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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.