Figure 13/ eamungs earnngs I 4- WWI% I I r Utilities • 1 A xi T r /W3 I I I I a Irplfns Of 4— — — earnngs returns —0 Wa fps mai Twia T i Wastr. I I Retailers Individuals(i) Wealth = w(i) Shares of National Income kr° 1.70 1.65 1.60 k55 WO Total Compensation a eiN y ydm. 0,40 # %.......% Wages and Salaries Sa w a, We.... we gees- as y. % .... Ye, .... ... S is \ 1948 1952 1956 1960 1964 1968 1972 1976 1900 1964 1988 1972 1996 2003 Figure 1.3.8 onsumptan 301 EFTA00625429

350 300 250 ZO 150 I IT so C 0 P fig 1.4.1.1 - model 1AI • r.::., r' 1+,1 /\ 10000 100 10 1 loo.aeo % • • a ext Income eto • • • . • •• •• • •••%%, _ 3X. 1:0) 12:1) I40) fig 1.4.1.2 - model 1A • full data Incom• 1000.000 I 0:0D :CO 302 EFTA00625430

ION fig 1.4.1.3 - model 1Al • raw data —Poveer (raw data) 103 C y = 3E+40x12261 R2 = 0.9926 10 Income 100)000 103 000 200 260 50:03 030 Figure 1.4.3.1 - Model 1C I • girl data - GLV fit 303 EFTA00625431

I MOD 00D I OD Of; sc 411, 0 E .0 3 DOD OD C 03 wealth 3 Income ECM 1003:0 ••• • • • • • • Figure 1.4.3.21 • full data I COO 00:C Figure 1.4.3.3 - Model 1C income' ••• • • ••••••••••••••••‘•..-- • raw data GLV fit CC0DD 2DC013 0C00X 30CC03 D00X0 O:003 304 EFTA00625432

In 1003 C C 100 10 450 400 350 303 293 Figure 1.4.3.41 . full data • Income 1003000 200 • 150 1 0 0 • C o . 0 930 • • Figure 1.4.4.1 - Model 1D I . raw data —GLV fit w • 11:03 1500 2003 weam 2500 3000 3930 1000 1500 5003 305 EFTA00625433

1000 CC a- 100 10 1 100 Figure 1.4.4.2 - Model 1Di • full data • wealth 1000 CO income 1000:0 10000 Figure 1.4.4.3 - Model 1D income • raw data — GLV fit ••••: ••••••••••••••80••••••••••••••••••••••• iO3:N0 1:00:0 30:0:0 19:00) 401:00) 306 EFTA00625434

10:00 ICOO 100 10 1 100000 Figure 1.4.4.4 - Model D incomel • full data I 09 08 07 0.6 0.5 0.1 03 02 01 o Income !caw) " rim 1.621 e—gini coefficient wealth - -•-- gini coefficient total income - poverty tittle wealth - poverty tatio Income I / I - a- a- se' a.. / I 0 01 02 03 04 Profit Ratio (rho) 05 06 07 08 0.9 307 EFTA00625435

160 140 120 100 eo 60 40 20 o .4 -6 -10- -12 - -14 .16 .18 -20 Figure 1.6.3 —*—decile tali° wealth la00 income 0.1 0.2 0.3 0.4 0.5 Profit Ratio (rho) 0.6 07 08 0 Figure 1.6.5 —i—alpha —Linear 'alpha, 09 1 y = 26 437x - 29 037 R2 = 09979 0 Plat Palle (oho 0 1 02 04 06 07 308 EFTA00625436

10200 11200 411 b• 100 10 itt00 Figure 1.7.1.11 • no constraint - compulsory consumption •• • • • • • 100 Figure 1.7.2.11 it00 • compulsory saving 1 • no compulsory saving Y C y 100 10 1c00 wealth 1COX • 103 1000 wealth MOM 309 EFTA00625437

