Posts Tagged ‘uk’

The Kassandra Project

Government wants personal details of every traveller

Phone numbers and credit card data to be collected under expanded EU plan

This article appeared in the Guardian on Saturday February 23 2008 on p1 of the Top stories section. It was last updated at 02:17 on February 23 2008.
Passengers in line at Heathrow airport

Airline passengers will be monitored at every stage of their journey under the proposals. Photograph: David Levene

Passengers travelling between EU countries or taking domestic flights would have to hand over a mass of personal information, including their mobile phone numbers and credit card details, as part of a new package of security measures being demanded by the British government. The data would be stored for 13 years and used to “profile” suspects.

Brussels officials are already considering controversial anti-terror plans that would collect up to 19 pieces of information on every air passenger entering or leaving the EU. Under a controversial agreement reached last summer with the US department of homeland security, the EU already supplies the same information [19 pieces] to Washington for all passengers flying between Europe and the US.

But Britain wants the system extended to sea and rail travel, to be applied to domestic flights and those between EU countries. According to a questionnaire circulated to all EU capitals by the European commission, the UK is the only country of 27 EU member states that wants the system used for “more general public policy purposes” besides fighting terrorism and organised crime.

The so-called passenger name record system, proposed by the commission and supported by most EU governments, has been denounced by civil libertarians and data protection officials as draconian and probably ineffective.

The scheme would work through national agencies collecting and processing the passenger data and then sharing it with other EU states. Britain also wants to be able to exchange the information with third parties outside the EU.

Officials in Brussels and in European capitals admit the proposed system represents a massive intrusion into European civil liberties, but insist it is a necessary part of a battery of new electronic surveillance measures being mooted in the interests of European security. These include proposals unveiled in Brussels last week for fingerprinting and collecting biometric information of all non-EU nationals entering or leaving the union.

All airlines would provide government agencies with 19 pieces of information on every passenger, including mobile phone number and credit card details. The system would work by “running the data against a combination of characteristics and behavioural patterns aimed at creating a risk assessment”, according to the draft legislation.

“When a passenger fits within a certain risk assessment, he could be identified as a high-risk passenger.”

A working party of European data protection officials described the proposal as “a further milestone towards a European surveillance society.

“The draft foresees the collection of a vast amount of personal data of all passengers flying into or out of the EU regardless of whether they are under suspicion or innocent travellers. These data will then be stored for a period of 13 years to allow for profiling. The profiling of all passengers envisaged by the current proposal might raise constitutional concerns in some member states.”

The Liberal Democrat MEP Sarah Ludford said: “Where is this going to stop? There’s no mature discussion of risk. As soon as you question something like this, you’re soft on terrorism in the UK and in the EU.”

Britain is pushing for a more comprehensive system based on the experience of a UK pilot scheme that has been running for the past three years. Officials say Operation Semaphore, monitoring flights from Pakistan and the Middle East, has been highly successful and has resulted in hundreds of arrests.

The scheme has seen one in every 2,200 passengers warranting further investigation, with a tenth of those “being of interest”. British officials say rapists, drug smugglers and child traffickers have been arrested and want the EU scheme to cover “all fugitives from crown court justice”.

But Ludford said: “If you ask the UK government how many terrorists have been picked up, I don’t think you get a very straight answer.”

EU officials have asked the Home Office minister Meg Hillier for information about the arrests of suspected terrorists.

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In “Killer Corporations: grow rate from 2005 to 2007” we wrote about the trends of the number of corporations in the world top economies. We saw something strange. So we wanted to analyze more deeply: we wrote the Kassandra Report – Dec2007, whose we past the most important words.

 

Kassandra Report – Dec.2007

Status of this report

With this report we want to analyze the relationship among the world economies and corporations. In particular we want to put in evidence four zones of interest:
1. Area of powerful countries A1;
2. Hybrid Area of countries and powerful corporations A2;
3. Area of corporations A3;
4. Area of rest of the world A4.

