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World Population, Demographic Transition Model, Primate Cities

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World Population, Demographic Transition Model, Primate Cities 11/1/2016 World Population, Demographic Transition Model, Primate Cities http://navigator‐ iup.passhe.edu/login?url=http://digital.films.com/ PortalPlaylists.aspx?aid=1972&xtid=34174 Thomas Malthus (Malthusian Theory) • Famously predicted that the population of the Earth would steeply rise after the industrial revolution • Authored , An Essay on the Principle of Population • Several editions from 1798 – 1826 • Theory states that Population grows geometrically (1, 2, 4, 8…) while food supply grows arithmetically (1 ,2 ,3, 4 ,5…) • Suggested that as population grew faster than food supply, ‘checks’ on population must occur • War, disease, famine • Said the fertility of the poor put pressure on industrial capitalism • Anti‐Capitalist critics argued it was not the poor who were pressuring production, it was the increased rate of production that was pressuring the poor! 1 11/1/2016 World Population Distribution Stats: • Uneven population distribution uneven population density • World is increasingly urbanizing • 50% of the world’s population lives in cities • Europe and South America are two of the most urbanized regions with close to 80% urbanized • 90% of all people live north of the Equator • 60% live between 20° and 60° North (Temperate Climate) • 50% of the world’s population live on just 5% of its land area • Almost 90% of the population live on less than 20% of its land area • People favor lowland areas over high altitude areas • 80% live below 500 meters above sea level • Coastal areas have the densest settlement • 60% of the world’s population lives within 100 km of the ocean Population Distribution of Latin America 2 11/1/2016 Rural‐to‐Urban Migration in Latin America Demographic Transition Model (DTM) • A general rule‐of‐thumb that identifies periods of development with population characteristics • The DTM is based on variations in • Crude birthrates –the annual number of live births per 1000 population • Crude death rates –the annual number of deaths per 1000 population • Five Phases identified: • Phase 1 –High births, high deaths • Phase 2 –High births, declining deaths • Phase 3 – Declining births, Low deaths • Phase 4 –Low births and low deaths • Phase 5 –Deaths higher than births 3 11/1/2016 Characteristics of DTM Phases: • Phase 1 – High births, high deaths No Latin American country is in this phase today –all have • Pre‐industrial economy passed through this phase • Phase 2 – High Births – Declining Deaths • Developing Country • Improving food and water supply Many Latin American countries • Improving Sanitation currently in this phase, including; • Bolivia • Improvements in farming technology • Peru • Improvements in education • Paraguay • Results in a large population increase • Guatemala 4 11/1/2016 Characteristics of DTM Phases: • Phase 3 – • Phase 4 – Declining Births –Low Deaths Low births and low deaths • Contraception • Stabilization of population • Wage increases • Idealized end point • Urbanization Uruguay, Cuba in this phase, • Reduction of subsistence agriculture Chile and Argentina approaching • Increase in status and education of women • • Reduced child labor Phase 5 – Deaths higher than births • Increase in parental investment in children • Shrinking population • Population growth begins to level • Threat to Industrial Societies off • Norm in post‐ Industrial/deindustrialized Brazil and Mexico in this phase societies • Mitigated through immigration No Latin American country in this phase Phase 3 Line Graph 5 11/1/2016 Phase 4 Line Graph Phase 1 –High births, high deaths Phase 2 –High births, declining deaths Phase 3 – Declining births, Low deaths Phase 4 –Low births and low deaths Phase 5 –Deaths higher than births Mexico is emerging out of Phase 2 and into Phase 3 6 11/1/2016 Population Pyramids ‐ Mexico Notice top age is 80+ years Population Pyramids All of Latin America Mexico Notice top age is 75+ years Notice top age is 100+ years 7 11/1/2016 Population Density • Population Density –is the number of people living per geographic unit (i.e., per square mile or per square kilometer) Examples: “Urbanized Areas” of the USA http://en.wikipedia.org “Urban Areas” For the 2010 census, the Census Bureau redefined the classification of urban areas to "a densely settled core of census tracts and/or census blocks that meet minimum population density requirements, along with adjacent territory containing non‐residential urban land uses as well as territory with low population density included to link outlying densely settled territory with the densely settled core. To qualify as an urban area, the territory identified according to criteria must encompass at least 2,500 people, at least 