1. Interpreting the Regression Line The slope coefficient gives the marginal effect on the endogenous variable of an increase in the exogenous variable. The interpretation of the slope coefficient depends on the units of measurement. In this case both series are measured in £ million at constant prices. The slope coefficient tells us that an increase in GDP of £1m leads to an increase in investment of £180K.

2. Log-linear equations The slope coefficient of a log-linear regression gives us the elasticity of y with respect to x. This equation tells us that a 1% increase in GDP will result in a rise of about 1.35% in investment spending. Note:

3. Interpreting the regression line The intercept is chosen so that the regression line passes through the sample means of the data

4. It does not make much sense to think of the intercept as the value of y when x is zero. Although this is mathematically true, the zero value of x often lies well outside the range of the data.

5. Levels or Differences? Economic variables often contain a trend. Differencing will remove the trend from the data.

6. Regression in differences Regressions in levels may give an unrealistic impression of the explanatory power of equations when the data is trended. An alternative is to estimate in first differences

7. An equation estimated in the first differences of the logarithms of the variables constitutes a relationship in growth rates.