By studying economic data on Gross Domestic Product (GDP) reported by International Monetary Fund in the years from 2000 to 2007, and those reported by Fortune Global 500 in the years 2005-2007 and by Forbes in the years 2000-2004 about revenues, we made a list of top 100 economies and some statistics.
In 1996 Steve Gorelick made a similar list by using GNP instead of GDP, and profits. But we’re analyzing economy: we want to consider revenues and GDP.
In “Of the world’s 100 largest economic entities, 51 are now corporations and 49 are countries” compiled by Sarah Anderson and John Cavanagh of the of the Institute for Policy Studies in their Report on the Top 200 corporations released in December 2000, they considered GDP and sales.
From Wikipedi, Sales are the activities involved in selling products or services in return for money or other compensation. It is an act of completion of a commercial activity.
The “deal is closed”, means the customer has consented to the proposed product or service by making full or partial payment (as in case of installments) to the seller.
Academically, selling is thought of as a part of marketing, however, the two disciplines are completely different. Sales often forms a separate grouping in a corporate structure, employing separate specialist operatives known as salespersons (singular: salesperson). Sales is considered by many to be a sort of persuading “art”. Contrary to popular belief, the methodological approach of selling refers to a systematic process of repetitive and measurable milestones, by which a salesperson relates his offering of a product or service in return enabling the buyer to achieve his goal in an economic way.

What is the difference between revenue, income, and gain?


You can read here that Revenue is the amount earned from a company’s main activities such as selling merchandise or providing services.
A gain results from a peripheral activity, such as selling the old delivery truck. A gain is the amount received that is in excess of the asset’s carrying amount (book value). For example, if the company receives $3,000 for the truck, and its carry amount was $600, the company will report a gain of $2,400.

Income is sometimes used instead of the word revenue: some people refer to the rent they receive as rent income. Generally, accountants use the word income to mean “net of revenues and expenses.” For example, a retailer’s income from operations is sales minus the cost of goods sold minus operating expenses.

The terms Revenue and Income are often used in reporting earnings. What is the difference?

Audrey W. answered that Revenue (sometimes called sales) refers to all the money a company takes in from doing what it does — whether making goods or providing services. Other sources of funds — including investment gains — are usually labeled as such but also included as revenue. (Occasionally, you’ll see this number referred to as “gross income.”)
For these reasons we can make the same statistics made by Sarah Anderson and John Cavanagh in 2000 about the top economies entities in the world.
If you don’t want to read all these lists, we suggest you to go to the end of this article, where there are interesting results on strange behavior of world economies which sound like conspiracy and manipulation.

Then we reported the tables with the top 280 world economies in the years from 2000 to 2007.

Number of Corporations vs First World Top Economies

number of corporations in the world top economies

We can see almost the same behavior for seven graphs, in an years range where a lot of corporations became other corporations, changed names, failed, and so on.
Statistical oscillations come from 0% to 2.5% point to point, for an average mean oscillation of 0.0089 %.
We want to analyze the relationship among the number of corporations and the first economic entities in the world in the range 70-160 economies. We found an incredible result:

kassandra report about corporations and world top economies

 

There is a linear correlation among these numbers with a correlation factor greater than 0.996 for each distribution over seven years. It means that we can describe this area with a linear model.

Four zones

We said that we can build four zones in order to describe the relationship between the corporations number and the world economies:

1. Area of powerful countries A1;
2. Hybrid Area of countries and powerful corporations A2;
3. Area of corporations A3;
4. Area of rest of the world A4.

 

A1

We have only countries in this area. As you can see from the previous tables, these countries are always the same.

A2

In this area we can see almost the same number of countries and corporations. If we consider only the first 100 economies, we can see an average of corporations of about 45%.

A3

In this area we see a lot of corporations. We must consider the percentages:
• 0% in the top 20;
• 45% in the top 100;
• 62% in the top 160;
• 36% in the top 280.

A4

In this area we see only countries: there are no corporations.

Conclusions

We have no corporations in the top 20, but we have always the same countries with little oscillations.

Then we see some corporations, for a worrying percentage of 45% in the top 100. There is an incredible linear behavior between top 70 and top 160; at the same time we see that 62% of top 160 economic entities are corporations.

We don’t see corporations between top 161 and top 280, but we see always the same countries, with some oscillations.

There are 280 entities, which are in any way dependent each other. These dependences could create oscillations, more or less visible, but it is quite difficult to have the same behavior for seven years.

What if this trend is not random?

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By studying economic data on Gross Domestic Product (GDP) reported by International Monetary Fund in the years from 2005 to 2007, and those reported by Global 500 by Fortune in the same years about revenues, we made a list of top 100 economies and some statistics…
They follow the top 100 in the years 2005, 2006 and 2007.

