经济与社会科学2020sticerd.lse.ac.uk
人们为何深陷贫困？
Why Do People Stay Poor?
入门 · 约 60 分钟读完前置知识：基础经济学概念、统计学基础
导读
这篇 LSE 工作论文（EOPP 67）探讨“为什么人们会持续贫困”这一问题，研究贫困持续存在的机制。从评论讨论来看，论文涉及储蓄率分布等微观经济数据分析，而 HN 读者更多围绕“穷人因结构性原因（高利率、小额购买溢价、缺乏机会）而难以脱贫”展开讨论。
HN 关注点：贫困的成因与阶层流动性是 HN 经典话题，讨论焦点集中在“贫穷税”（穷人反而花更多钱）以及个人通过技能转型（如学编程）脱贫的可能性。
HN 评论精选
这几条评论里：支持 1 质疑 1 补充 1 亲历 1
亲历亲历者分享从洗碗工转型为程序员脱贫的经历，强调机会与时间积累的重要性
如果没有完成从洗碗工/工厂工作到软件开发的跨越，我不知道自己怎么才能摆脱贫困（现在也还没完全摆脱），毕竟我的收入涨了 4 倍。以低时薪直接用时间换钱太残酷了，我以前每周洗 70 小时的盘子。和室友合住的话，我一年 1-2 万美元也能过，靠体力活能挣到但存不下多少。我很幸运单身、没有孩子这类直接责任。我认为只要有网络、时间和意愿，人可以改善自己的生活，但不能简单说“去学编程”。机会很重要——我技术性无家可归时能睡朋友沙发，这就是最低限度的机会。我的跨越并不快，转型花了至少 2 年，还不算之前 3 年的自学，期间我一边洗碗一边接外包。
jcun4128查看英文原文
Without making the jump from washing plates/factory work to software I don't know how I would have escaped(still haven't) considering my pay increased 4 times. Just brutal when you trade hours for money directly at a low rate, I was doing 70hrs washing plates before and it was nothing ha. Edit: there is the thought of living within your means, personally with a roommate I could live on $10-$20K a year which you can make doing labor jobs but not a lot saving. I'm lucky being single/having no direct responsibility eg. children. It is my opinion though that if you want to/have internet/time then you can alter your life for the better, but yeah can't just say "learn to code". But other options available. I see the point about opportunity because I had a friend to crash on his couch when I was technically homeless that is helpful/bare min opportunity. My jump was not fast, it took at least 2 years not including the 3 years before that of self-study/personal interest. I freelanced on the side while working as a dishwasher before first in office/full time job.
支持穷人因各种结构性原因反而承担更高的单位成本，形成“贫穷税”
简单的答案：因为穷人的开销更高。下层阶级一辈子租房而不是买房；买 20 件装 20 美元的必需品买不起，只能买 5 美元的 2 件装，还得为再次采购多花路费；雇主不提供工作服和工具，得自己买；贷款利率是 25% 而不是 5%；因为存不下钱，还要付滞纳金、透支费。
jfrunyon查看英文原文
Easy answer: because expenses are higher for poor people. Instead of buying a home, the lower class rent their whole life. Instead of their daddy giving them a home, the middle class pay interest on a mortgage most of their life. Instead of buying a 20-pack of $necessary_product that costs $20 and will last for months, the lower class buy a 2-pack that costs $5 and lasts a couple weeks because they need the $15 to pay rent. And then they have to spend more money on gas (or bus fare, or a taxi, or time and energy walking, or ...) to get to the store again sooner. Instead of the employer providing any supplies that are needed, the lower class have to buy their own uniforms or tools. Instead of a 5% interest rate on their loan, they have a 25% interest rate. Because they don't make enough money to set some aside as savings, they have to pay late fees or NSF fees or overdraft fees.
