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WINTER 2010

V O L . 5 1 N O. 2

GENTRIFICATION Definition, Types of Intervention, Spyros Makridakis, Robin M. Hogarth and Anil Gaba Definition, Types of intervention, Concerns of Gentrification Concerns

As Hogarth showed in 1720 after the South Sea Bubble, people have always expected forecasters to protect them. And forecasters have always been punished for it.

Why Forecasts Fail.

What to Do Instead

By Mr. George-Sp. C. ATHANASOPOULOS Harvard University, Graduate School of Design, Student,

By Mr. George-Sp. C. ATHANASSOPOULOS Architect LEADING Student of the School of Architecture THE QUESTION Technical University of Crete How can Spyros Makridakis, Robin M. Hogarth and Anil Gaba managers use forecasting 1. Introductory approach: Defining the concept tools to plan 1.

Introductory approach: Defining the concept ANTISTHENIS, the ancient Greek philosopher, (444 BC - 370 BC, Athens), effectively and ANTISTHENIS, the ancient Greek philosopher, BC -“principle”: 370 BC, Athens), among other wise heritage he left us, he established(444 great the build better fieldwise of forecasting hasleft advanced significantlya ain recent“principle”: years. amongThe other heritage us,definition he established great acquisition of knowledge startshe with the of the content of concepts. the strategies?

Why Forecasts Fail.

What Why to Do Instead Forecasts Fail.

But managers needstarts to learn from history about what they can and acquisition of knowledge with theindefinition the content of concepts.

Based, therefore, on this “principle” a first, if of not final, approach, the term FINDINGS cannot predict, and develop plans that are sensitive to surprises. most areas of 1 Based, therefore, on this “principle” in a first, if not final, approach, the term (and urban gentrification) is indicated (in the area of Planning) (or XInbusiness, gentrification accurate

BY SPYROS MAKRIDAKIS, ROBIN M. HOGARTH AND ANIL GABA 1 forecasting is not gentrification (and urban gentrification) indicated (in thefrom areathis, of Planning) (or possible. Future Sociology as well), as the “refining” of a cityisarea, the removal (in various is Sociology as well), as the “refining” of a city area, fromthere this, of (inartists, various uncertainty ways), of social groups, usually of low-income andthe theremoval placement much greater than most managers ways), of social groups, usually of low-income and the placement there of artists, the operation of art galleries, restaurants, etc. However this “change”, regardless of acknowledge.

IT SEEMS LIKE a long time ago in a galaxy far, far away. But in reality it was 2006, on this very the operation ofconsequences art galleries, restaurants, etc.also However this “change”, regardless of XStatistical regularity whatever other has, results rising of land prices (and the planet. The entire world was booming, partly on the back of triple-A investment innovations devised not imply whatever otherspeculation). consequences has, results also rising of land prices (and the does predictability. potential by relative a master race of financial Jedi. And then: crash, bang, global recession. Suddenly it was all over. of seeking potential relative speculation).

Triple-A turned into a euphemism for “subprime,” which began translate into “toxic.”

The term gentrification is found at first in theitself UK in to early 1960s and itThe refers to XInstead predictability, Thebanking term gentrification first UK in earlyor1960s and itareas refersofto managers should F Oout R Ewith C Sfound Tbonuses I N Gat Jedi were trend cast —people many in intothe bankruptcy, takeover nationalization. the then observed ofAisno wealthy to buy property in poor channel their Welcome to the empire of the credit crunch. the then observed trend wealthy people to there buy property in poor areas R E P R I N Tefforts N U M B Einto R 5being 1214 London, upgrade them, stay of themselves sometimes and thus old residents areof prepared for By now, it’s a story as well known as “Star Wars.”sometimes But what fascinates us about the storyold of theresidents crisis London, upgrade them, stay themselves there and thus are different being indirectly “squeezed”. contingencies. is one single, often overlooked fact — that almost no one saw it coming: none of the experts, none of being indirectly “squeezed”.

A description of this phenomenon is the included the work of Sociologist academics,in none of the politicians and, as far as Ruth models were capable of emoti A description ofperiod, this phenomenon iswesituations included the work ofSoSociologist Ruth GLASS at the same while similar were recorded inthink other major WINTER 2010 SLOAN MANAGEMENT 83 know, none ofin the banking CEOs. we it’s MIT surprised by the size REVIEW of their erro GLASS at the same period, while similar situations were recorded in other major ■ On a more positive note, averagi time for business experts and practitioners to come cities in Western countries, by other Researchers.

ABOUT THE predictions of several individua to termsseveral with the reality, harsh as it and is, that for accurate cities in Western countries, bypreoccupied other Researchers.

Since then, the issue has scholars its more RESEARCH or not) generally improves forec forecasts simply aren’t possible in their world.

(See Since then, the issue preoccupied several below, scholars andthe for various its more The origin ofhas the research for comprehensive approach are being summarized from Averaging forecasts based o “About the Research.”)

In addition to highlighting this article is referenced in comprehensive approach are being summarized below, from the various interpretations of the phenomenon the sidebar “Why Simple of gentrification, R E Psolace R I N T N UinM B E R model 5 1 2 1 4 also improves accuracy. that alarming point,the we’dfollowing: like to offer some interpretations the phenomenon the following: Statistical Models is Aredue Bet- of In a sense, theof phenomenon togentrification, a trend a new category of social These empirical conclusions r the form ofof an analogy with natural disasters.

We’ll groups ter.” After Spyros Makridakis anyone making business decision also use our earthquake and hurricane comparisons to “return” to the city,finished leaving the purlieus for several reasons: high costs in money his first study on to examine twowhere types of work uncertainty.

Finally, we’ll ofmanagers forecasting using the 111 to downtown, and time to travel from the purlieus place is, lack the formulate a strategy, le time series, he approached context provide a framework for making decisions, plans termat comes from Sociologist Ruth GLASS, 1912-1940.

Ruth GLASS wasbetter born inof high uncertainty and sense1.ofThe safety the distributed residencies outside town centres, search for Robin M. Hogarth, a cognican’t even imagine? and strategies in the absence accurate forecasts.

Berlin, where she made her first studies. In 1932 she published anofimportant study entitled: tive psychologistentertainment who was services of health, education, “at theweheart of the city”,movements (possibly) Fundamentally, believe that business needs a Youth Unemployment.atThe same year she left Germany and after continuous for the time a colleague. lower living cost of, “withdrawal” from private car easier access to markets, etc. studies and research in“Since Geneva, Prague, London and New York she came back to London, where The Sucker That Could whole new attitude toward the future. sophisticated statistiin According 1943 she published regarding cityphenomenon planning. In 1950 sheto became teacher Have in theGone Down to another approach, is due a systematic and calstudies forecasting methods the University informal College of London, where socialof research.

Her public andpursuing an answer, let’ don’t work so well, ” she continued A Briefher History Prediction Before long-term effort by organized groups, manufacturers, brokers ofaction buying Makridakis “perhapsfor justice. See also: COLLINS ENGLISH DICTIONARY. her work are characterized by asaid, passion in the Social Sciences was arguably the worst day so far and selling realCOLLINS estate,oneetc., theCo depreciation initially of part of the urban web, in shouldfor advocate the use London 2009.

10th edit. Wil. SONS AND Ltd. WIKIPEDIA: The Free Encyclopedia: To understand our fascination with the shortcomsis — Friday, October 10, 2008, w of intuition?”

“No way, ” reG. ALEXANDRI: http://www.uncanny.net/ wetzel/gentry.htm a Gentrification: variety of ways, in order Abstract. to achieve the “assisted”, “voluntary”, (actually

What to Do Instead

COURTESY OF WIKIPEDIA/ SCANNED FROM THE GENIUS OF WILLIAM HOGARTH OR HOGARTH’S GRAPHIC WORKS

plied Hogarth. “Research in psychology shows that simple statistical models predict more accurately than the judgments of even highly qualified professionals in difficult diagnostic tasks.” It turned out that Hogarth had also done work on prediction showing how, although far

ings of prediction, we invite you to travel back in time to an episode that occurred in our world of business school academia in the 1970s and 1980s. At that time, business professors and other social scientists hoped that post-space-age computing technology and sophisticated models would enable them to have the same success in forecasting as their colleagues in the physical sciences had. For a variety

Industrial Average experienced point drop in history (679 points 1311 2521 many companies went into free f Some six months earlier, H U.S. Secretary of the Treasury, w statements: I have great, great confidence in markets and in our financial in

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ings prediction, wein invitemodel you to travel back inacc done work on prediction plied Hogarth.

“Research the sidebar “Why Simple improves that alarming point,inwe’dalso like to of offer some solace colleaguesalso in the physical s how, although farthat occurred in our world of Statistical Models Are Bet- psychology shows that sim- showing time to an episode These empirical conc the form of an analogy with natural disasters. We’ll of reasons, these hopes w perfect, simple models ter.” After Spyros Makridakis ple statistical models predict from business school academia in the 1970smaking and 1980s. At anyone also use our than earthquake and hurricane comparisons empirical evidencebusines has dem can perform surprisingly well more accurately the F O R E C A S T I N G finished his first study on that time, business professors and other social scimanagers to examine two types ofcompared uncertainty.

Finally, with both morewe’ll ■ The judgments of even highly FORECASTING forecasting using the 111 futureformulate is often aabist entists hoped that post-space-age complex statistical models professionals in time series, he approached qualified contextthe ofcomputing high provide a framework for making decisions, plans exactly same.uncerta That m intuitive judgment. diagnostic tasks.” It andtechnology Robin M. Hogarth, a cogni- difficult and sophisticated models would enable can’t even imagine? and strategies in the absence of accurate forecasts. patterns and relationship In the to late 1970s, turned out that Hogarth had tive psychologist who was them have the same DEV. success in forecasting as their Fundamentally, we believe that business needs a of ture E¶.A¶.

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Instead, how people can planhopes ac- were fromby simple models cal time forecasting methods Have Gone we know, none of the banking CEOs. So we think it’s surprised the size of their els that can —Down and th ■ On a more positive note, averaging thefit independen for business experts andperfect, practitioners toerrors, comeontoo. empirical evidence the following: tions in situations wherehas it is demonstrated canA perform surprisingly well don’t work so well,” ■ On a more ABOUT THEand practitioners Brief History of Prediction Before pursuing an an positive note, averaging the independent time for business experts to come almost perfectly.

Howev predictions of several individuals (whether expert to terms with the reality, harsh as it is, that accurate impossible to rely on accu- a bit like the past, but never compared with both more Makridakis said, “perhaps ABOUT RESEARCH F O R ETHE C A S T I N G to terms with ■ The future is often in the Social Sciences was arguably thepredict worst 1 d predictions of several individuals (whether experts the reality, harsh as it is, that accurate don’t necessarily t or not) generally improves forecasting accuracy. forecasts simply aren’t possible in their world.

(See The work RESEARCH The origin of the research for one should advocate the use complex statistical models rate predictions. exactly the That means that extrapolating 1 same.

To understand our fascination with the shortcomsis — Friday, October 10 generally improves forecasting accuracy. forecasts simply aren’t possible in in their world. (See took many years and multiConversely, simple statist and intuitive judgment. of intuition?”

“No way,”or re-not)In Averaging forecasts ■based on more than one “About the Research.”) addition to highlighting The origin of the research for this article is referenced patterns and relationships from the past to the fuings of prediction, we invite you toalso travel back inaccuracy.

Industrial Average expe ple digressions, asimproves they In the late 1970s, plied Hogarth.

“Research in based on more than one “About thethe Research.”)

InSimple addition to highlighting this article is referenced in sidebar “Why the past very well, but th model that alarming point,Averaging we’d like toforecasts offer some solace in ture can’t provide accurate predictions. pursued their individual Makridakis and Hogarth repsychology shows that simthe sidebar “Why Simple Statistical Areto Bettime to andisasters. episodeWe’ll that occurred in our worldconclusions of predicting pointraise dropthe in future history (6 model also improves accuracy. that alarming point,Models we’d like offer some in an analogy These empirical vital issuesthan fo the solace form of with natural careers on different contisolved to pursue research the academics, of Makridakis the politicians and, as far as predict modelsbusiness were capable of emotion, would be1980s. ple statistical models Statistical Models Are Bet■ they There arefor plenty of statistically sophisticated mod- i ter.” Afternone Spyros school academia the 1970s and At decisions: many companies These empirical conclusions raiseinvital issues the form of an analogy with natural disasters. terparts.(See “Why Simpl anyone making business How canwent senio also useWe’ll our than earthquake and hurricane comparisons nents. in 2006, they on how can ac-errors, more accurately the surprised ter.” After Spyros Makridakis finished histhe firstbanking study onCEOs. we know, none of So we think it’s bypeople the size ofplan their too. elsBut that can fit — and thus “explain” — past dataea that time, business professors and other social sciSome six months anyone making business decisions: How can senior also use our earthquake and hurricane comparisons ■ Empirical evidence up with Anilformulate Gaba, a a strategy, let alone a plan,has in a to examine two types oftions uncertainty.