1,100 10:00 -Nc tas K00 EC00 4E00 :COO 0 103 Figure 1.7.2.2 . no compulsory saving compulsory saving 1003 Diabetes Hypertension Cancer Lung &saw Hem disease. Figure L3.L Rates of illness are lower at both low and high educational levels in England compared to the USA?'' Figure 1.8.1 wealth 310 EFTA00625438

Social ciao Figure 13.3 Death rates among working-age men are town in all occupational classes in Sweden compared to England and Wales.!" Figure 1.8.2 'S 0 England and Wales ElSweden Father's social class Figure I .4 Infant mortality rates are lower m all occupational classes in Sweden han in England and Wales.'" High Figure 1.8.3 1 Figure 1.9.1.1 - model 1EI • full data • ICO wealth 311 EFTA00625439

Fig. 1.9.2.1 Offset Normal Distribution Proportion 6 iw a. 2 0 0 Skill 50 100 150 200 heights of males Figure 1.9.2.2 [Newman 2005] 250 Average Value 312 EFTA00625440

Figure 22.1 e = earnings (wages) 10000 Km C C x = Inputs, raw materials power, intermediate goods & services, etc Mx = Money paid for inputs r I Firms(j) Capital = k(j) value added negentropy rr - = returns (profit, rent, interest, dividends, etc) y = Outputs = Goods & Services Wastes, heat, etc increase in entropy r C- My = Money paid for Goods & Services Capital negentropy source I II I ▪ Individuals Wealth = w(j) • • L = labour negentropy source C = Consumption increase in entropy Figure 2.3.1.1 w 0 • • Capital .th000 runs • Capital 20.000 runs Capital - 50.000 runs Capital - 100.000 runs capital ' 10.000 100.000 I DOODCO l000.000 IMMO 000 I.000.(09.000 313 EFTA00625441

1000 l00 10 Figure 2.3.1.21 10000 10300 10 Y = 6E+00il 2032 Y = 2E+08)(104os R2 = 0.9937 R2 = 0.9977 y = 131644O 6233 R2 = 0.9922 100000 002033 capital 0,000.0:0 0 • Capital -10.000 runs • Capital .20,000 runs —1 ▪ Capital • 50.000 runs • Capital - 100,000 runs —Power (Capital -10.000 runs) —Power (Capital -20,000 nine) —Power (Capital -50,000 tuns) —Power (Capital -100,000 runs) Y = 1 E+ 09x1 Cle64 R' = 0.9943 • image= Figure 2.3.2.1! • capital 100 capital 314 EFTA00625442

t C C :0 IUJAIJ ICOJ I 1W Figure 2.3.2. • capital —Power (capital) y = 4E+640 °15 R2 = 0.9948 10 100 capital 70 gel Figure 2.3.3.1 capital I • capital U 315 EFTA00625443

10 ICO 100 90 80 70 60 1.) 50 40 y = 14766)0613°4 R 2 = 0.9738 Figure 2.3.3./1 • capital —Power (capital) • 1:03 lOPOO capital '0 Co) 0» 1 Figure 3.1.1 Copper Price (1966 $)1 -price 30 20 10 0 65 70 75 to es year 90 ss 00 05 10 316 EFTA00625444

3 25 2 0. 15 05 0 Figure 3.2.1 Copper Supply Curve —price I 70 80 Figure 3.3.1 - Model 3A J J J V J iji production i io J time v. J J ti U J I J !2C: 1C0 - commodity price V ti 317 EFTA00625445

• 4. I Figure 3.3.2 - Model 3B1 11 If Ii ft — commodity price J I HH i t J I 2 1s Figure 3.3.3 - Model 3C J V J J time 120 p k, ) — commodity price I 00 tl010 100 120 110 160 10) 700 318 EFTA00625446