One of our readers, Jonolan, observed that we cannot use GDP: yes, it’s almost true, but we used corporations’ revenues also.

In 1996 Steve Gorelick made a similar list by using GNP instead of GDP, and profits. But we’re analyzing economy: we want to consider revenues and GDP.

In “Of the world’s 100 largest economic entities, 51 are now corporations and 49 are countries” compiled by Sarah Anderson and John Cavanagh of the of the Institute for Policy Studies in their Report on the Top 200 corporations released in December 2000, they considered GDP and sales.

As you can read from Wikipedia about sales: Sales are the activities involved in selling products or services in return for money or other compensation. It is an act of completion of a commercial activity.

The “deal is closed”, means the customer has consented to the proposed product or service by making full or partial payment (as in case of installments) to the seller.

Academically, selling is thought of as a part of marketing, however, the two disciplines are completely different. Sales often forms a separate grouping in a corporate structure, employing separate specialist operatives known as salespersons (singular: salesperson). Sales is considered by many to be a sort of persuading “art”. Contrary to popular belief, the methodological approach of selling refers to a systematic process of repetitive and measurable milestones, by which a salesperson relates his offering of a product or service in return enabling the buyer to achieve his goal in an economic way.

What is the difference between revenue, income, and gain?

You can read here that Revenue is the amount earned from a company’s main activities such as selling merchandise or providing services.

A gain results from a peripheral activity, such as selling the old delivery truck. A gain is the amount received that is in excess of the asset’s carrying amount (book value). For example, if the company receives $3,000 for the truck, and its carry amount was $600, the company will report a gain of $2,400.

Income is sometimes used instead of the word revenue: some people refer to the rent they receive as rent income. Generally, accountants use the word income to mean “net of revenues and expenses.” For example, a retailer’s income from operations is sales minus the cost of goods sold minus operating expenses.

The terms Revenue and Income are often used in reporting earnings. What is the difference? 

Audrey W. answered that Revenue (sometimes called sales) refers to all the money a company takes in from doing what it does — whether making goods or providing services. Other sources of funds — including investment gains — are usually labeled as such but also included as revenue. (Occasionally, you’ll see this number referred to as “gross income.”)

For these reasons we can make the same statistics made by Sarah Anderson and John Cavanagh in 2000 about the top economies entities in the world. 

If you don’t want to read all these lists, we suggest you to go to the end of this article, where there are interesting results on strange behaviour of world economies… which sound like conspiracy and manipulation

You can find the following numbers and many others in the pdf file that we created for you: Corporations and world economies numbers and statistics.

All numbers are in $ Billion. In the year 2005:

United States 12433,925
Japan 4557,105
Germany 2796,222
United Kingdom 2246,331
China 2243,687
France 2137,514
Italy 1772,769
Canada 1135,454
Spain 1131,706
Brazil 882,043
Korea 791,572
India 778,666
Mexico 767,690
Russia 764,068
Australia 712,622
Netherlands 634,044
Switzerland 372,994
Belgium 372,623
Turkey 362,461
Sweden 358,481
Taiwan Province of China 355,187
Saudi Arabia 315,758
Austria 305,621
Poland 303,976
Norway 301,735
Wal-Mart Stores 287,989
Indonesia 286,957
BP 285,059
Greece 284,226
Exxon Mobil 270,772
Royal Dutch/Shell Group 268,690
Denmark 259,217
South Africa 241,889
Ireland 201,187
Finland 195,785
General Motors 193,517
Iran, Islamic Republic of 188,479
Portugal 185,433
Argentina 181,549
Hong Kong SAR 177,784
DaimlerChrysler 176,688
Thailand 176,222
Toyota Motor 172,616
Ford Motor 172,233
General Electric 152,866
Total 152,610
ChevronTexaco 147,967
Venezuela 143,443
United Arab Emirates 133,000
Israel 131,330
Malaysia 130,835
Czech Republic 124,988
Colombia 122,900
ConocoPhillips 121,663
AXA 121,606
Chile 118,976
Allianz 118,937
Singapore 116,704
Volkswagen 110,649
Hungary 110,506
Pakistan 109,599
New Zealand 108,849
Citigroup 108,276
ING Group 105,886
Algeria 102,103
Nippon Telegraph & Telephone 100,545
Romania 98,861
Philippines 98,718
Nigeria 98,564
American Intl. Group 97,987
Intl. Business Machines 96,293
Siemens 91,493
Carrefour 90,382
Egypt 89,794
Ukraine 86,137
Hitachi 83,994
Assicurazioni Generali 83,268
Matsushita Electric Industrial 81,078
Kuwait 80,780
McKesson 80,515
Honda Motor 80,487
Hewlett-Packard 79,905
Nissan Motor 79,800
Peru 79,485
Fortis 75,518
Sinopec 75,077
Berkshire Hathaway 74,382
ENI 74,228
Home Depot 73,094
Aviva 73,025
HSBC Holdings 72,550
Deutsche Telekom 71,989
Verizon Communications 71,563
Samsung Electronics 71,556
State Grid 71,290
Peugeot 70,642
Metro 70,159
Nestlé 69,826
U.S. Postal Service 68,996
BNP Paribas 68,654

