Financial Inequalities And Their Effect On The US Image

This article was included in the Economist and posed an interesting point in which the author sites the works of Janet Gornick, a writer for the New Yorker.  The author begins this piece by explaining a chart that includes a value known as the Gini coefficient which is reflective of the amount of discrepancy that exists within any given country based upon the income of a nation’s average after taxation.  This chart shows the United States as the nation with the highest income variation when compared with other selected nations.
   

The author then continues by summing up the stance Gornick, by reiterating her ideas in explaining the reasons for the discrepancies that exists in the comparison of the US with that of other countries.  In essence, Gornick concludes that due to the differing structure that America operates upon, the US yields a different income variation than those of other countries.  The author of this piece adds to this idea by adding alternative examples of how differently the US focuses upon public funding and taxation through the use of programs such as social security and public education.

Although this piece was well written in formulating reasons to explain the income discrepancies, the method of which Gornick goes about collecting and displaying data seems incomplete in showing all of the possible reasons that could attribute to the discrepancies.  It would have been beneficial to include an alternate exhibit that noted the population size of each of these countries as well the resources available in each individual nation.  Due to the vast amount of factors that each of the pieces of data are based upon, it is too presumptuous to rely solely on the outcome of the chart, in a further sense the chart is not fully representative on the official standing of each country.  Each of these nations possesses a different amount of resources readily available so, it is not easy to simply compare the income variations that exist within and since they serve varying populations, it is even harder to conclude anything based upon these figures.  

Through further research upon this topic, it was found that the United States is only one of many countries that retain an advantage based upon the natural resources available to them.  From this study it was found that many countries that possess these advantages were not mentioned in the income discrepancy chart.  One example is the nation of Saudi Arabia, who utilizes their nation’s oil reserves to generate revenue and holds a large portion of the market share of providing petroleum oil to the world.  Furthermore, when one compares the inequalities posed by incomes by nations, it can be found that Mexico actually ranks higher than the US depending upon the source.  Even though this article proved to be intriguing, it still lacks in a complete analysis.   

Gini coefficient, after taxes and transfers^[13]

Country	mid-70s	mid-80s	around 1990	mid-90s	around 2000	mid-2000s	Late 2000s
Australia				0.309	0.317	0.315	0.336
Austria		0.236		0.238	0.252	0.265	0.261
Belgium		0.274		0.287	0.289	0.271	0.259
Canada	0.304	0.293	0.287	0.289	0.318	0.317	0.324
Chile				0.527		0.503	0.494
Czech Republic			0.232	0.257	0.260	0.268	0.256
Denmark		0.221	0.226	0.215	0.226	0.232	0.248
Estonia						0.349	0.315
Finland	0.235	0.209		0.218	0.247	0.254	0.259
France		0.300	0.290	0.277	0.287	0.288	0.293
Germany		0.251	0.256	0.266	0.264	0.285	0.295
Greece	0.413	0.336		0.336	0.345	0.321	0.307
Hungary			0.273	0.294	0.293	0.291	0.272
Iceland						0.257	0.301
Ireland		0.331		0.324	0.304	0.314	0.293
Israel		0.326	0.329	0.338	0.347	0.378	0.371
Italy		0.309	0.297	0.348	0.343	0.352	0.337
Japan		0.304		0.323	0.337	0.321	0.329
South Korea						0.306	0.315
Luxembourg		0.247		0.259	0.261	0.258	0.288
Mexico		0.452		0.519	0.507	0.474	0.476
Netherlands	0.263	0.272	0.292	0.297	0.292	0.284	0.294
New Zealand		0.271	0.318	0.335	0.339	0.335	0.330
Norway		0.222		0.243	0.261	0.276	0.250
Poland					0.316	0.349	0.305
Portugal	0.354		0.329	0.359	0.356	0.385	0.353
Slovak Republic						0.268	0.257
Slovenia						0.246	0.236
Spain		0.371	0.337	0.343	0.342	0.319	0.317
Sweden	0.212	0.198	0.209	0.211	0.243	0.234	0.259
Switzerland					0.279	0.276	0.303
Turkey		0.434		0.490		0.430	0.409
United Kingdom	0.268	0.309	0.354	0.336	0.351	0.331	0.345
United States	0.316	0.337	0.348	0.361	0.357	0.380	0.378

Mazie, Steven. "Inequality in America: Gini in the Bottle." The Economist. The Economist Newspaper, 26 Nov. 2013. Web. 27 Nov. 2013.

"The World’s Most Resource-Rich Countries." 247wallst.com. N.p., 18 Apr. 2012. Web. 27 Nov. 2013.

"List of Countries by Income Equality." Wikipedia. Wikimedia Foundation, 27 Nov. 2013. Web. 27 Nov. 2013.

At UWB, Graphics Alone Just Don’t Sell

The numbers don’t lie…right?

Considering my semi-obsession with food documentaries, particularly ones like Food Inc. and Fast Food Nation, Julie Jargon’s “At McDonald’s, Salads Just Don’t Sell” article in the Wall Street Journal immediately caught my eye. On the surface, Ms. Jargon seemed to logically explain the issues surrounding McDonald’s sales fluctuations by noting that its business has floundered since it failed to introduce a blockbuster product since its McGriddles in 2003. She also mentioned external (competitor product introductions, criticism from the documentary “Super Size Me” and the recession) and internal factors (a crowded menu and longer drive-thru performance times) that directly affected McDonald’s past 11 years of sales and included the following graph to visually describe the company’s percentage change in global sales.

Closer inspection, however, quickly revealed holes in the article that eroded its informational credibility – especially due to the meaninglessness of the supporting graph. In the meat of her article, Jargon stated that salads comprise only 2-3% of the company’s U.S. sales – yet the graph displayed global sales? The only time Jargon mentioned global anything in the article was when “McDonald’s Chief Executive Don Thompson warned in July that the shaky global economy would continue to pressure McDonald’s growth” ¹, and yet she explicitly illustrated global sales as the only chronological demographic in her graph.  Since the rest of the article was centralized around American consumer behavior, shouldn’t the graph have been a measurement of U.S. sales? Jargon also named specific healthy menu options in her graph but neglected to explain how much influence on sales or percentage change each of the listed products accounted for. Was she prevaricating their impact on sales, or did she simply not know? What relevance, then, did her graph even have to the article as a whole? Wouldn’t the graph make more sense if it included an additional section below the healthy options timeline that chronologically noted other items McDonald’s introduced over the 11-year time span (such as the premium coffees program) and the aforementioned external and internal factors so that the reader can better understand how and why McDonald’s sales fluctuated?

So many questions.

In short, the graph was just a pretty but useless picture of meaningless statistics. If this graph was literally analyzed by a layman without support of Jargon’s article, he or she would only deduce that McDonald’s global sales were directly and only affected by the sales of those particular products…nothing more. Post-analysis, I was disturbed that this article was published on the front page of the Business & Finance section of the Wall Street Journal, one of the most prestigious newspapers in the world. That’s prime real estate! Sure, the numbers didn’t lie…but in this case they didn’t mean anything.

¹ Jargon, Julie. "At McDonald's, Salads Just Don't Sell." WSJ.com. Wall Street Journal, 18 Oct. 2013. Web. 25 Nov. 2013. <http://online.wsj.com/news/articles/SB10001424052702304384104579139871559464960>