7000 Figure 4.2.1 Labour Supply Curve) 6000 —earnings income 5000 E O 4000 C Q C E 3000 U0 0 2000 1000 0 0 Figure 4.3.11 [ 0 200 400 600 800 1000 1200 1400 Capital Employed — capital_employed — earnings income — production revenue -x- capital available cash wealth total wealth 6 10 12 time lc 16 18 20 319 EFTA00625447

500 Figure 4.3.21 400 300 200 • /et e k IOU ti i V II P 0 - it / ta- i f I 4tf 0.• op i2J . 0.(} ....... ..... 0•0•..0.• o—o—o bi 5 10 15 20 25 30 35 40 time 45 50 -100 e 1 t -200 I I 0 -300 :OD Figure 4.3.31 —capital employed —z— productIon_revenue —0— cash wealth — 0— earnIngsincome — — capItal_avalleble total_wealth —capItal_employed —a— earnings Income production revenue — eapitai_avaimi• —c—cash_wealth total_wealth 320 EFTA00625448

ZO !O: 14000 12000 10011 0000 E0:0 4000 10:1 0 -2-at Figure 4.3.4 .5" •—•—caplIal emplerd —0— *antis &Ken —o— ',seduction jeveitue —r— uyhalK —c—cisb_wcath _..0 rf — -" Imo _ 136 e e 118 toe — '4 Figure 4.3.5 p p y -- :— edininyb_ulcume - n - production revenue — — capital available total_iileatth —n—cash_wealfh ll I A i A I i o 1 1 li i I I A i Oil 4 i I 1 li 7 il II I r i I A i l l e I i li II 1 2 II III F.i O 0 ii Ii 11 I it p i i di g 011 6 !fl 4 II I i I II 6 III I II ' II 41, Ohl On d i il II I g I 4 i I il l i t I If III ii I ti iirlIk 6 I i iii t'i fi ii i In , ' II i l i II 'III I iii , I nil I ill' 4 I ,1 plum, I il V MI II* II ioI 8 S Iii t I iiI I, I Il It ti II , I il ii i I 4 I (f. I AI I I Il II I S 11 I { I \I I/ I 4 0 1 I If III II II • 4 / Il 1 li 0 } II II 13 d i l b li ti 5 1 °I 4 IS u II 0 I I I I el 1 , i u 1 II I 1 8, II "C/1; I 'S time - 0 321 EFTA00625449

10000 8000 6000 4000 2000 -2000 -4000 -6000 -8000 -10000 10000 1000 100 Figure 4.3.61 — capital employed — <— earnings_Income — 0— production_revenue — — capital_available —c—cash wealth — total wealth 10 time 12 ti Figure 4.5.1 Real Interest Returns - UK (1729 = 1) - US (1798 =1) — E)q)on. (UK (1729 = 1)) — Expon. (US (1798 =1)) 1870 year 1770 1820 1920 1970 2020 322 EFTA00625450

LONG-TERM STOCK MARKET REAL RETURN 8 6 4 2 0 -2 •4 -6 -8 Real S&P 500 return index Qog) Trend real annual return = 7.1% 1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000 Figure 4.5.2 100.000.000 10,000,000 1,000,000 100.000 gdp 10,000 1,000 Source: Global Financial Data & New Star estimates Figure 4.5.3 GDPI — UK (2005 £) - US (2005 $) — Bpon. (UK (2005 1)) — Expon. (US (2005 $)) 1820 1870 yea. 1920 1970 1770 2020 323 EFTA00625451

Figure 4.9.1 • I • • • Capital • I • I • returns anufacturing/ Services Capital - K 1+ I. I • Capital L returns earnings I Goods & services y My labour earnings lal-pour Individuals Wealth - W Consumption 324 EFTA00625452