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However, U.S. theseSecretary complex of models entists tohoped post-space-age the Tr managers formulate a strategy, let alone a plan, in ahigh to examine two typesheofapproached uncertainty.qualified Finally, we’ll decision scientist, who enimpossible rely on that accuprofessionals in forecasting using the 111 time series, judgment is even worse ABOUT THE context ofcomputing uncertainty and futures that they provide a framework for making decisions, plans predictions of several individuals (whether experts to terms withM. theHogarth, reality, aharsh as itdifficult is, thatdiagnostic accuratetasks. don’t necessarily predict the statements: future quite as well. couraged the collaboration predictions.

The work Mr. George-Sp. C.and ATHANASOPOULOS ” It rate time series, he approached cogni- decisions, and sophisticated models would enable RESEARCH oftechnology high uncertainty futures that they provide a Robin framework for making plans By than are statistical mode can’t even imagine? and strategies incontext the absence of accurate forecasts.

1 or not) generally improves forecasting accuracy. forecaststive simply aren’t who possible in their that■led toforecasting this article and astatistical models took manytoyears and multisimple don’t explain turnedworld. out that(See Hogarth had Robin Hogarth, cogni- for and TheM. origin of the aresearch them have the same success in as their I have con Harvard University, Graduate School of Conversely, Design, Student, can’t even imagine? strategiespsychologist in the absence was of accurate forecasts.

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In additionalso to done highlighting article is referenced the past very well, but they generally are better atfin colleagues in the physical sciences had.

For a variety markets and in our Fundamentally, we believe that business needs a By Mr. George-Sp. C. ATHANASSOPOULOS Architect than a moderately well-i The Sucker That Could whole new attitude toward the future.

Making Luck Work For You pursued their individual showing although far at the time a colleague.

“Sincepoint, sophisticated statistisidebar “Why Simple model also improvesthese accuracy. that alarming we’d like to offer some how, solace in the future than are their complex counofStudent reasons, hopes werepredicting unfounded.

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That extrapolating in the Social Sciences wasfascination arguably the worst day so far in means thejudgment present criTo understand our with the shortcomsis — Friday, October 10, 2008, when the Dow Jone couraged the collaboration and intuitive judgment. one should advocate the use “Nofor way, ” retime series, he approached context ofpatterns high uncertainty and futures that theyto themodels. provideofa intuition?” framework making decisions, plans than are statistical President George W. Bu and relationships from the past To understand our fascination with shortcomOctober 10, 2008, Dow Jones MIT SLOAN MANAGEMENT REVIEW WINTER 2010 one-day that led to this and awhen prediction, weFriday, invite you to article travel back in84 the Industrial Average fuexperienced its largest In theoflate 1970s, sis — of Robin intuition?”

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■ In fact, an expert doesn’t predict more accurately ful that summer.

On Julo can’t provide accurate predictions.

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However, theseSecretary complex models continue incre that time, qualified businessprofessionals professors inand other socialtohoped sciSome sixalmost months earlier, Henry■Paulson, the are entists post-space-age computing U.S. of the Treasury,exports was making upbea impossible rely on that accujudgments of so even highly don’t work well, ” A Brief History of Prediction Before pursuing an answer, let’s go back to what extent of their forecasting mistakes.

If statistical don’t necessarily predict the future quite as well. productivity remains entists hoped that post-space-age computing U.S. Secretary of the Treasury, was making upbeat 1 predictions.and The work qualified professionals in difficult diagnostic tasks.” It ratetechnology sophisticated models would enable statements: Makridakis said, “perhaps in theturned Social Sciences was arguably the worst day so far in the present crimany multi■ Conversely, simple statistical models don’t explain confidence in the long difficult diagnostic tasks.the ” It use technology out1that Hogarthmodels had took and sophisticated would enable one should advocate them toyears haveand thestatements: same success in forecasting as their I have great, great confidence in our capital To understand our fascination with the shortcomsis —84 Friday, October 10, 2008, when the Dow Jones MIT SLOAN MANAGEMENT REVIEW WINTER 2010 ple digressions, as they turned out that Hogarth had also done work on prediction of intuition?”

“No way, ” rethegreat past very well, but they generally are better atfinancialour economy.…

I thin them to have the same success in forecasting as theirin the physical I have sciences great, confidence in our capital colleagues had.

For a variety markets and in our institutions.

Our pursued individual also done work on predictionin showing how,we although ings of prediction, invitefar you to traveltheir back in Industrialpredicting Average experienced its largest one-day counplied Hogarth.

“Research the future than are their isand sound.

I truly do.3 colleagues in the physical sciences had. For a varietythese hopes markets andunfounded. in our financial institutions.

Ourcomplex of reasons, were Instead, financial institutions, banks investment careers on different contishowing how, although far perfect, simple models in our world of psychology shows that simtime to from an episode that occurred point dropterparts.(See in history (679 points) and the shares of “Why Simple Models Areare Better.”) these hopes were unfounded.

Instead, institutions, and investment But in 2006, they financial empirical evidence has demonstrated thebanks following: banks strong. Our capital markets are from simple models can perform surprisingly well nents. pleperfect, statistical models predict of reasons, business school academia in the 1970s and 1980s. At many companies went into free fall.

■ Empirical has also that human But by lateflexible.

September, t 2 linked up with Anil is Gaba, a a bit empirical evidence the banks are strong.

Ourevidence capital markets areshown canmore perform surprisingly well comparedhas withdemonstrated both more accurately than the ■ following: The future often like the past, but never resilient.

They’re efficient.

They’re that time, business professors and other social sciSome six months earlier, Henry Paulson, the 2 decision scientist, who encompared with complex statistical judgments ofboth evenmore highly judgment is even worseflexible. at predicting the future son warned: ■ The future is often a bit models like the past, but never They’re They’re exactly the same.resilient.

That means thatefficient. extrapolating entists and hoped that post-space-age computing U.S. Secretary the Treasury, was making upbeat couraged the collaboration complex statistical models intuitive judgment. qualified professionals in thanof are The outwardly market turmoil exactly the same.

That means that extrapolating President George W. Bush stayed cheerw patterns and relationships from thestatistical past to themodels. futhatwould led to this article and a and intuitive judgment. thesophisticated late 1970s, difficult diagnostic tasks.” It technologyInand models enable statements: ■ In fact, anBush expert doesn’t predict more accurately poseshe great risk to U.S President George W. stayed outwardly cheerpatternsMakridakis and relationships from the past to the fuful that summer.

On July 15, 2008, said: ture can’t provide accurate predictions. book, Dance With Chance: In the late 1970s, and Hogarth returned out that Hogarth had them to have the same success in forecasting as their I have great, confidence in our capitalintelligent man thansophisticated agreat moderately well-informed, ful summer.

On July 15, 2008, he said: Our economy has continuedfinancial ture can’tsolved provide accurate predictions.

Making Luckare Work For You Makridakis Hogarth reto pursue research also doneand work on prediction ■ There plenty ofthat statistically modgrowing,system con- doesn colleagues in the physical sciences had.

For a variety markets and in our financial institutions.

Our (Oneworld, 2009). solved to pursue research far onplenty how people can plan acor woman on the street.

Americans’ personal s showing how, although ■ There are of statistically sophisticated modOur economy has continued growing, conels that can fit — and thus “explain” — past data sumers are spending, businesses are investing, of reasons, these hopeswhere were unfounded.

Instead, financial institutions, banks andextremely investment onfrom how perfect, people can planmodels actionsfit in— situations it is simple ■ Human beings are often surprised by the consumers and busine els that can and thus “explain” —almost past data sumers are spending, businesses are investing, perfectly.

However, these complex models exports continue increasing and American tions situations where it is impossible relydemonstrated on accuempirical evidencetohas the following: banks are strong. Our capital markets are caninperform surprisingly well extent their forecasting mistakes.

If statistical and job cr almost perfectly. However, these complex models exportsthe continue increasing and American don’t necessarily predict future of quite as well. productivity remains strong.investment We can have impossible towith rely both on accurate predictions. compared more ■ The future is often aThe bitwork like the past, but never resilient. They’re efficient. They’re flexible.2 don’t necessarily predict the future quite as well. productivity remains strong.

We can have rate predictions.

The work took many years and multi■ Conversely, simple statistical models don’t explain confidence in the long-term foundation of complex statistical models exactly the same. That means that extrapolating 84 don’t MIT SLOAN MANAGEMENT REVIEW WINTER 2010 foundation of took many years and multi■ Conversely, simple statistical in the long-term ple digressions, as theymodels and intuitive judgment. theexplain past very well,confidence but they generally are better at our economy.… I think the system basically President George W. Bush stayed outwardly cheerpatterns and relationships from the past to the fuple digressions, they their individual In the late as 1970s, the past pursued very well, but they generally arepredicting better at the future ourthan economy.… think the counsystem basically are theirI complex is sound. I truly do.3 ful that summer. On3 July 15, 2008, he said: ture can’t provide accurate predictions. pursued their individual careers on different contiMakridakis and Hogarth repredicting the future than are their complex coun- “WhyisSimple sound. Models I truly do. terparts.(See Are Better.”) careers contiBut inof2006, they sophisticated solvedontodifferent pursue research ■ There nents. are plenty statistically modOur economy has continued growing, conterparts.(See “Why Simple Models Are Better.”)

■ Empirical evidence has also shown that human But by late September, the tone had changed. Paul nents.

But in 2006, they linked up with Anil Gaba, a on how people can plan acels that can fit — and thus “explain” — past data sumers are spending, businesses are investing, evidence has who also enshown that human is even But by late at September, had changed.

Paullinked Anil Gaba, a it is ■ Empirical decision scientist, tionsupinwith situations where judgment worse predictingthe thetone future son warned: almostcouraged perfectly.

However, these complex models exports continue increasing and American decision scientist, who collaboration impossible to rely on enaccujudgment is eventhe worse at predicting the son warned: thanfuture are statistical models.

The market turmoil we are experiencing today don’t necessarily predict future quite as well. productivity remains strong. We can have couraged the collaboration led to this articlethe and a rate predictions.

The work than arethat statistical models. market turmoil weaccurately are experiencing today ■ In fact, an expert The doesn’t predict more poses great risk to U.S. taxpayers. When the that ledmany to thisyears article and a book, Dance Chance: took and multi■ Conversely, simpleWith statistical models don’t explain confidence in the long-term foundation of ■ In fact, an expert doesn’t predict more accurately poses great risk tointelligent U.S. taxpayers. than a moderately well-informed, man When the financial system doesn’t work as it should, book, Dance With Chance: Making Luck Work For You ple digressions, as they the past very well, but they generally are better at our economy.… I think the system basically than a moderately intelligent man on the financial work as it should,Americans’ personal savings, and the ability of Making Luck Work For You (Oneworld, well-informed, 2009). or woman street. system doesn’t pursued their individual 3 predicting the future thanfrom are their complex counis sound. I 1912-1940. truly do.

The term comes Sociologist Ruth GLASS, Ruth GLASS born in (Oneworld, 2009). or1.woman on the street. personal savings, of was careers on different conti■ Human beings areAmericans’ often extremely surprised byand the the ability consumers businesses to finance spending, Berlin, where “Why she made her first studies. In 1932 she published an important studyand entitled: terparts.(See Simple Models Are Better.”) nents. But in 2006, they 4 ■ Human beings are often extremely surprised by the consumers and businesses to finance spending, extent ofshe theirleft forecasting mistakes.

If statistical investment and job creation Youth Unemployment.

The same year Germany and after continuous movements for are threatened.

■ Empirical evidence has also shown that human But by late September, the tone had changed.

Paullinked up with Anil Gaba, a extent of their forecasting mistakes. If statistical investment and job creation are threatened.4 and research in at Geneva, Prague, London New York she came back to London, where decision scientist, who en- studies judgment is even worse predicting the future son and warned: e politicians and, as far as models were of emotion, they would be 2010 MITcapable SLOAN MANAGEMENT REVIEW WINTER SLOANREVIEW.MIT.EDU she published studies regarding city planning.

In 1950 became teacher in the couraged the collaboration in 1943 84 than are statistical models.

The market turmoil we areshe experiencing today ingthat CEOs. wearticle thinkand it’sa REVIEW surprised byCollege the size ofoftheir errors, too.

84 MIT SLOAN MANAGEMENT WINTER 2010 SLOANREVIEW.MIT.EDU led toSo this University London, where she continued her social research.

Her public action and ■ In fact, an expert doesn’t predict more accurately poses great risk to U.S. taxpayers. When the Dance With ■ On a more positive note, averagingby theaindependent andbook, practitioners toChance: come her work are characterized passion for justice. See also: COLLINS ENGLISH DICTIONARY. than a moderately well-informed, intelligent financial system doesn’t work as it should, Making Work For You 10th predictions of several individuals (whether arsh as it Luck is, that accurate edit. Wil. COLLINS SONS ANDexperts Coman Ltd. London 2009. WIKIPEDIA: The Free Encyclopedia: (Oneworld, 2009). or woman on the street.

Americans’ personal savings, and the ability of 1

GENTRIFICATION Definition, Types of Intervention, Definition, of intervention, ConcernsTypes of Gentrification Concerns

1. Introductory approach: Defining the concept 1. Introductory approach: the concept (444 BC - 370 BC, Athens), ANTISTHENIS, the ancientDefining Greek philosopher, ANTISTHENIS, the ancient Greek philosopher, BC -“principle”: 370 BC, Athens), among other wise heritage he left us, he established(444 a great the among other wise heritage leftthe us,definition he established a greatof“principle”: acquisition of knowledge startshe with of the content concepts. the acquisition of knowledge starts with theindefinition the content of concepts.

