dataanalysiswithgapmider

[dataanalysiswithgapmider]

Initial Look At GAPMIDER DATA

The data I will be using is the Gapmider data, which is socio-economic data of the population of several countries though out different regions around the world.

The  topic of interests is understanding how geography plays a role in the similarities of countries in terms of the socio-economic status of the population.

In terms of variables, I will be looking at several variables that geography may play. These include: Polity Score, Relectric-per-person, Oil-per-person, Urban-rate, Internet-use, and HIV-rate,

I have chosen these variables because these variables have several aspects are related to geography to include: political, geographic, economic, and industrial development variables.

Some questions I would like to answer are:

Which variables s are affected the least and most by geography?

Do countries that share border share similar variables?  If so, which ones are the most and least variables shared?

               Given the above the variables, which population of countries enjoy the greatest quality of life?    

References:

               Chang, Bowon. (2010),”The power of geographical boundaries: Cultural, political, and economic border effects in a unitary nation.” URL:http://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=2328&context=etd.

Troudi, Hajaer ,(2016),” Assessment of access to electricity and the socio-economic impacts in rural areas of dev eloping countries. URL: http://www.academia.edu/8465293/Assessment_of_access_to_electricity_and _the_socio-economic_impacts_in_rural_areas_of_developing_countries.

Nela, Vlahinić-Dizdarević and Sasa Zikovic, (2011), “OIL CONSUMPTION AND ECONOMIC GROWTH INTERDEPENDENCE IN Small European Countries” URL: http://hrcak.srce.hr/index.php?show=clanak&id_clanak_jezik=115183&lang=en

 Drissa Sia, S Jody Heymann,and Arijit Nandi, (2014), “Socioeconomic inequalities in HIV/AIDS prevalence in sub-Saharan African countries: evidence from the Demographic Health Surveys,” URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3930550/

Parkhurst , Justin. (2009) “Understanding the correlations between wealth, poverty and human immunodeficiency virus infection in African country”. URL: http://www.who.int/bulletin/volumes/88/7/09-070185/en/

Search Terms:

Urban

Border

Electric rate

Oil consumption

Socio-economic

HIV rate

GDP

 My hypothesis is that countries that share  similar geographic locations share ’ socio-economic status of with the population, and has an effect on the every-day quality -of- life for the population

An initial review of the literature and data indicates the countries are in the same regions likely do have similarities of the variables, but can differ in other aspects. For example, when looking at two neighboring Middle Eastern countries, Oman and the UAE do have commonalities in terms of Polity-Score (both -8) and  Urban-rate ( UAE is 77.8 and Oman is 71.62) but are not similar in term of electric rate  per person ( UAE is 11,155 and Oman is 2,125). Another example is the bordering African countries of Kenya and Uganda have similar HIV-rate 6.5 and 6.3, but have far different Polity-score, with Kenya have a score of  7 and Uganda having a score of -1.