-I • Nuns 4.10.1 Figure 4.11.1 Fin ncial Sector A Cap al - 7:Cageai • I I Caps • I I I • — — -- I r resins I realms' I : Iv Individuals Country A Wealth - i Corcturnpb Goods & semees My I Oarnmos Cools s serrkesy Cada' t Manufacturing! Services A Capital - K GOVERNMENT (Tres ury and Central Bank): (Buys goods and services, gold and assets; makes transfer payments) FIAT MONEY (Treasury Coin. Federal Reserve Notes. Bank reserves) MUMS IN fans -r Cagrai Cageai• Y ',toms Manufact ring! Service B Capital K Financial Sector B Capital 0 I I I • I. casp I I I. 1 • I resins I. I____ • I. I. earnings • Goods servcese • — .f> Ita !Li tabour MY earnings Goods & :traces y Individuals Country B Weakh Ccnsurssboo PRIVATE SECTOR I LEVERAGING (High Powered HOARDS - I" Credit Activity (Bank money, Money) commercial paper, private bonds) HOUSEHOLDS Taxes (Treasury Coin, Federal Reserve Notes, Bank Reserves) DRAINS MY 325 EFTA00625453

7.00 6.00 5.00 4.00 O 3.00 2.00 1.00 Figure 4.112 Leverage (amplification) re Carttai awns Lever.. am. Meat., Capital • • • • r • — — •I • returnS ,y • Major Commercial Banks aptal • : Capital • Iinterest on (Nabonal • I Debt) Inaotola bi l Government Y I [ Capaal• • I .gl S I I Goods & servnes 1.19 *1 during/ Services Capital K returns labour eamngs Goods & services My Individuals Wealth - W labour eamngs Services (Defence Heath. Education, etc) Transfers (Pensions. Benefits. etc) Taxes Figure 6.3.1 UK House Prices I Earnings —house price / earnmg,. V LL Consume ban 0.00 1962 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 2012 326 EFTA00625454

50J completions (k) 250 200 150 '41/ 100 50 Figure 6.3.2 - Housebuilding Competionsi 40J 300 200 103 0 1951 1%1 1971 year 1931 1%1 —0— Private --Social — Local Authority — Total 2001 Figure 6.33 - US House Prices A Home Price Index 0 1885 1905 1925 1945 Year 1965 1985 2005 327 EFTA00625455

7.00 6.00 5.00 4.00 0 3.00 2.00 1.00 0.00 1952 1957 1982 1967 1872 1977 1992 1987 1992 1997 2002 2007 2012 Figure 6.3.4 UK House Prices I Earnings —h ouse puce can —19511970 1971.7009 - 19902009 A 328 EFTA00625456

Fixed-rate vs. floating rate systems Land Rate adjustment (percentage of new business) ' Belgium Denmark Germany Greece Spain France Ireland Italy Luxembourg Netherlands Austria Portugal Finland United Kingdom F (75%). M (19%). V (6%) F (75%), M (10%). V (15%) Mainly F and M F (5%). M (15%). V (80%) V (more than 75%) Fik1/O (86%). V (14%) V (70%), otherwise mainly M F (28%) V (90%) F (74%). M (19%). V (7%) F (75%). V (25%) Mainly V F (2%). V 97%), O (1%) V (72%). M (28%) • Fixed (F). interest rate fixed for more than five years or until final maturity. Mixed (M): interest rate fixed for one to five years. Vanable (V): interest rate renegotiable after one year or tied to market rates or adjustment at the lenders discretion Other (O) Source ECB (2003) Figure 6.3.5 [Hess & Holzhausen] Small stakes make arrears more likely Mortgage loan • to • value ratio 0-10 10.20 20-30 30.40 40.50 50.60 60.70 70.80 80-90 90.100 100-110 >110 0 Figure 6.3.6 10 20 30 Arrears rate (%) 329 EFTA00625457