The 45% are Corporations.

In the year 2006:

United States 13194,700
Japan 4366,459
Germany 2915,867
China 2644,642
United Kingdom 2398,946
France 2252,213
Italy 1852,585
Canada 1275,283
Spain 1231,733
Brazil 1067,706
Russia 984,925
Korea 888,267
India 873,659
Mexico 840,012
Australia 755,659
Netherlands 670,929
Turkey 401,763
Belgium 394,507
Switzerland 387,987
Sweden 384,388
Taiwan Province of China 364,563
Indonesia 364,239
Saudi Arabia 349,138
Poland 340,969
Exxon Mobil 339,938
Norway 335,856
Austria 323,828
Wal-Mart Stores 315,654
Greece 308,720
Royal Dutch Shell 306,731
Denmark 276,400
BP 267,600
South Africa 255,272
Iran, Islamic Republic of 222,387
Ireland 219,368
Argentina 212,595
Finland 209,771
Thailand 206,338
Portugal 194,790
General Motors 192,604
Hong Kong SAR 189,799
Chevron 189,481
DaimlerChrysler 186,106
Toyota Motor 185,805
Venezuela 181,608
Ford Motor 177,210
ConocoPhillips 166,683
United Arab Emirates 163,296
General Electric 157,153
Total 152,361
Malaysia 148,945
Chile 145,845
Czech Republic 142,517
Israel 142,250
ING Group 138,235
Colombia 135,883
Singapore 132,155
Citigroup 131,045
AXA 129,839
Pakistan 127,002
Romania 121,901
Allianz 121,406
Volkswagen 118,377
Philippines 117,562
Nigeria 116,488
Algeria 113,888
Hungary 112,899
Fortis 112,351
Crédit Agricole 110,765
American Intl. Group 108,905
Egypt 107,375
Ukraine 106,469
New Zealand 104,607
Assicurazioni Generali 101,404
Siemens 100,099
Sinopec 98,785
Kuwait 95,924
Nippon Telegraph & Telephone 94,869
Carrefour 94,454
HSBC Holdings 93,494
Peru 93,045
ENI 92,603
Aviva 92,579
Intl. Business Machines 91,134
McKesson 88,050
Honda Motor 87,511
State Grid 86,984
Hewlett-Packard 86,696
BNP Paribas 85,687
PDVSA 85,618
UBS 84,708
Bank of America Corp. 83,980
Hitachi 83,596
China National Petroleum 83,556
Pemex 83,382
Nissan Motor 83,274
Berkshire Hathaway 81,663
Home Depot 81,511
Valero Energy 81,362
Kazakhstan 81,003

The 44% are Corporations.

