Reddit Economics Network

Very quick R1:

Kate Nelischer, professor of urban planning at buffalo university, has a video with WIRED where she gets asked questions about America's housing crisis. Around the 1:30 mark she posts a graph showing that inflation adjusted incomes are up about 40% since 1985, inflation adjusted rent prices are up almost 150%. What's the problem? Her rent data aren't actually inflation adjusted -- they're nominal. This particular graph get passed around a lot on twitter. The original source is a company called "Real Estate Witch" who grab HUD's Fair Market Rent Data and income data from the Census. They claim to adjust the income series and the rent series for inflation using the Consumer Price Index.

To show that they didn't do this, I recreated their graph using inflation adjusted income and nominal rent prices.

People don't fact check every post and in a functional society we tend to trust that when people say they inflation-adjusted data that they did, in fact, do that, so I'm somewhat sympathetic to getting suckered by someone else's mistake. But if you're a professor who does anything with housing, their graph should be setting off immediate alarm bells. If you look at the share of renters spending 30% or more of their income on rent, it's hovered around 50% for the past 20 years. That's incompatible with their graph showing rent prices up 100% and income was up about 20%.

What's more frustrating though, is that if you look at the chart in the video, that data are binned into five year increments, which means whomever made this chart had to go out of their way to recreate a wrong chart.

As a bonus, if you want more validation, you can plot the Shelter component of CPI vs inflation adjusted income. You get the same basic chart. If you look closely, you actually see shelter inflation as measured by the CPI runs hotter than HUD's FMR data. Why is this? Because the original chart does a really dumb thing: it takes a naive median of rents without weighting by population. Once you weight by population you get something very close to the CPI.

link to charts:

their chart:

https://imgur.com/a/yf8v6qY

recreated version:

https://imgur.com/a/MJSeHZC

FRED Version:

https://imgur.com/a/8XvF51i

Recreation of FRED Version

https://imgur.com/a/mnFCxWE

link to original report: https://www.realestatewitch.com/rent-to-income-ratio-2022/

link to share cost burdened: https://www.bdcnetwork.com/new-data-finds-majority-renters-are-cost-burdened

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

Following up on this post in response to this nonsense with a proper RI:

"If you want a living wage, get a better job" is a fascinating way to spin, "I acknowledge that your current job needs to be be done, but I think that whoever does that job deserves to live in poverty"

First of all, what? Nothing in "If you want a living wage, get a better job" implies any acknowledgement that your current job needs to be done. But beyond that, it's completely wrong.

In textbook microeconomic analysis, workers are paid the marginal product of their labor†, which is the market value of the increased output from adding that worker to the firm's production process. In general, the marginal product of a worker doing a particular kind of work tends to fall as the number of people doing that kind of work increases.

Consider heart surgeons. If there's only one in the world, his labor is tremendously valuable. The surgeon will only have enough time operate on a tiny fraction of patients needing heart surgery, and is free to sell his services to the highest bidders. However, the number of patients needing heart surgery is finite. If anyone could learn to perform heart surgery skillfully with only a day of training, there would be far more than enough heart surgeons to operate on anyone who needed surgery, and wages for heart surgeons would fall to a very low level. This is a good thing, because it signals to aspiring heart surgeons that the world already has more than enough heart surgeons, and encourages them to go into some other line of work for which the need for additional workers is greater.

The wage a job pays does not depend on how much we need some people doing that job, but how much we need more people doing that job. Contrary to Vivian's claim quoted above, a low wage is usually an indication that your current job does not really need to be done that badly, at least not by as many people as are currently doing it, and that everyone would be better off if you got a higher-paying job.

†Yes, there are complications like monopsony power and positive externalities from certain kinds of work, but monopsony power is generally weak for low-wage jobs due to low search costs and low employer market concentration, and only a small minority of low-paying jobs have major positive externalities, so these do not seriously complicate the above in most cases.

(sorry about the title, trying to follow the sidebar rules)

https://np.reddit.com/r/jobs/comments/1by2qrt/the_answer_to_get_a_better_job/

The logic here, and the general argument I regularly see, feels incomplete, economically.

Is there a valid argument to be had that all jobs should support the people providing the labor? Is that a negative externality that firms take advantage of and as a result overproduce goods and services, because they can lower their marginal costs by paying their workers less, foisting the duty of caring for their laborers onto the state/society?

Or is trying to tie the welfare of the worker to the cost of a good or service an invalid way of measuring the costs of production? The worker supplies the labor; how they manage *their* ability to provide their labor is their responsibility, not the firm's. It's up to the laborer to keep themselves in a position to provide further labor, at least from the firm's perspective.

From my limited understanding of economics, the above link isn't making a cogent argument, but I think there is a different, better argument to be made here. So It's "bad economics" insofar as an incomplete argument, though perhaps heading in the right direction.

I've just launched a new YouTube channel which aims to explain economic concepts to non-expert audiences.

The first video is called "Why Sam Altman Wants 7 Trillion Dollars" https://youtu.be/UijlPh6cxPc

It uses recent headline grabbing statements by Open AI's CEO to give an introduction to how Schumpeter thought about credit and money's role in empowering entrepreneurs to re-shape an economy's productive capacity. (The Schumpeter bit is after the 5 min mark)

Making something that is entertaining, accessible and intellectually rigorous is my goal, so I'd love some feedback from this community of the first video, and how you think future ones could be better. Thanks in advance!

Video in Question:https://www.youtube.com/watch?v=sAGEOKAG0zw

In an old video about why animals never evolved with wheels, Michael Stevenson(creator of Vsauce) claims (at around the 4:45 mark) that one major reason why animals never evolved wheels was because they wouldn't build roads for them to move around on (1). Michael then claims that this was because animals couldn't prevent other animals from freeriding off of their road building efforts so animals had no incentive to construct them before he then claims that humans are able to do so via taxation. Thus, in the video, Michael effectively implies that roads are public goods that can only be provided at large scales via taxation which is why humans are the only species that built roads and use wheeled vehicles on a large scale. This is simply not true as the mass provision of public goods (like roads) without taxation is not only possible but has occurred before.

In the early 19th century, the US had a massive dearth of roads. Unlike today, local and state governments couldn't or weren't willing to finance the construction of roads. To remedy this issue, many states began issuing large amounts of charters for turnpike corporations to build turnpikes which were essentially toll roads. However, most investors knew early on that most turnpikes wouldn't be profitable.

"Although the states of Pennsylvania, Virginia and Ohio subsidized privately-operated turnpike companies, most turnpikes were financed solely by private stock subscription and structured to pay dividends. This was a significant achievement, considering the large construction costs (averaging around $1,500 to $2,000 per mile) and the typical length (15 to 40 miles). But the achievement was most striking because, as New England historian Edward Kirkland (1948, 45) put it, “the turnpikes did not make money. As a whole this was true; as a rule it was clear from the beginning.” Organizers and “investors” generally regarded the initial proceeds from sale of stock as a fund from which to build the facility, which would then earn enough in toll receipts to cover operating expenses. One might hope for dividend payments as well, but “it seems to have been generally known long before the rush of construction subsided that turnpike stock was worthless” (Wood 1919, 63)." (2)

However, despite the lack of profitability, large amounts of investors chose to invest in turnpike corporations despite them already knowing that most of them wouldn't profit from investing in turnpikes. 24,000 investors invested in turnpike corporations in just Pennsylvania alone. Such investment was not insignificant as by 1830, the cumulative amount of investment in turnpikes in states where significant turnpike investment represented 6.15 percent of the total 1830 gdp of those states. To put this figure into context, the cumulative amount of money spent on the construction on the US interstate system represented only 4.3% of 1996 US gdp (2). Thus, the amount spent on the construction of turnpikes was massive.

