The LR model is based on certain assumptions, some of which refers to the distribution of the random variable (error term : e) and finally some refer to the relationship between e and the explanatory variables. We will group them in two categories (i) STOCHASTIC Assumptions (ii) Other assumptions.

• Stochastic Assumptions:
  • ei is a random real variable.
  • The mean value of “e” in any PARTICULAR period is zero.
  • The variance of ei is CONSTANT in each period ( This is sometimes referred as assumption on “Homoscedastic” Variance).
  • The variable ei has a normal distribution.
  • The random terms of different observations (ei, ej) are statistically independent (no auto-correlation among error terms).
  • “e” is independent of the explanatory variable(s) (X).
  • The explanatory variables are measured WITHOUT error.
  • The Xi’s are set of fixed values in the hypothetical process of repeated sampling which underlies the LR model.
• Other Assumptions:
  • The explanatory variables are not perfectly linearly correlated.
  • The macro variables should be correctly aggregated.
  • The relationship being estimated is identified.
  • The relationship is correctly specified.

(Please refer to the Book – “The theory of econometrics – 2nd Edition by A. Koutsoyiannis”)