补充引用著名的“靴子理论”说明穷人被迫为劣质商品支付更高的长期成本
（引用特里·普拉切特《碟形世界》中 Vimes 队长的“ Boots 理论”）富人之所以富，是因为他们能花更少的钱。一双 50 美元的好靴子能穿十年，而穷人只能买 10 美元的便宜靴子，十年里花了 100 美元，脚却一直是湿的。
hprotagonist查看英文原文
The reason that the rich were so rich, Vimes thought, was because they managed to spend less money. Take boots, for example. He earned thirty-eight dollars a month plus allowances. A really good pair of leather boots cost fifty dollars. But an affordable pair of boots, which were sort of OK for a season or two and then leaked like hell when the cardboard gave out, cost about ten dollars. Those were the kind of boots Vimes always bought, and wore until the soles were so thin that he could tell where he was in Ankh-Morpork on a foggy night by the feel of the cobbles. But the thing was that good boots lasted for years and years. A man who could afford fifty dollars had a pair of boots that'd still be keeping his feet dry in ten years' time, while the poor man who could only afford cheap boots would have spent a hundred dollars on boots in the same time and _would still have wet feet_." This was the Captain Samuel Vimes 'Boots' theory of socioeconomic unfairness.
质疑数据分析师视角：指出论文图表中 KDE 估计可能产生的伪影并推荐 logKDE 方法
不细读论文不评论内容本身，但第 64 页图 (b)“储蓄率分布”左侧有个奇怪的小峰，很难从目测判断这是数据的真实特征还是朴素核密度估计的伪影。如果你在图里看到这种模式，建议尝试 logKDE 而不是 ggplot 里 geom_density() 那种普通 KDE，对近似指数分布的数据效果通常更好。
roenxi查看英文原文
I'm not going to comment about the article without reading it carefully; but just in case there are any aspiring data analysts online there is a chart that is interesting even without knowing anything about the data... On page 64 (65 as the PDF numbers it), chart (b) "Distribution of savings rate" has an awkward little peak on the left hand side of the chart. It is very difficult to tell from inspection whether that is a real feature of the underlying data or if it is an artefact naive kernel density estimation. If you ever see that pattern in your graphs, do consider trying logKDE [0] rather than ordinary Kernel Density Estimation a la geom_density() in ggplot. It also isn't perfect but the result is usually a bit better for things that approximate an exponential distribution. [0] https://cran.r-project.org/web/packages/logKDE/vignettes/logKDE.pdf
相关资源
从这篇论文所有 HN 讨论帖的全部评论里整理出来的链接。
- 视频与演讲
- 评论区提到的论文
历次讨论
- 2020Hacker News 讨论帖169 分 · 297 评
同领域还值得读
一切的回报率，1870–2015
The Rate of Return on Everything, 1870–2015
利用1870–2015年多国的长期数据，估算股票、住房等各类资本的回报率，并将其与经济增长率进行比较。
经济与社会科学2019 · 487 分 · 260 评进阶 · 约 100 分钟编辑精选一切资产的回报率，1870–2015
The Rate of Return on Everything, 1870–2015
构建了 1870–2015 年 16 个国家的长周期资产回报数据集，覆盖股票、住房、政府债券和短期票据，系统比较各类资产的真实回报与波动性。
经济与社会科学2018 · 215 分 · 151 评进阶 · 约 120 分钟编辑精选一切资产的回报率，1870–2015（2019）
The Rate of Return on Everything, 1870–2015 (2019)
这篇发表于《经济学季刊》的论文构建了 1870–2015 年间 16 个主要发达国家的股票、债券、房地产等资产收益率的长周期数据库。
经济与社会科学2024 · 190 分 · 148 评进阶 · 约 80 分钟编辑精选想法是否越来越难找？
Are ideas getting harder to find?
探讨“想法是否越来越难找到”：通过衡量多个领域的“研究生产率”，发现维持相同的增长需要投入指数级增长的研究资源，即研究效率在持续下降。
经济与社会科学2016 · 182 分 · 106 评入门 · 约 60 分钟编辑精选比特币与区块链的经济极限
The Economic Limits of Bitcoin and the Blockchain
芝加哥大学 Eric Budish 的论文从经济学角度分析比特币与区块链的根本限制：核心论点是只要攻击网络（双花或砸盘做空）的收益超过挖矿成本，51% 算力攻击就有利可图，而挖矿…
经济与社会科学2018 · 176 分 · 37 评进阶 · 约 90 分钟编辑精选