Given that most turnpikes were unprofitable, why did so many people choose to invest in the turnpikes? Most of the turnpikes had large positive externalities such as increasing commerce and increasing local land values. Thus, most turnpike investors indirectly benefited from investing in turnpikes.

"Turnpikes promised little in the way of direct dividends and profits, but they offered potentially large indirect benefits. Because turnpikes facilitated movement and trade, nearby merchants, farmers, land owners, and ordinary residents would benefit from a turnpike. Gazetteer Thomas F. Gordon aptly summarized the relationship between these “indirect benefits” and investment in turnpikes: “None have yielded profitable returns to the stockholders, but everyone feels that he has been repaid for his expenditures in the improved value of his lands, and the economy of business” (quoted in Majewski 2000, 49) " (2)

"The conclusion is forced upon us that the larger part of the turnpikes of the turnpikes of New England were built in the hope of benefiting the towns and local businesses conducted in them, counting more upon the collateral results than upon the direct returns in the matter of tolls" (3, pg 63)

Since the benefits of these early roads affected everyone who lived near or by the roads, its clear that there was nothing stopping free riders from taking advantage of the roads. However, despite the incentive to freeride, enough individuals contributed to the funding of the roads that massive amounts of turnpikes were nonetheless built. Its thus clear many communities across the early US were able to overcome the freerider problem without any use of taxation. While taxation is certainly a way to overcome the freerider problem, it certainly isn't the only way to ensure the mass provision of public goods like roads as evidenced by the turnpikes of early 19th century America.

Sources:

(1)-why don't Animals have wheels?: https://www.youtube.com/watch?v=sAGEOKAG0zw

(2)-Turnpikes and Toll Roads in Nineteenth-Century America: https://eh.net/encyclopedia/turnpikes-and-toll-roads-in-nineteenth-century-america/

(3)-The Turnpikes of New England and Evolution of the Same through England, Virginia, and Maryland: https://archive.org/details/turnpikesofnewen00woodrich/page/62/mode/2up

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

We haven't had enough RIs recently. I was talking about Blair Fix elsewhere, so I thought I'd this one.

Here is the blog post in question. It was written back in 2020 and the links to the pictures seem to have broken over the past four years.

Generally, Blair Fix argues that everyone else is wrong about economics. Usually, the writing is unnecessarily long-winded. Here we have Fix arguing at length the everybody else is wrong on productivity. In this RI I'll only deal with his ideas on the concept of productivity, I'll set aside the productivity/pay gap which he also discusses.

In this post, I debunk the ‘productivity-pay gap’ by showing that it has nothing to do with productivity. The reason is simple. Although economists claim to measure ‘productivity’, their measure is actually income relabelled.

We'll start by looking at Fix's initial justification for this idea.

Economists define ‘labor productivity’ as the economic output per unit of labor input:

Labor Productivity = Output / Labor Input

To use this equation, we’ll start with a simple example. Suppose we want to measure the productivity of two corn farmers, Alice and Bob. After working for an hour, Alice harvests 1 ton of corn. During the same time, Bob harvests 5 tons of corn. Using the equation above, we find that Bob is 5 times more productive than Alice: [1]

Alice’s productivity: 1 ton of corn per hour

Bob’s productivity: 5 tons of corn per hour

When there’s only one commodity, measuring productivity is simple. But what if we have multiple commodities? In this case, we can’t just count commodities, because they have different ‘natural units’ (apples and oranges, as they say). Instead, we have to ‘aggregate’ our commodities using a common unit of measure.

I will come back to this example later on. Certainly, it is correct.

To aggregate economic output, economists use prices as the common unit. They define ‘output’ as the sum of the quantity of each commodity multiplied by its price:

Output = ∑ Unit Quantity × Unit Price

So if Alice sold 1 ton of corn at $100 per ton, her ‘output’ would be:

Alice’s output: 1 ton of corn × $100 per ton = $100

Likewise, if Bob sold 5 tons of potatoes at $50 per ton, his ‘output’ would be:

Bob’s output: 5 tons of potatoes × $50 per ton = $250

Using prices to aggregate output seems innocent enough. But when we look deeper, we find two big problems:

‘Productivity’ becomes equivalent to average hourly income. ‘Productivity’ becomes ambiguous because its units (prices) are unstable.

I expect that a lot of people here are not very surprised by this. For example, look at this page on the OECD website. It begins with "GDP per hour worked is a measure of labour productivity". This is hardly a secret.

‘Productivity’ is hourly income relabelled

By choosing prices to aggregate output, economists make ‘productivity’ equivalent to average hourly income. Here’s how it happens.

Economists measure ‘output’ as the sum of the quantity of each commodity multiplied by its price. But this is precisely the formula for gross income (i.e. sales). To measure gross income, we multiply the quantity of each commodity sold by its price:

Gross Income = ∑ Unit Quantity × Unit Price

To find ‘productivity’, we then divide ‘output’ (gross income) by the number of labor hours worked:

Productivity = Gross Income / Labor Hours When we do so, we find that ‘productivity’ is equivalent to average hourly income:

Productivity = Average Hourly Income

So far, so good. Fix has told us something that I think everyone knows. Not just everyone here, but everyone who is vaguely familiar with Economics. He hasn't mentioned inflation yet, we'll come to that later.

So economists’ measure of ‘productivity’ is really just income relabelled. The result is that any relation between ‘productivity’ and wages is tautological — it follows from the definition of productivity.

Here is where the real problems start! Fix has just told us that productivity is income relabelled, but what he showed above is that "labour productivity" is a name for income-per-hour. Income is not the same as income-per-hour.

It would be unreasonable to use income as a measure of productivity. Because doing so would not tell us how much effort is required to obtain the income. Income per hour is different. The "per hour" part gives us at least some information about how much effort was needed to obtain the income. Of course, it's not full information, it tells us nothing about other inputs that may be used. That's why there are other more complex productivity statistics.

It's worth going back to Alice and Bob here:

Alice’s productivity: 1 ton of corn per hour

Bob’s productivity: 5 tons of corn per hour

Fix didn't seem to have a problem with this. But is it really all that different to where we are now? Bob makes 5 tons of corn per hour. He then sells that corn. So, his income is also 5 tons of corn per hour. More specifically it is the revenue produced by selling 5 tons of corn per hour.

We should also note that together Alice and Bob produce 6 tons of corn. If that is all that is happening then, in the little economic unit consisting of Alice and Bob the 6 tons of corn are both all production and all income.

There's another problem:

The result is that any relation between ‘productivity’ and wages is tautological — it follows from the definition of productivity.

Income is not the same as "wages". Specifically, wages are the money income of workers. There are other incomes such as rents, interest and profits. Fix will come back to this point and so will I.

Now, I will skip over lots of things that Fix has to say, and come back to some of them later.

To understand the problems with the EPI’s method, we need to backtrack a bit. I’ve already noted that ‘productivity’ is equivalent to average hourly income. But this wasn’t quite correct. ‘Productivity’ is equivalent to real average hourly income:

Productivity = ‘Real’ Average Hourly Income

Unlike ‘nominal’ income, ‘real’ income adjusts for inflation. To get ‘real’ income, we divide ‘nominal’ income by a price index — a measure of average price change:

Real Income = Nominal Income / Price Index

At the start Fix told us that productivity is really income. Then he told us the productivity is really income-per-hour and tried to distract us from the per-hour bit. Now, he tells us that productivity is actually inflation-adjusted income per-hour.

