经济学人商业 || 阿片类药物泛滥成灾，祸患无穷
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感谢思维导图作者
Yao， 男， 准英专研究生， 二笔三口
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The drugs don’t work
“药”你何用
英文部分选自经济学人20200118期Business版块
The drugs don’t work
“药”你何用
The wider effects of the opioid crisis
阿片类药物泛滥成灾，祸患无穷
The impact of the opioid epidemic in America is staggering. Work by Anne Case and Angus Deaton of Princeton University has indicated that over prescription of pain-relieving drugs was a big factor in the increase in mortality among middle-aged whites that has occurred since 2000. The Council of Economic Advisers has estimated that, in 2018, the costs of opioid addiction (including the value of lives lost) were $696bn, or 3.4% of gdp.
阿片类药物在美国大肆泛滥，影响之大超乎想象。普林斯顿大学学者安妮·凯斯（Anne Case）与安格斯·迪顿（Angus Deaton）的一项调查显示，2000年以来中年白人死亡率不断上升，而镇痛药物开药过量是其中一大原因。据白宫经济顾问委员会（Council of Economic Advisers）估计，2018年阿片类药物上瘾造成的损失（损失的人命被量化为数字/人力资本，计入在内）高达6960亿美元，占美国GDP总量的3.4%。
Slowly but surely, more details are emerging. In 2017 Alan Krueger, also of Princeton, showed* that labour-force participation had fallen in American counties where more opioid pain medication had been prescribed. Now a new paper** by three academics from the University of North Carolina explores the impact of the epidemic on firms and business investment.
虽然进展缓慢，但的确有更多细节正逐渐浮出水面。2017年，普林斯顿大学另一位学者艾伦·克鲁格（Alan Krueger）表示，在阿片类镇痛药开具较多的部分美国郡县，劳动力市场参与度有所下降。近年来，北卡罗来纳大学三位学者发表了一篇论文，专门研究阿片类药物泛滥对企业及商业投资的影响。
As with Krueger’s research, the focus is on the labour market. The authors examine the change in the rate of opioid prescriptions in individual counties between 2002-06 and 2006-10, and compare it with changes in employment five years later (between 2007-11 and 2011-15).
和克鲁格一样，这几位作者的研究重点是劳动力市场。三位学者研究了几个郡县在2002-06及2006-10期间内阿片类药物处方率的变化，并与五年后（2007-11 和2011-15之间）的就业率变化进行了对比。
The delay is an attempt to get round the problem of separating correlation and causation. People who are unemployed may opt for the solace of opioids. But the authors reasonably assume that “opioid prescriptions written by doctors are independent of economic conditions five years later.” Furthermore, some doctors are much more likely to prescribe pain medication than others. Patients of doctors who prescribe more opioids are 5.8% less likely to be employed five years later.
研究中采用五年后的数据进行比较，这个做法排除了因果关系对相关性的干扰。无业人员或寻求阿片类药物的慰藉。但研究人员有理由认为“医生所开的阿片类药物处方并不会影响五年后的经济发展。”而且，有些医生本身更倾向开镇痛药物。这些医生的患者五年后无业的可能性比不倾向开镇痛药物医生的高5.8%。
What the academics find is that higher prescription rates are associated not just with a decline in employment but in the sales growth of firms sited in the worst affected areas. Sales are 1.7% lower for firms in the 75th percentile opioid counties than those in the 25th percentile. Businesses struggle, the authors suggest, because they cannot find the right workers. In addition, companies respond to the shortage of workers by investing more in information technology, substituting capital for labour.
三位学者发现就业率的下滑与开药剂量高有关。除此之外，在开药剂量重灾区，各家公司的销售量也难逃一劫。按阿片类药物用量排名，排名第75百分位的美国郡县的公司销售额比排名第25百分位的低1.7%。他们发现公司因招聘不到合适的员工而发展困难，步履维艰。此外，劳动力短缺迫使各公司增加信息技术投资来填补人力的敞口。
注：
In the 25th/50th/70th percentile: The 25th percentile is also known as the first quartile (Q1), the 50th percentile as the median or second quartile (Q2), and the 75th percentile as the third quartile (Q3). In general, percentiles and quartiles are specific types of quantiles.
例: If a child's weight is at the 50th percentile line, that means that out of 100 normal children her age, 50 will be bigger than she is and 50 smaller. Similarly, if she is in the 75th percentile, that means that she is bigger than 75 children and smaller than only 25, compared with 100 children her age.
Clearly, myriad factors affect growth rates, employment, investment and opioid use. The researchers therefore try to exclude alternative explanations for their findings. They check whether the results are robust by dropping some counties, such as those with the worst economic performance and those associated with “pill mills”—clinics identified by the Drug Enforcement Administration as having excessive prescription rates. To ensure results are not distorted by the types of firm being examined, they test the sample excluding manufacturing companies and firms with high exposure to Chinese imports. The impact of opioids on employment remains the same.
