1 China January inflation plunges to 0.8% (Straits Times) China’s inflation plunged to 0.8 per cent in January, its lowest level for more than five years, official data showed. The rise in the consumer price index (CPI) was sharply down from the 1.5 per cent recorded in December, according to figures provided by the National Bureau of Statistics (NBS).
The CPI figure reinforces signs of persistent weakness in the economy and broadens the scope for further stimulus steps by the central bank to ward off deflationary risks. Analysts had expected annual consumer inflation to be 1.0 percent in January, compared with 1.5 per cent in December.
2 India GDP formula baffles experts (BBC) The Indian economy grew by 7.5% between October and December compared with the same period a year earlier, official figures say. But there was confusion regarding the statistics after the way in which the gross domestic product (GDP) figure was calculated was changed. Economists warned the figures needed to be treated with caution.
The country’s new way of calculating GDP has baffled analysts since its release last month. India said the new formula is closer to international standards. But analysts say the new data does not correlate with other economic indicators, including industrial and factory production.
Some economists have said the latest figures should be “taken with a pinch of salt” and expressed scepticism over the figures at a time when India’s central bank has been talking about a slowdown. Jyotinder Kaul, principal economist at HDFC Bank, also questioned the “credibility” of the numbers.
India was believed to be in the midst of the worst economic slowdown since the 1980s with below 5% growth, a level that was considered to be too low to generate jobs for millions of young people. Indian Prime Minister Narendra Modi won last year’s general elections on a promise to reform and revive the economy and attract much-needed foreign investment. Optimism has grown, but the country is yet to see any of the big bang reforms Modi promised to revive the economy.
3 How Twitter predicts heart disease (Kristen V Brown in San Francisco Chronicle) New research from the University of Pennsylvania suggests that analyzing tweets on the social network can provide better insight into the prevalence of coronary heart disease in a community than many more traditional methods of prediction than factors such as smoking, diabetes and obesity — combined.
University of Pennsylvania searched geo-tagged tweets sent from 1,300 US counties between 2009 and 2010, sorting tweets according to the types of emotions they conveyed. Researches then compared the findings to CDC heart disease mortality data from the same years. The tweets conveying negative feelings closely matched with the CDC data.
Tweets about things such as anger, stress and fatigue, it turned out, were a signifier for heart disease risk. More optimistic tweets, on the other hand, were associated with a lower risk of disease. The new research was rooted in previous studies that showed characteristics such as depression and chronic stress are affiliated with an increased risk of disease.
Johannes Eichstaedt, the study’s lead author, said the hope is to eventually expand the research to understand how psychological traits are linked to physical health. However, big data has its limits. Google Flu Trends, once the great beacon for the promise of Big Data in health, has recently come under attack. Last spring, social scientists found that Google had consistently overshot the number of reported flu cases. Google, they said, was guilty of “big data hubris.”