In the year 2007:

United States 13794,221
Japan 4345,948
Germany 3259,212
China 3248,522
United Kingdom 2755,920
France 2515,241
Italy 2067,680
Spain 1414,646
Canada 1406,430
Brazil 1295,355
Russia 1223,735
India 1089,944
Korea 949,698
Australia 889,681
Mexico 886,441
Netherlands 754,883
Turkey 482,015
Belgium 442,774
Sweden 431,605
Switzerland 413,921
Poland 413,312
Indonesia 410,317
Taiwan Province of China 375,645
Saudi Arabia 374,457
Norway 369,252
Austria 366,719
Greece 356,258
Wal-Mart Stores 351,139
Exxon Mobil 347,254
Royal Dutch Shell 318,845
Denmark 310,674
Iran, Islamic Republic of 278,138
South Africa 274,501
BP 274,316
Ireland 253,313
Argentina 248,332
Finland 236,128
Venezuela 226,922
Thailand 225,815
Portugal 219,542
General Motors 207,349
Toyota Motor 204,746
Hong Kong SAR 202,960
Chevron 200,567
DaimlerChrysler 190,191
United Arab Emirates 189,644
ConocoPhillips 172,451
Colombia 171,738
Total 168,357
General Electric 168,307
Czech Republic 168,142
Malaysia 164,976
Chile 160,784
Ford Motor 160,126
Romania 158,532
ING Group 158,274
Israel 154,283
Singapore 153,488
Citigroup 146,777
Pakistan 143,766
Philippines 141,052
AXA 139,738
Hungary 136,358
Volkswagen 132,323
Sinopec 131,636
Ukraine 131,197
Crédit Agricole 128,481
Egypt 127,930
Nigeria 126,746
Algeria 125,866
Allianz 125,346
New Zealand 124,443
Fortis 121,202
Bank of America Corp. 117,017
HSBC Holdings 115,361
American International Group 113,194
China National Petroleum 110,520
BNP Paribas 109,214
ENI 109,014
UBS 107,835
Siemens 107,342
State Grid 107,186
Kuwait 103,367
Assicurazioni Generali 101,811
Peru 101,504
J.P. Morgan Chase & Co. 99,973
Carrefour 99,015
Berkshire Hathaway 98,539
Pemex 97,469
Deutsche Bank 96,152
Dexia Group 95,847
Kazakhstan 95,467
Honda Motor 94,790
McKesson 93,574
Verizon Communications 93,221
Nippon Telegraph & Telephone 91,998
Hewlett-Packard 91,658
International Business Machines 91,424
Valero Energy 91,051
Home Depot 90,837

The 44% are Corporations.

Analysis of result

Does it seem to be strange, isn’t it? Kassandra made other statistics for you. What do we find? The following graph:

Number of corporations in world economies, 2005 to 2007 statistics

Wow! It’s incredible! The same behaviour in three different years! Quite strange… This graphs shows that the number of corporations remains the same. It doesn’t show that there are always the same corporations in the first 50, 100, etc, world economies, but it shows that there are ALWAYS the same number of corporations.

How can it be possible, in a world of economic disorder? We made the math instead of you, what do we find?

We have 100 corporations in the first 160 positions, over a total of 280 positions. So we must calculate the probability that a set of 100 elements is in the first 160 positions.

We must consider the combinations with repetitions of 100 elements in a set of 160 elements and then divide the result for the combinations with repetitions of 100 elements in a set of 280 elements.

What does it means? Suppose that you have 10 balls in a box: 7 red and 3 blue. Suppose you want to know the probability that in anyway you select 5 random balls, you’ll have 3 blue balls. If you add a number to each ball, you must consider all the combinations with repetitions of 3 blue balls in 5 extractions from the box and divide them by the combinations with repetitions of 3 blue balls over ALL the extraction.

If now you consider 100 corporations instead of the 3 numbered blue balls and 280 economies instead of 10 balls and the first 160 positions instead of the first 5 extractions, you’ll reach our result!

Which result? The probability to obtain that behaviour is 3.6*10^-18 %. What? In decimal digits: 0.0000000000000000036 %. It’s almost the same probability to be destroyed from an asteroid in the next 100 years!

You must know that these are valid results only if we consider that there isn’t any relationship between corporations of year 2005 and those of 2006 or 2007. So we must expect a real constraint to combinations, based on strategies, relationships, and so on.

In that case the probability will grow, and we need a goo economist to say “how many” it grows: we can only say that there’ll be less zeros than before… but you could be sure that there’ll be too many zeros!

Mmmm… Did I say that the first seven economies are always the same countries, in the same positions? And that the first 15 economies are always the same countries, a little scrambled?

It sounds like conspiracy… It seems that They decided already what the world economies must be.

Why? Because money and power is rounding… but they’re rounding among the same protagonists, who don’t want to make too evident Their game.

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