National open university of nigeria introduction to econometrics I eco 355

1.0
 
INTRODUCTION 
The basic tool for econometrics is the linear regression model. In modern econometrics, 
other statistical tools are frequently used, but linear regression is still the most frequently 
used starting point for an analysis.
Estimating a linear regression on two variables can be 
visualized as fitting a line through data points representing paired values of the 
independent and dependent variables. 
Okun's law representing the relationship between GDP growth and the unemployment 
rate. The fitted line is found using regression analysis. For example, consider Okun's law, 
which relates GDP growth to the unemployment rate. This relationship is represented in a 
linear regression where the change in unemployment rate (
) is a 
function of an intercept (
), a given value of GDP growth multiplied by a slope 
coefficient 
and an error term, : 
The unknown parameters 
and 
can be estimated. Here 
is estimated to be −1.77 
and 
is estimated to be 0.83. This means that if GDP growth increased by one 
percentage point, the unemployment rate would be predicted to drop by 1.77 points. The 
model could then be tested for statistical significance as to whether an increase in growth 
is associated with a decrease in the unemployment, as hypothesized. If the estimate of 
were not significantly different from 0, the test would fail to find evidence that changes in 
the growth rate and unemployment rate were related. The variance in a prediction of the 

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dependent variable (unemployment) as a function of the independent variable (GDP 
growth) is given in polynomial least squares. 
2.0. OBJECTIVES 
At the end of this unit, you should be able to: 
1. To understand the basic Econometrics models 
2. To be able to differentiate between Econometrics theory and methods