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ECS 4863-ECONOMETRICS ASSIGNMENTS .

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ECS 4863-ECONOMETRICS ASSIGNMENTS . Question 1 1.1 Define Econometrics Econometrics is the analysis of economic phenomena using economic theory, mathematics and statistics. Econometric models are built using mathematical economics to obtain numerical results. 1.2 Explain how econometricians us...

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  • August 23, 2022
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  • 2022/2023
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Question 1


1.1 Define Econometrics
Econometrics is the analysis of economic phenomena using economic theory, mathematics and
statistics. Econometric models are built using mathematical economics to obtain numerical
results.


1.2 Explain how econometricians usually analyse a problem
- Statement of theory hypothesis: according to Keynes, marginal propensity to consume (MPC),
the rate of change of consumption for a unit change in income, is greater than 0 but less than
1.
- Specification of mathematical model of consumption: Keynes did not specify the precise form
of the functional relationship between consumption and income. So for simplicity a
mathematical economist may suggest the following Keynesian function:
Y = β1 + β2X + u 0 < β2 < 1
- Specification of the Econometric model of consumption: The purely mathematical model of
the consumption function is of limited interests to econometricians as it assumes an exact
relationship between consumption and income. To allow for inexact relationship between the
variables ab econometrician can modify the function to:
Y = β1 + β2X + u
- Obtaining Data: Data is needed to obtain numeric al values.
- Estimation of Econometric Model: Once data is obtained it is followed by estimating
parameters of the consumption function.
- Hypothesis Testing: Finding a suitable criteria to test if the estimates obtained are in line with
the expectations.
- Forecasting or Prediction
If the model chosen does not refute the hypothesis, it may be used for prediction of future
values of the dependent.
- Use Model for Control or Policy Purpose


1.3 Explain the meaning of the following terms
- (i) Total, explained and residual sums of squares tell us how much of the initial variation
in the sample were explained by the regression.
- (ii) Degrees of freedom is the number of values in a final calculation which are free to vary
without violating any constraints imposed on it.
- (iii) Simple correlation coefficient measured the degree of (linear) association (and not
causation) between the dependent variable Y and the single explanatory variable X.


1.4 Explain the properties of OLS Estimator
- It is a linear function of a random variable namely, the dependant variable Y in the
regression model.

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