This actually solves some of Fix's other problems. If he'd thought about things in different order perhaps this would have been clear:

In addition to making ‘productivity’ equivalent to average hourly income, using prices to measure ‘output’ also makes ‘productivity’ ambiguous. This seems odd at first. How can ‘productivity’ be ambiguous when income is always well-defined?

The answer has to do with prices.

We expect prices to play an important role in shaping income. Suppose I’m an apple farmer who sells the same number of apples each year. If the price of apples doubles, my income doubles. That’s how prices work.

Now, let's go back to that equation which includes the price index:

Real Income = Nominal Income / Price Index

Ah yes, in the nominator of the equation the income of the apple farmer has risen. However, we need to remember that the price of apples is also included in the denominator of the equation too. It's in the price-index used to adjust for inflation. Fix is wrong here because he has introduced the price-index aspect too late in his thinking.

Let's suppose that the price of apples rises and no other prices change. In that case nominal income will rise because of the extra income to apple farmers. Also, the price index will rise because of the rise in the price of apples.

Ideally, these things should cancel out. That's because the percentage increase in nominal income is the same as the percentage increase in the price index. If the index uses the Laspeyres method then it could cancel out. If it uses another method then it won't cancel out exactly. We also have to remember that in practice the measure of income may be wider than the basket of goods included in the price index. So, in practice there will be inaccuracies.

Notice that here, I'm not saying that price indexes are perfect for measuring price inflation, nor that any specific index is perfect. Reasonable people can have arguments about what to include in the basket, or what statistical aggregation method to use. My point is simply that productivity as a concept accounts for inflation in whatever way the user of it prefers. For example, if you think that price index X is better than price index Y then you can use that to calculate productivity. If you think all price indexes are bad then you can't calculate productivity, but that's also a reasonable viewpoint.

Suppose that Alice grows 1 ton of corn and 5 tons of potatoes. Bob grows 5 tons of corn and 1 ton of potatoes. Whose output is greater? The answer is ambiguous — it depends on prices.

Fix continues to give us an example where the prices of two goods change, one goes up and the other goes down. Does this contain the problem that Fix describes?

Yes and no. Certainly, you can't compare apples to oranges. Nor can you compare corn to potatoes directly.

However, we should remember what productivity measurements are for. To start with consider a small group, or an individual like Bob. Let's say that Bob is working in a modern economy which is dominated by trade. In that case what matters to Bob is how much money his work earns him. So, it is very sensible for his metric of productivity to be dollars per hour (adjusted for inflation by whatever process Bob finds works best for him). Alternatively, let's suppose that Bob is actually Robinson Crusoe on his island. In that case he really does have a problem of comparing the utility he will get out of various different projects. But that problem doesn't apply to the normal case of the modern market economy.

So, small groups may measure productivity, like individuals and companies. Also, larger groups measure productivity, like nations. In this case the situation is rather different. We should remember something that Fix mentions himself more than once. At the high level, production is also income.

It's worth contrasting two of Fix's sentences here. Fix describes critically the things that you "have to believe" to use productivity statistics, he writes:

You have to believe that prices ‘reveal’ utility, and that monetary income is the same as economic ‘output’.

And elsewhere:

The national accounts are based on the principles of double-entry bookkeeping. This means that for every sale there is a corresponding income.

Why should I have a problem believing that income is the same as output when it's the simple consequence of the world we live in? It is impossible to buy something without at the same time giving someone else an corresponding income. It may be that statistical agencies mismeasure these things. But, that doesn't stop them from being actually equal.

It is not that prices "reveal" utility, but that shifts in demand are driven by shifts is preferences. Suppose that people come to prefer corn to potatoes. In that case the price of corn increases and the price of potatoes decreases. Similarly, the volume of corn sold increases and the volume of potatoes sold decreases. Now, of course, the productivity of the corn industry is more important than it was, and the productivity of the potato industry is less important. There is no point in guessing what the productivity of the potato industry could be if people still preferred the same amount of potatoes as they did before, nor is doing that really possible.

Now, I want to be clear about what I'm saying here. My point is simply that labour productivity makes logical sense as a statistic. Also, it's well known what it measures. It is not always a very useful statistic. Other forms of productivity measurement have advantages. But there isn't the mystery or confusion here that Fix claims there is.

I could criticise much more, but this RI is already very long.

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

Original Post

RI: Each component is considered in equal weight, despite the components having substantially different weights (eg: Consumer spending is approximately 70% of total GDP, and the others I can't call recall from Econ 101 because that was awhile ago). Equal weights yields a negative computation, but the methodology is flawed.

That said, the poster does have a point that relying on public spending to bolster top-line GDP could be unmaintainable long term: doing so requires running deficits, increasing taxes, the former subject to interest rate risks, and the latter risking consumption. Retorts to the incorrect calculation, while valid, seemed to ignore the substance of these material risks.

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

https://np.reddit.com/r/austrian_economics/comments/1avwm0w/thought_you_might_like_the_inflation_sub_didnt_lol/

This post has 600+ upvotes and there are many people in the comments section defending deflation so I'm going to refute all the main arguments.

Or maybe deflation actually incentivises people to save instead of always consuming?

This comment correctly accesses that deflation incentivizes people to save instead of consuming but it portrays it as something beneficial for the economy. While economists generally agree that it is harmful for the majority of people to have extremely high time-preference, the majority of people having an extremely low time-preference would lead to many industries (especially industries that fulfill a human want rather than a human need) closing due to a lack of demand. When many industries close, there is mass unemployment. With all those people unemployed, there would be more decreases in aggregate demand. This is called the deflationary spiral.

My car is always worth less tomorrow?? As long as your investment outpaces the deflation you make more money. I don’t see why people would stop investing if inflation was at 2% when any good investment targets 10% annual growth.

Cars are not known for having a high ROI. This is because they depreciate in value overtime. The reason most people buy a car is because of their utility, not because they expect to sell it off at a later date. This comment then goes on to admit that people will be incentivized to invest as long as it's more profitable to invest than hold on to the money. This actually proves the point that economists make. As there is more deflation, there will be less industries that are able to outpace it, leading to a sharp decrease in investment for those industries.

Yes then you buy when everything is cheap. I'm not too keen on chopping off my arm for a Big Mac because of the fear my home would explode if it were a little bit less money.

This argument is a misrepresentation of reality. Inflation usually doesn't lead to people chopping their arms off because their house will explode. The comment ironically proves the point that economists make about artificially decreasing time preferences because the commenter admits that they will delay their purchases until products get cheaper.

Reminder that according to economists, inflation is a good thing because it prevents poor people from being able to save money and it encourages rich people to invest and get richer.

This claim lacks any evidence or examples. Economists usually don't make value-judgements and their goal is not to keep people poor.

“Heh heh you don’t like inflation, well DEFLATION is worse. Far far worse. It’s basically the end of the world.”

These comments claim that the argument against deflation is "because everyone says it". This is not true because there are arguments like the deflationary spiral, the empirical data regarding time periods with high deflation, the incentives deflation brings, etc. that showcase the negative effects of deflation for an economy.

First, allow me entertain you with some context: https://np.reddit.com/r/japannews/comments/1atis9u/japan_drops_to_26th_globally_in_annual_pay_for_it/kqy29kl/?context=10000

It will never happen unless japan finds huge natural resources of gas/petroleum. Or anything that directly contributes to the national wealth.