Figure 7.21 - Binomial Distribution 0.6 1.0 0.0 0.1 0.2 0.1 0.4 nIN 0.5 0 Figure 7.3.1 a NP 64,0 44.4 30.0 17,4 5.7 5.7 17.4 30,0 44,4 64.0 SP 260 280 300 Temperature (K) 320 b NP 64,0 44.4 30.0 '7.4 5.7 5.7 ' 7.4 30,0 44,4 64.0 SP 0 0.2 0.4 0.6 D.8 Fractional cloud cover 0.7 —0— =red - - - Observed 0.8 NP 53.1 36.8 23,5 11,5 0.9 Meridional heat flux (1018 W) Figure 2. Latitudinal distrfttions of (a) mean air temperature. (b) cloud cover. and (c) meridional heat transport in the Earth. Solid line cones indicate those predicted with the constraint of maximum entropy production (equation (9)). and dashed lines indicate those dawned. Reprinted from Pal: ridge (197.9 with permission from the Royal Meteorological Society. 330 EFTA00625458

Fluid cools by losing heat through the surface t i t t t tA 00000 ' ' ' I t ' Heat input Figure 7.3.3 331 EFTA00625459

650 645 640 635 630 625 Mar 25 17 1300 +11.98 +1.92% -7.18 -1.13% -2.26 -0.36% +11.41 +1.82% +1.35 +0.21% GMT Mon 21/3 Tue 22/3 Wed 23s3 Thu 2413 Fri 25/3 Figure 9.2.1 116.00 115.50 115.00 114.50 Mar 25 14 35 OD GMT +0.11 +0.10% +1.29 +1.13% -0.54 -0.47% +0.35 +0.30% +0.32 +0.28% Mon 21/3 Tue 22/3 Wed 23/3 Thu 24/3 Fri 25/3 Figure 9.2.2 332 EFTA00625460

Figure 9.3.2 Z•= 18 TVVe 0 50 100 150 200 250 300 350 W/m' Figure 9.3.1 2 I PIAO .•• °Cremoq cr':':;:.'...'.' ' - ----------- i , , , d.. M A r•O7 ' 1,- - - ... ; 8 A to 1 A Arable land availability, hectares m K Cerrado E Amazon rainforest Sena° in Wetlands 0 Farm 1 GROSSO ! MOW ) 'Crirasclla BOLIVIA GO/AS ----- • - •, SAO IpA81O Rio de o `,_.Vane of o '4) Paranagua. ei Paulo ATLANTIC OCEAN I a In use MN Potential Brazil United States Russia India China Australia Canada Argentina Source: FAO 0 100 200 300 400 500 333 EFTA00625461

