Once downloaded project file, you will need to transfer the data into Excel (copy and paste itin rather than re-type so as to avoid mistakes) and use the commands and functions in Excel to undertakethe statistical analysis.Follow the instructions in your project document, providing full and clear answers. Interpret your answersfully, by providing complete statistical and economic interpretations.Writing up the Project ReportProject should be written up in a report style, with an introduction summarising the research questions,data and methods used. It should conclude by highlighting key results, drawing conclusions and, whereappropriate, policy implications.Further:? Use numbered headings and sub-headings.? Number all tables and graphs, and refer to them in the text, with a brief discussion of each.

project_1.doc

marking_scheme.pdf

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L1022: Assessed Coursework Project

Project 1

The Relationship between Infant Mortality, Income and Public Expenditures in

Sri Lanka 1951 to 1981

Infant mortality rates have fallen sharply in most countries, rich and poor, over the

second half of the twentieth century. Different hypotheses have been proposed to

explain this unprecedented trend over the broad sweep of history. Income per capita

increased steadily in large parts of the world during this period. Also expenditure on

healthcare and education is now significantly higher than in the 1950s. The objective

of this project is to establish whether GDP, health and educational expenditures per

capita are determinants of the infant mortality rate in one particular country: Sri

Lanka.

The data below contains information on the infant mortality rate (IMR), real Gross

Domestic Product per capita in rupees (GDPPC), as well as educational and health

expenditures per capita in rupees (EDUCPC and HEXPPC) for Sri Lanka, covering

the period 1951 to 1981.

1. Describe the data, using summary statistics and graphs, as appropriate.

2. Calculate the pair-wise correlation coefficients between IMR and each of the other

variables. Test the statistical significance of each correlation coefficient.

3. Estimate a regression model of the form:

IMRt =a + ß1GDPPCt + ß2HEXPPCt +ut

where the t subscript corresponds to year t, Interpret the coefficients that you

obtain, and comment on their economic and statistical significance..

4. Interpret the R2 statistic from the regression and test whether it is statistically

significant.

5. Predict the IMR for Sri Lanka at a GDP per capita level of 750 rupees, assuming

HEXPPC is at its mean value.

6. Re-estimate the model including the EDUCPC variable and comment on any

changes to the results and goodness of fit:

IMRt =a + ß1GDPPCt + ß2HEXPPCt + ß3EDUCPCt +ut

Explain how the omission of EDUCPC in part 3 may have biased the results.

(Note: it is sufficient to discuss the changes, without explicitly showing the testing

procedure).

7. What conclusions do you draw from your analysis?

1

Copy and paste the data into Excel and conduct all the analysis in Excel.

Year

1951

1952

1953

1954

1955

1956

1957

1958

1959

1960

1961

1962

1963

1964

1965

1966

1967

1968

1969

1970

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

IMR GDPPC HEXPPC EDUCPC

82

617.59

8.8

14.6

78

629.63

10.51

16.47

71

619.4

10.78

16.96

72

623.65

10.84

15.96

71

648.85

10.67

15.51

67

634.94

11.4

17.84

68

622.72

11.87

19.88

64

619.15

12.9

22.09

58

617.71

14.72

24.84

57

641.41

14.28

24.14

52

646.34

15.86

29.64

53

649.81

14.56

30.31

56

655.75

14.77

31.44

55

697.83

13.82

32.27

53

694.04

13.98

33.38

54

688.95

14.45

32.49

48

705.56

14.38

30.53

50

744.75

14.74

30.13

53

767.87

15.99

32.26

47

786.16

16.1

35.53

45

780.63

16.16

32.42

46

786.43

15.62

33.67

46

802.6

13.8

31.03

51

825.15

11.63

24.44

45

883.11

12.63

25.89

44

842.48

14.28

28.66

42

860.07

13.45

25.17

37

924.96

15.42

25.25

38

956.14

16.54

29.78

34

997.82

15.84

32.29

29.5

1034.6

14.08

30.93

where:

Year

IMR

GDPPC

EDUCPC

HEXPPC

= the year of observation;

= Infant Mortality Rate per 1000 live births

= Real GDP per capita in rupees

= Real Educational Expenditures per capita in rupees

= Real Health Expenditures per capita in rupees

2

Marking Scheme for L1022 Project

Each project document contains instructions on what to do with the data. You need to ensure

you follow those instructions. Once you have copied and pasted the data into Excel, perform

the analysis as stated in each question in your project document.

The suggested general format for writing up the project and marks available for each section

is as follows:

1. Select a project and indicate its title. Begin with a short introduction summarising

your project. Define your variables, and identify the questions you will address using

the provided data. [10%]

2. Descriptive statistics: calculate descriptive statistics and summarise the key features

of the data using suitable graphs. Provide a written interpretation. [15%]

3. Correlations: find the correlation coefficients between pairs of variables and test their

statistical significance. [10%]

4. Regression model: estimate the regression model in the project sheet and display the

results in a table. Comment on the economic and statistical significance of the

estimated coefficients. [20%]

5. Interpret the R2 and test the overall goodness of fit of the model. [10%]

6. Prediction: show your workings and interpret your predictions. [10%]

7. Re-define the model as required in the project sheet and estimate it. Comment on any

changes to the results and goodness of fit. Note: it is sufficient to discuss the changes,

without explicitly showing the testing procedure. [15%]

8. Conclusions. What are the overall findings of the project? [10%]

Remember that top marks will only be awarded to clearly presented, accurate and well

written answers. For example: tables presented without supporting explaining explanation

will not score high marks.

…

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