Working Partners: Agistrioti Iris, Feiran Yang
The purpose of this post is to introduce some examples of “Demographic Data Analysis”, show how analysis should be done involving specific mathematical models to use as tools, and further on perform accurate interpretation of the analysis as depicted in graphs and pyramids. In this post I will demonstrate real examples (using the World Population Data Sheet 2010) on which I will apply the methods and principles of appropriate demographic data analysis as well as convey, as effectively as possible, a compelling picture of the population pyramids.
In my effort to accurately depict all of the terms we covered in class, I will also always bear in mind information and details mentioned in our textbook. I will try to cover as many countries’ densities as possible and from a greatest possible variety of regions. My aim is to underline the differences within countries and regions in terms of demographic data and distribution. As mentioned in our textbook, “Within continents, human populations attain their highest densities in eastern, southeastern, and southern Asia” (Molles, 257) and for that reason I have included (in cooperation with my partner), China as a country of demographic interest within my analysis.
Further on, are stated: my demographic analysis and the results found during class with my partner in a question-answer format:
Use the World Population Data Sheet for 2010 to answer the following questions:
- 1. China and India have the largest populations in the world. Which of these two countries adds more people to its population annually? [Calculate the numbers added by applying the rate of natural increase to the population of each country. Hint: the rate is a percent]
|Country||Number of people added annually|
These results were calculated by initially finding the rate of natural increase of each selected country and then multiply it by the population number of each country respectively.
- 2. What proportion of the world’s people live in the following continents/regions and what are the projected proportions by 2025 and 2050?
|Continent||% living today||% by 2025||% by 2050|
The results were found by initially finding the world’s total population. After that, we found separately the populations of each region and compared them (division: /) to the world’s total population. This calculation resulted to 5 different percent rates (for year:2010, today) which we repeated two times more for the years 2025 and 2050 to find the estimated population increase of each region in the future.
Use the data above and Excel to construct a bar chart showing the regional distributions of the world’s population for the current year, 2025, and 2050. Save your graph.
To perform this step, we transferred all our data (final table with resulting numbers) in an Excel sheet. With the help of the appropriate tools of Excel we managed to construct the necessary bar-chart of the world’s population distribution.
The World’s population is going to be decreased. 2050’s population is going to be smaller it is in 2025, and the population in 2025 is going to be smaller than it is today.
- What proportion of the world’s people live in less developed countries (LDCs) and in more developed countries (MDCs) today? What proportion is projected to live in LDCs and MDCs in 2025 and in 2050?
|Countries||% of world’s population today||% of world’s population in 2025||% of world’s population in 2050|
Again by using the World’s total population (found for question 1), we found the total population living in less developed countries and compared that to the world’s total population number. The result was the percent proportion of total world’s population living in less developed countries. The remaining percentage represented the proportion of total world’s population living in the more developed countries. The same whole procedure was repeated for the years 2025 and 2050.
Discuss with your partner a) the economic and b) the social implications of the changing proportions of the world’s people in LDCs and MDCs. Record your observations.
Having taken into account our results calculated for the % proportions of people living in more or less developed countries, my partner and I concluded to some interesting observations: The proportion of people living in the less developed countries is seemingly going to increase from today until the year 2050, whereas the proportion of people living in the more developed countries is estimated to decrease from today until 2050. This observation could possibly be translated into a possible future forecast of a global economic depreciation. The social implication of this could take the dimensions of possible migration (of people living in more developed countries to move to less developed ones).
- 4. Examine the crude birth rate, crude death rate, and rate of natural increase of any three countries (one being your own country) listed on the World Population Data Sheet.
|Country||Crude birth rate (%)||Crude death rate (%)||Rate of natural increase (%)|
The resulting numbers placed in the table above were found in the world’s population data sheet. In particular, the crude birth and death rates were initially in the form of number per 1000 people so these numbers had to be divided by 1000 to find the actual rate percentage.
Discuss with your group partner the mathematical relationship among these three rates. Record your observations.
The mathematical relationship among the three rates is the following:
The rate of natural increase is the difference between Crude birth rate and Crude death rate (CBR-CDR).
5. Select 2 LDCs and 2 MDCs from the data sheet and compute the age-dependency ratios for each.
After having selected 4 different countries (Niger, Guinea, Canada & Germany), we used the formula of the age-dependency ratio as was given:
|% of population under age 15 + % of 65 and over||X 100|
|% of population ages 15-64|
[Hint: The three percents will equal 100%. ]
Discuss with your partner the implications of your observations:
- o What factors do you think contribute to a high age-dependency ratio?