N Ew S clENTi sT LETTERS cleared of parasites. With the increasing number of people travelling it might be a good idea if pharmacists made a habit of dispensing warning leaflets along with anti.malarials, describing the symptoms of the disease and urging sufferers to get themselves to a doctor. And roll on the day someone develops an effective vaccine against malaria. Sue Birchmore Sparkhill, Birmingham Crystal clear In "Not liquid gold" (Technology, 13 February) a basic error was made in understanding the physics of fenoelectric liquid crystals (FLCs). The article attributed their behaviour to them "generating a magnetic field". In fact, magnetic fields have almost no part to play in detailing the behaviour of such systems. In an FLC the molecules self- organise in such a fashion that individual molecular dipoles (electrical not magnetic) reinforce to produce a macroscopic electric polarisation. This is then switched in an external electric field. In a flat-panel display surface alignment forces are used to store this induced ordering in the absence of an applied electric field; hence the so called bistability or ferroelectric behaviour. Harry Walton Schuster Laboratory University of Manchester People and particles If Professor Morrison is interested in applying ideas from modem physics to economics ("Complexity: Beyond chaos", special supplement, 6 February), he may be interested in looking at the clear parallels between thermodynamic systems and economic systems. For example, the distribution of wealth between the freely interacting people of a state—typically, a lot of people without very much and fewer people with quite a lot—closely resembles the distribution of energy between freely interacting particles in an open thermodynamic system. This may point to solutions of the eternal problem of capitalism, that although it is 13 Mardi 1993 good at creating wealth, it seems very poor at distributing it. For example, a mathematically trivial (but politically difficult) solution for the elimination of poverty would be the creation of a legally enforceable maximum wealth. If this was set low enough—at double the average wealth—this would produce a statistical distribution close to the distribution of abilities found inhuman societies. Clearly such a solution is impractical as Britain is not a closed system and high energy particles would migrate to the Bahamas, Channel Islands, etc. However, it does point the way to more subtle ways of using statistical theory to create closed systems at low wealth levels which could be "pressurised" by governments, rather than using present systems of taxation and welfare which merely fight the existing statistical distribution head on and are therefore doomed to failure. Mike Willis Kb.* Stephen, Cumbria Giants and dwarfs John Gribbin's article, "On the shoulders of giants" (Forum, 13 February) implies that Newton was the originator of this famous remark. In their informative book, "Blueprints: Solving the mystery of evolution", Maitland A. Edey and Donald C. Johanson give the source as Bernard of Chartres (circa 1100): "We, like dwarfs on the shoulders of giants, can see more and farther, not because we are keener and taller, but because of the greatness by which we are carried and exalted? No mention of dwarfs in Newton's remark but then he wouldn't want to give succour to the vertically-challenged Hooke, would he? John Hunter Fauldhouse, West Lothian Totally phased Tony Lang's article "Through a glass strangely" (Forum. 23 January) on prisms that refract the "wrong way" was no doubt intended to be humorous, but I found it quite disappointing and indicative of a lack of understanding of basic principles in optics. fang's entire thesis is based on the erroneous supposition that the index of refraction is the ratio of the speed of light in a vacuum to the optical group velocity. From this he concludes that materials making up the wrong-way prisms have index less than one and hence one could use such materials for faster-than. light communication and so forth. As every student knows, the index is the ratio of the vacuum velocity to the phase velocity. Lang's conclusion holds only for materials in which the phase and group velocity are the same, materials in which the frequency is proportional to the wave number. This condition in fact holds for no material, but can model dielectrics over a limited frequency range. There are many materials where this is not so and that have index less than one. I have, sitting on my desk, a chunk of photonic band gap material for which the index of refraction is zero at a certain frequency. In this case the phase velocity is infinite! However, no instantaneous communication is possible because—as every student knows—it is the group velocity and not the phase velocity that determines the maximum speed of signal transmission. In fact the group velocity is zero at infinite phase velocity in my chunk of stuff. If I made a prism out of this material, it would refract electromagnetic waves "the wrong way" just as on the Pink Floyd album—one of my favourite records, by the way. Jonathan Dowling US Army Missile Command Redstone Arsenal, Alabama New names Work on a New Dictionary of National Biography has now begun, funded by a grant from the British Academy. The New DNB, which will be published UNISTAT for Windows * NEW * Version 1.2 * UNISTAT lot Windows Is a complete data handling, analysis and presentation package bringing together a powerful spreadsheet. a wide range of statistics and presentation quality 2D and 3D graphics. JA.StAT tenon la We sweat's-vet Iv Iverofc cola handev F.palevoi tin., I 23. fwd. calase2-14. Of. Sek. Led webs* no- DOE alb Exe44 20 sea 30 °dz., plots. pt be. wow caws. T ar bars. conlderce ranies No yfues. I9 <Oa). Onutvia. awe and weboentnisbeitandshans clots 2Dand 30mlferwanfral fvls 7C4 D"a/OnPIC4"." hannolion winter support. Descrettw notate, havarrn.190Untwsontunewrissvonhal 40 prawn andnen penumbra Nut sixties, of feasts. erasion coOfwerita contegivey trams csinvL•bt00.1 w4 Ova. <.n. westa. MO'?A. ANCCVA. chain. dvan•vnt gyvvvid cavemen,. Woe mov.(1,C•S•Ya, Se41ng csnrKIli cenesnon UNISTAT Ltd. Unistat Nous& d Shirland Mows. Maids Vale. London 11/9 SOY Tot: 081 964 1130. Fax 08t 964 0531. 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