(a)State in algebraic notation and explain the assumption about the classical linear regression models disturbances that are referred to by the term ‘homoscedasticity’. (b) What would the consequence be for a regression model if the errors were not homoscedastic? (c) How might you proceed if you found that (b) were actually the case? (d) What do you understand by the term ‘autocorrelation’? (e) An econometrician suspects that the residuals of her model might be autocorrelated. Explain the steps involved in testing this theory using the Durbin–Watson (DW) test. (f) The econometrician follows your guidance in part (b) and calculates a value for the Durbin– Watson statistic of 0.95. The regression has 60 quarterly observations and three explanatory variables (plus a constant term). Perform the test. What is your conclusion?
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
(a)State in algebraic notation and explain the assumption about the classical linear regression
models disturbances that are referred to by the term ‘homoscedasticity’.
(b) What would the consequence be for a regression model if the errors were not homoscedastic?
(c) How might you proceed if you found that (b) were actually the case?
(d) What do you understand by the term ‘autocorrelation’?
(e) An econometrician suspects that the residuals of her model might be autocorrelated. Explain
the steps involved in testing this theory using the Durbin–Watson (DW) test.
(f) The econometrician follows your guidance in part (b) and calculates a value for the Durbin–
Watson statistic of 0.95. The regression has 60 quarterly observations and three explanatory
variables (plus a constant term). Perform the test. What is your conclusion?
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