Hans is a professor of public health who specializes also in data visualization. He has shown how data can inform policy-making.
The following video is a must see for those interested in numbers for decision-making and/or alleviating poverty. Also, you’ll love Hans for his sense-of-humour.
Watch the entire video to see him swallow a sword at the end to make his point:
anything is possible.
http://www.ted.com/talks/hans_rosling_reveals_new_insights_on_poverty.html
Why households in poor countries have more children? Is it because of religious reasons, i.e., no contraceptives allowed. Or is it because of disease, i.e., high infant mortality rates due to disease result in parents having a large number of children because the parents are not certain how many children, if at all, will survive.
The following animation presents data from the World Bank that suggests that with a decline in infant mortality rate over time, the fertility rates declined as well. What could also be extrapolated is that with the decline in the incidence of numerous diseases, the infant mortality rates have declined sharply in certain countries. The lag with fertility rates implies that it would take some time for the fertility rates to decline in response to the lower infant mortality rates.
Each bubble in the animation represents a country.
Is the iPad craze subsiding? A few days after its release one could see that the Internet hype around the product is now settling. The graph below shows a decline in the number of Internet searches conducted on Google for shopping interests.
The regional interest is the highest in the United States followed by Japan, Netherlands, Germany, and Canada. China ranked 9th in the web-interest in the product. Even though Canada’s population is much smaller than that of UK or France, Canadians are more intrigued by iPad even though it is not yet available for sale in Canada.
All forecasts are wrong, some are useful. Despite the uncertainty surrounding forecasts, news media remains obsessed with the ranking of forecasts and forecasters. These rankings obscure the fine point that forecasts are, not can be, wrong and long-term forecasts are more wrong than the sort-term forecasts.
Understanding Economic Forecasts (David F. Hendry and Neil R. Ericsson editors, MIT Press, 2001) lists numerous accounts of how guesswork may also beat sophisticated econometric forecasts!
Below is another ranking of forecasters that has Dr. Sherry Cooper’s team at Nesbitt Burns mentioned as well.
Consistency lands him on top of forecasting mountain
By Rex Nutting, MarketWatch
WASHINGTON (MarketWatch) -- One of the best economic forecasters is a guy who's never quoted in the newspapers and never yells on CNBC. He just gets the numbers right -- at least more right than anyone else.
You've probably never heard of Spencer Staples, the owner, top economist, and chief bottle washer for a relatively new economic research firm, EconAlpha. Staples is the winner of the March Forecaster of the Month award from MarketWatch, beating out 43 other forecasters.
Indicators Forecast Actual ism 56.90% 56.50% nonfarm payrolls -79,000 -36,000 trade gap -$39.9 bln -$37.3bln retail sales -0.30% 0.30% housing starts 562,000 575,000 industrial production -0.30% 0.10% consumer price index 0.00% 0.00% durable-goods orders 0.90% 0.50% new home sales 310,000 308,000 consumer confidence 51 52.5 Not only did Staples win the monthly award, he's also now the top forecaster in our contest over the past 12 months, knocking 2009's Forecasters of the Year Nigel Gault and Brian Bethune of IHS Global Insight out of the top spot.
Staples won the March award based on his predictions on 10 top economic indicators released in the month, including the Institute for Supply Management index, the consumer price index and new-home sales. On six of the numbers, his predictions were among the 10 most accurate.
Staples earned his undergraduate degree at Colby College in Maine, and got his career started at Bear Stearns. He went to the United Kingdom 20 years ago and worked for Mizuho Corporate Bank and an investment management company. Along the way, he earned an MBA from the Henley Business School.
He started his own firm in 2008, hoping to provide institutional investors with more consistent forecasts of the high-frequency economic data, the numbers that are released every week or every month, the numbers that tend to move financial markets the most.
Staples says forecasting the high-frequency data takes fundamentally different skills than forecasting over a longer period of time. Long-term forecasters try to eliminate the statistical noise caused by one-time aberrations in the data, such as weather, the timing of holidays and the like. They want to know the trend.
On the other hand, high-frequency forecasters embrace the noise.
Staples takes this further than do many of his colleagues. He flatly refuses to talk about the longer-term trends.
"My strength is in the high-frequency area," Staples said in a phone interview.
