2019年经济学人印度经济增长的骗局(2)（打印版）

If India's statistics are overstated, who or what is to blame?

如果印度的统计数据被夸大，那么哪些人或物应受到责怪呢？

Political meddling is an inadequate answer, although this government, under Narendra Modi, has done plenty to arouse suspicion.

仅责怪政治干预是不够的，虽然在纳伦德拉·莫迪领导下的政府已经做了很多引起怀疑的事情。

In November statisticians revised down growth figures from last decade, taking the shine off the previous government's record.

在11月，统计学家对过去十年的增长数据进行了下调，使上届政府的政绩黯然失色。

In January they revised up growth in 2016-18, the two fiscal years most affected by Mr Modi's daft

在1月，他们上调了2016-18年的经济增长，这两个财年受到了莫迪愚蠢行为

and disruptive decision to remove highdenomination bank notes from circulation. Both exercises raised eyebrows.

以及取消流通高面额纸币的破坏性决定的极大影响。两项行动均引人侧目。

But Mr Subramanian sidesteps these two recent controversies, excluding the latest revisions from his analysis.

但萨勃拉曼尼亚先生回避了这两个近期的争议问题，将最新的修订排除了他的报告。

Instead he concentrates his fire on a more fundamental technical change:

相反，他把精力集中在一个更根本的技术变革上：

a new method of calculating GDP, from 2011-12 onwards, that was adopted in early 2015.

2015年初采用了一种计算GDP的新方法，从2011年至2012年开始。

Much of the preparation for this switch dated back to the previous government.

这一转变的大部分准备工作可以追溯到上届政府。

And one of the new method's strangest results was an upward revision of growth in the tumultuous year before Mr Modi took office,

而新方法最奇怪的结果之一是对莫迪上任前动荡年份的经济增长进行了上调，

when the economy was reeling from high inflation and capital outflows. That contradicts the charge of political interference.

当时经济正受到高通胀和资本外流的冲击。这与政治干预的指控相矛盾。

Why would Mr Modi's government fiddle the figures to flatter its hated predecessor?

莫迪政府为何要篡改数据，以讨好其令人憎恨的前任呢？

The new method may nonetheless suffer from other shortcomings.

尽管如此，新方法可能还存在其他缺点。

It may, for example, have failed to cope with the drop in oil prices in 2014.

例如，它可能无法应对2014年的油价下跌。

To illustrate: if an Indian company imports 10,000 rupees-worth of crude oil and adds 100 rupees of value to it,

举例来说：如果一家印度公司进口价值一万卢比的原油并增加100卢比的价值，

it might sell the refined product for 10,100 rupees.

它可能会以10100卢比的价格出售这种精制产品。

If the oil price subsequently halves, the company might try selling the same product for 5,110 rupees, boosting its margin.

如果油价随后下跌一半，该公司可能会试着以5110卢比的价格出售同样的产品，以提高利润率。

An unwary statistician might conclude that Indian prices have dropped dramatically.

一个不太谨慎的统计学家可能会得出结论，印度的物价已大幅下跌。

But the Indian part of the total (the only bit that matters for GDP) has increased in price (from 100 to 110 rupees).

但是其中印度的那一部分（GDP中唯一重要的部分）价格上涨了（从100卢比涨到了110卢比）。

The confused statistician may then treat an increase in rupee profits as evidence of real growth, not merely higher prices.

然后困惑的统计学家可能会将卢比利润的增长视为实际增长的证据，而不仅仅是价格上涨。

Such problems are less likely in more developed G20 countries, which keep better track of the prices of inputs.

在更发达的20国集团（G20），此类问题不太可能发生，因为这些国家对投入价格的跟踪能力更强。