This content provides information about the Methodology of Econometrics / Hypothesis Testing

1. Methodology of Econometrics /
Hypothesis Testing

2.  Hypothesis is a statement or assumption that is yet to
be proved.
Simple Hypothesis:
When a hypothesis specifies all the parameters of a
probability distribution , it is known as simple
hypothesis.
Composite Hypothesis:
When a hypothesis specifies only some of the
parameters of a probability distribution , it is known as
Composite Hypothesis.

3.  Null Hypothesis-Ho :
For applying the test of significance we
first set up a hypothesis-a definite statement
about the population parameters.Such a
hypothesis which is usually a hypothesis of
no-difference is called null hypothesis and it is
denoted by Ho
Example:
Ho- There is no significant difference between the
two sample means (ie)µ1=µ2.

4.  Alternate Hypothesis-H1:
Any hypothesis which is complementary to the null
hypothesis is called an alternative hypothesis , usually
denoted by H1.
Example:
There is a significance difference between two
sample means.
Symbolically,
H1: μ1≠μ2 (two sided or directionless alternative)
If the statement is that A gives significantly less than B
(or) A gives significantly more
yield than B. Symbolically,
H1: μ1 < μ2 (one sided alternative-left tailed)
H1: μ1 > μ2 (one sided alternative-right tailed)

5.  This is where the algebra enters. We need to use
mathematical skills to produce an equation. Assume a
theory predicting that more schooling increases the
wage. In economic terms, we say that the return to
schooling is positive. The equation is:
 Y=β1+β2X

6.  Here, we assume that the mathematical model is correct
but we need to account for the fact that it may not be
so. We add an error term, u to the equation above. It is
also called a random (stochastic) variable. The
econometric equation is:
Y=β1+β2X+u

7.  Data can be collected by using sampling methods or
experiments.
Data
 The information collected through censuses and
surveys or in a routine manner or other sources is called
a raw data.
There are two types of data
 1. Primary data
 2. Secondary data.

8. Once the hypothesis is formulated we
have to make a decision on it. A statistical
procedure by which we decide to accept or
reject a statistical hypothesis is called testing
of hypothesis.

9.  Here, we quantify β1 and β2
i.e. we obtain numerical estimates. This is done by
statistical technique called regression analysis.
Example:
Y=12.50+0.6X+u

10.  If the hypothesis testing was positive, i.e. the theory was
concluded to be correct, we forecast the values of the
wage by predicting the values of education.
Example:
Y=12.50+0.6X
X=10 means then Y=18.50 it is Forecasting
Y=20 means then X=14.1 it is Prediction

11.  Lastly, if the theory seems to make sense and the
econometric model was not refuted on the basis of the
hypothesis test, we can go on to use the theory for
policy recommendation
Example:
Using the model for agricultural Polices.

12. ANY QUESTIONS?