通胀计算的新方法:大数据

2016-03-22 19:17:17

通货膨胀的概念很好解释,但价格的上涨却极难预测。首先,统计员要搞清人们买了什么东西,购买的比例是多少(一篮子商品)。他们必须连续追踪这些产品的价格变化。最后,他们必须对新产品、口味变化及价格上涨做出解释。 

大数据会让这一切变得简单。当前的美国消费者物价指数需要派遣工作人员到各个店铺去记录价格。这个篮子是基于消费者的调查,该数据每三天更新一次。这种方法与网购相比笨拙许多。从理论上讲,在线篮子和物价可以直接追踪数据。

美国技术公司奥多比正在尝试这一方法。公司从其客户浏览的网站中收集匿名的购买数据,美国500强零售商在线销量的四分之三都在统计之中。奥多比意图通过这庞大的信息数据来计算“在线物价指数”(DPI),从而同官方的通胀数据竞争。 

与传统方式相比,DPI有很多优点。DPI 可以追踪140万种产品,而CPI只能追踪8万个。DPI追踪的是实际成交价格,而不是商场的广告价格,因此准确度更高。各国的经济学家们也可以从大量的数据中推断出价格变化对消费者购买意向的影响。 

DPI指数完全不含线下价格以及汽油、租金等消费的价格,因此不可能取代CPI指数。但也表明了官方数据确实可能错过一些暴涨和暴跌的情况,尤其是在科技领域。研究人员发现,在DPI指数中,电脑的价格在今年一月下跌了13.1%,接近CPI数据的两倍,电视价格的跌幅也大于CPI数据。差距甚大的原因可能是技术更新的速度太快了。调查人员发现,80%的技术产品消费是购买新产品,而DPI指数能更灵敏地捕捉到数据的变化。

如果这种现象普遍存在,那么实际的通胀水平将低于官方数据。各国央行、借款人、节俭的人以及任何购买长期合约的投资者都要对此提高警惕。这也意味着 GDP 被低估了。如果整体消费水平是准确的,而通胀水平被高估,那么实际产出会高于预期水平。 

官方的统计员也在完善他们的调查方式。CPI指数现在也涵盖了检索网站自动生成的数据。但若不尽早地对大数据加以重视,官方数据将迎来极其强大的竞争对手。 

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. 

本文翻译由兄弟财经提供

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

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