Based, therefore, on this “principle” a first, if of not final, approach, the term Based, therefore, on this “principle” in a first, if not final, approach, the term (or gentrification (and urban gentrification) is indicated (in the area of Planning) gentrification (and urban gentrification) is indicated (in the area of Planning) (or Sociology as well), as the “refining” of a city area, the removal from this, (in various Sociology as well), as the “refining” of a city area, the removal from this, (in various ways), of social groups, usually of low-income and the placement there of artists, ways), of social groups, usually of low-income and thethis placement of artists, the operation of art galleries, restaurants, etc. However “change”,there regardless of the operation of art galleries, restaurants, etc.

However this “change”, regardless whatever other consequences has, results also rising of land prices (and theof whatever otherspeculation). consequences has, results also rising of land prices (and the potential relative potential relative speculation).

The term gentrification is found at first in the UK in early 1960s and it refers to The term gentrification found atpeople first in the UK in early 1960s and itareas refersofto the then observed trend ofiswealthy to buy property in poor the then observed trend of wealthy people to buy property in poor areas London, upgrade them, stay themselves sometimes there and thus old residents areof London, upgrade them, stay themselves sometimes there and thus old residents are being indirectly “squeezed”. being indirectly “squeezed”.

A description of this phenomenon is included in the work of Sociologist Ruth A description ofperiod, this phenomenon is situations included inwere the recorded work of Sociologist Ruth GLASS at the same while similar in other major GLASS at the same period, while similar situations were recorded in other major cities in Western countries, by other Researchers. cities in Western countries, bypreoccupied other Researchers.

Since then, the issue has several scholars and for its more Since then, the issue has several below, scholars andthe for various its more comprehensive approach arepreoccupied being summarized from comprehensive approach are being summarized below, from the various interpretations of the phenomenon of gentrification, the following: interpretations of the phenomenon of gentrification, the following: In a sense, the phenomenon is due to a trend of a new category of social groups to “return” to the city, leaving the purlieus for several reasons: high costs in money and time to travel from the purlieus to downtown, where work place is, lack of the sense of safety at the distributed residencies outside town centres, search for better services of health, education, entertainment “at the heart of the city”, (possibly) lower living cost of, “withdrawal” from private car easier access to markets, etc.

According to another approach, the phenomenon is due to a systematic and long-term informal effort by organized groups, manufacturers, brokers of buying and selling real estate, etc., for the depreciation initially of part of the urban web, in G. ALEXANDRI: Abstract. http://www.uncanny.net/ wetzel/gentry.htm variety of ways, inforecasting orderaccuracy. to achieve the “assisted”, “voluntary”, (actually or not) generally improves ssible in their world. (See a Gentrification:

■ Human beings are often extremely surprised by the Averaging forecasts based on more than one addition to highlighting extent their forecasting 14in model alsoof improves accuracy. mistakes. If statistical ike to offer some solace These empirical conclusions raise vital issues for th natural disasters. We’ll MIT SLOAN MANAGEMENT REVIEW WINTER 2010 anyone making business decisions: How can senior d 84 hurricane comparisons managers formulate a strategy, let alone a plan, in a uncertainty. Finally, we’ll context of high uncertainty and futures that they making decisions, plans can’t even imagine? nce of accurate forecasts. ve that business needs a

consumers and businesses to finance spending, investment and job creation are threatened.4

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GENTRIFICATION Definition, Types of Intervention, Definition, of intervention, ConcernsTypes of Gentrification Concerns

President Bush was reportedly less circumspect, WHY SIMPLE STATISTICAL MODELS ARE BETTER DuringWHY the 1970s, one of the authors, a statistician who was working in aBETTER busiwas reportedly circumspect, SIMPLE STATISTICAL MODELS ARE BETTER Bush was reportedly less circumspect, WHY SIMPLE STATISTICAL MODELS ARE stating: President “IfPresident moneyBush isn’t loosened up, less this sucker ness school, realized thatone executives were deeply preoccupied with forecasting.

During thethe 1970s, of the authors, a statistician who was working in ainbusiDuring 1970s, one of the authors, a statistician who was working a busi“If5“If money isn’t loosened up,up, thisthis sucker money isn’t loosened sucker couldstating: gostating: down.”

Their main interest was business and economic data: the sales of their prodness school, realized thatthat executives were deeply preoccupied with forecasting. ness school, realized executives were deeply preoccupied with forecasting.

5 5 could go down.” could down.”

So much forgothe politicians. What about the proucts, their company’s profits and exports, and information about exchange Their main interest waswas business and economic data: thethe sales of their prodTheir main interest business and economic data: sales of their prodmuch foritfor the politicians.

What about thethe proSo much politicians.

What about professionalsSowhose job is the to forecast?

Well, they didn’t rates and industrial output …profits things like that. ucts, their company’s and exports, andand information about exchange ucts, their company’s profits and exports, information about exchange fessionals whose job itsome isittoispublic forecast?

Well, they fessionals whose to forecast?

Well, they didn’t The statistician was concerned practitioners were making their forecasts rates andand industrial output …that things likelike that. fare much better.

Here arejob statements bydidn’t rates industrial output … things that.

Bywithout Mr. George-Sp. C.concerned ATHANASOPOULOS the of thewas latest, most theoretically sophisticated methods.

Thebenefit statistician concerned thatthat practitioners were making their forecasts The statistician was practitioners were making their forecasts farefare much better.

Here areare some public by by much better.

Here some public statements the International Monetary Fund during the statements period: Instead, they seemed to prefer simpler techniques, whichStudent, they could at methods. least Harvard University, Graduate of Design, without thethe benefit ofSchool the latest, most theoretically sophisticated without benefit of the latest, most theoretically sophisticated methods. thethe International Monetary Fund during the period: International Monetary Fund during the April 2007: “Notwithstanding the recent bout of period: explain to theirthey bosses.

And so the statistician decided to teach them a lesson.

Instead, seemed toC. prefer simpler techniques, which they could at least Instead, they seemed to ATHANASSOPOULOS prefer simpler techniques, which they could at least George-Sp. Architect 2007: “Notwithstanding thelooks recent bout of of ByHeMr. April 2007: “Notwithstanding the recent bout financialApril volatility, the world economy still well embarked ontheir a research project demonstrate the superiority explain to bosses.

AndAnd sothat the statistician decided to teach them aoflesson. explain to their bosses. so would the statistician decided to teach them a lesson.

Student of the School of Architecture 6 financial volatility, the world economy still looks well financial robust volatility, the world economy still looks well the latest statistical techniques. set for continued growth in 2007 and 2008.”

He He embarked on aonresearch project thatthat would demonstrate thethe superiority of of embarked a research project would demonstrate superiority 6 6 The professor and his research assistantUniversity set about collecting sets of Technical of many Crete the latest statistical techniques. set set forfor continued robust growth 2007 andand 2008.” the latest statistical techniques. continued robust growth in 2007 2008.”

October 2007: “The problems in in credit markets economicThe and business data over time from a wideset range of collecting economic andmany busiprofessor and his research assistant about many setssets of of The professor and his research assistant set about collecting October 2007: “The problems in credit markets October 2007: “The in is credit markets have been severe, and while theproblems first phase now ness sources.

They came up with 111 different time which then andand economic andand business data over time from a series, wide range ofthey economic busieconomic business data over time from a wide range of economic busi1.

Introductory approach: Defining the concept have been severe, and while the first phase is now have been severe, and while the first phase is now over, we are still waiting to see exactly how the conused to mimic the real process of Each series was split into two ness sources.

They came upforecasting. with 111111 different time series, which they then ness sources.

They came up with different time series, which they then 1.

Introductory approach: Defining the concept over, we are stillout. waiting see exactly thethe conover, we are still waiting topoint, see exactly how consequences will play ... Atto this wehow expect earlier andthe later data.

The researchers simply pretended that the later used todata mimic real process of -forecasting.

Each series was split into twotwo used to mimic the real process of370 forecasting.

Each series was split into ANTISTHENIS, the ancient Greekparts: philosopher, (444 BC BC, Athens), will play out. ... At thisthis point, wewe expect part hadn’t happened yet and proceeded fitresearchers various statistical techniques, parts: earlier data and later data.

Theto researchers simply pretended thatthat thethe later sequences will play out. ...

At point, expect parts: earlier data and later data.

The simply pretended later globalsequences growth to slow in 2008, but remain at a buoyANTISTHENIS, the ancient Greek philosopher, (444 BC 370 BC, Athens), among other wise heritage he left us, he established a great “principle”: the both simple and sophisticated, to the earlier data.

Treating that earlier data as partpart hadn’t happened yetyet and proceeded to fit statistical techniques, 7 growth hadn’t happened and proceeded tovarious fit various statistical techniques, global to slow in 2008, butbut remain at aatbuoyglobal growth to slow in 2008, remain a buoyant pace.” among wise heritage leftthe us, he established a great the “the past, ” simple they used both approaches “the future, ” then back both and sophisticated, toto the earlier data.

Treating thatsat earlier data as as acquisition of knowledge startshe with definition ofand the content of“principle”: concepts. both simple sophisticated, topredict the earlier data.

Treating that earlier data 7 7 other ant pace.” ant pace.”

April 2008: “Global growth is projected to slow anddefinition compared their with what had happened. “the past, ” they used both approaches toof predict “the future, ” then sat sat back “the past, ”“predictions” they used both approaches toactually predict “the future, ” then back acquisition of knowledge starts with the of the content concepts.

Based, therefore, on this “principle” in a first, if not final, approach, the term April 2008: “Global growth is to slow April “Global growth is projected to slow to 3.7% in 2008 ...2008: Moreover, growth is projected projected to Toand theand theoreticians’ chagrin, the practitioners’ simple techniques turned compared their “predictions” with what had actually happened. compared their “predictions” with what had actually happened.

1 (andgrowth Based, therefore, this “principle” inbeindicated aTo first, if (in not final, approach, the term i togentrification 3.7% in 2008 ... Moreover, is projected to to to 3.7% inunchanged 2008 ... Moreover, growth isgentrification) projected out is to more accurate than the their own statistically sophisticated methods. urban area ofpractitioners’ Planning) (or the theoreticians’ chagrin, the practitioners’ simple techniques turned remain broadly in 2009. ...on The U.S. To the theoreticians’ chagrin, the simple techniques turned 1 (and i i In out theout wake of his embarrassment, the statistician searched for a way tomethods. to be more accurate than their own statistically sophisticated methods. remain broadly unchanged in 2009. ...

The U.S. to be more accurate than their own statistically sophisticated remain broadly unchanged in 2009. ...

The U.S. gentrification urban gentrification) is indicated (in the area of Planning) (or economy will tip into a mild recession in 2008 as Sociology as well), as the “refining” of a city area, the removal from this, (in various explain why that was so.

His rationale: Complex models try to find nonexistent In the wake of his embarrassment, the statistician searched for a way to In the wake of his embarrassment, the statistician searched for a way to economy willwill tiptip into a mild recession inthe 2008 as as of a city area, the removal from this, (in various economy into a mild recession in 2008 the result of mutually reinforcing cycles in Sociology as well), as the “refining” ways), of social groups, usually of low-income and the placement there ofmodels artists, patterns in past data; simple models ignore such “patterns” and extrapolate explain why that waswas so.

HisHis rationale: Complex models tryjust to find nonexistent explain why that so. rationale: Complex try to find nonexistent thethe result of of mutually reinforcing cycles in thethe result mutually reinforcing cycles housing and financial markets, before starting a in trends.

The professor also went on to repeat the “forecasting hindsight” patterns in past data; simple models ignore such “patterns” and justjust extrapolate ways), of social groups, usually of low-income and the placement there ofwith artists, patterns in past data; simple models ignore such “patterns” and extrapolate the operation of art galleries, restaurants, etc.

However this “change”, regardless of housing andin financial markets, before starting a a housing and financial markets, before starting modest recovery 2009 as balance sheet problems experiment many times over the years, large setswith ofwith data and trends.

TheThe professor also went onusing to thethe “forecasting hindsight” trends. professor also went onrepeat toincreasingly repeat “forecasting hindsight” the operation of art galleries, restaurants, etc.

However this “change”, regardless of whatever other has, results also rising of land prices (and the ii But 8 problems more experiment powerful computers. the same empirical truth came back each time: modest recovery inare 2009 asconsequences balance sheet many times over the years, using increasingly large setssets of data andand modest recovery in slowly 2009 asresolved.” balance sheet problems experiment many times over the years, using increasingly large of data in financial institutions ii But ii land whatever other consequences has, results also rising of prices (and the 8 8 Simple statistical models are better at forecasting than complex ones. more powerful computers. thethe same empirical truth came back each time: more powerful computers.

But same empirical truth came back each time: in financial institutions are slowly resolved.” potential relative speculation). in financial institutions are slowly resolved.”

October 2008: “The world economy is entering Simple statistical models areare better at forecasting than complex ones. statistical better at forecasting than complex relative speculation).

