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Yet there are also deeper changes at play.
然而，也有更深层次的变化在起作用。
The first relates to covid-19 disruptions.
第一个变化与新冠肺炎带来的干扰有关。
The world lurched from crashing to soaring growth as lockdowns came and went.
随着封控的到来和结束，世界从崩溃忽然转向高速增长。
This has played havoc with the "seasonal adjustments" common to most economic numbers.
这对大多数经济数据中常见的"季节性调整"造成了严重破坏。
In February the BLS changed the factors that it applies to inflation, which makes interpreting monthly rates much more difficult.
今年2月，劳工统计局改变了适用于通胀的因素，使得解读月度通胀率变得更加困难。
Annualised core inflation in the final quarter of 2022 "increased" from 3.1% to 4.3%.
2022年最后一个季度的年化核心通胀率从3.1%升至4.3%。
It is also harder than normal to understand euro-zone inflation.
理解欧元区的通胀也变得比平时更难。
Kamil Kovar of Moody's Analytics, a consultancy, notes that depending on how seasonal adjustment is done, core month-on-month inflation in March was as low as 0.2% or as high as 0.4%.
咨询公司穆迪分析的卡米尔· 科瓦尔指出，根据季节性调整的不同方式，3月份核心环比通胀率最低为0.2%，最高为0.4%。
The second change relates to sample sizes.
第二个变化与样本大小有关。
The pandemic accelerated a trend in which a growing share of people fail to respond to official surveys.
疫情加速了一种趋势，即越来越多的人没有对官方调查做出回复。
In America the response rate for the survey used to estimate vacancies has fallen from nearly 60% just before the pandemic to around 30%.
在美国，用于估计职位空缺的调查回复率已从疫情前的近60%降至30%左右。
When covid struck, the response rate to Britain's labour-force survey fell by roughly half.
当疫情来袭时，对英国劳动力调查的回复率下降了大约一半。
During lockdowns, some businesses closed.
在封控期间，一些企业停业了。
People fell out of the habit of filling in questionnaires.
人们不再有填写调查问卷的习惯。
Distrust in government may also have grown, leaving people disinclined to help statisticians.
对政府的不信任也可能增加，导致人们不愿配合统计学家。
Falling response rates probably increase data volatility. They may also lead to bias.
回应率的下降可能会增加数据的波动性，还可能导致偏差。
The people who stopped responding to surveys appear less prosperous than those who continue to do so, misleadingly inflating income.
不再回复调查的人似乎不如继续回复调查的人富裕，从而误导性地夸大了收入。
Jonathan Rothbaum of the Census Bureau suggests that real median household income growth in America from 2019 to 2020 was 4.1%, not 6.8% as originally reported, after proper corrections for non-response.
人口普查局的乔纳森·罗斯鲍姆表示，在对没有回复的情况进行适当修正后，2019年至2020年美国家庭收入的实际中位数增长率为4.1%，而不是最初报告的6.8%。
Since 2020 non-response has continued to push up income statistics by about 2%.
自2020年以来，不回复的情况继续将收入统计数据推高了约2%。
A report by Omair Sharif of Inflation Insights, a consultancy, suggests that correcting for "non-response bias" may also have contributed to recent big revisions to American earnings data.
来自咨询公司通胀洞察的奥马尔·谢里夫在一份报告中指出，对"无回复偏差"的修正可能也是导致近期美国收入数据大幅修改的原因之一。
The third reason for confusion stems from the disparity between "hard" and "soft" data--objective measures such as the level of unemployment, and subjective measures such as people's future expectations.
导致困惑的第三个原因源于"硬"数据和"软"数据之间的差距。前者是客观指标，如失业率，后者是主观指标，如人们对未来的预期。
Normally the two types move in sync.
正常情况下，这两种类型的数据同步变化。
Right now they are far apart.
眼下，它们相差甚远。
"Soft" measures look recessionary.
"软"指标看起来经济在衰退。
"Hard" measures point to a decent expansion.
"硬"指标表明经济在良好地扩张。
The divergence may reflect people's grumpiness with inflation.
这种差异可能反映了人们对通胀的不满。
Prices in the rich world are still rising by 9% year on year.
富裕国家的物价仍在以同比9%的速度上涨。
Investors and statisticians will get better at understanding the world economy during periods of volatility and inflation.
在动荡和通胀时期，投资者和统计学家将对世界经济有更好的理解。
As the effects of the pandemic fade, so will distortions to seasonal adjustments.
随着疫情影响的消退，季节性调整带来的失真也会消退。
Economists have already made progress in incorporating alternative data into forecasts, helping to overcome the problem of declining responses.
经济学家在将替代数据纳入预测方面已经取得了进展，从而帮助克服了回复减少的问题。
But this is scant comfort for governments and businesses that need to make decisions right now--or for people just trying to keep up with the news.
但对于现在需要做出决策的政府和企业，或者只是试图跟上新闻报道的人来说，这带来的安慰寥寥无几。
Do not be surprised if the global economy remains sfumata for a while yet.
如果全球经济形势在一段时间内仍如晕涂而成的画一样模糊不清，请不要感到惊讶。