Once the currency depreciates, there's no turning back. 150 yen becomes the new 110 yen.

https://img.capital.com/imgs/blocks/750xx/USD-JPY-historical-chart-2019.png

As someone half Turkish, I'm familiar with this topic.

All Turkish people love to go to the econometrics hell and back, I see. I love my Turkish friends, as well as my colleagues in my econ department, but I don't think my friends outside of the department studied econ.

The government benefits from deliberate currency weakening, allowing market-driven price increases without criticism

Depends on the situation, and right now one of the headlines is being unable to afford certain imports e.g. 'why import if there are no buyers?'

boosting tourism and exports

True, except Japanese government restricted travels in 2022

reducing foreign debt

Such debt contracts typically include inflationary + currency exchange rate variations

For instance, the Turkish government intentionally weakens the lira to cut high-tech labor costs, lower foreign debt (31.1% compared to the EU's 117.4% of nominal GDP in 2022), and enhance tourism (tourist numbers grew from 9.6 million in 2016 to 50 million in 2023).

Well, this is the first time I hear someone supportive of Turkish econ policies. I don't think they're doing themselves much of a favour though.

The reason why the USD/JPY or EUR/JPY exchange rate is the way it is now is partially due to the central banks' interest rates. The US Fed and the ECB recently peaked interest rates, while Bank of Japan has had -0,01% for some years now.

See https://youtu.be/tbA8PmEAu-0

This is an excerpt from a video that describes a person manipulating the order book.

Does anyone know the details he actually says that he places an order 50 cents higher than the $2 price and then buys his own order with ethereum and makes it look like the price just went to $2.50 from $2

Does anyone have details on this?

Where are the tools to monitor this?

It sounds like it might be impossible if people are able to create fake identities.

What protects exchanges from market manipulation like this?

If things like this happen then doesn't this make the entire exchange system questionable?

Reference https://www.singlelunch.com/2022/01/09/an-anatomy-of-bitcoin-price-manipulation/

https://np.reddit.com/r/socialscience/comments/1ap6g7c/cmv_economics_worst_of_the_social_sciences_is_an/

How is this an attempt to CMV?

Perhaps we could dig into why econ focuses almost exclusively on production through a self-interest lens and little else. They STILL discuss the debunked rational choice theory in seminars today along with other religious-like concepts such as the "invisible hand", "perfectly competitive markets", and cheesy one liners like: "a rising tide lifts all boats".

The reality is that economists play with models and do math equations all day long out of insecurity; they want to been seen as hard science (they're NOT). They have no strong normative moral principals; they do not accurately reflect the world, and they are not a hard science.

Econ is nothing but frauds, falsehoods, and fallacies.

CMV

OP's comment below their post.

It goes into more detail than the title and is the longest out of all of their comments, so each line/point will be discussed.

Note that I can discuss some of their other comments if anyone requests it.

Perhaps we could dig into why econ focuses almost exclusively on production through a self-interest lens and little else.

It is correct that there is a focus on individual motivations and behavior, but I am not sure where OP is getting the impression that economists care about practically nothing else.

They STILL discuss the debunked rational choice theory in seminars

Rational choice theory simply argues that economic agents have preferences that are complete and transitive. In most cases, such an assumption is true, and when it is not, behavioral economics fills the gap very well.

It does not argue that individuals are smart and rational, which is the colloquial definition.

"invisible hand"

It is simply a metaphor to describe how in an ideal setting, free markets can produce societal benefits despite the selfish motivations of those involved. Economists do not see it as a literal process, nor do they argue that markets always function perfectly in every case.

"perfectly competitive markets"

No serious economist would argue that it is anything other than an approximation of real-life market structures at best.

Much of the best economic work for the last century has been looking at market failures and imperfections, so the idea that the field of economics simply worships free markets is simply not supported by the evidence.

cheesy one liners like: "a rising tide lifts all boats"

Practically every other economist and their mother have discussed the negative effects of inequality on economic well-being. No legitimate economist would argue with a straight face that a positive GDP growth rate means that everything is perfectly fine.

The reality is that economists play with models and do math equations all day long out of insecurity

Mathematical models are meant to serve as an adequate if imperfect representation of reality.

Also, your average economist has probably spent more time on running lm() on R or reg on Stata than they have on writing equations with LaTeX, although I could be mistaken.

they want to been seen as hard science (they're NOT)

Correct, economics is a social science and not a natural science because it studies human-built structures and constructs.

They have no strong normative moral principals

Politically, some economists are centrist. Some are more left-learning. Some are more right-leaning.

they do not accurately reflect the world

The free-market fundamentalism that OP describes indeed does not accurately reflect the world.

A previous post dunked on another NBC (National Bank of Canada) report here: https://np.reddit.com/r/badeconomics/comments/1985ji4/bad_antiimmigration_economics_from_rneoliberal/?share_id=ftS1mq3C6SMZFU7tTPj4X

So I'm here to critique them in their new report, which is arguably even worse.

Please be gentle, it's my first time writing something like this.

https://www.nbc.ca/content/dam/bnc/taux-analyses/analyse-eco/hot-charts/hot-charts-240212.pdf

Canada: The GTA (Greater Toronto Area) labour market unable to absorb population boom

We really wish we could talk about something other than population when we refer to Canada, but as an emeritus

professor of economics recently reminded us, Canadian demographer David Foot once said that "demography explains about two-thirds of everything". Which brings us to the latest employment report, which showed a historic monthly increase in the working-age population in January: a whopping 125,000 people (or 4.7% at an annualized rate). At the municipal level, nowhere was the pressure more acute than in the Greater Toronto Area (GTA), where the population aged 15+ jumped by a record 32,600 people over the month (an annualized rate of 6.8%). The GTA, which accounts for about 18% of Canada's population, is currently responsible for more than 25% of the country's population growth. With the current interest rate structure, it is simply impossible for the labour market to absorb such a large number of newcomers. As today's Hot Chart shows, the GTA's employment-to-population ratio fell to 61.4% in January, its lowest level since 2021, when the economy was still impacted by COVID. The GTA, which historically had an employment rate that was on average 0.8% above the national average, is now suddenly below the rest of the country. A deteriorating labour market amid a population boom will continue to stress the infrastructure and finances of Canada's largest metropolitan area for the foreseeable future. We strongly advocate the creation of a non-partisan council of experts to provide policymakers with a transparent estimate of the total annual population growth that the economy can absorb at any given time. This council could play a key role in maintaining Canada's international reputation as a welcoming place for foreign talent.

R1: They claim that there is a limit to how quickly the number of employed people can grow, specifically in Canada. (Lump of labour fallacy)

I'm going to focus firmly on Canada as a whole because that's really what this report is about. First off we'll tackle the flaws in their analysis. Second we'll show that the claim they are trying to make is false.

​

Flaws in Analysis

I mean, there isn't much of a methodology in this report, is there?

I think it goes without saying that overlaying the graphs (see the NBC report) of two time series does not establish causation. Not only that but their very own employment graph implies that the variable has a cyclical nature to it, with peaks and troughs on and on, even outside of recessions.

Despite the report seemingly being just about the GTA, they seem to mention Canada, Canada, Canada, a hell of a lot, implicitly extrapolating the trends within the GTA to the whole of Canada.

Does non-peer reviewed count as a methodological flaw? Oh and they have a quote from a guy.

​

Why their claim is false

So we know that even a very large (7%!) and sudden increase in labour supply results in the increase being absorbed, with no increase in unemployment (Card, D. 1990).