October 2008: “The world economy isis entering October 2008: “The economy isfound entering at first in Simple a major potential downturn in the face ofworld the most dangerThe term gentrification the UK in models early 1960s and it refers to ones. a major downturn in gentrification the face of the most a major downturn in the face of the most dangerThe term iswealthy found atpeople first in letting the UK in early and itareas refersofto it. However, before ourselves off the1960s hook, ous financial shock in mature financial markets the then observed trend ofdangerto buy property in poor it. However, before letting off the hook, financial shock in in mature financial markets it. However, before letting ourselves the hook, financial shock financial markets let’s consider our track record of ourselves predicting inoff ecosinceous theous 1930s.

Global growth ismature projected to slow the then observed trend of wealthy people to buy property in poor areas London, upgrade them, stay themselves sometimes there and thus old residents areof let’sand consider ourSadly, track record of is predicting ecosince thein 1930s.

Global growth is projected to slow let’s consider our track ofnot predicting in ecosince the 1930s. growth is projected to slow nomics business. the record great.inold substantially 2008, andGlobal a modest recovery would London, upgrade them, stay themselves sometimes there and thus residents are being indirectly “squeezed”.

9 and andand business.

Sadly, thethe record is not great. substantially 2008, a modest recovery would nomics business.

Sadly, record is not great. substantially in 2008, and a modest recovery would nomics only begin later in in 2009.” being indirectly “squeezed”.

9 of 9 Abegin description this phenomenon is Bubble, included in the Trouble work of Sociologist Ruth begin later in George 2009.” only later in 2009.”

Soonly Henry Paulson, Bush and the IMF Bubble, Forecast AHenry description ofBush this phenomenon isthesituations included in the work of Sociologist Ruth So So Henry Paulson, George and the IMF Bubble, Bubble, Forecast George Bush and the IMF Bubble, Bubble, Forecast atPaulson, the same period, while similar were in other major Remember Japanese miracle?

Backrecorded inTrouble theTrouble 1980s, didn’tGLASS predict the credit crunch.

But that doesn’t GLASS at the same period, while similar situations were recorded in other major Remember the Japanese miracle?

Back in the 1980s, didn’t predict the credit crunch.

But that doesn’t Remember JapaneseJapan’s miracle?

Back in the 1980s, predict the credit But that doesn’t everyone was tryingthe to emulate business sucmean cities todidn’t say no one predicted it,crunch. right? Businessin Western countries, by other Researchers. everyone was trying emulate Japan’s business to say noWestern oneone predicted it, forecasters, right?

Businesseveryone was trying to emulate Japan’s business suctoin say no it, right?

Businesscities countries, by other Researchers. cess. The boom, fueled bytogains in productivity and sucWeek,mean inmean itsSince annual survey ofpredicted business then, the issue has preoccupied several scholars and for its more 10 business cess.

The boom, fueled by gains in productivity and Week, inSince its annual survey of forecasters, cess.

The boom, fueled by gains in productivity and Week, in its annual survey of business forecasters, concluded: quality, was the envy of the world.

During the 1980s, published on December 20, 2007, then, the issue has preoccupied several scholars and for its more comprehensive approach are being summarized below, from the various 10 10 concluded: quality, was thethe envy of the world.

During thethe 1980s, published on on December 20,20, 2007, concluded: the Nikkei quality, was envy of sixfold, the world.

During 1980s, published December 2007, 225 stock index rose from around comprehensive approach are being summarized below, from the various of thethat phenomenon oftothe gentrification, the following: Nikkei 225 stock index rose sixfold, from around Nikkei 225 stock index rose sixfold, from around Theinterpretations economists project, on average, the 6,500the almost 39,000.

But at the end of 1989, the interpretations of the phenomenon of gentrification, the following: In aeconomists sense, the phenomenon due6,500 to a trend of39,000. a anew category ofthe social groups The economists project, average, thatthat thethe isJapanese to almost 39,000.

But atdecline. the endend ofApril 1989, The project, on average, 6,500 to almost But at the of 1989, the economy will grow 2.1% fromon the fourth stock market began long By grow from theleaving fourth Japanese market began a long decline.

By By April economy grow from the fourth the2003, Japanese market a long April in money toeconomy “return” to the city, purlieus forstock several reasons: high costs quarter of 2007will towill the end2.1% of2.1% 2008, vs.

2.6% when it stock briefly started tobegan recover, thedecline.

Nikkei quarter oftwo 2007 to the endend of 2008, vs.

2.6% 2003, when it of briefly started recover, thethe Nikkei quarter ofto 2007 to the of[out 2008, 2.6% 225 had 2003, when itits briefly started to recover, Nikkei in 2007.

Only of the forecasters of vs. lost 80.5% peak value.towork and time travel from the purlieus to downtown, where place is, lack of the in 2007.

Only two of the forecasters [out of of 225lesson hadhad lost 80.5% of its peak value. in1.

2007.

Only two of the forecasters [out 225 lost 80.5% of its peak value.

54 in total] expect a recession.

The is that, whether we’re talking about The termat comes from Sociologist Ruth GLASS, 1912-1940.

Ruth search GLASS for wasbetter born in sense of safety the distributed residencies outside town centres, 54 54 in total] expect ashe recession.

The1932 lesson is whether we’re talking about in total] expect a recession.

The lesson is that, whether we’re talking about the dot-com boom ofthat, the 20th century, the South Berlin, where made her first studies.

In she published an important study entitled: services of health, education, entertainment “at the heart of the city”, (possibly) thethe dot-com boom ofand the 20th thethe South dot-com boom of the 20th century, South Could itYouth be, then,Unemployment. that the current crisis is a same “black year Seashe Bubble ofGermany the 18th century or thecentury, Amsterdam The left after continuous movements for lower cost of, “withdrawal” from private easier access to markets, etc.where Could it be, then, that thethe current crisis is ais“black Sea Bubble of 17th the 18th century or thecan Amsterdam studies and research in Geneva, Prague, London New York she came back to London, Could itliving be, then, that current crisis a “black Sea Bubble ofcar the 18th century or the Amsterdam swan,” the term eloquently coined by Nassim Nichtulip mania of and the century, no one ever 11 in 1943 she published studies regarding city planning.

In 1950 she became teacher in the swan,” the term eloquently coined by Nassim Nichtulip mania of the 17th century, no one can ever According to another approach, the phenomenon is due to a systematic and swan,” the2007 termbook eloquently coined

by Nassim tulip maniapoint. of the 17th century, no one can ever to mean a rare and Nicholas Taleb in his predict the bursting 11 London, 11 to University College of where she continued her social research.

Her public action and to mean a rare and olas Taleb in his 2007 book predict the bursting point. mean a rare and olas Taleb in his 2007 book predict the bursting point. unique event that is not only completely unexpected So what about less ambitious forecasts directed long-term informal effort by organized groups, manufacturers, brokers of buying her event work are characterized by aunexpected passion forSo justice.

See also: COLLINS ENGLISH DICTIONARY. unique that is not only completely unexpected what about ambitious forecasts directed unique event that is of not only completely what about less ambitious forecasts but also outside the realm our imaginations?

If theatdepreciation a single So company orless industry?

1968, C. the Jaydirected and selling real estate, etc., for initially ofInpart of urban web, in 10th edit. Wil. COLLINS SONS AND Co Ltd. London 2009.

WIKIPEDIA: The Free Encyclopedia: but also outside the realm of our imaginations?

If at a single company or industry?

In 1968, C. Jay but also outside the realm of our imaginations?

If at athen single company or Anaconda industry? Co. In 1968, so, we humans may be forgiven for failing to forecast Parkinson, president of the — a C. Jay Gentrification: G. ALEXANDRI: Abstract. http://www.uncanny.net/ wetzel/gentry.htm a variety of ways, in order to achieve the “assisted”, “voluntary”, (actually so,so, wewe humans may be forgiven forfor failing to forecast then president of the Anaconda Co.Co. —— a a humans may be forgiven failing to forecast Parkinson, Parkinson, then president of the Anaconda SLOANREVIEW.MIT.EDU SLOANREVIEW.MIT.EDU SLOANREVIEW.MIT.EDU

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FORECASTING

GENTRIFICATION Definition, Types of Intervention, Definition, of intervention, ConcernsTypes of Gentrification Concerns

FORECASTING

major producer of copper and part of a cartel that founders, there were no takers at their modest price. had been hiking up its prices for more than 35 Yahoo! Inc. and a whole bunch of well-known venture years — proclaimed, “This company will be going capitalists didn’t even make an offer. major producer of copper and part of a cartel that founders, there were no takers at their modest price. strong 100had andbeen evenhiking 500 years from now.”

Within up its prices for more than 35 Yahoo! Inc. and a whole bunch of well-known venture An Analogy Aseven Powerful 15 years the company had collapsed and the will whole years — proclaimed, “This company be going capitalists didn’t make an offer.

As An Earthquake industry had been by years the invention By Mr. George-Sp. C. ATHANASOPOULOS strong 100decimated and even 500 from now.”of Within Physical scientists generally very good at makfiber optics, made obsolete the use of copAn Analogyare As Powerful 15 which years the company had collapsed and the whole Harvard University, Graduate School of Design, Student, 12 As An Earthquake industry had been decimated by the invention of ing George-Sp. predictions.

But C. the ATHANASSOPOULOS scientific community per wires in the telecom industry.

By Mr. Architect Physical are generally very good at makfiber optics, which madeBear obsolete the use Today, amid all the fuss about Stearns, Leh-of copknows its ownscientists limits. Scientists accept that it’s imStudent of the School of Architecture 12 ing to predictions. the scientific community per and wiresAIG, in the man Brothers it’stelecom easy to industry. forget that it has all possible predict theBut timing and location of large Technical University of Crete Today, amidmore all therecently fuss about Bear knows itsIndeed, own limits.

Scientists accept that it’s imhappened before — and than theStearns, Great Lehearthquakes. current understanding of the man Brothers and AIG, it’s easy to forget that it has all possible to predict the timing and location of large In 1998, Long-Term Capital Manageprocesses that produce earthquakes suggests that happened before — and more recently than the Great earthquakes. Indeed, current understanding of the 1.Depression.

Introductory approach: Defining the concept ment LP, an investment fund managed by experts no one should be able to pinpoint their occurrence Depression. Inapproach: 1998, Long-TermDefining Capital Manageprocesses that produce earthquakes suggests that 1.

Introductory the concept ANTISTHENIS, the ancient Greek philosopher, BC -frequency 370 BC, Athens), that included two Prize-winning economists, in advance. the(444 intensity of earthment LP,Nobel an investment fund managed by experts no oneYet should be able to and pinpoint their occurrence ANTISTHENIS, ancient philosopher, (444 BC 370pattern.

BC, Athens), was saved from bankruptcy by a consortium ofGreek banks quakes exhibit aYet remarkably consistent In the among other heritage he left us, he established a great “principle”: that wise included two the Nobel Prize-winning economists, in advance. the intensity and-frequency of earthany year, are 134 earthquakes among other wise heritage he leftthe hegiven established aroughly great the was knowledge saved from bankruptcy by a consortium ofus, banks quakes exhibit a remarkably consistent pattern. In acquisition of starts with definition ofthere the content of“principle”: concepts. worldwide measuring to 6.9 on the Richter any given year, there6.0 are roughly 134 earthquakes acquisition of knowledge starts with the definition of the content of concepts.

Based, therefore, on this “principle” in a first, if not final, approach, the term VARIATIONS IN COMMUTING TIME TO OFFICE 6.0ofto7.0 6.9toon theand Richter scale,worldwide 17measuring a value 7.9, one 1 (and Based, therefore, onOFFICE this inindicated aaround first, ifwith not final, approach, the term The bars represent the numbers of for different times (in minutes) that“principle” Pierre VARIATIONS INdays COMMUTING TIME TO urban gentrification) is the area oftoPlanning) (or gentrification around (in 17 with a value of 7.0 7.9, and one at 8.0scale, or above.

The bars represent the numbers days for different times (in minutes) 1 needed to get to the office.

The smooth curveof(in the background) shows how a that Pierre gentrification (and urban gentrification) is indicated (in the area of Planning) (or at 8.0 or above.

Sociology as well), as the “refining” thehowever, removal this, (in various needed to get to the Pierre’s office. The smooth curve (in the background) shows howof a a city area, Our point, is thatfrom statistical regularity normal distribution approximates commuting times.

Our point, however, is that statistical regularity normal distribution approximatesas Pierre’s commuting times.“refining” of a city area, Sociology well), as the the removal from this, (in various ways), of social groups, usually of low-income placement there based of artists, does notand equalthe predictability.

For example, Number of Days does not equal predictability. For example, based ways), of social groups, usually of low-income and the placement there of artists, on the historical data, we“change”, have a pretty good idea Number of the Days 100 operation of art galleries, restaurants, etc.

However this regardless of on the historical data, we have a pretty good idea 100 -2 -3 -1 Mean +1 +2 +3 -3 -2 -1 Mean +1 +2 +3 that the next 35 years will bring roughly 44 earththe operation of art galleries, restaurants, etc.

