ASSESSMENT-2 Global managerial economics Analysing demand and estimating the demand function 10% weighting 1000-words This case study is designed to assess students’ understanding of demand theory...

ASSESSMENT-2 Global managerial economics

Analysing demand and estimating the demand function

10% weighting

1000-words

This case study is designed to assess students’ understanding of demand theory and application of the Excel functionalities. It is to introduce the steps and quantitative methods and tools to estimate demand function which the primary objective of a microeconomic analysis. It will involve the estimation of demand using graphical methodology and OLS regression methodology using real data. It will be introduced that how estimated regression model will be used for forecasting future demand for the subject product.

The Excel spreadsheet, Demand Model.xlsx, includes quarterly data from Jan 2010 to March 2021 of unleaded petrol prices, quantity demanded and other variables which are considered as the determinant of demand.

Tasks

1. Identify the main determinant of demand for unleaded petrol. Write the functions of demand in the following form and explain the economically interpretable relationships.

Q _d = f(X₁, X₂, X₃, X₄ )

Analyze why and in which way the demand is affected by the determinants of demand for the unleaded petrol.

2. Using graphical method estimate (drive) the demand curve by plotting the price (P) and quantity demanded (Q _d ) using XY chart. Comment on the relationship between P and Q^D. If there are any discrepancies Contrary to the law of demand, provide an appropriate explanation.

3. Apply Regression analysis. To complete the modelling of the demand function, you hypothesize that the quarterly quantity demanded of unleaded petrol Q^D is function of its retail price (P), population (POP), Income (GDP) and Consumer Price index (CPI) representing prices of related goods.

For this task you are required to utilise multiple regression analysis is to be conducted using quarterly time series data for the period from 2010 to 2021. The model has he following form:

Q_d = b₀ + b₁ P + b₂ GDP + b₃ POP + b₄ CPI + e_i

Where:

bs: are the intercept and estimated coefficients with the regression procedure

e_{i :} is the error term

Questions

1. Using economic theory, what are the hypothesised signs of the parameters, (b₀ , b₁, b₂, b_{3 ,} b₄)
2. Estimate the regression equation using excel and write the estimated equation.
3. Interpret the estimated b coefficients for independent variables.
4. Compare your hypothesized signs (question 1) with your estimated sign. If there are any discrepancies, provide an appropriate explanation.
5. Using the results from the regression analysis, are your estimated parameters statistically significant? Write null and alternative hypothesis and apply t test procedure to justify the significance of the β coefficients and explain.
6. Write null and alternative hypothesis to apply F test procedure to test the validity of the model you estimated and explain

^7. Interpret the estimated adj R²

4. Developing a numerical example explain how estimated regression model can be used to forecast the demand for the next quarter.

5. Conclusion

Provide a brief summary of the procedures you applied, problems, limitations and other issues of estimating demand.