通脹計算的新方法：大數據

通貨膨脹的概念很好解釋，但價格的上漲卻極難預測。首先，統計員要搞清人們買了什麼東西，購買的比例是多少（一籃子商品）。他們必須連續追蹤這些產品的價格變化。最後，他們必須對新產品、口味變化及價格上漲做出解釋。 

大數據會讓這一切變得簡單。當前的美國消費者物價指數需要派遣工作人員到各個店鋪去記錄價格。這個籃子是基於消費者的調查，該數據每三天更新一次。這種方法與網購相比笨拙許多。從理論上講，在線籃子和物價可以直接追蹤數據。

美國技術公司奧多比正在嘗試這一方法。公司從其客戶浏覽的網站中收集匿名的購買數據，美國500強零售商在線銷量的四分之三都在統計之中。奧多比意圖通過這龐大的信息數據來計算“在線物價指數”(DPI)，從而同官方的通脹數據競争。 

與傳統方式相比，DPI有很多優點。DPI可以追蹤140萬種產品，而CPI只能追蹤8萬個。DPI追蹤的是實際成交價格，而不是商場的廣告價格，因此準確度更高。各國的經濟學家們也可以從大量的數據中推斷出價格變化對消費者購買意向的影響。 

DPI指數完全不含線下價格以及汽油、租金等消費的價格，因此不可能取代CPI指數。但也表明了官方數據確實可能錯過一些暴漲和暴跌的情況，尤其是在科技領域。研究人員發現，在DPI指數中，電腦的價格在今年一月下跌了13.1%，接近CPI數據的兩倍，電視價格的跌幅也大於CPI數據。差距甚大的原因可能是技術更新的速度太快了。調查人員發現，80%的技術產品消費是購買新產品，而DPI指數能更靈敏地捕捉到數據的變化。

如果這種現象普遍存在，那麼實際的通脹水平將低於官方數據。各國央行、借款人、節儉的人以及任何購買長期合約的投資者都要對此提高警惕。這也意味著GDP被低估了。如果整體消費水平是準確的，而通脹水平被高估，那麼實際產出會高於預期水平。 

官方的統計員也在完善他們的調查方式。CPI指數現在也涵蓋了檢索網站自動生成的數據。但若不盡早地對大數據加以重視，官方數據將迎來極其強大的競争對手。 

Big data provide new ways to gauge price rises 

INFLATION is a simple concept, but price rises are surprisingly hard to measure. First, statisticians must work out what stuff people buy, and in what proportions (the “basket” of goods). Then they must track the prices of those goods over time. Finally they must decide how to account for new products, changing tastes and the fact that if the price of, say, apples rises, some people will buy another fruit instead rather than pay more. 

Big data could make all of this easier. At the moment, calculating America’s consumer-price index (CPI) involves sending people into shops to note down prices. The basket is based on a survey of consumers which is updated only every three years or so. This looks increasingly cumbersome in a world where every online purchase is logged, somewhere, in a database. In theory online baskets and prices, at least, could be tracked digitally. 

Adobe, a technology firm, is trying to do just that. The firm collects anonymised sales data from websites that use its software. The amount of data available is vast: according to the firm, it includes three-quarters of online spending at America’s top 500 retailers. It is using this ocean of information to compile a “digital price index” (DPI) to rival official measures of inflation. Two economists, Pete Klenow of Stanford University and Austan Goolsbee of the University of Chicago, are helping the firm to crunch the numbers. 

The DPI has several advantages over the conventional approach. It tracks 1.4m goods, compared with the CPI’s 80,000. It is based on actual purchases rather than advertised prices, increasing its accuracy. And the volume of data allows Messrs Klenow and Goolsbee to use fancier statistical methods to account for people changing what they buy as prices move. 

The new index completely misses changes in offline prices and spending on things like petrol and rent. It will not replace the CPI any time soon. It does suggest, however, that official statistics may themselves be missing big price movements, especially for consumer technology. The researchers found that the price of computers fell by 13.1% in the year to January, almost double the 7.1% fall recorded in the CPI. Televisions fell more in price than the CPI reports, too. The speed of innovation in technology might account for the difference. The researchers found that fully 80% of technology spending is on new products, which the more nimble DPI can incorporate quickly. 

If this is a widespread phenomenon, and inflation is lower than officially recorded, that has implications for central bankers, borrowers, savers and anyone who strikes long-term contracts. It also means that GDP might be understated, says Mr Klenow. If overall spending is recorded accurately but inflation is exaggerated, output must be higher than thought. 

Official statisticians are improving their methods. The CPI includes some prices that are collected automatically by “scraping” websites(something Britain’s statisticians are also experimenting with). But if their take-up of big data is sluggish, official statistics could eventually face disruptive private-sector competition. 

本文翻譯由兄弟財經提供

文章來源：http://www.economist.com/news/finance-and-economics/21695097-big-data-provide-new-ways-gauge-price-rises-how-much-doggy