Homework 5: Visualising Country Data
Country Data
This Markdown exists so that we can take a look at some data associated with the nations of the world.
I am, and always have been, fascinated with political science, macro-socio-economic trends, and what pokes and prods humans into doing what they do.
It is my hope that this product will shed some insight into those behaviors which are successful and unsuccessful on a macro-scale.
But first, a little setup.
Obviously, we need data to work with. Fortunately, some hurried googling pointed me to kaggle, where I got this. Download the .csv to your working directory THEN import it using the following url:
# Download your file from the interwebs
download.file(
"https://www.dropbox.com/s/2z5ihlbqbgjldo5/countries%20of%20the%20world.csv?dl=1",
destfile = "Country_Data.csv",
mode = "wb"
)
# Isn't that URL ugly?
# Let's import that stuff so we can work with it.
Country_Data<-read.csv("Country_Data.csv")We also need some libraries to make this all work.
library(ggplot2)
library(tidyverse)## -- Attaching packages ------------------------------------------------------------------------------------------------------------------------------------------ tidyverse 1.2.1 --## v tibble 1.4.2 v purrr 0.2.5
## v tidyr 0.8.1 v dplyr 0.7.6
## v readr 1.1.1 v stringr 1.3.1
## v tibble 1.4.2 v forcats 0.3.0## -- Conflicts --------------------------------------------------------------------------------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(corrplot)## corrplot 0.84 loaded# This is just book-keeping, but its a good foundation with which to build any R product. Finally, some data.
Transitioning Economies
The great economic transitions for humanity have been huge leaps in potential. From Hunter-Gatherers to settled farmers, early humans no longer worried (as much) about where their next meal would come from. Much later we transitioned into increasing levels of industrialization until, in the modern era many humans now no longer even worry about where their STUFF comes from!
As post-industrial nations no longer need concern themselves with interior productive capacity and the power of international trade is leveraged, people can transition into a Service or Intellectual based economy, where the power of one’s thought and intellectual output is the predictor of one’s economic success.
Working hard is no longer enough in the post-industrial world, one must also work smart. This metric is illustrated in the below plot, which shows the Per-Capita-GDP and a positive association with the adoption of robust Service Sectors in their economies.
Technology a Predictor?
Not Always…
So, we’ve established that increases in Service Sector Adoption seem to produce a 1:1 increase to GDP per capita. Excellent. Service Sectors almost universally rely on a high standard of technology, so it stands to reason that increased technological adoption rates would also have a direct relationship with increased GDP, right?
Well, not exactly. In regions which would be called “Developing” that is still very much the case. Macroecon shows us that initially, investments in Capital (technology) pay huge dividends in GDP, but as Capital Utilization increases you reach a point of diminishing returns.
Look at Asia versus Western Europe, for example. Europe has been at the forefront of Industrialization and has always had high techology adoption rates, therefore investements into technology will have less positive impact on GDP there than they will in Developing Economies (like in Asia) where we’re seeing economies rapidly playing catch up.
A word of warning to these economies, however, year-over-year double digit GPD Growth is simply unsustainable, as you get closer and closer to that techological adoption tipping point…as China is currently discovering.
Away from your phone for a second…
One of the worst events in someone’s life is to have thier young family snuffed out before it even begins. Unfortunately, despite the excellent access to care we enjoy in the Western World, there are huge swaths of this planet with either incomplete, inadequate, or simply innaccuarate information and facilities to help support a clean, safe, birthing enviornment.
Fortunately, there are great strides being made across the planet to educate people. Literacy is not directly related to materinity in any direct manner. However, increased investment into efforts to educate the populace - generally - frequently start at the first step - reading.
Access to reading, and later, access to the internet provides a population with a nearly limitless library of the sum total of human knowledge. Additionally, increases in education almost always pay direct dividends in the medical field. My data set doesn’t include incidences of disease, or efforts to combat them (vaccination data, for example). But it does have Infant Mortalitiy statistics.
This is an incredibly heartening statistic.
Coastlines and You
Maritime Trade, the key to prosperity in the post-industrial world.
This correlogram (say that five times, fast!) was intended to show a correlation between access to a signficant coast-line and a positive uptick in GDP.
It…really didn’t. At least not to my eye. But this is still fascinating. We see some of my earlier assertions born out again.
Wealthier countries adopt Service Sectors into their economy…but what’s also interesting is they experience positive net immigration.
Countries with strongly growing internal populations (before Migration is counted) have large Agriculture sectors in thier economies. That also makes sense, given the labor-intensive nature of that field, and the cost-saving realities of that market.
If anything, my initial thesis of Coastline = Wealthy has no strong, or negative correlation…instead, coastlines seem to negatively dispose a country towards large-scale industrial sectors…which admittedly runs counter to my expectation.
Migration Winners and Losers
Migration is a factor of Macro Economics. Populations self-adjust to where there are opporunities for work, safety and to raise a family in some degree of peace.
It should be no surprise, then, that Migration Losers (regions which spike negative) are experiencing a combination of sectarian strife and endemic poverty, disease and lack of education.
Migratory winners, by comparison, are experiencing explosive economic growth (more than their passive pop growth can support) which creates huge opportunity for those willing to go through the hassle of moving thier entire life to a new country.
The Asian Economies are perhaps the biggest star in this sector, especially Japan which has historically been very opposed to large scale immigration, has been forced to open its proverbial doors, due to dangerously low domestic population growth. But South Korea and China are also immigrating huge populations of migrant employees. While assimilation is likely to be a big hurdle, many of these nations offer great quality of life - especially Korea and Japan - the likes of which are simply unattainable in some regions of the world.
Conclusion
While I imagine this to be a living document, as I get better at learning R. I hope this has been educational, I’ve certainly learned an awful lot in generating this document and am eager to keep growing my practice.
Until then, I’ll be filling our my Japanese Work Visa Packet!
-Sayonara, Joe