1,500 of which reside outside institutional group quarters." Urban Areas of the United States of America[1] Population Land Area Land Area Density Density Rank Name[Note 1] (2010 Census) (km²) (sq mi) (Population / km²) (Population / sq mi) 1 New York‐‐Newark, NY—NJ—CT 18,351,295 8,936.0 3,450.2 2,053.6 5,318.9 Los Angeles‐‐Long Beach‐‐ 2 12,150,996 4,496.3 1,736.0 2,702.5 6,999.3 Anaheim, CA 3 Chicago, IL—IN 8,608,208 6,326.7 2,442.8 1,360.6 3,524.0 4 Miami, FL 5,502,379 3,208.0 1,238.6 1,715.2 4,442.4 5 Philadelphia, PA—NJ—DE—MD 5,441,567 5,131.7 1,981.4 1,060.4 2,746.4 6 Dallas‐‐Fort Worth‐‐Arlington, TX 5,121,892 4,607.9 1,779.1 1,111.5 2,878.9 7 Houston, TX 4,944,332 4,299.4 1,660.0 1,150.0 2,978.5 8 Washington, DC—VA—MD 4,586,770 3,423.3 1,321.7 1,339.9 3,470.3 9 Atlanta, GA 4,515,419 6,851.4 2,645.4 659.0 1,706.9 10 Boston, MA—NH—RI 4,181,019 4,852.2 1,873.5 861.7 2,231.7 11 Detroit, MI 3,734,090 3,463.2 1,337.2 1,078.2 2,792.5 12 Phoenix‐‐Mesa, AZ 3,629,114 2,969.6 1,146.6 1,222.1 3,165.2 13 San Francisco‐‐Oakland, CA 3,281,212 1,356.2 523.6 2,419.5 6,266.4 14 Seattle, WA 3,059,393 2,616.7 1,010.3 1,169.2 3,028.2 15 San Diego, CA 2,956,746 1,896.9 732.4 1,558.7 4,037.0 16 Minneapolis‐‐St. Paul, MN—WI 2,650,890 2,646.5 1,021.8 1,001.7 2,594.3 17 Tampa‐‐St. Petersburg, FL 2,441,770 2,478.6 957.0 985.1 2,551.5 18 Denver‐‐Aurora, CO 2,374,203 1,730.0 668.0 1,372.4 3,554.4 19 Baltimore, MD 2,203,663 1,857.1 717.0 1,186.6 3,073.3 20 St. Louis, MO—IL 2,150,706 2,392.2 923.6 899.0 2,328.5 27 Pittsburgh, PA 1,733,853 2,344.4 905.2 739.6 1,915.5 8 11/1/2016 http://www.newgeography.com • The least dense urban areas with more than 2.5 million population are all in the United States. • The least dense is Atlanta, with 1800 people per square mile or 700 per square kilometer. • The second least dense is, perhaps surprisingly, Boston, despite its reputation for high density. • Boston's population density is 2200 per square mile or 800 per square kilometer. • Also, perhaps surprisingly, Philadelphia is the least dense urban area in the world with more than 5 million population, while Chicago is the least dense urban area of more than 7.5 million. http://www.newgeography.com 9 11/1/2016 Global Population Densities populationlabs.com http://www. Primate City (a result of rapid urbanization) Some Primate Cities of Latin America • A primate city is the major city of a include: country, serving as the financial, political, and population center Central America: and is not rivaled in by any other •Mexico City, Mexico city in that country •Guatemala City, Guatemala •Havana, Cuba •Managua, Nicaragua • In general, a primate city must be •Panama City, Panama at least twice as populous as the •Port‐au‐Prince, Haiti •San José, Costa Rica second largest city in the country •San Salvador, El Salvador •Santo Domingo, Dominican Republic • The presence of a primate city in a South America: country usually indicates an •Buenos Aires, Argentina imbalance in development •Caracas, Venezuela • An expanding core •Lima, Peru • A stagnant periphery •Montevideo, Uruguay •Santiago, Chile 10 11/1/2016 GINI Coefficients • The GINI Coefficient is a useful metric for understanding the state of cities (or countries) with regard to distribution of income or consumption • It is the most widely used measure to determine the extent to which the distribution of income (or consumption) among individuals (or households) deviates from a ‘perfectly equal distribution’ • Equal Distribution (of income) meaning every individual has an equal amount of income • Not going to happen, correct? But it does give us an indicator as to how the income in a place is distributed throughout the population –and that is useful! • The data used here is supplied by the United Nations and is collected from national surveys and censuses (which will each have a different level of accuracy) • Most GINI coefficients are usually compiled for a region or country • GINI coefficients for cities are a relatively new way using data to look a the income distribution of cities GINI Coefficients • The GINI coefficient is derived from a statistical formula and expresses the degree of evenness or unevenness of any set of numbers as a number between 0 and 1 • based on the Lorenz curve which plots the proportion of the total income of the population (y axis) that is cumulatively earned by the bottom x% of the population • A Gini Coefficient of 0 would indicate equal income for all earners • A Gini Coefficient of 1 would mean that one person had all the income and nobody else had any • So… lower Gini Coefficients indicate more equitable distribution of wealth in a society, while higher Gini Coefficients mean that wealth is concentrated in the hands of fewer people • Sometimes the Gini Coefficient is multiplied by 100 and expressed as a percentage between 0 and 100.
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