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今年的诺贝尔经济学奖授予了三位在克服全球贫困中做出革命性贡献的学者:麻省理工学院的阿比吉特·巴纳吉(AbhijitBanerjee)和埃丝特·迪弗洛(EstherDuflo)以及哈佛大学的迈克尔·克雷默(MichaelKremer)。以此表彰他们“在减轻全球贫困方面的实验性做法”。
但他们的方法在实践中是如何起作用的呢？为什么它被认为是开创性的？它究竟在多大程度上改变了世界上最贫困人口的生活？快跟小编一起来看一看吧。
Don't Assume – Test!
For decades, programs and policies to help the poor have largely been designed around what seemed like reasonable assumptions:
Kids in poor areas can't afford new textbooks — so surely giving them free ones will improve their test scores.
Impoverished women have a hard time finding jobs – so surely giving them a "microloan" of a few hundred dollars to start a small business will boost their incomes.
几十年来，扶贫的项目和政策基本上都是围绕着看似合理的假设来设计的:
贫困地区的孩子买不起新的课本，所以给他们免费的课本肯定能提高他们的考试成绩。
贫困的妇女很难找到工作，所以给她们几百美元的“微贷款”来开办小企业肯定会增加她们的收入。
But Kremer, beginning in the 1990s, and joined by Banerjee and Duflo some years later, helped lead a growing movement of economists who were concerned by what they saw as a key flaw in that approach: Assumptions are just that. Without evidence you can't be sure they are true. After all, just because peoples' lives improved after they were given a particular form of aid doesn't mean it was the aid that made the difference.
从上世纪90年代开始，克雷默发起了一场不断发展壮大的经济学家运动。几年之后，班纳吉和迪弗洛也加入了他的行列。在他们看来，这种解决方案存在一个关键性缺陷:缺乏证据支持。毕竟，仅仅因为人们的生活在得到某种形式的援助后得到了改善，并不意味着是这种援助起了作用。
Some totally unrelated factor could have been at work – say, a concurrent rise in overall economic growth or a different aid program distributed at the same time. Also, the money available for aid programs is finite. So even if a particular intervention does help, it might not be the best use of resources if there's a different intervention that would deliver bigger results. The only way to find out is to put your assumptions to the test.
也有可能是一些完全不相关的因素在起作用，例如，整体经济增长的同时（人们生活水平也在）提高，或者同时在实施另一个不同的援助项目。此外，用于援助项目的资金是有限的。因此，即使一种特定的干预确实有所帮助，但如果还有另一种效果更好的干预，那么这可能不是对资源的最大化利用。找出答案的唯一方法就是检验你的假设。
The Nobel winners helped develop and popularize the application to poverty research of a method: the randomized controlled trial – or RCT. In a nutshell, to see if a particular aid program works for a given population, you compare its impact to the results for an otherwise identical "control" group of people to whom you did not give the aid.Poverty researchers who focus on the value of RCTs are so committed to the concept that their colleagues have dubbed them "randomistas."
诺贝尔奖得主协助开发和推广了一种应用于贫困研究的方法:随机对照试验(RCT)。简而言之，要想知道一个特定的援助项目是否对特定的人群有效，你可以将它的影响与你没有给予援助的“控制组”的结果进行比较。关注随机对照试验价值的贫困研究人员非常坚信这一概念，以至于他们的同事称他们为“随机化者”。
What have the randomistas revealed?
Returning to the example of microloans for would-be women entrepreneurs who can't qualify for financing from a bank because they are too poor: A raft of RCTs (including some by members of this year's Nobel team) have disproved the once popular notion that microloans can substantially boost the incomes of poor people. (As this article explains, it's not that microloans are never useful for poor people. They can be. It's just that the evidence suggests their broader impact is muted.)
让我们回到为潜在的女性创业者提供微贷款的例子上来，她们因为太穷而不能从银行获得融资：大量的随机对照试验(RCT)（包括今年诺贝尔奖小组的一些成员）驳斥了一度流行的观点，即小额贷款可以大幅度提高穷人的收入。（正如这篇文章所解释的，并不是说小额贷款对穷人毫无用处。他们有用，只是有证据表明它们的影响范围较小。）
Similarly, RCTs by members of the Nobel team and others have shown that when it comes to education, there's a limit to the effect of intuitively reasonable measures such as reducing the student-teacher ratio, providing free lunches and ... you guessed it, distributing textbooks.
