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Development Economics HW # 1

Due back: October 14th 2022

NOTE: Please submit on Blackboard before the beginning of the online seminar (1230)

Q1) Find the following figures for 2015 for the UK (hint: for this exercise, you will need to access the World Development Indicators database published by the World Bank: go to http://data.worldbank.org/ and click on “databank” and then “World Development Indicators”) (10 points):

a) Gross Domestic Product (in current local currency units)

b) Gross Domestic Product (in current US$)

c) Gross Domestic Product, Purchasing Power Parity (in current international $)

d) Gross Domestic Product, Purchasing Power Parity (in constant 2017 international $)

e) Gross Domestic Product per capita, Purchasing Power Parity (in constant 2017 international $)

f) Explain the difference between each of the above measures. Why are the numbers different if each is measuring the same thing?

Q2) Find the following figures for 2015 for South Africa (10 points):

a) Gross Domestic Product (in current local currency units)

b) Gross Domestic Product (in current US$)

c) Gross Domestic Product, Purchasing Power Parity (in current international $)

d) Gross Domestic Product, Purchasing Power Parity (in constant 2017 international $)

e) Gross Domestic Product per capita, Purchasing Power Parity (in constant 2017 international $)

f) Comparing the figures obtained in Q1 and Q2, which country has higher output overall? Which measure would you recommend experts use to determine this, and why?

Q3) Please generate a line graph plotting life expectancy at birth for males and females separately over time (for the 2001 to 2019 time period) for the following countries: (Afghanistan; Brazil; Cameroon; Denmark; Estonia; Finland; Ghana; Honduras; India; Japan). You may use graphs by country, or by gender, but make sure to label the graphs appropriately. Please make sure to label the axes and that the reader can distinguish the data. Which country has shown the highest improvement on each metric? Which country has come closest to reducing gender disparity? (10 points).

Q4) Use the World Bank dataset to download life expectancy by gender for all countries for 2010, and plot a graph with female life expectancy on the Y axis, and male life expectancy on the X axis. Comment on any patterns that you observe. (10 points)

Q5) One measure of inequality within countries is the GINI index. The World Bank’s World Development Indicators dataset provides an estimate of this at certain points in time. Please generate a graph of all countries with average income on the X-axis (you may use whichever income metric you like, but justify your choice) between the years 2010 and 2015, and the GINI coefficient on the Y-axis using the data from the latest year the data is available (post 2000). Comment on any patterns that you see, and report the number of countries you used in the analysis (hint, the GINI coefficient will be unavailable for many countries during this time period, so just drop those countries). (10 points)

Q6) Generate a graph focusing on (1) the relationship between the proportion of individuals employed in agriculture and income; (2) the relationship between the proportion of individuals employed in industry and income; and (3) the relationship between the proportion of individuals employed in services and income. Do you find evidence to support the claim that economic growth entails moving from primary, to secondary, to tertiary goods? Explain. (10 points)

Q7) “Education and income are positively correlated.” Use data from the World Bank databank (http://data.worldbank.org/) for all countries to test this idea. Download 2 indicators: Net primary school enrolment, and Gross National Income per capita, Purchasing Power Parity (in constant international $). (Note: don’t worry about the countries that do not have both sets of data). Use a scatterplot to display the relationship, with enrolment on the Y- axis. Report the correlation coefficient, and explain what this says about the statement. (10 points)

Q8) Marks will be based on the presentations in seminars in weeks 2 and 3 (30 points).