Economyths: Ten Ways that Economics Get it Wrong

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Icon, 2010 - Economic forecasting - 316 pages
14 Reviews
From the inability of wealth to make us happier, to our catastrophic blindness to the credit crunch, "Economyths" reveals ten ways in which economics has failed us all. Forecasters predicted a prosperous year in 2008 for financial markets - in one influential survey the average prediction was for an eleven per cent gain. But by the end of the year, the Standard and Poor's 500 index - a key economic barometer - was down 38 per cent, and major economies were plunging into recession. Even the Queen asked - Why did no one see it coming? An even bigger casualty was the credibility of economics, which for decades has claimed that the economy is a rational, stable, efficient machine, governed by well-understood laws. Mathematician David Orrell traces the history of this idea from its roots in ancient Greece to the financial centres of London and New York, shows how it is mistaken, and proposes new alternatives. "Economyths" explains how the economy is the result of complex and unpredictable processes; how risk models go astray; why the economy is not rational or fair; why no woman (until 2009) had ever won the Nobel Prize for economics; why financial crashes are less Black Swans than part of the landscape; and, finally, how new ideas in mathematics, psychology, and environmentalism are helping to reinvent economics.

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Review: Economyths: Ten Ways Economics Gets It Wrong

User Review  - Samuel Smith - Goodreads

Typical writing to cure the worlds problems book. Read full review

Review: Economyths: Ten Ways Economics Gets It Wrong

User Review  - Goodreads

Typical writing to cure the worlds problems book. Read full review

Contents

Introduction
1
The anarchic economy
9
The connected economy
28
Copyright

12 other sections not shown

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About the author (2010)

David Orrell is an applied mathematician and author of popular science books. He studied mathematics at the University of Alberta, and obtained his doctorate from Oxford University on the prediction of nonlinear systems. His work in applied mathematics and complex systems research has since led him to diverse areas such as weather forecasting, economics, and cancer biology. His work has been featured in the New Scientist, the Financial Times and on BBC Radio.

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