However this “change”, regardless of Standard Standard Standard Standard Standard Standard has, results that the next 35 years will bring roughly 44 earthwhatever other consequences also rising of land prices (and the Standard Standard Standard Standard Standard Standard Deviations Deviations Deviation Deviation Deviations Deviations Deviations Deviations Deviation Deviation Deviations Deviations quakes with an intensity of 7.5 up to 7.6 on the quakes with an intensity of 7.5 up to 7.6 on the whatever otherspeculation). consequences has, results also rising of land prices (and the 80 potential relative 80 Richter scale.scale.

But But seismologists have nonoclue Richter seismologists have clueasasto to potential relative speculation).

The term gentrification is found at firstwhen in the UK inthey’ll early 1960s and it refers to or where they’ll occur (apart from when or where occur (apart frombeing beingin in 60 60 The term gentrification found atpeople first in the UK in early 1960s and it refers to the then observed trend ofiswealthy to buy property in poor areas of the world’s earthquake-prone zonesand andacacone ofone theofworld’s earthquake-prone zones the then observed trend of wealthy people to buy property in poor areas of companied by aftershocks).

Will these zones be companied by aftershocks).

Will these zones be London, upgrade them, stay themselves sometimes there and thus old residents are 40 populated or unpopulated?

Will there aresidents tsunami?

40 London, upgrade them, stay themselves sometimes there and thus old are populated or unpopulated?

Will there bebea tsunami? being indirectly “squeezed”.

Will they large-scale death and destruction?

Will they causecause large-scale death and destruction? being indirectly “squeezed”.

A description of this phenomenon is included in the work of Sociologist Ruth No scientist can say.

20 scientist can say.

20 A description ofperiod, this phenomenon is No included inwere the work ofcope Sociologist Ruth How, then, doesrecorded the world earth-major GLASS at the same while similar situations inwith other How, then, does the world cope with earthquakes?

Instead of relying on prediction, the focus GLASS at the same period, while similar situations were recorded in other major 0 cities in Western countries, by 51other Researchers. quakes?

Instead of relying prediction, the focus 33 35 37 39 41 43 45 47 49 53 0 is on being prepared.

If on you’re lucky enough to live cities Western by other Researchers.

33 35 37 39 41 in43 45 to Get 47tocountries, 49 51 has 53 preoccupied Minutes theissue Office Since then, the several and for is on in being prepared.

If world, you’reengineers lucky enough toits live more a rich part ofscholars the can construct Minutes to Get to the Office Since then, the issue has several scholars and for its more in a rich part ofcapable the world, engineers canvery construct buildings of withstanding strong comprehensive approach arepreoccupied being summarized below, from the various buildings capable of withstanding very strong comprehensive approach are being summarized below, from the various and governmental bodies.

The reason might give you tremors.

But if you live in a poor region, you take interpretations of the phenomenon of gentrification, the following: a chillingof sense ofThe déjà vu: It was donegive in the name of yourBut chances and suffer the consequences. and governmental bodies. reason might you tremors. if you live in a poor region, you take interpretations the phenomenon of gentrification, the following: Ina achilling sense, the phenomenon is due to a your trend of aandnew category of social groups saving entire system.

Of course, hurricanes such as Katrina can cause sense ofthe déjà vu: financial It was done in the name of chances suffer the consequences. to “return” to the city, leaving the purlieus for several reasons: high costs in In money In fairness, it’s not just business catastrophes that just as much devastation as big earthquakes. saving the entire financial system.

Of course, hurricanes such as Katrina can cause failfrom to forecast. also oftento unable to contrast where earthquakes, meteorologists canlack usuallyof the and time to experts travel theThey’re purlieus downtown, work place is, In fairness, it’s not just business catastrophes that just as muchtodevastation as big earthquakes.

In predictcomes success.

Take Google Inc., Ruth for exampredict1912-1940. where hurricanesRuth will strike a few days in born in term fromalso Sociologist GLASS, GLASS was experts fail to forecast.

They’re oftenresidencies unable to contrast to earthquakes, meteorologists can usually sense1. ofThe safety atbusiness the distributed outside town centres, search for better ple.she At themade end of the 1990s, thestudies. founders tried to1932 sell advance.

If you’re out atimportant sea with a safe harborentitled: Berlin, where her first In she published an study predictof business success.

Take Google Inc., for exampredict where hurricanes willthe strikecity”, a few days in services health, education, entertainment “at the heart of (possibly) their company with its unique nearby, early extremely useful.movements On land, Youth The samesearch yeartechnology she leftfor Germany andwarning afteratiscontinuous for ple.Unemployment.

At the end of the 1990s, theknown founders to sell advance.

If you’re sea with a staying safe harbor $1.6 million.

If they’d thattried less than 10private years however, the keyout isaccess being prepared: home, lower living cost of, in “withdrawal” from car to markets, etc.where studies and research Geneva, Prague, London and Neweasier York she came back to London, their company with its unique search technology formarket nearby, early warning is extremely useful. On land, it would bestudies worth $230 billion (the covering your windows andbecame down.

In in the in According 1943 shelater published regarding cityphenomenon planning.

In 1950 she teacher to another approach, the is due tofastening a staying systematic and $1.6 million.

If they’d known that less than 10 years however, the keythere is being prepared: home, capitalization in mid-2008), they might have set some cases may be time and resources for a University College of London, where she continued her social research.

Her public action and long-term informal byFortunately organized groups, manufacturers, brokers ofInbuying later itare would be worth $230 billion (the market their sights a effort little higher. for Google’s covering windows and ENGLISH fastening down. mass evacuation (as occurred with Gustav inDICTIONARY. August her work characterized by a passion for justice.

Seeyour also: COLLINS and selling realCOLLINS estate, etc., for theCo depreciation initially ofbepart the urban in capitalization in mid-2008), they might have set London some cases there may time of and resources for web, a 10th edit. Wil. SONS AND Ltd. 2009.

WIKIPEDIA: The Free Encyclopedia: 86 MIT SLOAN MANAGEMENT REVIEW WINTER 2010 Fortunately for Google’s their sights aways, little higher. mass “assisted”, evacuation (as occurred withSLOANREVIEW.MIT.EDU Gustav in August G. ALEXANDRI: http://www.uncanny.net/ wetzel/gentry.htm a Gentrification: variety of in order Abstract. to achieve the “voluntary”, (actually

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GENTRIFICATION Definition, Types of Intervention, Definition, of intervention, ConcernsTypes of Gentrification Concerns

2008, when 1.8 million people were moved from almost all the values in a normal distribution lie the coastal areas of southern Louisiana). But hurriwithin three standard deviations of the mean, while canes can change course (as Gustav did), once again 95% lie within two standard deviations. There are highlighting the inaccuracy of predictions. almost no extreme values; most of Pierre’s journey As an analogy, think of the enormous number times are clustered neatly around the average of 43 of small businesses or new ventures that start fail George-Sp. minutes. The graph represents what we call “subByorMr. C. ATHANASOPOULOS worldwide. The precise figures vary from year to way uncertainty.” It effectively models the time it Harvard University, Graduate School of Design, Student, year, but there is a continual process of businesses takes Pierre to get to his office each morning, toBy Mr. George-Sp. C. ATHANASSOPOULOS Architect entering and leaving the market — with some regether with the uncertainty of being earlier or later Student of the School of Architecture gions of the world more prone to both startup and than the average. Indeed, Pierre has used it to make Technical University of Crete failure than others. A few companies that hang on probabilistic predictions of how long his journey through the early years may go on to be hugely sucwill take — and was satisfied to find that his fore1. Introductory approach: Defining the concept cessful; many more simply survive. Sticking with casts were accurate. Pierre’s model makes some 1. Introductory approach: Defining the concept the natural disaster analogy, small-business failures important (444 assumptions. begin, it assumes that ANTISTHENIS, the ancient Greek philosopher, BC -To370 BC, Athens), can be seen as minor movements financial tecfuture days are from the same distribution ANTISTHENIS, the ancient Greek philosopher, (444 BC -“principle”: 370 BC, Athens), among other wise heritage he of left us, he established adrawn great the tonics, while the collapses of thehe Lehman Brothers, as was observed in past. “principle”: there is nothe among other wise heritage leftthe us,definition he established a the great acquisition of knowledge starts with of the content ofProvided concepts.

Enrons and WorldComs are the larger tremors. And major change — a prolonged shutdown of the enacquisition of knowledge starts with theindefinition the content of concepts.

Based,thetherefore, on this “principle” a first, if of not final, approach, the term current recession is a major earthquake, shaktire Métro system, interruptions to the city’s power 1 Based, therefore, on this “principle” in a first, if not final, approach, the term (and urban gentrification) is indicated (in—the Planning) (or gentrification ing Western capitalism to its core and sending huge supply, a strike thatarea is a safeof assumption.

As long 1 (and urban gentrification) is indicated (in the area of Planning) (or gentrification Sociologyaftershocks as well),rippling as the “refining” the removal from this, (in various across the world. of a city area, as there’s continuity between the past and future, Sociology as well), as the “refining” of a city area, the fromthere this, of (inartists, various the model reliable. ways), of social groups, usually of low-income and theisremoval placement Back to Normal In addition to liking a reliable commute, Pierreof ways), of social groups, usually of low-income and the placement there of artists, the operation of art galleries, restaurants, etc. However this “change”, regardless Of course, there are limits to the earthquake analalso likes exoticthis vacations.

Unfortunately, on a trip of the operation of art galleries, restaurants, etc.

However “change”, regardless whateverogy. other consequences has, results also rising of land prices (and the Large earthquakes are extreme, if imaginable, Thailand he had a deadly accident. While seeking whatever other consequences has, results toalso rising of land prices (and the potential relative speculation). events that occur rarely, even in temblor-prone shade under a palm tree, a coconut fell on his head. potential relative speculation).

The term gentrification is found at first in the UK in early andof ita highly refers zones. Many things that occur in the business Our unlikely hero was1960s the victim un-to The term gentrification found atpeople first in likely the UK in early 1960s and itareas refers world may not be predictable, but their unpredictevent that we call “coconut uncertainty” — of a to the then observed trend ofiswealthy to buy property in poor the then observed trend of wealthy people to buy property in poor areas ability can at least be modeled.

In other words, kind of freak happening that you just can’t plan for.

London, upgrade them, stay themselves sometimes there and thus old residents areof there are two types of uncertainty that practitioThe truththere is that and most real-life situations are mix-are London, upgrade them, stay themselves sometimes thus old residents being indirectly “squeezed”. ners need to“squeezed”. be aware of. We call them subway and tures of subway and coconut uncertainty, which is being indirectly A description of this phenomenon is included in the work of Sociologist Ruth coconut uncertainty, respectively, and we’ll explain precisely why coconut uncertainty interests us.

A description ofperiod, this phenomenon is situations included inwere the recorded work of Sociologist Ruth GLASS atby the same while similar in othercan’t major way of a story.

In technical terms, coconut uncertainty be GLASS at the same period, while similar situations were recorded in other major cities in Western countries, bycalled other Researchers.

Let’s imagine a character Pierre.

He’s a modeled statistically using, say, the normal districities in Western countries, by other Researchers. graduate France’s famous engineering school, several bution. That’s because there more and Since then, of the issue has preoccupied scholars andarefor itsraremore Sincethethen, the issueandhas preoccupied severalevents scholars and for its more École Polytechnique, he lives and works in unexpected than, well, you’dthe expect.

In addicomprehensive approach are being summarized below, from various Paris. One of his passions is recording how longsummarized it tion, there’s no regularityfrom in the occurrence of comprehensive approach are being the various interpretations of the phenomenon of gentrification, thebelow, following: takes him to get to work each morning via Paris’s coconuts that can be modeled.

And we’re not just interpretations of the phenomenon of thecategory following: In a sense, phenomenon is due togentrification, a trend of a new of social groups highly the efficient Métro system. The wait generally talking about Taleb’s “black swans” — truly bizarre to “return” to between the city, leaving purlieus for several costs inThere money varies almost nothingthe and just a few minevents thatreasons: we couldn’thigh have imagined. are utes.

However, therethe are purlieus many one-day and time to travel from to strikes, downtown, where work and place is, lack the also bubbles, recessions financial crises,of which which cause considerable delay or even force may 1912-1940. nottown occur often but dosearch repeat atfor infrequent termcan from Sociologist Ruth GLASS, Ruth GLASS was born in sense1.ofThe safety atcomes the distributed residencies outside centres, better Berlin, where hertofirst 1932 an important entitled: him toshe walkmade all the way work.studies.

Some days,In too, the she andpublished irregular intervals.

Coconuts, instudy our view, are services of health, education, entertainment “at the heart of the city”, (possibly) Youth Unemployment.

The same year she Germany continuous large crowds of tourists on the platform canleft force less rareand thanafter you’d think.

They don’tmovements need to be big for lower living cost of, in “withdrawal” from private car easier access tospace. markets, etc.be studies and Geneva, Prague, London andand New York came to London, himresearch to miss a train. hairy andshe come fromback They can alsowhere in According 1943 sheThe published studies regarding city planning.

In 1950 she became teacher in the to another approach, the phenomenon is due to a systematic and graph of Pierre’s daily commuting times fits small and prickly and occur without warning. CoUniversity College of London, where she continued her social research.

