Methodology of Econometrics

1. 1
Assignment 1:
By: Pawan Kawan
What is econometrics? What are the methodologies of Econometrics?
Answer:
Econometrics is the measurement of economic relationship. It is derived from two words of
Latin origin, ‘economia’ means economy and ‘measure’ means measurements. It is a special
type of economic theories formulated in mathematical forms and combined with empirical
measurement of economic phenomenon. Econometrics is the application of mathematics,
statistical methods, and, more recently, computer science, to economic data and is described
as the branch of economics that aims to give empirical content to economic relations. More
precisely, it is "the quantitative analysis of actual economic phenomena based on the
concurrent development of theory and observation, related by appropriate methods of
inference." An introductory economics textbook describes econometrics as allowing
economists "to sift through mountains of data to extract simple relationships. The name
Econometrics was first introduced by Norwegian Economist and Statistician Ragnar Frisch in
1962.
Econometrics may be defined as the social science in which the tools of economic theory,
mathematics, and statistical inference are applied to the analysis of economic phenomena. It
is used to estimate the numerical value of the parameters of the economic relationship and
verifying economic theories. In short:
Economics + Mathematics = Mathematical Economics
Mathematical Economics + Statistics = Econometrics
Econometrics is the unification of economics, mathematics, and statistics. This unification
produces more than the sum of its parts. Econometrics adds empirical content to economic
theory allowing theories to be tested and used for forecasting and policy evaluation.
The Economist's Dictionary of Economics defines Econometrics as "The setting up of
mathematical models describing mathematical models describing economic relationships
(such as that the quantity demanded of a good is dependent positively on income and
negatively on price), testing the validity of such hypotheses and estimating the parameters in
order to obtain a measure of the strengths of the influences of the different independent
variables."
Thus, Econometrics is a branch of economics or an application of statistical techniques &
economic model to get numerical results or to verify economic theorems. The main concept
behind econometrics is usually as a set of statistical tools which allows economists to test and
verify hypotheses using real world data.
Therefore, Econometrics takes economic models and tests them through statistical trials. The
results are then compared and contrasted against real-life examples.

2. 2
Methodology of econometrics:
Broadly speaking, econometric methodology proceeds along the following lines:
1. Statement of theory or hypothesis
In the first step the economic theory or hypothesis should be stated in a precise way.
For example, Keynes stated: “Consumption increases as income increases, but not as
much as the increase in income.” It means that “The marginal propensity to consume
(MPC) for a unit change in income is greater than zero but less than unit.”
2. Specification of the mathematical model of the theory
In the second step we specify models and theoretical prediction in a mathematical
language.
Where,
Y= consumption expenditure
X= income
β1 and β2 are parameters.
β1 =intercepts
β2 = slope coefficients
3. Specification of the econometric model of the theory
In the next step, we can combine economic theory, mathematical model and statistical
data to estimate the consumption function in the econometric model as,
Y= β1 + β2X + U; 0< β2<1;
Where,
Y = Consumption expenditure
X = Income
U = Stochastic or random variable
4. Obtaining Data
To estimate the econometric model, we need the statistical data related to the model.
In our example, above we need the data of consumption expenditure and gross
domestic product. For example,
Y = Personal Consumption expenditure
X = Gross Domestic Product all in Millions Rupees
β1 and β2 are parameters; β1 is intercept and β2 is slope coefficients; U is distance term
or error term. It is a random or stochastic variable. Let the following table shows the
income and expenditure from 1990 to 2011.
Year X Y
1990 2447.1 3776.3
1991 2476.9 3843.1
1992 2503.7 3760.3

3. 3
1993 2619.4 3906.6
1994 2746.1 4148.5
1995 2865.8 4279.8
1996 2969.1 4404.5
1997 3052.2 4539.9
1998 3162.4 4718.6
1999 3223.3 4838.0
2000 3260.4 4877.5
2001 3240.8 4821.0
5. Estimating the Econometric Model
The next step is to estimate the model from the data using suitable estimators. There
are various methods of estimation for the model. The following is the estimated
regression line using ordinary least square method.
Ŷ = -231.8+ 0.7194X
Here, MPC is about 0.72 and it means that for the sample period when real income
increases 1 Rupee then it leads to real consumption expenditure increases of about 72
paisa.
6. Hypothesis Testing
Are the estimates accords with the expectations of the theory that is being tested? Is
MPC<1 statistically? If so, it may support Keynes theory. Confirmation or refutation
of economic theories based on sample evidence is object of Statistical Inference
(hypothesis testing).
7. Forecasting or Prediction
With given future values of X, what is the future value of Y. GDP = Rs. 6000 million
in 2004, what is the forecast consumption expenditure? Ŷ = -231.8+ 0.7194 (6000) =
4084.6. Income Multiplier M = 1/(1-MPC) = 3.57. Therefore, decrease (increase) of
Re 1 in investment will eventually leads to Rs. 3.57 decrease (increase) in income.
8. Using model for control or policy purposes
The final step is related to the policy measure and controlled measures. For example,
if , Y = 4000 = -231.8+ 0.7194X and X= 5882, MPC = 0.72, an income of Rs. 5882
Bill will produce an expenditure of Rs. 4000 Bill. By fiscal and monetary policy,
Government can manipulate the control variable X to get the desired level of target
variable Y.

4. 4
The methodology of Econometric analysis can be summarized as below:
Figure: Anatomy of Econometric Methodology
Functions of Econometrics
and
Format of Regression Analysis
FUNCTIONS OF ECONOMETRICS
Econometrics has basically three closely interrelated functions. The first is to test
economic theories or hypotheses. For example, is consumption directly related to income? Is
the quantity demanded of a commodity inversely related to its price? The second function of
econometrics is to provide numerical estimates of the coefficients of economic relationships.
These are essential in decision making. For instance, a government policy maker needs to
have an accurate estimate of the coefficient of the relationship between consumption and
income in order to determine the stimulating ( ie the multiplier) effect of a proposed tax
reduction. A manager needs to know if a price reduction increases or reduces the total sales
Econometric Theory
Estimation
Mathematic Model Econometric Model Data Collection
Hypothesis Testing
Forecasting
Application
in Control or
Policy Studies

5. 5
revenues of the firm and by how much. The third function of econometrics is the forecasting
of economic events. This, too, is necessary in order for policy makers to take appropriate
corrective action if the rate of unemployment or inflation is predicted to rise in the future.
FORMAT OF REGRESSION ANALYSIS
It is identified with regression analysis, according to which a dependent variable is
related to one or more independent (ie. explanatory) variables. But since the relationships
amongst the economic variables are inexact, a disturbance or error term must be included.
Thus, econometrics can deduct or predict a wide variety of relationships among variables in
models like a production function or a consumption function model etc.
Regression analysis studies the causal relationship between one economics variable to be
explained (the dependent variable) and one or more independent or explanatory variables.
When there is only one independent or explanatory variable, we have simple regression. In
the more usual case of more than one independent or explanatory variable, we have multiple
regression.
A (random) disturbance error must be included in the exact relationship postulated by
economic theory and mathematical economics in order to make them stochastic (i.e. in order
to reflect the fact that in the year world, economic relationships among economic variables
are inexact and somewhat erratic).