Discuss briefly its assumptions and the consequences for the ols in case of their violation

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

1. Explain what is meant by an error term. What assumptions do we make about the error term when estimating an ordinary least squares (OLS) regression. 

 2.  Give at least three examples from economics where you expect some nonlinearity in the relationship between variables. Interpret the slope in each case.

 3.  How is the slope coefficient interpreted in a log-linear model, where the dependent variable is (i) in logarithms but the independent variable is not (i.e. a log-linear model), (ii) in a linear-log model and (iii) in a log-log model? 

4.  Formulate the Gauss-Markov theorem. Discuss briefly its assumptions and the consequences for the OLS in case of their violation. Illustrate your answers with examples and graphs when appropriate. 

 5.  Explain the concept of non-stationarity of time series. Give examples of economic time series which are (1) stationary and (2) non-stationary. How does the autocorrelation function (ACF) help in detecting non-stationarity? 

 6. Carefully discuss the advantages of using heteroskedasticity-robust standard errors over standard errors calculated under the assumption of homoskedasticity. Give at least two examples where it is very plausible to assume that the errors display heteroskedasticity. 

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