Her public action and long-termtheinformal by organized groups,conuts manufacturers, brokers of buying well-knowneffort bell-shaped curve of the normal can even be positive: an inheritance from a her work are characterized by a passion for justice. See also: COLLINS ENGLISH DICTIONARY. (See “Variations inthe Commuting Time long-lost relative, a lottery win orurban a yachting invita-in and selling realCOLLINS estate, etc., for depreciation initially of part of the web, 10th edit.distribution.

Wil. SONS AND Co Ltd. London 2009.

WIKIPEDIA: The Free Encyclopedia: In in his statistics he learned that tion from a rich client.

G. ALEXANDRI: Abstract. http://www.uncanny.net/ wetzel/gentry.htm a Gentrification: varietytoofOffice.”) ways, order class, to achieve the “assisted”, “voluntary”, (actually SLOANREVIEW.MIT.EDU

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FORECASTING

GENTRIFICATION Definition, Types of Intervention, Definition, of intervention, ConcernsTypes of Gentrification Concerns

Pierre didn’t study psychology along with engias many other daily series of data in economics and neering and statistics. But if he had, he might have business. But it’s not the same shape as the normal come across research showing that while people may distribution shown by the smooth pattern in the be quite aware that rare events can occur, and may background. In particular, there are more extreme FORECASTING even be able to imagine several examples, they connegative daily changes in the oil price — both up sistently underestimate the probability of at least one Byand down — than you would expect if the values Mr. George-Sp. C. ATHANASOPOULOS such event (including the ones they didn’t imagine) were normally distributed. For example, between Harvard University, Graduate School of Design, Student, study along with engi- June as many otherOctober daily series 11, of data in economics andwent up otherdidn’t words, wepsychology tend to underestioccurring.13 In Pierre 20 and 1990, oil prices By Mr. George-Sp. C. ATHANASSOPOULOS Architect and statistics. But if he had, he might have business. But it’s not the same shape as the normal mate the size neering of the class of rare events. And that can 160%, from $26 to $67.30. By February 25, 1991, come across research showing that while people may distributionStudent shown by theof smooth in the of Architecture thepattern School lead to serious, sometimes mortal errors.

Engineerthey were back down tothere $28.areThroughout be quite aware that rare events can occur, and may background.

In particular, more extreme that peTechnical University of Crete ing disasters, for example, often because there were vertiginous daily and falls, even be able to imagine severalarise examples, they con- riod, negative daily changes in the oil price — rises both up sistently crash underestimate probability of at least and down — than you would expect if the values “fail-safe” systems due tothethe breakdown ofone including several of the 13 values greater than 1. Introductory approach: concept such event (including the ones they Defining didn’t imagine) the were normally distributed. For example, between only one previously unconsidered component.

10.41% and the 21 lower than –10.35%, respec13 In other words, we tend to underestioccurring.

June 20 and October 11, 1990, oil prices went up 1.

Introductory approach: Defining the concept the$26 other hand, during of the timeAthens), ANTISTHENIS, Greek philosopher, (444 BCthe-25,rest 370 BC, mate the size of thethe class ofancient rare events. And that can tively.

160%,On from to $67.30.

By February 1991, Coconut Oil? maybe fordown a few more volatile pe- Athens), lead towise serious, sometimes errors.

Engineerthey were back to days $28.

Throughout that pe- BC, ANTISTHENIS, themortal ancient Greek philosopher, (444 BC -“principle”: 370 among other heritage he left us,(and he established aduring great the ingatdisasters, for example example, often arise because riod, there were vertiginous daily rises small and falls, Now let’s look a real-life that affects us riods, too), there were also more rises than among other wise heritage he left us, he established a great “principle”: the acquisition of knowledge starts with the definition of the content of concepts. crash due to the breakdown of including several of the 13 values greater than all: the price “fail-safe” of oil. Insystems 2008, the soaring price of oil you would “normally” expect. acquisition ofoneknowledge starts with the definition of the content of concepts. only previouslyon unconsidered component.

10.41% and the 21 lower than –10.35%, respecBased, therefore, this “principle” in a first, if not final, approach, the term reminded the world that there was such a thing as In short, prices nice, predictable tively.

On theoil other hand,don’t duringdisplay the rest of the time 1 (and urban Based,Coconut therefore, on this “principle” inmaybe auncertainty. first, if Thus, not final, approach, the term gentrification) is indicated (in the area of Planning) (or gentrification inflation, something that most Western economists subway people whose job it is to Oil? (and for a few days during more volatile pe1 (and urban gentrification) is indicated (in the area of Planning) (or gentrification Now let’s look at a real-life example that affects us riods, too), there were also more small rises than Sociology as well), as Consider the “refining” of a city area, the removal from this,more (in various had all but forgotten about. the graph dispredict tomorrow’s oil price must cope with all: price of oil.

Inthe 2008, “refining” the soaring price ofof oil a you would “normally” expect.

Sociology asthewell), city area, the removal from this, (inartists, various playingof daily changes in oilas prices over a two-decade coconuts than might reasonably expect.

And, ways), social groups, usually of low-income andthey the placement there of reminded the world that there was such a thing as In short, oil prices don’t display nice, predictable period.

(See “Changes in Oil Prices, 1986-2008.”) as we saw above, the entire developed world is at the ways), of social groups, usually of low-income and the placement there of artists, inflation, something that most Western economists subway Thus,this people“change”, whose job it is to regardless the operation of art galleries, restaurants, etc. uncertainty.

However of On first impression, the galleries, graph a rather nice,dis- mercy oftomorrow’s these lurking coconuts. had all but forgotten about.has Consider the graph predict oil price must cope with more the operation of art restaurants, etc.

However this “change”, regardless of whatever other consequences has, results also rising of land prices (and the changes in oilthe prices over apattern two-decade coconuts than might reasonably expect. symmetrical playing shape,daily with roughly same So what dothey economic forecasters doAnd, in such cirwhatever other consequences has, results also rising of land prices (and the period.

(See speculation).

“Changes in Oil Prices, 1986-2008.”) as we saw above, the entire developed is at the potential relative cumstances?

Remember, it’s world difficult — if not On first impression, the graph has a rather nice, mercy of these lurking coconuts. potential relative speculation).

The term gentrification is found at first in the UK in early 1960s and folit refers to to modelforecasters uncertainty doesn’t symmetrical shape, with roughly the same pattern impossible So what — do economic do in that such cirThe term gentrification found atpeople first in the UK in early 1960s and itareas refersofto CHANGES IN OIL PRICES, 1986-2008 low known statistical models.

Forecasters have the then observed trend ofiswealthy to buy property in poor cumstances? Remember, it’s difficult — if not The bars represent the numbers of days that daily changes in oil prices (expressed as impossible —done to model uncertainty that doesn’t folthe then observed trend of wealthy people to buy property in poor areas traditionally exactly what Pierre did.

In practiLondon, upgrade stay themselves sometimes there and thus old residents areof percentages) had different values.

The smooth curve (in thethem, background) shows a CHANGES IN OIL PRICES, 1986-2008 known statistical models. Forecasters have callow terms, they havethere treated and unexpected like London, upgrade them, stay themselves sometimes thusevents, old residents are The bars represent the numbers of days that daily changes in oil prices (expressed as theoretical normal distribution.

It does not fit the empirical data, which have both being indirectly “squeezed”. traditionally done exactly what Pierre did. In practipercentages) had different values. The smooth curve (in the background) shows a the steep 1973-1974 oil price increase or the more remany more outliers and values being closer to the mean. The data“squeezed”. are from the U.S. Energy cal terms, they have treated unexpected events, like indirectly theoretical normal It does not fit the which have both Adistribution. description ofempirical thisdata,phenomenon is included inoilthe work ofmore Sociologist Ruth Information Administration. rise 1973-1974 of 2007-2008, as outliers have to be steep price increase or the that remany more outliers and values closer to the mean. The data are from the U.S. Energy A description of this phenomenon cent isthe included inwere the work oftoSociologist Ruth GLASS situations recorded in other major Information Administration. at the same period, while similar cent rise of 2007-2008, as outliers that have be ignored because they can’t be modeled.

Number of Days GLASS at the same period, while similar situations were recorded in other major ignored because they can’t be modeled.

Number of Days 900 cities in Western countries, by other Researchers.

Now, don’t get us wrong. The field of forecasting 900 Now, don’t get us wrong. The field of forecasting cities in Western countries, bypreoccupied other Researchers. has excellent work over the— years both Since then, the issue has several scholars and for its more 800 hasproduced produced excellent work over the years both — 800 Since then, the issue has preoccupied several scholars and for its more practical and academic.

It created has created models ofvarious practical and academic.

Itbelow, has models of the comprehensive approach are being summarized from 700 700 subway uncertainty uncertainty thatthat can can be assessed with re-with resubway be assessed comprehensive approach are being summarized below, from the various 600 interpretations of the phenomenon of gentrification, following: markable precision andthe incorporated into all kinds 600 markable precision and incorporated into all kinds interpretations of the phenomenon of gentrification, the following: 500 of analyses to produce the best possible decisions.

In a sense, the phenomenon is due toofaanalyses trend ofproduce a new category of social groups 500 bestwith possible decisions.

However, it’sto just not set upthe to cope coconuts, 400 to “return” to the city, leaving the purlieus for several reasons: high costs in money However, it’s just not set up to cope with coconuts, which are a fact of life in the real world of business.

400 300 In essence, message is: By all means make and time to travel from the purlieus to downtown, where work place is, lack of the which are athen, factour of life in the real world of business.

200 300 — just don’t believe them.

Inforecasts essence, then, our message is:Ruth By all means make termat comes from Sociologist Ruth GLASS, 1912-1940.

GLASS wasbetter born in sense1.ofThe safety the distributed residencies outside town centres, search for 100 200 Berlin, where she made her first studies.

In 1932 she published important study entitled: forecasts — just don’t believean them. <-10.35% >10.41% Juggling With Coconuts: services of health, education, entertainment “at the heart of the city”, (possibly) 0 Youth Unemployment.

The+7.16% same+10.41% year she leftThe Germany Three A’s and after continuous movements for -10.35% -7.11% -3.21% 0.029% 100 lower living cost of,in+3.27% “withdrawal” from private car easier access to markets, etc.where studies and research in Geneva, Prague, London and New York she came back to London, Percent Daily Change Oil Price In the end, we admit that our message isn’t particu<-10.35% >10.41% Juggling With Coconuts: 0 in According 1943 she published studies regarding city planning. became teacher in the larly positive. PeopleIn still1950 have to she maketo decisions to another approach, the phenomenon is due a systematic and The Three A’s -10.35% -7.11% -3.21% 0.029% (Official +3.27% +7.16% Source: Energy Information Administration Energy Statistics from the U.S. +10.41% Government): based on what they think will happen in theHer future.public action and http://tonto.eia.doe.gov/dnav/pet/pet_pri_spt_s1_d.htm University College of London, where she continued her social research.

Percent Daily Changeinformal in Oil Price effort by organized In long-term groups, brokers of buying the end, wemanufacturers, admit that our message isn’t particuher work are characterized by a passion for justice. See also: COLLINS ENGLISH DICTIONARY. larly positive.

People still have toof make decisions 88 MIT SLOAN MANAGEMENT REVIEW WINTER 2010 SLOANREVIEW.MIT.EDU and selling real estate, etc., for the depreciation initially of part the urban web, in 10th edit.

Wil. COLLINS SONS AND Co Ltd. London 2009.

WIKIPEDIA: The Free Encyclopedia: Source: Energy Information Administration (Official Energy Statistics from the U.S. Government): based what they think will happen in the future. http://tonto.eia.doe.gov/dnav/pet/pet_pri_spt_s1_d.htm G. ALEXANDRI: http://www.uncanny.net/ wetzel/gentry.htm a Gentrification: variety of ways, in order Abstract. to achieve theon“assisted”, “voluntary”, (actually

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GENTRIFICATION Definition, Types of Intervention, Definition, of intervention, ConcernsTypes of Gentrification Concerns

But we do But have we some do have advice somefor advice juggling for juggling with cocowith cocoFUTURE-PERFECT FUTURE-PERFECT THINKING THINKING AlthoughAlthough people have people great have difficulty great in difficulty predicting in predicting the future, the they future, havethey littlehave little nuts by using nuts by theusing threethe A’s:three Accept, A’s:assess, Accept,augment. assess, augment. difficulty in difficulty explaining in explaining the past. the Future-perfect past. Future-perfect thinking forces thinking you forces to exploit you to exploit Accept that Accept you’re thatoperating you’re operating in an uncertain in an uncertain iii iii hindsighthindsight (even if it (even is purely if it imaginary). is purely imaginary). world. Psychologically, world. Psychologically, it’s tough, it’sbut tough, ignoring but ignoring ununHere’s anHere’s example an … example … certaintycertainty is not anis option. not an option.