The employment rate for Canada, and the United States Canada's is 0.8ppts above the pre-pandemic high (although trending downwards for awhile now). The USA (not experiencing a rapid increase in population), is 0.03ppts above pre-pandemic and just recently started trending down as well, this is despite the tepid population growth in the States. A caveat: this is for 15-64 but the NBC report and Stats Canada use 15+ to calculate the employment rate.

Canada's unemployment rate is at historic lows The unemployment rate for Canada ticked down to 5.7% from 5.8% the previous month. Now Canada has a different methodology for determining unemployment then the United States but if you adjust this number to the US methodology you get 4.8%, which, even when it comes to the US, is a very low number. Everyone who wants to work is working.

​

In short, there is not a limit to how quickly the number of employed people can grow, the labour market is not deteriorating and even if it were it has nothing to do with immigrants.

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

This is an R1 of my post from 2 days ago about CAFE standards. Embarrassingly, much of the literature I had read while investigating the programme predated the Bush/Obama reforms and so in practice only reflected the original formulation. Most critically I missed how the "new"er (this is 12 years old now) CAFE rules do not merely use footprint area to regulate vehicle CAFE classification, but adjust the CAFE minimum based on the footprint area.

The rules here are actually quite complicated, and few sources actually even publish the formula (it's 401 pages deep into the Federal Register final rule, which is a brief 577 pages long). In 2012, for passenger cars and light-trucks respectively:

[;\frac{1}{\min(\max(5.308\times10^{-4}a+6.0507^{-3},35.95^{-1}),27.95^{-1})};]

[;\frac{1}{\min(\max(4.546\times10^{-4}a+1.49\times10^{-2},29.82),22.27^{-1})};]

Where a is the wheelbase times track width. Notably, these functions are just ever so slightly concave up, I can only guess this has something to do with the CAFE standards themselves using a harmonic mean. Since 2016, the light-truck formula has been even more complicated to account for other energy saving measures.

This isn't a bona fide malincentive! However, it becomes one for two reasons:

1. The lower fuel economy standards for light-trucks is completely redundant, since larger vehicles (regardless of class) are already (in theory) given appropriately lower goals based on their footprint.

2. The relationship between footprint and fuel economy targets within each category are EXTREMELY generous to large footprint designs.

Whitefoot and Skerlos (2011) estimated that, controlling for engine size and vehicle height, a 1% increase in footprint was associated with a 0.53% increase in weight (unfortunately, this doesn't include the interaction of the controls with footprint, which is obviously correlated). Under such a relationship, in 2022 a car design with a 56ft^2 footprint has a 12% lower expected lb-mi per gallon target, whereas a 74ft^2 truck design has an 18% lower expected target than a 41ft^2 design.

When both the footprint and truck/car classification difference are accounted for, this grows to a whole 33% difference! Go figure, I need to make sure I'm not 20 years out of date on a policy next time I attempt to defend it.

It's a very popular talking point among urbanists, "policy wonks", and environmentalists that the weaker CAFE standards for light trucks have led to the proliferation of the infamous, almost comically oversized vehicles in America.

First, let's establish the counterfactual. In absence of CAFE, it's a reasonable assumption that the partial equilibrium of the car market is efficient, and there's some given mixture of larger and smaller vehicles on the market. Next, let's introduce a CAFE regime where all vehicles count towards a single CAFE rule. I'm by no means a physicist, but by definition, an object of greater mass requires proportionally more energy to be moved (more on this later), and, shocker, that means they require more fuel. In order to meet a binding CAFE, car manufactures will need to either either reduce their offerings of heavier vehicles, raise their prices on them beyond equilibrium, or introduce fuel economy improvements into the design that wouldn't need to be introduced for smaller vehicles, all of which distort the market into having smaller vehicles.

This is distortionary, and introducing a two tiered regime such as that of 'passenger cars' and 'light-trucks' in the actual CAFE rules somewhat alleviates it. It would distort the market, however, is if passenger cars were held to a standard that effectively forces manufactures to change their passenger cars in ways that they needn't do with their light-trucks.

Using the 2022 EPA automotive trends report, I was able to estimate (by eyeballing) that the average CAFE passenger car is in the ballpark of 3827 lbs, whereas the average CAFE light-truck is in the ballpark of 4783 lbs. For a 2022 CAFE standard of 48.2 and 34.2 mpg, this comes out to 184461 and 163579 pound-miles per gallon respectively. The difference between these is about 12%.

#BUT!

Remember how I pointed out the definition of kinetic energy? Well that's a bit idealized, and in practice there are other considerations, like more weight means more momentum, larger vehicles have more drag, amongst other factors. When we take these into consideration, I'm not so sure that the 12% estimate is even a significant effect size, and if I used other benchmarks like horsepower or volume instead of weight, the results would've been similar.

As other redditors have pointed out, there are in fact issues with distortion on the margin between the two categories. But the solution isn't to "close the light truck loophole", it's to add additional categories or just outright modify CAFE into Corporate Average tonnage fuel economy.

One final point, the historical data just does not support claim that CAFE standards forced motorists into driving larger vehicles. In figure 3.2 we can observe that the popularity of pick-up trucks in the US well predates CAFE and is fairly persistent. Minivans/vans have actually almost disappeared from the new car market. But most importantly, SUVs (car) have actually become more popular despite being on the wrong side of the margin. In figure 3.5, we can observe that all vehicles have become heavier since bottoming out around 1985. This is further shown in figure 3.6 (heads up, it's a little bit incoherent about whether weight classes are ceilings, floors, or centers), 3.8, 3.9, 3.12, and 3.13: Vehicles have gotten larger, heavier, and more powerful, not just at the margin, but throughout the distribution, and if anything, the strongest effects are at the tails, not the margin of CAFE standards.

Using figure 3.3 on page 19 and figure 3.5 on page 23, I came up with [;3750\times\frac{0.26}{0.26+0.115}+4000\times\frac{0.115}{0.26+0.115}=3827;]

[;5250\times\frac{1/6}{1/6+1/25+251/600}+4750\times\frac{1/25}{1/6+1/25+251/600}+4600\times\frac{251/600}{1/6+1/25+251/600}=4783;]

The Ludwig Institute is, as far as I can tell a not-particularly prominent think tank mostly centered around the idea that commonly reported government statistics about the state of the economy are, in some way, flawed. In particular, they argue that all the government statistics are under-reporting how bad the US economy truly is.

I haven't seen media outlets pick them up much, but we do get questions about them on askecon from time to time, so I figured it would be nice to be able to link to a post explaining why I think their work is mostly very bad.

I'll be focusing on one particular component -- housing -- of their True Living Cost index, which purports to be a Consumer Price Index (CPI) that's more representative for a typical low-income household. For what it's worth, this isn't actually a bad idea; it'd be nice to have an inflation index that was calibrated for a lower income consumer's consumption bundle since the consumption bundle of a lower-income household might be systematically different than for a higher-income one.

Thankfully, the BLS has done this already, and they find that lower-income households have experienced somewhat higher rates of inflation than higher-income ones; from 2003 to the end of 2021 lower income households experienced a cumulative 3 percentage points more inflation than the representative household and 6 percentage points more than a high-income household.

​

3 percentage points is very different from what the Ludwig Institute reports in their True Living Cost Index, however:

the cost of household minimal needs rose nearly 1.4 times faster than the CPI from 2001-2020, 63.5% compared to the CPI’s 46.2%

​

One of the biggest reasons for this discrepancy, and what the focus of this R1 will be on, is the treatment of housing. The Ludwig Institute writes:

The CPI Housing Index rose 54%; the TLC Index for housing rose 149%

​

This is, obviously, a massive difference, so let's look at the Ludwig Institute's Methodology Report to see what could be driving it.

