Ascription is an Anathema to any Enthusiasm

These highly skew’d distributions are extremely hard to visualize; you just can not get a feel for how vast the population of “other” is.  I give some examples of that in this previous posting, using people’s names as an example.

The folks that wrote the recent report on the worldwide distribution of wealth take a run at the problem in the usual way; putting the data into various buckets.  For example  they know that 40% of the total wealth of the planet is held by the richest 1% of the population.  We can make a pie chart showing were they live.  They live in the Europe, the US, and Japan.  In this visualization you can’t see the other, i.e. the vast majority of the world’s population, the other 99%; notice how China, India, Africa, etc. are all invisible on this chart.

We could try to get a picture that shows these other folks by making a series of pie charts.  For example we might make ten charts each showing 10% of the world’s population.  For example this next chart shows the richest 10% of the world’s population; and where they live:

Korea, Mexico, Agentia, Brazil showed up; but still no sign of China, India, Africa, etc.   The report’s authors found a way to address the problem by making the chart below.  This chart displays a pile of similar pie charts.  The first pie chart above is the chart you get if you take convert the right edge of the chart below.

So this shows that India, Africa, and “Other Asia-Pacific” house most of the world’s poorest.

But yet the visualization problems remain.  Notice two things.  First, that 40% of the total wealth is held by a tiny tiny sliver running along that right edge.  Secondly, that these regional buckets are very misleading.  Even inside those regions only a very tiny minority of the population is wealthy.  See if you can figure out what slice shape denotes a higher or lower Gini for that region?

I predict the national economic statistics will show a substantial increase in worker productivity in the next quarter.

Why? The new beta version of Firebug shows clearly how long it takes for various web pages to load. I know of three web sites who’s load time has been improved by significant margins already and I expect we will see a speed up to from 5-10 across the board.

I predict data: URLs (see also) will suddenly become quite popular. Finally, we need an Apache module ASAP that automatically splices in data urls for small GIFs and css files.

I feel duty bound to post about the recently released report on the worldwide wealth distribution put out by the “World Institute for Development Economics Research” at the United Nations University in Finland.  There is little in this report that surprises me.  Wealth is very skewed.  For example: “the study estimates that the global wealth Gini for adults is 89%.  The same degree of inequality would be obtained if one person in a group of ten takes 99% of the total pie and the other nine share the remaining 1%.”

The skew varies widely from country to country.  If there is some central authority in charge, let’s call him Zippy, Zippy might decide to reward some people with more wealth than others.   Zippy might pick any of an assortment of basis for his rewards: talent, birth, luck, effort, beauty, behavior, height, power, etc.  The Gini index is a metric of how big much Zippy decides to reward.  If he hands out no rewards then the Gini index is zero and the wealth is perfectly evenly spread out; if the index is one then he picks on person and given them all the money.
The chart below, derived from table 9 in the report, shows an alternate way to look at what Zippy has done in various countries.  It shows how much wealth the bottom 90% captured.

Zippy likes the rich.  He really likes them in the US and Switzerland.  He’s a bit nicer to everybody else in some other countries, for example in Japan, China, and Spain.

I do like this blog, the world needs more well done ranting.

I bought a new cell phone with a year’s contract. It’s a cute phone. We like it.

The phone goes for about $200 on eBay, and after all the rebates are said and done I’ll have spend minus $50 dollars. The service is $480/year. So one way to look at is they paid me $250 to lock in $480 in revenue; e.g. to clear $230. That’s of course not quite right because Amazon, who sold me the phone, got a kickback, they certainly paid a few bucks for the phone and then of course there is a bit of cost to complete the phone calls.
It’s a perfectly nice phone, but it has a very slippery keyboard.

But now that I have this phone it is a study in modern telecom up-selling. The user interface is a rats nest of buttons and menus; and many of these offer you the chance to spend more money. There are at least three dozen places in the UI where you can spend a few more dollars. Here’s a short list of just a few of the stupid ways they try to get me to spend another few bucks:

• Sign up for crippled web service (i.e. WAP). $6/month
• Send an SMS.
• Send a photo.
• Call information for a phone #.
• Get a weather report.
• Get a sport’s score.
• Horiscope

Just what you’d expect in an abusive locked in relationship, it’s obnoxious. It is far too easy it is for an unsuspecting phone user to randomly poke buttons and spend money. Twice already I’ve thought: “Damn, if I’d poked the button one over I’d have spent money.” I think the slippery keyboard design was intentional.