In fact, whether In fact, whether your your Assume you’re Assume theyou’re CEO of thea CEO majorofairline, a major and airline, in order andtoinformulate order to formulate your your corporatecorporate strategy, you strategy, needyou to forecast tooil forecast prices oil forprices the next forfive the years. next five years. interest interest is in tomorrow’s is in tomorrow’s oil price,oilnext price, quarter’s next quarter’s By Mr. George-Sp. C.need ATHANASOPOULOS First, imagine First,that imagine five years that five have years already havepassed. alreadyYou’re passed. now You’re ablenow to look able to look sales data, sales next data, year’s nextstock year’s price, stockearthquakes price, earthquakes or or Harvard University, Graduate of Design, Student, back on what back happened on what happened overSchool that over period. that It period. turns out It turns that oil out prices that oil have prices beenhave been simply getting simplyto getting work to onwork time,on you time, can’tyou be can’t realis-be realisquite lowquite and stable low and over stable the “past” over five “past” years,five which years, was which a great was benefit a greattobenefit to By Mr. George-Sp. C. the ATHANASSOPOULOS Architect tic about ticassessing about assessing the chances the chances of a given of aevent given event the airlinethe (and airline your(and career). yourHowever, instead ofinstead just enjoying of just that enjoying imaginary that imaginary Student ofcareer). the However, School of Architecture good luck,good explain luck, —explain or tell the — or story tell the of ---story howof such --- how favorable such favorable circumstances circumstances occurring occurring unless you unless firstyou confront first confront all the other all the other University Crete came about. came What about. were What theTechnical were particular the particular economic economic and geopolitical andof geopolitical events that events that possibilities possibilities that might thatcome might true come instead. true instead. contributed contributed to the low, tostable the low, oil stable prices?oil prices?

Assess the Assess levelthe of uncertainty level of uncertainty you face.you By face. all By all Now,concept takeNow, a second take atrip second forward tripfive forward yearsfive on the years time on machine. the time machine.

This time,This time, 1. Introductory approach: Defining the means, model means,your model uncertainty your uncertainty as if it were as ifsubway it were subway however,however, when youwhen look back you look at oilback prices, at oil you prices, are exasperated. you are exasperated.

All you see Allisyou see is 1.

Introductory approach: Defining the concept uncertainty: uncertainty: Use a statistical Use a statistical model ifmodel you’re you’re feeling mayhem: a period of a period steep and of steep highly and volatile prices volatile that prices made that running madethe running air- the airANTISTHENIS, theiffeeling ancient Greekmayhem: philosopher, (444 BC -highly 370 BC, Athens), almost line impossible. almost impossible.

Once again, Once explain again, explain happened. what happened.

What were What the were the mathematical, mathematical, thenother consider then wise consider how coconut how coconut unceruncerANTISTHENIS, the ancient Greek philosopher, (444 BC -what 370 BC, Athens), among heritage he left us,line he established a great “principle”: the particularparticular economiceconomic and geopolitical and geopolitical events that events led tothat thatled painful to that scenario? painful scenario? tainty might tainty come mightinto come into Ironically, play.heritage Ironically, having having among other wise leftthe us,definition established great the acquisition ofplay. knowledge startshe with ofofthatthe of“principle”: concepts.

If he you do that If you kind do exercise kindcontent ofaaexercise few times, a few focusing times, on focusing the realms on the ofrealms your of your acceptedaccepted uncertainty, uncertainty, you can you startcan to gather start tomore gather more own experience, own experience, you’ll start you’ll tofinal, develop start toaapproach, develop feelingof for a feeling different for futures different and futures the and the acquisition of knowledge starts with the definition of the content concepts.

Based, therefore, on this “principle” in a first, if not the term data anddata judgments and judgments than youthan might youotherwise might otherwise have have fact that they fact that are all they plausible. are all plausible.

Some of these Somefutures of thesewill futures involve will coconuts involve coconuts of of 1 Based, therefore, on this “principle” in a first, if not final, approach, the term (and urban gentrification) is indicated (in the area of Planning) different kinds different and,kinds though and, there though is no there formal is no technique formal technique for converting for(or converting plausibil- plausibilthoughtgentrification thought relevant.relevant.

Take, forTake, example, for example, the salesthe of asales of a 1 gentrification (and urban gentrification) (in the area oftoinsights Planning) into is probability, ityindicated into probability, you can use youyour can new use your insights new develop appropriate develop (or appropriate risk risk Sociology asunknown well), as the area, the removal from this, (intovarious first novel first bynovel an unknown by an author.

It author. sounds It“refining” like sounds a like a of aitycity protectionprotection strategies. strategies.

That is theThat essence is the of essence future-perfect of future-perfect thinking. It thinking. involvesIt involves Sociology as well), as the “refining” of a city area, the removal from this, (in various uniqueways), case. unique Butcase. our But suggestion our suggestion to publishers to publishers is to is to of social groups, usually of low-income and the placement there of vivid artists, harnessing harnessing the claritythe of hindsight clarity of hindsight to develop tomore develop vivid more pictures of pictures the future. of the future. ignore the the ignore uniqueness. the of uniqueness.

Instead, Instead, look at the look track at the track ways), social groups, usually of low-income and thethis placement of artists, It’s aetc. wayIt’s not aonly way to not accept, only toassess accept, and assess augment andthere augment the likelihood the likelihood of a coconut operation of art galleries, restaurants, However “change”, regardless of of a coconut record ofrecord the sales of the of first-time sales of first-time authors in general. in general. hittingetc. you hitting onHowever the you head on the but head also to but devise also to a plan devise for acoping plan for with coping it in advance. withof it in advance. the operation ofauthors art galleries, restaurants, this “change”, regardless whatever other consequences has, results also rising of land prices (and the You haveYou no have validno reason validtoreason believe tothat believe the that uncerthe uncerwhatever otherspeculation). consequences has, results also rising of land prices (and the potential relative tainty surrounding tainty surrounding your new your author new differs authorfrom differs from and smallest and smallest observations. observations.

Why? Well, Why? to estimate Well, to estimate a a potential relative speculation).

The term gentrification ishefound firstaccurately, inyou the UK in early 1960s the wider the population wider population of new authors of new authors that he or that she orrange she at accurately, range need you to observe need to observe values atvalues the and at theit refers to The term gentrification found at first in the UK in early and refersofto belongsthe belongs to —then especially to — especially if you’ve ifused you’ve an used industry anis industry two extremes. two extremes.

However, However, bybuy definition, by definition, extreme1960s extreme valval- it observed trend of wealthy people to property in poor areas the then observed trend of wealthy people to buy property in poor areas standard standard process process for collecting for collecting reader feedback reader feedback ues occur ues only occur rarely, only so rarely, you’re so unlikely you’re unlikely to observe to observe London, upgrade them, stay themselves sometimes there and thus old residents areof 14 Doubling 14 Doubling what you’ve what obyou’ve (also known (also as known human asupgrade judgment). human judgment).

Therefore, Therefore, you themselves you in them them smallsometimes in samples. small samples.

London, them, stay there and thus oldobresidents are being indirectly “squeezed”. served in served a limited in a number limited number of past occurrences of past occurrences is a is a should have should a reasonable have a reasonable estimate estimate of just how of just low how low being indirectly “squeezed”.

A description of thisprobably phenomenon isof included in the work of Sociologist Ruth crude way crude way of estimating, say, the 95% say, the range.

95% range. or high or thehigh salesthe might salesgo. might Thatgo. range range probably A description ofThat this phenomenon isestimating, included inwere the work of Sociologist Ruth GLASS at the same period, while similar situations recorded inpast other major On the hand, otherif hand, you have if you a wealth have aofwealth past of covers 95% covers of 95% all possible of all possible outcomes. outcomes.

Done that?

Done that?On the other GLASS at the same period, while similar situations were recorded in other major cities intake Western countries, byincrease other Researchers. data (oil data prices, (oilfor prices, example), for example), you mayyou notmay neednot to need to Well, now Well, takenow the estimated the estimated range …range and increase … and Western countries, bypreoccupied other Researchers. double your double range. yourHowever, range. However, we’dscholars stillwe’d recommend still recommend it! Henceit!cities the Hence next in the step: next Augment. step: Augment.

Since then, the issue has several and for its more Since then, issueChances has preoccupied scholars and for various its more multiplying it by at least itseveral by1.5. at least Remember, 1.5.

Remember, as wefrom saw as we saw Augment Augment the range the of range uncertainty. ofthe uncertainty.

Chances are are comprehensive approach aremultiplying being summarized below, the earlier, people earlier,tend people to underestimate tend to underestimate the size of thethe size of the good that good you’ve thatjust you’ve underestimated just underestimated the range the ofrange of being comprehensive approach are summarized below, from the various interpretations of the phenomenon of gentrification, the following: class of of potential classgentrification, of potential coconuts, coconuts, not tothe mention notfollowing: to mention the size the size uncertainty, uncertainty, no matter nohow matter realistic how realistic youphenomenon thought you thought interpretations of the In awhen sense, phenomenon isof due tothea coconuts trend of a new category of social groups the coconuts of themselves. themselves. you wereyou when were you assessed you the assessed it. Extensive it. Extensive empirical empirical to “return” to consistently the city, leaving the purlieus for several reasons: high costs in money evidence evidence shows that shows people that people consistently underestiunderestiFromtoForecasting From Forecasting towhere Planning to Planning mate uncertainty mate time uncertainty — to their — powers theirfrom of powers imagination of imagination and travel the purlieus downtown, work place is, lack of the Given the Given number theoutside number of disastrously oftown disastrously badcentres, forecasts bad forecasts —search — for are usually are worse usually than worse their than powers their mathematmathemat1.of The term fromofSociologist Ruth GLASS, 1912-1940.

Ruth GLASS wasbetter born in sense safety atcomes theofpowers distributed residencies Berlin, where she made her first studies.

In published anclear important study entitled: and notand just1932 not in the justshe last in few the last years few —years it’s — it’s that clear that ics. We services have ics.

We advice have for advice those for who’d those like who’d to stretch like to stretch of health, education, entertainment “at the heart of the city”, (possibly) Youth Unemployment.

The same year shebusinesses left Germany and after continuous movements for businesses need a different need a different strategy strategy to cope to with cope with their imaginations, their imaginations, but if you’re but ifnot you’re feeling notcreative, feeling creative, lower living cost of, “withdrawal” from private car easier access to markets, etc.where studies and research in Geneva, Prague, London and New York she came back to London, coconutcoconut uncertainty. uncertainty.

As we saw As with we saw earthquakes with earthquakes we havewe a rule haveofa rule thumb. of thumb.

(See “Future-Perfect (See “Future-Perfect in 1943 she published studies regarding city planning.

In 1950 she became teacher in the According to another approach, the phenomenon is due to a systematic and and hurricanes, and hurricanes, the key is thenot keytoisdevelop not to develop precise precise Thinking.”)

Thinking.”)

University College of London, where she continued her social research.

Her public action and long-term by organized groups, manufacturers, plans based plans onbased predictions, on predictions, but to have but emergency to havebrokers emergency of buying Basically, Basically, our rule our is:informal Ifrule youis: have If you a effort small haveamount a small amount her work are characterized by a passion for justice. See also: COLLINS ENGLISH DICTIONARY. plans for plans aLondon variety for a of variety possibilities. ofWIKIPEDIA: possibilities. you live IfThe you in Free live inEncyclopedia: of historical of10th historical data that’s data relevant that’s relevant for modeling for modeling the the and selling real estate, etc., for the depreciation initially ofIfpart of the urban web, in edit.

Wil. COLLINS SONS AND Co Ltd. 2009.

Paris, it’s Paris, notthe necessary it’s not necessary to plan for to plan an“voluntary”, earthquake for an earthquake (actually future, adouble future, the double difference theways, difference the largest the largest Gentrification: G.between ALEXANDRI: Abstract. http://www.uncanny.net/ wetzel/gentry.htm variety of inbetween order to achieve “assisted”, SLOANREVIEW.MIT.EDU SLOANREVIEW.MIT.EDU

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FORECASTING

GENTRIFICATION Definition, Types of Intervention, Definition, of intervention, ConcernsTypes of Gentrification Concerns

F O R E C A S T I N G or a piece of a satellite falling from the sky. But

3. G.W. Bush/press conference, James S. Brady Press

Briefing Room July 15, 2008, http://georgewbush-white there are some actions you can take that can prohouse.archives.gov/news/releases/2008/07/ 20080715-1. tect you from events you cannot predict. Indeed, html. many of us already do so by purchasing insurance 4. H.M. Paulson, “Paulson Testimony on Turmoil in U.S. 3. G.W. Bush/press conference, James S. Brady Press or a piecefire of adrills satellite falling from the or practicing in the workplace.

Mostsky. in-But Credit Markets, ” Sept. 23, 2008, http://blogs.wsj.com/ Briefing Room July 15, 2008, http://georgewbush-white there policies are somecover actions you range can take can pro- economics/2008/09/23/paulson-testimony-on-turmoil-insurance a wide of that potential

By Mr. George-Sp. C. ATHANASOPOULOS house.archives.gov/news/releases/2008/07/ 20080715-1. us-credit-markets/. tect you events you techniques cannot predict.

Indeed, disasters, andfrom the evacuation practiced html.

Harvard University, of Design, 5. “TalksGraduate Implode DuringSchool a Day of Chaos; Fate of BailoutStudent, many of usbealready by purchasing for fire would just as do wellsosuited for bomb insurance scares, H.M. Paulson, “Paulson Testimony on Turmoil in U.S. Plan4.Remains Unresolved, ”C. New York Times, Sept. 26,

By Mr. George-Sp. ATHANASSOPOULOS Architect or practicing fire drills in the workplace. Most in- 2008, floods or gas leaks.