Staples says he approaches forecasting as an information-management problem. With so much information now available about every aspect of the economy, the trick is to know what to trust and what to ignore, he said. Asked for an example, he laughed, saying he didn't want to give away his secrets.
Indeed, Staples provides us with less explanation of his forecasts than anyone else in our contest.
Instead of writing hundreds or even thousands of words to explain his forecasts and what the implications might be, as many of his peers do, Staples simply emails us the bare essentials, like this: "February Non-Farm Payroll is expected to be -79K, with the Unemployment Rate at 9.8%." Everything else is "intentionally left blank." It's for the eyes of his clients only.
Staples is convinced that his clients can make money off forecasts that are consistently accurate.
"I think there is alpha imbedded in some forecasts," he said. Normally, investors think of short-term deviations from the trend as volatility, or beta. But Staples suggests that, for some market participants, a good forecast of those deviations can be like a regular dividend check: It's alpha.
This past year, Staples' forecasts have been plenty consistent. No one can get all the numbers right, but he's been more consistent than most. He's finished in the top 15 in our contest in nine of the past 12 months, more times than anyone else.
The runners up in the March contest were Peter D'Antonio of Citigroup Global Markets, Sherry Cooper's team at BMO Capital Markets, Michelle Girard and Omair Sharif of RBS Securities, and tied for fifth: Avery Shenfeld and Meny Grauman of CIBC World Markets and Ethan Harris's team at Bank of America Merrill Lynch.
The median forecasts that MarketWatch publishes each week in the Economic Calendar come from the forecasts of the 10 economists who've scored the highest in our contest over the past 12 months, as well as the forecasts of the most recent winner.
Over the past year, the top economists are, in order: Staples of EconAlpha; Bethune and Gault at IHS Global Insight; Maury Harris of UBS; the RBS team formerly headed by Stephen Stanley; Ethan Harris of Merrill Lynch; D'Antonio of Citi; David Resler of Nomura Securities; John Silvia's team at Wells Fargo Securities; Lou Crandall of Wrightson ICAP; and independent economic consultant Brian Jones.
300,000 sold on the very first day. Millions most likely be sold in the next weeks. Apple’s iPad, touted as the ultimate device for digital media consumption, has been a rave in North America. However, the global response shows that the iPad has generated more craze in the Asia Pacific (Singapore, Hong Kong, Taiwan, South Korea, Philippines, and Australia) than in Europe or North America.
A review of the Google-based searches reveal that Singapore and Hong Kong led the world in web-based hype for the iPad followed by the United States. The map below shows the geography of interest generated by iPAD in the past three months.
The ultimate high for iPAD was observed on January 28, 2010, on the internet when the product was formally revealed by Steve Jobs. Since its release this week, the web-based interest in the product has started to climb again.
Outside of the United States where iPad is available for sale, Toronto in Canada has generated the most interest about iPAD in the past three months ending April 05, 2010.
From the print edition of The Economist:
The data deluge
Feb 25th 2010
Businesses, governments and society are only starting to tap its vast potential
EIGHTEEN months ago, Li & Fung, a firm that manages supply chains for retailers, saw 100 gigabytes of information flow through its network each day. Now the amount has increased tenfold. During 2009, American drone aircraft flying over Iraq and Afghanistan sent back around 24 years’ worth of video footage. New models being deployed this year will produce ten times as many data streams as their predecessors, and those in 2011 will produce 30 times as many.
Everywhere you look, the quantity of information in the world is soaring. According to one estimate, mankind created 150 exabytes (billion gigabytes) of data in 2005. This year, it will create 1,200 exabytes. Merely keeping up with this flood, and storing the bits that might be useful, is difficult enough. Analysing it, to spot patterns and extract useful information, is harder still. Even so, the data deluge is already starting to transform business, government, science and everyday life (see our special report in this issue). It has great potential for good—as long as consumers, companies and governments make the right choices about when to restrict the flow of data, and when to encourage it.
Plucking the diamond from the waste
A few industries have led the way in their ability to gather and exploit data. Credit-card companies monitor every purchase and can identify fraudulent ones with a high degree of accuracy, using rules derived by crunching through billions of transactions. Stolen credit cards are more likely to be used to buy hard liquor than wine, for example, because it is easier to fence. Insurance firms are also good at combining clues to spot suspicious claims: fraudulent claims are more likely to be made on a Monday than a Tuesday, since policyholders who stage accidents tend to assemble friends as false witnesses over the weekend. By combining many such rules, it is possible to work out which cards are likeliest to have been stolen, and which claims are dodgy.
