## What is breusch and Pagan Lagrangian multiplier test?

Dennis Cook and Sanford Weisberg in 1983 (Cook–Weisberg test). Derived from the Lagrange multiplier test principle, it tests whether the variance of the errors from a regression is dependent on the values of the independent variables. In that case, heteroskedasticity is present.

**What is the null hypothesis of LM test?**

The null hypothesis is that there is no serial correlation of any order up to p. Because the test is based on the idea of Lagrange multiplier testing, it is sometimes referred to as an LM test for serial correlation. A similar assessment can be also carried out with the Durbin–Watson test and the Ljung–Box test.

### How do you choose between fixed and random effects?

The most important practical difference between the two is this: Random effects are estimated with partial pooling, while fixed effects are not. Partial pooling means that, if you have few data points in a group, the group’s effect estimate will be based partially on the more abundant data from other groups.

**What does breusch Pagan test do?**

What is the Breusch-Pagan Test? The Breusch-Pagan test is used to determine whether or not heteroscedasticity is present in a regression model. The test uses the following null and alternative hypotheses: Null Hypothesis (H0): Homoscedasticity is present (the residuals are distributed with equal variance)

## What will you conclude about a regression model if the breusch Pagan test results in a large P-value?

If the Breusch-Pagan Test for heteroskedasticity results in a large p-value, the null hypothesis of heteroskedasticty is rejected.

**What would you conclude about a regression model if the breusch Pagan test results in a small p-value?**

8. What will you conclude about a regression model if the Breusch-Pagan test results in a small p-value? a. The model contains homoskedasticty.

### What does the breusch Pagan test tell us?

Breusch Pagan Test It is used to test for heteroskedasticity in a linear regression model and assumes that the error terms are normally distributed. It tests whether the variance of the errors from a regression is dependent on the values of the independent variables. It is a χ2 test.

**What does serially correlated mean?**

Serial correlation is the relationship between a given variable and a lagged version of itself over various time intervals. It measures the relationship between a variable’s current value given its past values. A variable that is serially correlated indicates that it may not be random.

## What is the difference between the breusch Godfrey test and the Durbin Watson test?

Whereas the Durbin-Watson Test is restricted to detecting first-order autoregression, the Breusch-Godfrey (BG) Test can detect autocorrelation up to any predesignated order p. It also supports a broader class of regressors (e.g. models of the form yi = axi + byi-1 + c).

**Should I use RE or FE?**

The decision to choose between RE and FE models depends upon the statistical significance of the standard deviation of this random coefficient. If this standard deviation is statistically different from zero, RE is the preferred model structure, otherwise FE is the preferred model.

### What is Hausman test used for?

Hausman. The test evaluates the consistency of an estimator when compared to an alternative, less efficient estimator which is already known to be consistent. It helps one evaluate if a statistical model corresponds to the data.

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