同样，诺奖团队成员和其他人的随机对照试验表明，在教育领域，某些看似合理的措施的效果是有限的，比如降低学生—老师比例、提供免费午餐和……你猜对了，分发课本。
Instead, some of the biggest boosts to student educational outcomes come from less obvious fixes such as providing kids with cheap de-worming pills that dramatically reduce the number of days they have to miss school due to tummy trouble. Also in the most impactful category: targeting assistance to the lowest performing students and making teacher contracts contingent on their students' performance.
相反，对学生教育成果的最大推动力来自于一些不太明显的解决办法，比如为孩子提供廉价的除虫药片，这大大减少了他们因肚子不舒服而缺课的天数。同样影响很大的手段还包括：为表现最差的学生提供针对性帮助，并根据学生的表现制定教师合同。
The randomistas' reach ...
Over the last two decades there's been an explosion in the use of RCTs. Some are aimed at uncovering the underlying factors that keep people trapped in poverty. Others are effectively "impact evaluations" – as they're called in the movement — of specific policies and programs for the poor.
Many of these studies originated from a network of more than 180 researchers around the world that Banerjee and Duflo helped found at MIT in 2003. It's called the Abdul Latif Jameel Poverty Action Lab, or J-PAL.
在过去的二十年里，随机对照试验的使用呈爆炸式增长。有些旨在揭示使人们陷入贫困的根本因素。另一些是针对穷人的具体政策和项目的有效“影响评估”——这在运动中被称为“影响评估”。
其中许多研究都来自这个网络。2003年，班纳吉和迪弗洛在麻省理工学院(MIT)协助建立了一个由全球180多名研究人员组成的网络，它叫做阿卜杜勒·拉蒂夫·贾米尔贫困行动实验室，简称J-PAL。
The randomista movement has also inspired various governments to use RCTs to inform and tweak the design of major programs. This includes "Teaching at the right level" (TaRL) – an approach pioneered by an Indian NGO that has been tested with the help of J-PAL researchers. It has been applied by local governments in India and Africa to improve elementary school instruction for millions of children.
随机化运动还促使各国政府利用随机对照试验来了解和调整主要项目的设计。这包括“正常水平教学”(TaRL)——一个由印度非政府组织首创的方法，已经在J-PAL（贫困行动实验室）研究人员的帮助下进行了测试。印度和非洲的地方政府用此方法了改善数百万儿童的小学教育。
... and the limits of their influence
Even as they tout the successes, many champions of this evidence-based approach to fighting poverty say it's not being used widely enough. For instance, some staff at the U.S. Agency for International Development have been pushing an experimental effort to use RCTs to test whether any given aid program is more impactful than simply handing out an equivalent amount in cash. But that effort has run into resistance. Former staffers there say it's at least partly because there's an inherent bias against trusting poor people to spend cash wisely – regardless of what the evidence shows.
Meanwhile, there's also debate among economists as to whether the focus on RCTs obscures deeper, more fundamental drivers of poverty – such as systemic inequality – that must be addressed if there's any hope of truly improving lives.
就在他们吹捧成功的同时，这种基于证据的扶贫方法的许多拥护者表示，这种方法的使用（范围）还不够广泛。例如，美国国际开发署(U.S. Agency For International Development)的一些工作人员一直在推动一项实验性工作，即使用随机对照试验来测试那些已经实行的援助计划是否比简单地发放等量的现金更有效。但这种尝试遇到了阻碍。那里的前工作人员说，至少有一部分原因是人们固有的偏见，不管证据如何，他们都不相信穷人会明智地花钱。
与此同时，经济学家们也在争论，对随机对照试验的关注是否掩盖了更深层、更根本的贫困驱动因素，比如系统性不平等，如果有任何能真正改善生活的希望，就必须解决掉这些问题。
What's the impact of this Nobel Prize?
Of course it's too soon to tell. But Duflo says she and her fellow recipients plan to figure out how to make use of the $915,000 prize to further their research. And perhaps the greatest impact will be the attention this brings to the approach they've pioneered. "It's a prize not just for us, but for the whole movement," said Banerjee at a joint news conference at MIT.
当然现在下结论还为时过早。但是迪弗洛说，她和其他获奖者在计划如何利用这笔91.5万美元的奖金来推进他们的研究。也许最大的影响将是他们所倡导的方法所引起的关注。班纳吉在麻省理工学院的联合新闻发布会上说：“这不仅仅是对我们的奖励，也是对整个研究方向的奖励。”
文章来源：
https://www.npr.org/sections/goatsandsoda/2019/10/15/770346240/how-the-3-nobel-winners-for-economics-upended-the-fight-against-poverty?from=singlemessage
图片来源：
https://www.pexels.com/
编译：覃安琪
排版：覃安琪