The age-dependency is “dependent” on how well the country is developed. Usually (and as follows from the results calculated in the table of question 5) the less developed the countries, the more people they have in the ages: under 15 or over 64. In contrast, the more developed the countries, the more people they have between the ages: 15 and 64.
- o What are some economic and social consequences of a high age-dependency ratio?
Usually, a high age-dependency ratio represents a low economically productive country. That is because a high age-dependency ratio implies that there are more people under the age of 15 and over the age of 64, both, groups of people that are non-productive and usually non-economically active to contribute in their country’s economical standards. Also, in terms of social consequences, countries of a high age-dependency ratio will require a society of a very well care-system (health care, and social security) for those people who are in the dependent ages.
Interpreting Age-Sex Graphs
In this activity you will construct population pyramids for specific countries and speculate on differences in the quality of life in these countries.
2. 1. From the following table select one country from each column (two countries) from for your case.
|Column A||Column B|
From the first column we selected FRANCE and from the second column we selected EGYPT.
2. 2. Open the U.S. Census Bureau “International Database,” available at http://www.census.gov/ipc/www/idb/ . Select “Data Access”. Select the assigned country (see Table 1 above) from the country list and hit “Submit”. In the new page select “Tables”. In the new page select “Excel” (see somewhere in the middle of your screen where it says: “Download all Tables as Excel”). From the Excel file record the following data for the country you selected.
- Table 1. Demographic indicators for France
|Demographic Indicators for France||2010|
|Midyear population (in thousands)||64768|
|Growth rate (percent)||0,5|
|Total fertility rate (births per woman)||2|
|Crude birth rate (per 1,000 population)||12|
|Births (in thousands)||805|
|Life expectancy at birth (years)||81|
|Infant mortality rate (per 1,000 births)||3|
|Under 5 mortality rate (per 1,000 births)||4|
|Crude death rate (per 1,000 population)||9|
|Deaths (in thousands)||560|
|Net migration rate (per 1,000 population)||1|
|Net number of migrants (in thousands)||95|
Table 2. Demographic indicators for Egypt
|Demographic Indicators for Egypt||2010|
|Midyear population (in thousands)||80472|
|Growth rate (percent)||2|
|Total fertility rate (births per woman)||3|
|Crude birth rate (per 1,000 population)||25|
|Births (in thousands)||2013|
|Life expectancy at birth (years)||72|
|Infant mortality rate (per 1,000 births)||26|
|Under 5 mortality rate (per 1,000 births)||32|
|Crude death rate (per 1,000 population)||5|
|Deaths (in thousands)||390|
|Net migration rate (per 1,000 population)||-0|
|Net number of migrants (in thousands)||-17|
Population Pyramid of France
Population Pyramid of Egypt
Compare the demographic indicators from the two countries. What generalizations can be made concerning demographic indicators and level of development? [for example, if the birth rate is high, then the level of development is…]. Form at least two generalizations that are supported by the pyramids and data charts.
After having recorded the tables and population pyramids for our two selected countries we found that the data in the tables as well as the population “movement” as demonstrated in the pyramids show interesting differences between the two countries.
One observation we made from the tables and population pyramids was the following:
The lower the birth-rate of a country, the greater is the chance of this country to be a developed one. Specifically, and according to the tables and graphs, Egypt has a very high birthrate (more than twice the birth rate of France) but France is certainly a much more developed country than what Egypt is.
Another observation from the demographic data tables is:
The more developed a country is, the higher its life expectancy. In particular, Egypt’s life expectancy is 72 (birth-years) whereas the life expectancy of France reaches the age of 81 (almost 10 years more than that of Egypt). This observation is somehow expected since more developed countries have also more developed technologies and medicines to sustain a higher life-expectancy than that of less developed countries. However, this is not always and everywhere the case. There are tribes that live with absolutely no technologies (almost zero development) but sustain a very high life expectancy (see “The Baka Pygmies” post in my blog).
Molles Jr., Manuel C. Ecology: Concepts and Applications, Fifth Edition. New York: McGraw-Hill, 2010.
World Population Data Sheet 2010. Population Reference Bureau. USAID. July 2010
Dr. Grekinis. “Class Activity: Demographic Data and Graphs”. Course Notes. Ecological Principles. Moodle Course home pahe. Dept. of Business Administration, American College of Thessaloniki. 27 November 2010.
U.S. Consensus Bureau. “International Database”. 27 November 2010. http://www.census.gov/ipc/www/idb/