Economic Measurement
Econometrics
Application of the mathematical statistics to economic data in order to lend empirical support to the economic mathematical models and obtain numerical results (GerhardTintner, 1968)
Econometrics
: The quantitative analysis of actual economic phenomena based on concurrent development of theory and observation, related by appropriate methods of inference (P.A.Samuelson, T.C.Koopmans and J.R.N.Stone, 1954)
Econometrics
The social science which applies economics, mathematics and statistical inference to the analysis of economic phenomena (ByArthur S.Goldberger, 1964)
Econometrics
The empirical determination of economic laws (By H.Theil, 1971)
Econometrics
makes statements that are mostly qualitative in nature, while econometrics gives empirical content to most economic theory.
Economic theory
is to express economic theory in mathematical form without empirical verification of the theory, while econometrics is mainly interested in the in the empirical verification of economic theory.
Mathematical economics
is mainly concerned with collecting, processing and presenting economic data. It does not being concerned with using the collected data to test economic theories.
Economic Statistics
provides many of tools for economic studies, but econometrics supplies the later with many special methods of quantitative analysis based on economic data.
Mathematical statistics
Methodology of Econometrics
- Statement of theory or hypothesis:
- Specification of the mathematical model of the theory.
- Specification of the econometric model of the theory.
- Obtaining Data
- Estimating the Econometric Model.
- Hypothesis Testing
- Forecasting or Prediction
- Using model for control or policy purposes
Methodology of Econometrics
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”
- Statement of theory or hypothesis:
Methodology of Econometrics
- Y = ß1+ ß2X ; 0 < ß2< 1
- Y= consumption expenditure
- X= income
ß1 andß2 are parameters;
ß1 is intercept, and
ß2 is slope coefficients.
- Specification of the mathematical model of the theory.
Methodology of Econometrics
- Y = ß1+ ß2X + u ; 0 < ß2< 1;
- Y = consumption expenditure;
- X = income;
ß1 and ß2 are parameters;
ß1 is intercept and
ß2 is slope coefficients;
u is disturbance term or error term. It is a random or stochastic variable.
- Specification of the econometric model of the theory.
Methodology of Econometrics
- Y= Personal consumption expenditure
- X= Gross Domestic Product all in Billion US Dollars
- Obtaining Data
Methodology of Econometrics
- Y^ = - 231.8 + 0.7194 X (1.3.3)
- MPC was about 0.72 and it means that for the sample period when real income increases 1 USD, led (on average) real consumption expenditure increases of about 72 cents.
Note: A hat symbol (^) above one variable will signify an estimator of the relevant population value.
- Estimating the Econometric Model.
Methodology of Econometrics
- Are the estimates accord with the expectations of the theory that is being tested? Is MPC < 1 statistically? If so,it may support Keynes’ theory.
- Hypothesis Testing
Methodology of Econometrics
- Confirmation or refutation of economic theories based on sample evidence is object of Statistical Inference (hypothesis testing)
- Hypothesis Testing
Methodology of Econometrics
- With given future value(s) of X, what is the future value(s) of Y?
- GDP=$6000Bill in 1994, what is the forecast consumption expenditure?
- Y^= - 231.8+0.7196(6000) = 4084.6
Y^= -231.8 + 0.7196(3000) =-231.8 + 2158.8 = 1927
- Forecasting or Prediction
Methodology of Econometrics
- Y=4000= -231.8+0.7194 X X 5882
- MPC = 0.72, an income of $5882 Bill will produce an expenditure of $4000
- Bill. By fiscal and monetary policy, Government can manipulate the control
variable X to get the desired level of target variable Y.
- Using model for control or policy purposes
ß1 and ß2 are ______
ß1 is _______
ß2 is _________
u is ______________. It is a random or stochastic variable.
ß1 and ß2 are parameters;
ß1 is intercept and
ß2 is slope coefficients;
u is disturbance term or error term. It is a random or stochastic variable.
u
random or stochastic variable.
