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“There are three types of lies: Lies, Damned Lies and Statistics”
Attributed to Benjamin Disraeli (Popularized by Mark Twain)

Before moving into an broader explanation of International Markets and Taxation, it is first critical that I share with you the methodology behind how I generated the facts and figures I am presenting, so that you may better determine the validity of the data…because, frankly, unless you are ethical in your approach to statistics and reporting, anyone with half a measure of skill with a spreadsheet can get the numbers to say anything they want them to say. And while there are those that will quibble with my methodology, I can guarantee that I have followed the exact same steps for every piece of data, every piece of data was manually retrieved, and I made no presumptions as to what the final numbers and measure would be:

Over the last several weeks, I have, as close to daily as possible given that it takes about 2.5 hours per day, recorded the lowest average prices of all products at all quality levels on the US, Romanian, Indonesian, Spanish, United Kingdom and Swedish markets. For those same markets I have daily tracked all taxation levels, all treasury levels, local currency values to Gold, minimum wage, average wage, and cost of living. In order to mitigate time frame impacts I have selected rotated through the order daily by starting with the last nation surveyed on the previous day and continuing in order through the sequence I named URISUS (US, Rom, Indo, Spain, UK, Sweden).

In order to determine the lowest average prices of all products at all quality levels, I went to each market and each product and then to each quality level and processed the prices as though I was an international buyer purchasing the lowest priced goods at that quality level for the first three companies (where available) at the same quality level. I then divided the entire purchase amount by the number of units purchased. I then converted that amount in it’s gold equivalent at the current local currency to gold conversion rate and the final value became the gold equivalent so that I could convert it into any of the six local currencies for comparison purposes.

*One caveat: When the nearest lowest price of the next company was egual to or greater than 200% of the current per unit price it was excluded from the calculation as not being indicative of minimum pricing)

As an example of this: At the time of this writing, I research Q2 Food on the Romanian market, the following three companies are offering the lowest per unit prices in RON (Romanian currency)

UberFoods – 53 Units @ 2.93 RON – Total Cost: 155.29 RON

Food Group RO – 48 Units @ 2.94 RON - Total Cost: 141.12 RON

Kondor Food – 7 Units @ 2.94 RON - Total Cost: 20.58 RON

Total Units Purchase😛 108

Total Cost of Purchase: 316.99 RON

Total Cost / Total Units = 2.935093 RON / Per Unit

Per Unit Cost * Current RON:GOLD Conversion Rate(.02) = .058702 GOLD (Average Cost Per Unit in GOLD)

Average Cost Per Unit in GOLD / US😨GOLD Conversion Rate(.01😎 = @ $3.26 USD

And for those of you keeping score at home the Romanian Q2 Food can be purchased in Romania for roughly $3.26 USD, US Q2 Food can currently be purchased in the US for approximately $2.91 USD; so for our Romanian friends, sorry, and for my eUS readership, stay home tonight to eat.

Now, multiply that average minimum product price calculation by, at last count 800-1000, and you start getting a hint of what I have been spending a massively-disproportionate-to-actual-val ue of time doing lately, but…eh…that’s what you get when you lose big in the weekly eUS Congress “Truth or Dare” game. Contributions for the 40+ hours I spent on this are highly appreciated (call it a class fee 🙂 )

Okay, so now we have spent a nauseating amount of time on methodology (and an even more nauseating amount of time in data input)..so what do the numbers tells us? Well, through the magic of Excel and Standard Deviation, I can share that the average product price range for all 6 nations (when all six nations had at least one unit for sale of same product and same quality at any time) for the time period spanning the last 15 days (442-457) in USD using the current conversion rate of US😨GOLD of .018:

$1.14 - $1.55 \ Q1 - Food
$2.23 - $3.07 \ Q2 - Food
$4.74 - $6.23 \ Q3 - Food
$7.39 - $10.36 \ Q4 - Food
$11.21 - $25.85 \ Q5 - Food
$2.60 - $4.27 \ Q1 - Gift
$4.72 - $8.14 \ Q2 - Gift
$7.33 - $8.61 \ Q1 - Weapon
$14.41 - $21.04 \ Q2 - Weapon
$26.91 - $32.52 \ Q3 - Weapon
$42.74 - $56.26 \ Q4 - Weapon
$77.42 - $105.86 \ Q5 - Weapon
$14.18 - $17.61 \ Q1 - Moving Tickets
$0.69 - $0.84 \ Q1 - Grain
$1.04 - $2.01 \ Q2 - Grain
$1.68 - $5.33 \ Q3 - Grain
$0.89 - $1.33 \ Q1 - Diamonds
$1.52 - $2.09 \ Q2 - Diamonds
$2.22 - $2.74 \ Q3 - Diamonds
$0.77 - $1.50 \ Q1 - Iron
$1.17 - $2.07 \ Q2 - Iron
$1.77 - $3.09 \ Q3 - Iron
$0.80 - $1.44 \ Q1 - Oil
$1.41 - $2.21 \ Q2 - Oil
$0.81 - $1.72 \ Q1 - Wood
$1.36 - $2.92 \ Q2 - Wood
$2.13 - $4.01 \ Q3 - Wood
$212.49 - $365.37 \ Q1 - House
$429.25 - $767.79 \ Q2 - House

Okay, so much for that unpleasantness. As interesting as it may seem to some, the reality is that unless the information is parsed by nation it really tells us nothing more than a conglomerated range for which we might expect to see prices in determining whether a purchase on a market is a good deal or a poor relative deal.

Now, when we look closer at the information on a nation by nation basis and compare national averages and ranges it provides for a better comparative analysis:

http://spreadsheets.google.com/pub?key=pG8NruebY8LQJQ8-3LUJyHw

To better understand this spreadsheet here is a key:

Column 1: Product/Quality

Column 2: Average pricing in USD day 442-457 (0.018 Gold Conversion)

Column 3: Standard deviation (For example, if the average price is $5.00 and the standard deviation is $1.00, then the range of expected prices in the control band would be $4.00 (AVG - ST DEV) to $6.00 (AVG + ST DEV).

Country specific columns:
- Blue = Within Expected Range
- Red = Higher than Expected Range,
- Green = Lower than Expected Price Range.

So, on this spreadsheet for Q2 Food the average price is $2.65 USD, the Standard Deviation is $0.42, therefore the expected price range in the URISUS countries would be $2.23 to $3.07. Indonesia has pricing higher than expected, Sweden has prices lower than expected, thus both are outliers in this model.

I will let you chew on that information a little bit before the next installment: eRep Economics 101, Part Quatro: International Pricing Outliers and Taxation.