First, what do they think the BLS is doing when they calculate the shelter component of the CPI?

There are further anomalies that result from the construction of the CPI. One is the failure for the CPI to represent the cost of shelter. Because the CPI measures housing costs as imputed rents (what someone thinks that their current dwelling would rent for) the CPI often does not react to market changes in current rents or housing prices. People are less likely to change their estimation of their house from year to year even if someone looking for rent that year will face different prices.

​

This is completely wrong. The BLS does not do this. The BLS gets their weights for owners' equivalent rents by asking owners what they think their house would rent for, but the values that make up inflation are coming from looking at rental prices for units that are comparable to what the owner lives in.

If an owner lives in a 2 bedroom single family home in Spokane, Washington, their rate of shelter inflation will be calculated by looking at changes in rent prices of similar 2 bedroom single family homes in Spokane, Washington and not by asking the owner of the house every year what they think they could rent the property for.

This isn't a perfect approach, in particular it will have problems when a particular neighborhood has very few rental properties, which can be common in some suburban areas, but it's a very bad look when an institute makes very strong claims and gets basic definitions wrong.

With that out of the way, what does the Ludwig Institute do?

At a really high-level, they take data from Housing and Urban Development's (HUD's) data on fair market rents, which represent the 40th percentile of rent prices* for various kinds of homes (studio, 1 bedroom, 2 bedroom, etc) at various geographies (county, MSA, etc) and use that to construct and index of rental inflation. There are some conceptual issues with this, but the main issue is that their numbers, as far as I can tell, are completely wrong. The numbers are so wrong they don't even agree with themselves.

They claim on their publications that from 2001-2020 the CPI Housing Index rose 54% and the TLC Index for housing rose 149%, but in the data that they say generates this statistic, housing inflation was only 114% over that time period. If you expand it to include 2022 you get up to 146%, which still isn't exact, but is at least closer. This discrepancy, as far as I can tell, comes from the fact that the graph they publish on their website says that the cost of housing increased by about 35% from 2001 to 2002. The fact that they thought there was 35% rental inflation in a year should have been a major red flag for their numbers.

I also have no idea where the claimed 54% is coming from. If you look at the CPI for shelter from 2001:2020 there was about a 64% increase in prices; if you look until 2022 it was about 88%.

So that's not good, but even worse when I try to replicate their numbers -- either the one's on the website or in the spreadsheet -- using HUD's own data I can't. In fact, when I try to replicate them I get something that tracks the CPI for housing very closely! Now, I'm not bothering to exactly replicate their methodology, but it's very noteworthy that me taking an hour to do some really quick and dirty calculations gets me very close to the CPI and they differ from the CPI by almost 60 percentage points (and by about 90 compared to what's on their website).

What's also very strange is that, outside their inability to understand how the CPI for housing works, their methodology for housing is mostly fine. They adjust for some quirks in FMR that I don't adjust for (see the footnote), but then there's all the weirdness of their spreadsheet not matching their publications, and both deviating so much from my numbers and the CPI. I almost wonder if they're making some Excel errors somewhere -- unfortunately they don't release anything detailing the exact steps they used to take the raw data and turn it into their spreadsheet.

To wrap, I actually think some of their ideas are fine, but the execution is so sloppy I'd ignore anything they put out.

• pic of inflation calcs: https://imgur.com/a/nNkQjW2
• there summary: https://assets-global.website-files.com/63ba0d84fe573c7513595d6e/63c1bb0c3b30d0736184ae8c_TLC%20White%20Paper%20Abridged.pdf
• their methodology report: https://assets-global.website-files.com/63ba0d84fe573c7513595d6e/65401d87a95f64045245334e_LISEP%20TLC%20Methodology.pdf
• bls inflation for lower income households: https://www.bls.gov/spotlight/2022/inflation-experiences-for-lower-and-higher-income-households/home.htm
• FAQ for owner's equivalent rent: https://www.brookings.edu/articles/how-does-the-consumer-price-index-account-for-the-cost-of-housing/
• link to my code: https://pastebin.com/BwJPXFYt

*40th percentile for the most part -- in a handful of areas, usually representing between 15-30 % of the US population, it will be the 45th or 50th percentile for certain years before 2016. It'd be better to adjust for this in my calculations, but enough counties bounce between categories that it should more or less wash out. For robustness, I redid the calculation using only counties that were always the 40th percentile and it changes nothing.

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

https://twitter.com/carolvorders/status/1748075594292531481?t=m-e1r8kHCnLELnwYII0iBQ&s=19

Carol misunderstands the nature of sovereign government debt. She believes it is a large burden (in and of itself) that accumulated net UK government spending has increased by nearly £2Tn since June 2010.

Carol calculates that in the 5000 days since David Cameron became Prime Minister of the UK, the "UK national debt" has increased by £380M a day on average.

This is bad economics because Carol doesn't seem to realise that government "debt" is non-government assets.

The largest holders of outstanding UK gilts (less those effectively redeemed by the Bank of England vis QE) are insurance companies, pension funds, and foreign net exporters (due to the UK's current account deficit, thereby allowing us to gain access to real goods and services in exchange for £ Sterling denominated assets).

Outlandishly posting that "in the 5000 days since Tories came to power, they've increased our nominal net financial assets by a staggering £380M a day" doesn't quite have the same ring to it.

There was a recent thread on r/neoliberal on immigration into Canada. The OP posted a comment to explain the post:

People asked where the evidence is that backs up the economists calling for reduction in Canada's immigration levels. This article goes a bit into it (non-paywalled: https://archive.is/9IF7G).

The report has been released as well

https://www.nbc.ca/content/dam/bnc/taux-analyses/analyse-eco/etude-speciale/special-report_240115.pdf

https://old.reddit.com/r/neoliberal/comments/197m5r5/canada_stuck_in_population_trap_needs_to_reduce/ki1aswl/

Another comment says, "We’re apparently evidence based here until it goes against our beliefs lmao"

Edit: to be fair to r/neoliberal I am cherry-picking comments; there were better ones.

The article is mostly based on the report OP linked. I'm not too familiar with economics around immigration, but I read the report and it is nowhere near solid evidence. The problem is the report doesn't really prove anything about immigration and welfare; it just shows a few worrying economic statistics, and insists cutting immigration is the only way to solve them. The conclusion is done with no sources or methodology beyond the author's intuition. The report also manipulates statistics to mislead readers.

To avoid any accusations of strawmanning, I'll quote the first part of the report:

Canada is caught in a population trap

By Stéfane Marion and Alexandra Ducharme

Population trap: A situation where no increase in living standards is possible, because the population is growing so fast that all available savings are needed to maintain the existing capital labour ratio

Note how the statement "no increase in living standards is possible" is absolute and presented without nuance. The report does not say "no increase in living standards is possible without [list of policies]", it says "no increase in living standards is possible, because the population is growing so fast" implying that reducing immigration is the only solution. Even policies like zoning reform, FDI liberalization, and antitrust enforcement won't substantially change things, according to the report.

Start with the first two graphs. They're not wrong, but arguably misleading. The graph titled, "Canada: Unprecedented surge" shows Canada growing fast in absolute, not percentage terms compared to the past. Then, when comparing Canada to OECD countries, they suddenly switch to percentage terms. "Canada: All provinces grow at least twice as fast as OECD"

Then, the report claims "to meet current demand and reduce shelter cost inflation, Canada would need to double its housing construction capacity to approximately 700,000 starts per year, an unattainable goal". (Bolding not in original quote) The report does not define "unattainable" (ie. whether short-run or long-run). Additionally, 2023 was an outlier in terms of population growth.