Mobile-phone operators, meanwhile, analyse subscribers’ calling patterns to determine, for example, whether most of their frequent contacts are on a rival network. If that rival network is offering an attractive promotion that might cause the subscriber to defect, he or she can then be offered an incentive to stay. Older industries crunch data with just as much enthusiasm as new ones these days. Retailers, offline as well as online, are masters of data mining (or “business intelligence”, as it is now known). By analysing “basket data”, supermarkets can tailor promotions to particular customers’ preferences. The oil industry uses supercomputers to trawl seismic data before drilling wells. And astronomers are just as likely to point a software query-tool at a digital sky survey as to point a telescope at the stars.
There’s much further to go. Despite years of effort, law-enforcement and intelligence agencies’ databases are not, by and large, linked. In health care, the digitisation of records would make it much easier to spot and monitor health trends and evaluate the effectiveness of different treatments. But large-scale efforts to computerise health records tend to run into bureaucratic, technical and ethical problems. Online advertising is already far more accurately targeted than the offline sort, but there is scope for even greater personalisation. Advertisers would then be willing to pay more, which would in turn mean that consumers prepared to opt into such things could be offered a richer and broader range of free online services. And governments are belatedly coming around to the idea of putting more information—such as crime figures, maps, details of government contracts or statistics about the performance of public services—into the public domain. People can then reuse this information in novel ways to build businesses and hold elected officials to account. Companies that grasp these new opportunities, or provide the tools for others to do so, will prosper. Business intelligence is one of the fastest-growing parts of the software industry.
But the data deluge also poses risks. Examples abound of databases being stolen: disks full of social-security data go missing, laptops loaded with tax records are left in taxis, credit-card numbers are stolen from online retailers. The result is privacy breaches, identity theft and fraud. Privacy infringements are also possible even without such foul play: witness the periodic fusses when Facebook or Google unexpectedly change the privacy settings on their online social networks, causing members to reveal personal information unwittingly. A more sinister threat comes from Big Brotherishness of various kinds, particularly when governments compel companies to hand over personal information about their customers. Rather than owning and controlling their own personal data, people very often find that they have lost control of it.
The best way to deal with these drawbacks of the data deluge is, paradoxically, to make more data available in the right way, by requiring greater transparency in several areas. First, users should be given greater access to and control over the information held about them, including whom it is shared with. Google allows users to see what information it holds about them, and lets them delete their search histories or modify the targeting of advertising, for example. Second, organisations should be required to disclose details of security breaches, as is already the case in some parts of the world, to encourage bosses to take information security more seriously. Third, organisations should be subject to an annual security audit, with the resulting grade made public (though details of any problems exposed would not be). This would encourage companies to keep their security measures up to date.
Market incentives will then come into play as organisations that manage data well are favoured over those that do not. Greater transparency in these three areas would improve security and give people more control over their data without the need for intricate regulation that could stifle innovation. After all, the process of learning to cope with the data deluge, and working out how best to tap it, has only just begun.
The latest figures have revealed that the foreign direct investments (FDI) fell by a $0.7 trillion in 2009. The US and China remained the largest magnets for FDIs.
India, however, has to be looked in a different light. Compared with FDI, the sums sent home by the expatriate Indian workers are by far significantly large, which shows that one should have a more composite instrument of measuring an economy’s ability to attract all foreign capital that arrives within its borders legally.
Also FDI fell by only 2.6% in 2009 in China and in fact FDI increased in Germany and Italy over the same period.
Foreign direct investment is on the wane
Feb 12th 2010 | From The Economist online
THE flow of foreign direct investment (FDI) fell by 39% in 2009 to just over $1 trillion, from a shade under $1.7 trillion in 2008, according to the UN Conference on Trade and Development. All kinds of investment—equity capital, reinvested earnings and intra-company loans—were affected by the downturn. Rich countries saw FDI inflows plunge by 41%, and foreign investment into developing countries fell by more than a third. Not every country was badly hit. FDI into China, where economic growth remained robust, declined by only 2.6%. Foreigners actually invested more in Germany and Italy last year than in 2008. Despite FDI plunging by 57% last year, America remained the world’s top investment destination.
AFP