显然，无数因素会影响销售增长率、就业、投资和阿片类药物使用。因此，研究人员尝试剔除一些其他因素。他们通过删除一些郡县来检验结果的可靠性，比如那些经济表现最差的及存在“药丸作坊”（美国毒品管理局认定为阿片类药物开药剂量过高的诊所）的郡县。为确保研究结果不会因所检验公司的类型失真，研究人员将制造业公司，以及中国产品进口量较高的公司从测试样本中删除。结果保持不变。
When it comes to employees, the authors include only workers aged between 18 and 60 (to exclude those about to retire) and those who have not previously been prescribed opioids. And they also examine emergency-room prescriptions—visits to the ER involve urgent cases and doctors are randomly assigned, reducing the chance that the results are driven by intentional drug-seeking behaviour. Increases in ER prescriptions are also associated with falls in employment and slower firm growth.
至于员工方面的因素，仅包括了18岁至60岁（剔除即将退休的员工），以及未持有过阿片类药物处方的员工。此外，他们还将急诊室处方（急诊患者通常情况紧急并且医生是随机分配的）纳入考量，从而减少有意觅药行为对研究结果的影响。急诊室开药剂量的增长也与就业下滑及公司销售增长放缓有关。
The clear negative impact of opioid abuse has significant implications. First, it shows the difficulties faced by economists when forecasting variables such as labour-force participation rates. Anyone constructing a model in the late 1990s could not reasonably have anticipated the opioid epidemic.
阿片类药物滥用产生的显著负面影响有着重要的意义。首先，经济学家们在预测一些诸如劳动力参与率之类的可变因素时会面临不少困难。公平合理地讲，任何在20世纪90年代后期构造经济模型的人都料不到阿片类药物会泛滥。
Second, the epidemic presents a strong argument for government intervention. It arose from a market failure: doctors were free to prescribe opioids and patients were free to take them. Neither group seems to have anticipated the addictive effects.
其次，阿片类药物的泛滥也给政府干预市场理论提供了有力的佐证。因为这就是市场自身调节失败的产物：医生毫无约束地开出阿片类药物处方，病人也同样可以不受约束地服用这些药。似乎医患双方都没有预料到这种行为将会导致上瘾的结果。
The authorities have reacted, with 25 states passing laws to regulate opioids use, starting with Massachusetts in 2016. Since 2017 the increase in deaths from opioid abuse seems to have halted. The academics also find some evidence of positive share-price gains for companies based in those states that passed regulations. Business doesn’t just need skilled employees; it needs workers who are free from addiction.
不过，美国各州政府已经采取了措施，2016年马萨诸塞州首开先河，随后其他24个州也陆续通过了规范管理阿片类药物使用的相关法律。自2017年以来，由于阿片类药物滥用导致的死亡人数的增长似乎得到了遏制。学者们还发现了一些证据，证明那些通过法规的州的公司股价上涨了。企业需要的不仅是技术熟练的“仔”，更需要不嗑“药”的“仔”。
* “Where Have All the Workers Gone? An Inquiry into the Decline of the US Labor Force Participation Rate”
“所有工人都去哪了？美国劳动力参与率下降的探究”
** “The Impact of the Opioid Crisis on Firm Value and Investment”, by Paige Ouimet, Elena Simintzi and Kailei Ye
“阿片类药物滥用对公司价值及投资的影响”，Paige Ouimet, Elena Simintzi and Kailei Ye
翻译组：
Emily，女，金融民工，经济学人粉丝
Clark，一笔，A translator, translating
VeRy，男，电气民工，经济学人资浅爱好者
校对组：
Humi，女，CATer，Catti二笔
Celine，女，英专，外应MA已录取
Hannah，女，教书匠，经济学人粉丝
Megan, 女，外事民工，热爱是唯一的信仰
Li Xia, 女， 我视英语为初恋，英语瞧我像备胎
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本次感想
Alan，男，金融工程硕士，经济学人粉丝
这篇文章讲的是医用鸦片在美国的影响，各种各样的research paper在探讨其影响几何。
统计学里并没有什么万能方法能够区分两组数据之间的相关性和因果性，两组数据的相关性一般用R2（R squared）来表示，或者是相关系数，它俩数值上相等；但在一组数据和几组数据做相关性测试时就只能用adjusted R2来描述了。如何判断因果关系，一般是需要用其他的方法证明的，例如解释货币供给会导致物价水平上升，这之间的价格传递机制就需要用微观经济理论解释。
在这篇文章里，作者用鸦片处方量差分和就业率差分做统计回归，就业率被滞后了五年，因为作者觉得鸦片处方量对五年后的经济不会有什么影响，从而能够得到一个纯相关关系。
同时因为有很多原因会影响到就业率、经济增长率和投资率，为了剔除这些其他因素的影响，作者们剔除了一些很糟糕经济状况的郡和那些过量开鸦片处方的郡，和那些大量进口中国产品的制造业企业（不过这么做在我看来完全不够剔除其他因素的影响）。
容我感叹一些美国教育里统计学课程真的相当相当扎实，除了少数人文艺术学科之外对于大多数学科统计学都是逃不掉的。
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