However, Canada has had strong population growth in the past. The report does not explain why past successes are unreplicable, nor does it cite any sources/further reading explaining that.

The report also includes a graph: "Canada: Standard of living at a standstill" that uses stagnant GDP per capita to prove standards of living are not rising. That doesn't prove anything about the effects of immigration on natives, as immigrants from less developed countries may take on less productive jobs, allowing natives to do more productive jobs.

The report concludes by talking about Canada's declining capital stock per person and low productivity. The report argues, "we do not have enough savings to stabilize our capital-labour ratio and achieve an increase in GDP per capita", which conveniently ignores the role of foreign investment.

Canada is growing fast, but a few other countries are also doing so. Even within developed countries, Switzerland, Qatar, Iceland, Singapore, Ireland, Kuwait, Australia, Israel, and Saudi Arabia grow faster. The report does not examine any of them.

https://www.cia.gov/the-world-factbook/field/population-growth-rate/country-comparison/

To conclude, this report is not really solid evidence. It's just a group of scary graphs with descriptions saying "these problems can all be solved by reducing immigration". It does not mention other countries in similar scenarios, and it denies policies other than immigration reduction that can substantially help. The only source for the analysis is the author's intuition, which has been known to be flawed since Thomas Malthus. If there is solid evidence against immigration, this isn't it.

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

https://np.reddit.com/r/Physics/comments/166hrgu/what_do_physicist_think_about_economics/

Four months ago, a user asked r/Physics about whether or not they looked down upon economics, given that in his experience at a Spanish university, it was the case that physicists dismissed economics as something easy and trivial.

While some responses were both respectful and insightful, there were unfortunately many others that did not exactly have such characteristics.

Economics is a BS discipline that is not actually a science

The previous commenters who said physicists and mathematicians laugh at economists a bit because their models are total bullshit and get to make all kinds of assumptions to arrive at a model that has no basis in reality is pretty spot on. The fact that is actually true about economics demonstrates why it’s less rigorous than physics or math (or biology, chemistry). The hard sciences cannot just take random things as assumptions, everything that is assumed must be observable or demonstrable in experiments and explained by a theory (and for physics, a set of equations). Math has to PROVE everything via deductive reasoning.

I challenge the user to name one basic tenet of economics that is not supported by empirical evidence.

It’s fairly obvious that the first principles of economics have not been flushed out because no one can create an economic model that actually predicts markets or economies of scale any better than flipping a coin.

Basic supply and demand along with industrial organization, game theory, etc., go a long way in explaining market structures/outcomes.

It’s not treated like a hard science because politics interferes with it and injects it’s bullshit into it constantly. We’re getting to the point now where politics is injecting its bullshit into everything, including the social sciences and biology via the pharmaceutical and medical care industries. If it starts happening more frequently and make it’s way into physics and math, it will strangle progress there just like it had in economics.

The assertion that politics has not influenced the hard sciences at all is quite difficult to defend when one considers history and current events.

As for the claim that progress has been strangled in economics, it encourage the user to read the latest research highlights released by the American Economic Association. They can be quite insightful!

One of the reasons economics gets crap is because some of it is earned. Classic Chicago School econ is less and less supported by evidence, with behavioural econ getting much more play. Yet despite example after example where behavioural economics explains how people actually act as economic agents, there are still.people who hold Chicago School perspectives as the truth. It'd be like being a physicist that didn't support relativity or QM because they were in the Newton School.

For one, I am assuming that they mean neoclassical economics, and perhaps specifically rational choice theory since they are comparing it to behavioral economics. Schools of economic thought such as the Chicago School of economics are not really a thing anymore.

Next, while it is true that behavioral economics sometimes does better at modeling economic behavior than rational choice theory, it is the case that for much of the time, rational choice theory is still adequate at explaining the decisions of economic agents.

Simply dismissing rational choice theory just because behavioral economics is sometimes "better" would be akin to throwing out Newtonian physics because of general relativity and quantum mechanics.

Physics is the Queen of sciences because enough time and money can resolve theories completely. Economics is the dismal science because it's experiments cannot be repeated, leaving many competing theories unresolved.

Although it is unfortunately not as common as it should be, replication does indeed occur in the field of economics.

It should also be noted that economics was originally called the "dismal science" by Thomas Carlyle, a 19th-century pro-slavery writer who expressed dismay at the fact that political economy often led to conclusions against the institution of slavery.

The Nobel Prize in Economic Sciences is not a real Nobel Prize

Ah do you mean the propaganda award (Nobel Memorial Prize in Economic Sciences) that economists have concocted to look like science.

The award was created by the Sveriges Riksbank in commemoration of the central bank's 300th anniversary, not by an international cabal of economists conspiring to gain legitimacy.

Not even that, the prize is, like most things in economics, simply crude capitalist/neoliberal propaganda. Economists made up this fake Nobel Prize to look like science.

The majority of Nobel Prize winners have won for ideas/thoughts that are not exactly associated with "capitalist/neoliberal" ideology. Their claim is just as ridiculous as Peter Nobel asserting that two-thirds of the winners have gone to stock market speculators.

Economists are neoliberal hacks who support the economic status quo

Capitalist apologists who firmly believe in the red scare propaganda and consider the "Free" Market to be an infallible supreme being.Moreover, they consider Marx either the devil himself or simply an idiot. Of course without ever having read a single sentence of his texts.But the most important thing is that they think capitalism is the best possible economic system. For them the history of mankind has ended with capitalism. People who completely seriously believe the unbelievable bullshit of Francis Fukuyama, Milton Friedman, Friedrich Hayek or Ludwig von Mises and think that it is the greatest wisdom. Oh and not to forget that they hate and fear socialism/communism/Marxism with religious fanaticism. Other economists are as rare as unicorns.

Economists are perfectly willing to accept that market policies are not always optimal while also not letting Marx live rent free in their heads.

And out of those four figures, practically none of them are "worshipped" by economists, with only some of Friedman and Hayek's ideas still being seen as relevant (and Friedman much more so than Hayek).

Also, I have the strange feeling that the user thinks about socialism much more than economists do...

Pretty much everything about economics is political, whether economists deny it or not. Economic models are usually presented as apolitical to hide the fact that they are highly ideological. For example, increasing unemployment is advocated by most economists to fight inflation and is the program of most central banks. It hardly gets more ideological and political. This nonsensical neoliberal propaganda is everywhere and it is part of the mainstream economics which understands/sells this as scientific facts. Today, economics is only a tool to legitimize neoliberalism. Everyone I listed above is not policy makers but famous economists of mainstream economics. Their models and ideas are considered by most economists as some kind of holy writ and the pinnacle of economic sciences, although they are largely pseudoscientific. Well, but string theory is not used by most physicists to argue that the following fact is good and right for "scientific" reasons:

Distribution of wealth - Wikipedia

Pretty much every economist advocates for a delicate balance between inflation and unemployment, which aligns with the goal of every competent central bank. It is asinine to suggest that they are somehow obsessed with lowering inflation as much as possible.

I do not think there is a single economist who treats those four figures and their work as some sort of holy bible...

As for their claim about wealth inequality, the majority of economists do think that it is a problem. And many of the panelists who voted disagree/uncertain did so because they perceived the factors causing inequality to be the problem, not inequality itself. Of course, there are disagreements over what are the exact causes, or over which cause is the most important, but the gravity of the issue is not at dispute.

