Download groups - UW Faculty Web Server

GROUPS
1
China
Spain
Zambia
Brazil
Denmark
Amado-Cattaneo, Roberto III
Geddes, Christopher James
Lampel, Valerie Anne
Ross, Hunter Churchill
Triggs, Ronald Robert Jr
2
United States
Mexico
Netherlands
Pakistan
Cote d'Ivoire
Erickson, Stacey S
Jergens, Jeffrey Charles
Pedlar, Christopher William
Somphane, Oleg Chommavong
Spellman, Kaila R
3
India
Belgium
United Kingdom
Indonesia
Cameroon
Berg, Michela Lynn
Fong, Francis Man Ho
Larson, Kalene Rae
Nausner, Sara Theres
Oviir, Rainer
4
New Zealand
Sweden
Algeria
Malaysia
Honduras
Hwang, Alex Seon
Kiel, Yuri Jay
Lonkar, Ajey Rajeev
Mintken, Christopher Kwon
Shupe, Samuel Williams
5
Argentina
Switzerland
Australia
Sri Lanka
Bangladesh
Oh, Steve Jr
Qadri, Aisha Khan
Selim, Fady N
Teachout, Andrew Kuebler
Wong, Egbert Siu
6
France
Ireland
Korea, Rep.
Guatemala
Bolivia
Chiappini, Philip John
Chin, Andrea Cristin
Dane, Kurtis Peter
Johnson, Sean Erle
Porter, Kendra Miane
7
Dominican Republic
Norway
Nigeria
Philippines
Dykstra, Taitea Kathleen
Faburrieta, Veronica
Li, Alan Sun
Madison, Britta Lynn
Group Work October 19
1. Who’s here? ___________________________, ___________________________,
___________________________, ___________________________,
___________________________,
2. Get a spreadsheet from the Online WDI.
Go to the UW Library Catalogue, and ask for the title “World Development Indicators.”
Click World Development Indicators Online and Connect.
Each person in the group:
For years, pick all (1960-2005)
For country, pick your country
For series, use “tree view” and from People – Population and Demographics
pick
Birth rate, crude (per 1,000 people)
Death rate, crude (per 1,000 people)
Fertility rate, total (births per woman)
Life expectancy at birth, total (years)
Mortality rate, infant (per 1,000 live births)
Population ages 0-14 (% of total)
Population ages 15-64 (% of total)
Population ages 65 and above (% of total)
Population, female (% of total)
Population, total
and from Economy – National Accounts (US$) – Constant 2000 prices
pick
GDP (Constant 2000 US$)
That will be eleven series in all.
Then click “view results.” Take a look in the window to be sure you have something
reasonable-looking. Double-check the series to be sure you have the exactly right ones.
Go down to “Data Export Options” and select “Save Data as an Excel File.”
Then just click (you don’t have to right-click) on the link at the bottom and an Excel
spreadsheet should magically appear. You may want to make some adjustments in how
data appear at this point.
3. Calculate these things:
GDP/capita for all years (GDP divided by population)
growth rates for population, GDP, and GDP/capita, for 1961-2005
(current year – previous year) * 100 / previous year
4. Make some nice graphs
Arrange data to make seven graphs:
a. line graph:
Birth rate, crude (per 1,000 people)
Death rate, crude (per 1,000 people)
b. line
graph: Life expectancy at birth, total (years)
c. line graph: Mortality rate, infant (per 1,000 live births)
d. Area graph:
Population ages 0-14 (% of total)
Population ages 15-64 (% of total)
Population ages 65 and above (% of total)
e. line graph: GDP
f. line graph: population
g. line graph: population growth rate, GDP growth rate, GDP/capita growth rate
We will work through the boring technicalities of Excel graphs together. Help each other
with this.
5. Compare
How do your countries vary in terms of current values of the variables we picked out?
Countries
Most
recent
GDP/capita
Growth
rate
Most
recent
population
growth
rate
1961
population
growth
rate
1960
Crude
birth
rate
1960
crude
death
rate
Most
recent
population
growth
rate
Most
recent
Crude
birth
rate
Most
recent
crude
death
rate
What explanations can you suggest for this variation?
How do your countries vary in the ways these variables have changed over the last 45
years? Do you see any “demographic transitions”?
What explanations can you suggest for these differences?
Take notes! Look at other groups’ results too if you can. This will help you see what is
unusual or not unusual about your country, and that will help you write your assignment
for next Tuesday.
6. (Only if we have time)
If you were Jagdish Bhagwati, what lesson would you draw from this?
If you were Bob Sutcliffe, what lesson would you draw from this?
If you are neither Jagdish Bhagwati nor Bob Sutcliffe, what might you learn from their
differing views? What research questions might we ask
7. As your assignment for Tuesday:
Do a little reading about on your country. A simple encyclopedia article should be
plenty. Don’t exhaust yourself searching for stuff.
Write 500 words relating the data generated above to the facts that you can find out about
your country. You don’t have to explain everything, and if something you are seeing in
the data remains puzzling after your reading, you should say so and say why. It is
perfectly OK to say that you find things that don’t seem to fit!
(Do be ultra, ultra-careful to distinguish between your own words from words you
find on the web! There’s no harm in quoting what people say. Get used to quoting and
referencing others’ work while keeping it carefully distinguished from your own
writing. Ask me or a librarian if you have any questions.)
Refer to the Wikipedia Demography article and to material in the WDI if you need to find
definitions of concepts.
Aim to really write a story – what is the demographic story that the data tell us, and how
can that story be related to or explained by other facts you can find out about your
country, and/or what significant puzzles or gaps remain. If you find yourself with a lot of
scattered observations, go back and see if you can give them a little shape.
If you like, you can put your country into context by comparing it with others.
As part of your writeup, print out and use at least two of your graphs. You ca make more
graphs of your own if you don’t like the ones you made in class. You might try actually
embedding the graphs in your word-processing document, if that doesn’t make your
computer melt down. Part of the point of this is that I want you to get practice in using
and presenting data as part of a verbal discussion.