equation model is said to be identified if we can obtain unique estimates of the coefficients in the model. The equations in identified models have a unique structure…
The OLS and other single equation models assume that variables treated as independent variables are exogenous. This implies a one-way relationship between independent and dependent variables. It is assumed that…