A very clear example that economics is at best just astrology for clueless politicians, and at its worst just an excuse to make tbe rich richer, was visible after the credit crisis in the Netherlands in 2008. Clueless PM Mark Rutte sought economical advice and from the economical community two opposite advices were given. A. This is the time for the goverment to support the people and (small) companies. B. Austerity. Fuck the people. Clueless Mark, being tbe rightwing little shithead he is chose B and dunked the Netherlands in an unnecessary long recession, actually one of the longest in the western world. The fact that an economical community can pretend to be a science and then, when needed, can be 50/50 split on what the best course of action is, while everybody has access to all macroeconomic information, shows that it is bogus and not science.

Countercyclical fiscal policy is seen as a reasonable course of action by most economists, especially when monetary policy has been exhausted. It is not a 50-50 split at all. Now, it is true that there is dispute over when exactly to execute such policy, and over whether or not the increase in debt outweighs the short-term economic stimulus, but the user fails to present this nuance at all.

Economic consensus has been reached on many other issues as well, as explained in the FAQ.

https://www.reddit.com/r/Economics/wiki/faq_methods/#wiki_can_economists_reach_consensus_on_any_issue.3F

Econ teaches you how the status quo is correct and natural. It is the opposite of science and thus far easier to do and make money in.

The idea that economics merely defends the status quo is ridiculous. The recent research into the impact of higher minimum wages is just one single example of how economic thinking has shifted over time.

As for the claim that economists make more money than physicists, salary data from the BLS shows that physicists actually make more money than economists do.

https://www.bls.gov/ooh/life-physical-and-social-science/economists.htm

https://www.bls.gov/ooh/life-physical-and-social-science/physicists-and-astronomers.htm

*EDIT: As u/modular_elliptic explained, physics professors do make somewhat less than economics professors, so their claim is technically true for academia. Moreover, there are more options that one can do with an economics degree.

Here ye, here ye, the Joint Committee on Finance, Infrastructure, Academia, and Technology is now in session. In this session of the FIAT committee, all are welcome to come and discuss economics and related topics. No RIs are needed to post: the fiat thread is for both senators and regular ol’ house reps. The subreddit parliamentarians, however, will still be moderating the discussion to ensure nobody gets too out of order and retain the right to occasionally mark certain comment chains as being for senators only.

RI tax for the mod gods. Again /u/JustTaxLandLol is just the one that happens to have finally pushed me over the edge to write this, but my response is because this is a common sentiment. u/onetrillionamericans might also be interested.

My excel art wasn't met with as great reviews as I hoped so it is back to MSPaint we go. Although I will borrow the first two plat layouts of 50' front lots and 100' front lots from my previous post on the relationship between density and infrastructure.

The third image above illustrates a linear rent gradient in a linear city 1 mile wide with 100' lots that will stretch 24 miles in two directions from the city center in order to contain 100,000 households. The equilibrium condition in a city like this is that total land+commute cost must be equivalent at every point on the gradient. With ag land at $1,000/acre (~0 for our lots), average wages of $30/hour and a federally funded freeway designed to provide free flow 60mph speeds during the peak hour the annual travel cost at the agricultural fringe = 24 miles * 2 back and forth * $30/hour / 60 miles/hour=$24/day. At a 5% discount $24/day for 40 years has a present value of $151.486.01 ~ $150k. When faced with an amenity/job that is worth locating in the city the a consumer should be indifferent between locating at the urban fringe on a $250 lot or paying $150k to be located just outside downtown. The fourth image above adds the same rent gradient if instead of 100' lots the lots were 50'. The same calculation gets us a peak land value of $75k.

RESTRICTIONS ON DENSITY ARE RESTRICTIONS ON PROXIMITY AND THE REASON LAND IS VALUABLE IN CITIES IS BECAUSE THERE IS SOMETHING PEOPLE WANT TO BE CLOSE TO. IF YOU ALLOW MORE PEOPLE TO BE CLOSE TO IT THE VALUE OF PROXIMITY FALLS

But don't we find that upzoning a parcel increases the value of that parcel?

For example, its been a while since I read the paper but, if memory serves Yonah Freemark essentially found that spot upzoning was perfectly capitalized in land prices. If that applied in my example we would expect to see all land values double instead of fall by half. What's the difference?

The spot upzoning. The fifth image above illustrates the impact of a spot upzoning of a single 100' parcel 6 miles from the city center two two 50' parcels 6 miles from the city center. The city extent (the ~24 miles) would shrink by 24/100000 to 23.99976. Due to the shorter maximum commute distance all remaining 100' parcels would fall in price by $1.50 but now this lucky land owner has two parcels where there used to be one. The previous value of the single 100' lot was $113,614.51 and now they have two lots. So far we've abstracted away the value of land, all that is needed by our consumers is a lot/location, which is essentially what literature following Glaeser and Gyuorko's zoning tax utilizes to measure the real impacts of zoning. So, under my model, this spot upzoning would exactly match Yonah's findings, the two lots should be able to be sold for exactly twice (the original price minus $1.50), in reality it will be even slightly more lower because there is some extra value in having a 10,000 square foot lot but as the zoning tax literature shows there is a significant spread between average and marginal land values under zoning. Even in the real world, two lots will be significantly more valuable than 1/2 the original price of the one lot. But, that is precisely because the rest of the lots remained zoned at 100'.

IF WE HAD A WIDESPREAD REMOVAL OF ALL RESIDENTIAL DENSITY REGULATIONS (AND THE IMPLICIT RULES BACKED INTO THE REST OF OUR URBAN PLANNING REGULATIONS) WE WOULD SEE PRICE FALL FOR ALL LAND AND ALL HOUSING TYPES THROUGHOUT THE WHOLE EXTENT OF THE CITY.

What if instead we accidently made some of our cities better places to live?

The sixth graph at the imgur link above illustrates the equilibrium condition for city population, with the C1 an C2 illustrating increased costs due to zoning, from an older RI. As we lower the artificially high sum of land and travel costs this will induce more people to move to the city allowing the capture and creation of continuing increases in agglomeration benefits that we find in larger cities. It may end up that a city that allows itself to grow eventually reaches a point where its future land prices are higher than artificially lower land prices under constraints when the city was smaller. But, that would only be because we are also significantly higher on that upward sloping benefits curve too.

Drawing is easy.

Narratives are easy.

Numbers are hard.

When people post online, they are probably not putting too much time into thinking about what drawings their brain renders and what narratives they are following.

Then, we get comments in threads like this ELI5 thread which claim that progressive taxation is fair because it imposes equal disutility on those taxed. And crucially, that the reason why it is justified is because utility is logarithmic.

They are wrong.

Let's set up a function to calculate the proportion of income that should be taxed to get constant disutility under logarithmic utility, where y is income, x is non-taxed proportion, and u is the disutility. log(y * x) = log(y) - u. Then, let's solve for x with Wolfram Alpha because I can't be arsed to do it by hand.

The solution is x = e^-u. The tax, 1 - x, does not vary in y (income). Logarithmic utility therefore justifies flat taxes, the ones where the rate is the same, not progressive ones.

The intuition behind this requires going beyond "line curves right". Logarithms also have the (nice) feature of turning the difference of two logarithms into per cent changes. How a constant difference in logarithms (the disutility) leads to a constant per cent value should then be obvious.

How can you justify progressive taxation under equal disutility? Well, if you adopt a constant relative risk aversion function, just jack up the IES parameter beyond 1. (And if you take the IES parameter down to zero you can then justify head taxes.)