Homework 2
Economics 2000
Assigned Thursday, October 6th, 2011
Due: Friday, October 14th, 2011
1. Health Care Costs. Find the advanced countries with the most expensive health care.
Go to World Bank’s Databank Link Choose International Comparison Program
(2005). Under the Country menu select i. Western European countries (France,
Germany, Italy and Spain); ii. Scandinavian countries (Denmark, Sweden, Finland,
Norway) and iii. advanced Asian economies (Hong Kong, Japan, Korea, and
Singapore); and iv. the United States. You should have 13 countries total selected. Hit
.
1106 Health. Hit
.
Exchange rate (LCU per US$, period average), and PPP (LCU per international $).
Hit
.
2005 and hit
. From
Shift Classification and Time to Page and Series to Column
Choose
and
to export to Excel.
a. Calculate the cost of health care relative to the United States as the PPP divided by
the exchange rate for each economy. Calculate the average cost of health care in each
group i.-iv. (i.e. i. Western European countries; ii. Scandinavian countries and iii.
advanced Asian economies; and iv. USA). Which group has the most expensive
health care?
i.
ii.
iii.
iv.
Western Europe
Scandanavian
East Asian
USA
Price
0.736451
0.967358
0.412317
1
On average, US health care is most expensive, though the Scandanavian average cost is
nearly as high (and somewhat higher).
b. Explain why expensive health care might be bad for typical health levels. Can you
think of any reason why costly health care might indicate a good environment for
health?
Naturally, if it is costly to purchase health care, then people will be squeezed out of the
market and might be less likely to purchase health care. This could be damaging for their
health. Expensive health care, on the other hand, might represent higher costs due to high
quality.
c. Compare health expenditures with health outcomes. Choose
World Development Indicators & Global Development Finance. From
and
choose the thirteen countries in groups i.-iv. Hit
. Under
choose
and select A. Life expectancy at birth, total (years)
and B. Mortality Rate, Infant (per 1,000 life births) . From
choose C. Immunization, DPT (% of children, 12-23 months).
Hit
.
2005 and hit
. From
Shift Time to Page and Series to Column
Choose
and
to export to Excel.
Calculate the average level in each group i.-iv of each of the three indicators of health
A.-C.
i.
ii.
iii.
iv.
Life
Mortality
Immunization
Expecancy
rate
DPT
at Birth
infant
%of children
Western Europe
79.94939024
4.025
95.5
Scandanavian
79.31219512
3.275
94.75
East Asian
80.48213415
3.2
96.66667
USA
77.33902439
6.8
96
d. Compare the different country groups according to cost of health care and health
performance. Is any group doing exceptionally well or exceptionally poorly in terms
of health indicators? How does this compare with health care costs in those regions.
Clearly, Asian health outcomes are highest in all categories with a life expectancy of
3 full years above the US and less than half of infant mortality. East Asia also has the
highest immunization rate. US health outcomes are the worst perhaps because of
having the most expensive healthcare.
2. Soccer Salaries. You find a newspaper article from 2010 containing information on
the five highest paid soccer players (at the time). All five played in Spain or Italy and
were paid in Euros
Team
€ Millions Home Country
1 Cristiano Ronaldo Spain (Real Madrid)
13.17 Portugal
2 Zlatan IbrahimovicSpain (Barcelona)
12.12 Bosnia & Herzogovenia
3 Lionel Messi
Spain (Barcelona)
10.60 Argentina
4 Samuel Eto'o
Italy (Jnternazionale Milano)
10.60 Cameroon
5 Kaka
Spain (Real Madrid)
10.14 Brazil
Assume that the players return to their hone countries to spend their money. Rank
the players according to purchasing power. Convert their salary using exchange rate
data from World Bank World Development Indicators: 1) Go to the Databank; 2)
Select the appropriate 5 countries; 3) Go to Series and select
and select DEC alternative conversion factor (LCU per
US$); From
and
PPP conversion factor GDP (LCU per International $). Choose
and
.
a. Use the DEC alternative conversion factor (LCU per US$) as a measure of the
exchange rate with the US$ and convert the salaries of the soccer players into
their home currency (Hint: the home currency of Portugal is the Euro).