Credit Markets,” Sept. 23, 2008, http://blogs.wsj.com/ http://www.nytimes.com/2008/09/26/ Student of the School of Architecture economics/2008/09/23/paulson-testimony-on-turmoil-inbusiness/26bailout.html. surancehow policies a wide range of potential Exactly you cover deal with uncertainty is for us-credit-markets/. Technical University of Crete 6. International Monetary Fund, “World Economic thetoevacuation techniques youdisasters, and yourand team decide. Perhaps you’llpracticed use a 5. “Talks Implode During Day ofinChaos; Fate of Bailout Outlook 2007: Spillovers and aCycles the Global for fire would be as well suited scares, hedging strategy or just develop a plan B for forbomb evolving Plan Remains Unresolved, New York2007).

Times, Sept. 26, Economy” (Washington, D.C.:”IMF , April 1.your Introductory approach: Defining the concept floods or gas leaks.Or maybe you’ll take a “venbusiness model.

2008, http://www.nytimes.com/2008/09/26/ 7.the International Monetary Fund, “World Economic 1. Introductory Defining concept business/26bailout.html.

Exactlyapproach how youtoapproach: deal with uncertainty is forphilosopher, ture capital” innovation, developing Outlook” (Washington, D.C.: IMF , October 2007).

ANTISTHENIS, the ancient Greek (444 BC - 370 BC, Athens), 6. International Monetary Fund, “World Economic younew and ideas your at team toknowing decide.

Perhaps use a 8.philosopher, several once, that onlyyou’ll one or ANTISTHENIS, the ancient Greek (444 BC 370 BC, Athens), Monetary Fund, “World Economic among other wise heritage he left us, heInternational established a great “principle”: the Outlook 2007: Spillovers and Cycles in the Global or develop a plan B is fortoevolving twohedging are likelystrategy to succeed.

The main thing stop Outlook” (Washington, D.C.: IMF, April 2008). among other wise heritage he left us,definition heEconomy” established aD.C.:great “principle”: the (Washington, IMF, April 2007). acquisition of knowledge starts with the of the content of concepts. your business model.

Or maybe you’ll a “ven- 9. International Monetary Fund, “World Economic believing your own predictions about thetake future 7.

International Monetary Fund, “World Economic acquisition of knowledge starts with the definition of the content of concepts.

Based, therefore, on this “principle” in a first, if not final, approach, the term Outlook 2008: Financial Stress, Downturns, and capital”plans approach to innovation, andture to develop that will be sensitivedeveloping to sur(Washington, D.C.: IMF, October 2007).

1 (and urban (Washington, IMF, October Based, therefore, on this “principle” inOutlook” a first, if (in notD.C.: final, approach, the term gentrification) is indicated the area of 2008).

Planning) (or gentrification several new ideas at once, knowing that only one or Recoveries” prises, whether future credit crunches or other 8. International Monetary Fund, “World Economic 1 10. J.C. Cooper, “No Recession, Butarea …,” BusinessWeek gentrification (and urban gentrification) is indicated (in the of Planning) (or two are likely to succeed.

The main thing is to stop recessionary forces.

Outlook” (Washington, D.C.: IMF , April 2008).

Sociology as well), as the “refining” of a city area, the removal from this, (in various (Dec. 20, 2007). believing your own predictions about the future As coconuts go, the current economic crisis is a Sociology as well), as the “refining” of a city area, the removal from this, (in various 9.

International Monetary Fund, “World Economic ways), of social groups, usually of low-income and the 11. N.N. Taleb, “The Blackplacement Swan: The Impactthere of the of artists, Outlook 2008: Financial Stress, Downturns, and develop will be sensitive to sur- Highly big and hairy fromplans outerthat space.

Will global, ways), oftoone social groups, usually of free low-income and(Washington, the placement there Improbable” (New York: Random House, 2007). of artists, the operation of art galleries, restaurants, etc.

However this “change”, regardless of Recoveries” D.C.: IMF, October 2008). prises, whetherturn future crunches or other market capitalism out credit to be another of those 12.

S. Makridakis, R.M. Hogarth and A. Gaba, “Dance the operation of art galleries, restaurants, etc.

However this “change”, regardless of whatever other consequences has, results also rising of land prices (and the 10.

J.C. Cooper, “No Recession, But …, ” BusinessWeek recessionary forces. great political ideas that didn’t work in practice? We With Chance: Making Luck Work For You” (Oxford: (Dec. 20, 2007). whatever other consequences has, results also rising of land prices (and the potential speculation).

Asrelative coconuts the currenttoeconomic don’t know, but it’sgo, interesting speculate,crisis and is a Oneworld Publications, 2009).

11. N.N. Taleb, “The Black Swan: The Impact of the potential relative speculation).

A. Tversky and D.in Kahneman, “Judgment and Under it refers to hairy one outer space.

Will global, alsobig important.

In from the end, the empire of capitalism The term gentrification is found at free first13.in theImprobable” UK early Highly (New York:1960s Random House, 2007).

Uncertainty: Heuristics andearly Biases,” 1960s Science, New Series The term gentrification found atpeople first in the UK in and itareas refersofto market capitalism turn outit’s toof beisanother of fithose probably strike back, and likely that the the will then observed trend wealthy to buy property in poor Makridakis, Hogarth and A. Gaba, “Dance 185,12. no.S.4157 (Sept. 27R.M. , 1974): 1124-1131. greatJedi political ideas to that didn’t work in practice? nancial will return preeminence (albeit, with Wepeople the then observed trend of wealthy to buy property in poor areas With Chance: Making Luck Work For You” (Oxford: London, upgrade them, stay themselves sometimes there andthat thus old residents areof 14. That also applies to samples are imaginary.

See Oneworld Publications, 2009). don’tdiminished know, but by it’s interesting to speculate,isand Psometimes powers regulation).

Capitalism .

Juslin, A. Winman and P .

Hansson, “The Naïve Intuitive London, upgrade them, stay themselves there and thus old residents are being indirectly “squeezed”.

13. A. Tversky and D. Kahneman, Under end, the empire of capitalism notalso just important. a good ideaIn —the it can work in practice again.

Statistician: A Naïve Sampling Model “Judgment of Intuitive Confibeing indirectly “squeezed”.

Uncertainty: andReview Biases,” Science, New SeriesRuth AButdescription of back, this phenomenon inHeuristics the work of114, Sociologist dence Intervals,” Psychological no. 3 (2007): will strike it’shistory likely that the is fi- included thisprobably time we should learnand from about 185, no. 4157 in (Sept.

27, 1974): 1124-1131.

678-703.

Anancial description ofpredict. this phenomenon included the work of Sociologist Ruth GLASS atcanthe same period, while similar were recorded in other major Jedi return to preeminence (albeit, withis situations what we andwill cannot 14.

That alsoand applies to samples that are imaginary.

See major i. S.situations Makridakis M. Hibon, “The Accuracy ofin ForecastGLASS at the same period, while similar were recorded other powers diminished by regulation).

Capitalism is ing: PAn cities in Western countries, by other Researchers. . Juslin, A. Winman and P.”Hansson, “The Naïve Intuitive Empirical Investigation, Journal of the Royal Spyros Makridakis is an emeritus professor of not just a goodthe idea — it can work in practice again. cities in Western countries, by other Researchers.

Statistician: A Naïve Sampling Model of Intuitive Statistical Society, Series A, 142, no.

2 (1979): 97-145.

Since then, issue has preoccupied several scholars and forConfiits more decision sciences at INSEAD and founding chief Intervals,” Psychological Review 114, no. 3 (2007): Butofthis time wethe should learn and from history about ii. S.dence editor the Journal of Forecasting the InternaSince then, issue has preoccupied several scholars and for its more Makridakis, A. Andersen, R. Carbone, R. Fildes, M.various comprehensive approach are being summarized below, from the 678-703. tional Journal of and Forecasting.

Robin M. Hogarth is R. Lewandowski, J. Newton, E. Parzen and R. what we can cannot predict. comprehensive approach are beingHibon, summarized below, from the various i. S. Makridakis and M. Hibon, “The Accuracy of Forecastinterpretations of theatphenomenon the following: ICREA Research Professor Universitat Pompeu of gentrification, Winkler, “The Accuracy of Extrapolation (Time Series) ing: AnResults Empirical ”Competition, Journal of the Royal Fabra, Barcelona. Anil Gaba isphenomenon the Orpar Chaired of gentrification, Methods: of aInvestigation, Forecasting ” Journal interpretations of the the following: Spyros Makridakis is an emeritus professor of In a sense, the phenomenon is due to aoftrend ofSociety, a new category of social groups Statistical Series A, 142, no. 2111-153; (1979): 97-145.

Professor of Risk Management at INSEAD, where Forecasting 1, no. 2 (September 1982): and S. decision sciences at INSEAD and founding chief he directs the Centre on Decision Makingthe and Risk and M. Hibon, “The M3-Competition: Results, to “return” city, leaving for reasons: costs inM.money editor ofto thethe Journal of Forecasting and thepurlieus Interna- Makridakis ii. S.several Makridakis, A. Andersen, R.high Carbone, R. Fildes, Analysis. They are the coauthors of Dance With Conclusions and Implications,” International Journal of tional Journal of Forecasting.

Robin M. Hogarth Hibon, R. Lewandowski, J. Newton, E. Parzen and R. of the and Chance: time to travel from purlieus tois downtown, where work place lack Making Luck Work Forthe You (Oneworld PubForecasting 16, no.

4 (October-December 2000):is, 451-476.

ICREA Research Professor at Universitat Pompeu Winkler, “The Accuracy of Extrapolation (Time Series) lications, 2009).

Comment on this article or contact 1.of The term from Sociologist Ruthiii.GLASS, 1912-1940.

GLASS wasbetter born in sense safety atcomes the outside town centres, search for Fabra, Barcelona.

Anil distributed Gaba is the Orparresidencies Chaired Methods: of a Forecasting Competition, ” Journal For a furtherResults application of this Ruth method, see T.S. Pitsis, the authors at smrfeedback@mit.edu.

Berlin, where her first studies. sheM.published an important study Professor ofshe Riskmade Management at INSEAD, whereIn 1932 Forecasting 1, no. 2 (September 1982): “Con111-153; and S.entitled: S.R.of Clegg, Marosszeky and T. Rura-Polley, services of health, education, entertainment “at the heart of the city”, (possibly) directs the Centre onThe Decision Making andshe Risk leftstructing Makridakis and M.Dream: Hibon, M3-Competition: Results, the Olympic Acontinuous Future Perfect Strategy YouthheUnemployment. same year Germany and after“The movements for REFERENCES Analysis.cost They are coauthors of Dance With Conclusions and Implications, ” International Journal of Project Management, ”she Organization Science 14, no. 5of etc. lower living of,thein “withdrawal” from private car access to markets, studies and research Geneva, Prague, London and Neweasier York came back to London, where Chance: Making Luck Work For You (Oneworld Pub- (September-October Forecasting 16, no.

4 (October-December 2000): 451-476.

2003): 1. See also, J. Surowiecki, “Thestudies Wisdom of regarding Crowds” in According 1943 she published cityphenomenon planning. In 1950 sheto became teacher in the to Comment another approach, the is 574-590. due a systematic and lications, 2009). on this article or contact iii.

For a further application of this method, see T.S. Pitsis, (New York: Anchor Books, 2005).

University College of London, where she continued her social research.

Her public action and the authors at smrfeedback@mit.edu. long-term informal effort byto Calm organized groups, manufacturers, brokers of buying S.R. 51214.

Clegg, M. Marosszeky and T. Rura-Polley, “ConReprint “Paulson Says He’ll ‘Do What It Takes’ Mar- for justice. her2.work are characterized by a passion Seethe also: COLLINSA Future ENGLISH DICTIONARY. structing Olympic Dream: Perfect Strategy Copyright © Massachusetts Institute ofof Technology, 2010. kets, ” Mar.Wil. 16, 2008, http://www.bloomberg.com/apps/ and selling real estate, etc., for theCodepreciation initially of part the urban web, in REFERENCES 10th edit.

COLLINS SONS AND Ltd. London 2009.

WIKIPEDIA: The Free Encyclopedia: of Project Management,” Organization Science 14, no. 5 All rights reserved. news?pid=20601087&sid=aPR8k.dkNie0&refer=home.

G. ALEXANDRI: Abstract. http://www.uncanny.net/ wetzel/gentry.htm (September-October 2003): 574-590. a Gentrification: variety of ways, in order to achieve the “assisted”, “voluntary”, (actually 1. See also, J. Surowiecki, “The Wisdom of Crowds”

20

(New York: Anchor Books, 2005).

90 MIT SLOAN MANAGEMENT REVIEW WINTER 2010

2. “Paulson Says He’ll ‘Do What It Takes’ to Calm Markets,” Mar. 16, 2008, http://www.bloomberg.com/apps/ news?pid=20601087&sid=aPR8k.dkNie0&refer=home.

90 MIT SLOAN MANAGEMENT REVIEW WINTER 2010

SLOANREVIEW.MIT.EDU

Reprint 51214.

Copyright © Massachusetts Institute of Technology, 2010.

All rights reserved.

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