【文章标题】：Working on Economics with Fable 5
【文章标题】：《用Fable 5研究经济学的历程》
【文章正文】：
For the past few months I’ve been working on a theory. It started out as just a fun little data exercise looking at some different types of taxes and benefits and how it effects what people buy and how much they work.
过去几个月我一直在研究一个理论。最初这只是一个有趣的小数据实验，研究不同类型的税收和福利如何影响人们的消费选择和工作时长。
During that time I took advantage of opus and later fable to help me get data, but as I was doing that of course opus might interject with some assumption I had wrong or some paper that shows the opposite.
期间我借助opus和后来的fable获取数据，但操作过程中opus会突然指出我的错误假设，或是提供相反结论的论文。
This back and forth continued for some time, and, well, it’s culminated in a theory. I’ve since started working alongside my co-author from the Stockholm School of economics on formalizing the theory.
这种反复持续了一段时间后，最终形成了一个理论。现在我已开始与斯德哥尔摩经济学院的合著者共同推进理论的形式化工作。
My original version, in my voice. Visual, anecdotal, not much in the way of maths or technical details.
我的初版是个人化的表述：可视化、案例化，缺乏数学和技术细节。
The paper. The same theory, but formal. Very similar to the framework developed by nobel prizewinning economist Daron Acemoglu alongside Pascual Restrepo.
论文版本则是形式化的相同理论，其框架与诺贝尔奖得主达龙·阿西莫格鲁和帕斯夸尔·雷斯特雷波开发的模型高度相似。
The paper uses the same task based model of Acemoglu and Restrepo, and essentially we add the logic of classical economicsand input-output recursion to it to “pin” the wage.
论文沿用了阿西莫格鲁和雷斯特雷波的任务基础模型，并加入古典经济学逻辑和投入-产出递归来”锚定”工资水平。
That is significant because, well, current economics doesn’t know how wages are set in aggregate.
这很重要，因为现行经济学尚未解决工资总量的决定机制问题。
That might sound surprising but essentially all wage models are estimates or they have some free parameters you can change or have to supply some other way.
听起来可能令人惊讶，但现有工资模型要么是估算值，要么包含可调整的自由参数，或需要外部输入。
All we did was assume “hey, maybe the classical economists were right, they just didn’t know about how technology can effect the wage”.
我们只是假设”古典经济学家可能是对的，他们只是不懂技术如何影响工资”。
So, all we need to do is take the scarcity models of classical economists, add on the wage level from the marginal task (Acemoglu and Restrepo) and you just end up with a model that fits history like a glove.
因此只需继承古典经济学家的稀缺性模型，加上边际任务工资理论（阿西莫格鲁和雷斯特雷波），就能得到与历史完美吻合的模型。
Here’s some of the maths:
以下是部分数学表达：
From Acemoglu and Autor/Restrepo, we get how technology influences the wage:
根据阿西莫格鲁和奥托/雷斯特雷波的理论，技术对工资的影响表现为：
[技术影响工资的数学公式]
ρ is the rental price of a machine, γ is the “edge at the marginal human task” which is essentially how much better a human is than a machine at something which could be automated.
ρ表示机器租赁价格，γ是”人类边际任务优势”，即人类在可自动化任务上优于机器的程度。
μ you should think of as “technology”, and it can go up or down depending on what kind of technology is invented.
μ可理解为”技术水平”，其升降取决于技术发明类型。
During the industrial revolution, we got lots of physical automation (steam engines etc) but not so much cognitive (although, analog-mechanical battleship firing computers are like, super cool counter examples, check it out 1953 instructional video).
工业革命时期出现了大量体力自动化（蒸汽机等），但认知自动化较少（不过1953年战舰机械模拟计算机是个超酷的反例）。
Anyways steam engines etc caused μ to rise. Conversely, computers caused μ to fall in an interesting specific way, which probably gave us the great stagnation, and, well, AI might make μ fall more generally.
蒸汽机等技术使μ上升，而计算机以特定方式降低μ，这可能导致了经济大停滞，AI则可能更广泛地降低μ。
That’s μ, what about γ? In the paper we define γ as:
说完μ，γ如何定义？论文中：
[γ的数学定义]
κ is how much machines cost you need to make a machine λ is how much labor cost you need to make a machine, and τ is how much land, oil, ore, other fixed stuff you need to make a machine.
κ是制造机器所需的机器成本，λ是所需劳动力成本，τ是所需土地、石油、矿石等固定要素。
So, γ contains itself in its definition, but we can recurse this function, plugging it into itself (and plug our wage definition in too), and then we get:
γ的定义包含自引用，但通过函数递归（并代入工资定义）可得：
[递归函数表达式]
And plugging that into our wage function we get:
代入工资函数后得到：
[最终工资函数]
And the intuitive idea for this is that the wage is set by technology and access to physically scarce things (land as an example, but tbh you can add other things you think are scarce), and then it’s scaled by how efficiently machines can make machines (κ) and how much labor you need to make machines (λ).
直观理解是：工资由技术水平和稀缺资源（如土地）决定，并受机器制造效率(κ)和人力投入(λ)调节。
That’s it. Also none of the maths stuff I’ve done is particularly novel, the recursion is like from 1936 (Leontief, Sraffa), land rent is from Ricardo (1817!), none of this is new I just smushed it all together.
这些数学工具都不新颖——递归来自1936年（里昂惕夫、斯拉法），地租理论源自李嘉图（1817年），我只是做了整合。
So what does it mean? Well, lot’s of things, but two main ones: housing prices and rents rising in relation to the other things we buy should not be surprising, the model predicts that if μ falls which kinda happened around the 1970s, and really got going after the internet took off.
这意味着：首先，房价租金相对其他商品上涨是合理的，模型预测μ下降会导致此现象（1970年代开始显现，互联网兴起后加剧）。
The other is that AI might, uh, really really lower μ. But! The model also has a solution that just falls right out of the maths, and it’s also nothing new, it’s George (1879).
其次，AI可能大幅降低μ。但模型也给出数学推导的解决方案——乔治（1879年）的旧主张：对稀缺资源征税并用于消费补贴。
You need to tax the things you think are scarce, and you need to use that to fund consumption. That’s it.
具体而言就是征收土地税，我建议再加主权财富基金（持有股票可捕获网络效应等跨国稀缺性）。挪威已成功实践——虽不如直接征税理想，但跨国土地税协调尚需时日。
George proposed taxing land, and that’s like, probably most of what you need, I’d propose also adding a sovereign wealth fund because owning some stocks allows you to capture other kinds of scarcity, like network effects and stuff, and even more importantly it works across borders: you can’t tax another countries land but usually you can own their companies. Norway already does this super successfully.
图表显示地税基增长情况（阴影区因测算方式不同）：
[图表说明：不同分类输入可能导致对稀缺要素的判断差异]
It’s not as “perfect” as taxing scarce stuff directly so, probably countries should get together and swap land rents based on trade disparities but eh, that’s like, a thing we think about ages from now. Here, you can see the rent base rising, this is basically “how much can/should a land/scarce tax capture”:
(the shaded area is because this is an estimate, the inputs to the graph are different classifications and you can argue one or the other thing doesn’t represent scarce factors, so you have different possible measures.