1 Cristiano Ronaldo
2 Zlatan Ibrahimovic
3 Lionel Messi
4 Samuel Eto'o
5 Kaka
€ Millions Home Country
Xrate
Xrate Converted
13.17 Portugal
0.755
13.16672
12.12 Bosnia & Herzogovenia
1.477
23.70642
10.60 Argentina
3.912689
54.95015
10.60 Cameroon
495.277
6955.713
10.14 Brazil
1.760133
23.6329
b. Use the PPP conversion factors to convert this sum in LCU (local currency units)
into a measure of purchasing power (denominated in international $).
1 Cristiano Ronaldo
2 Zlatan Ibrahimovic
3 Lionel Messi
4 Samuel Eto'o
5 Kaka
Xrate
Home Country
Converted PPP
PPP Converted
Portugal
13.16672 0.633975
20.76851
Bosnia & Herzogovenia 23.70642 0.758078
31.27176
Argentina
54.95015 2.246234
24.46324
Cameroon
6955.713 249.9464
27.82882
Brazil
23.6329 1.694172
13.94953
3. World Income Distribution. Measure changes in Global Income Distribution by
calculating a GINI coefficient for the world economy. Go to World Bank World
Development Indicators and hit
and then
. Choose
. From
and
and
GDP per capita, PPP (constant 2005
international $) and GDP, PPP (constant 2005 international $). Hit
.
2010 and hit
to Page and Series to Column
. From
Shift Time
Sort the data according to GDP, PPP (constant 2005 international $) from largest to
smallest (the Sort tool can be found in Excel under Data) in descending order.
Eliminate all economies with no data. Examine the top Q=150 countries in terms of
size. Re-sort the data according to GDP per capita, PPP (constant 2005 international
$), this time in ascending order from poorest to richest. Treat the average person in
each country as a single person. Calculate the AVERAGE of GDP per Capita across
countries. Calculate the LEVEL as AVERAGE×Q. Index the countries q=1,…,150
where q=1 is the poorest country Congo, Dem. Rep. and q =150 is the richest country
GDP per Capitaq
Luxembourg. For country q, calculate their share as shareq 
.
LEVEL
Starting at q = 1, calculate the Lorenz curve as the cumulative distribution LCq =
LCq-1 + shareq. In this case, share1 = 0.000178, share2 = 0.000209, and share3
=0.000214, so LC1 = 0.000178, LC2 = LC1+ share2 = 0.000386, and LC3 = LC2 +
share3 =0.000601 and so on till LC150 = 1. In this case, the area under the world’s
Lorenz curve consists of 150 trapezoids of equal width. Calculate the area of the
LCq  LCq 1 1
trapezoid for country q as
 . Add the sum of the trapezoids and
2
Q
calculate the GINI coefficient for the world economy.
For 2010
Sum of Trapezoid Area
GINI
INDEX
0.225899
0.548202
54.82023
a. Compare the inequality across countries with the inequality within Sweden, Brazil,
and China in 2010.
From the class notes, we see that the World Income distribution is comparable to the
income distribution within Brazil, one of the most notoriously inequal economies.
Country Name
Brazil
China
Sweden
GINI
56.4
41.5
25
b. Repeat the process using data for 1990 instead of 2010. Has world income inequality
changed over time?
For 1990
Sum of Trapezoid Area
GINI
INDEX
0.223981
0.552038
55.20383
We see that since 1990, the GINI coefficient for World Income Distribution has barely
budged. The world is almost as unequal today as it was in 1990.
c. This measure of world income inequality treats the world as if it were made of 150
people each representing a single country. But we know that some very large
countries including China and India amongst others have grown very quickly. Discuss
how the knowledge of this fact might change how we think about the dynamics of
global income inequality?
Two relatively poor countries, China and India, have grown very quickly in the last
twenty years substantially increasing income levels in those regions and bringing the
income levels of these countries closer to the relatively rich countries. These two
countries are only two out of 150, however, and so there success does not have a big
impact on GINI coefficient when we treat countries as equally sized. However, since these
countries are so large, their success has actually narrowed world income distributions.
This can be seen (as in the tutorial) when we calculate a World GINI weighted by
population.