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Monetary Monopoly Model By Sam Levey

Sam Levey has a new Levy Institute working paper: “Modeling Monopoly Money: Government as the Source of the Price Level and Unemployment.”As I discuss in Section 4.3 of Modern Monetary Theory and the Recovery, the “Monetary Monopoly Model” is the core …

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This article was originally published by Bond Economics

Sam Levey has a new Levy Institute working paper: “Modeling Monopoly Money: Government as the Source of the Price Level and Unemployment.

As I discuss in Section 4.3 of Modern Monetary Theory and the Recovery, the “Monetary Monopoly Model” is the core macro model that captures some of the key ideas of Modern Monetary Theory (MMT). The key concept is that the government needs to set a key price (or a set of prices) in order to determine the price level of a fiat currency. This is contrast to mainstream models, where pinning down the price level is an embarrassing theoretical muddle.

Price Level Determination Primer

For a commodity currency, real factors can be used to pin down the price level in a model. (Sure, the real world can be messier, but the model logic will still be present.) Let us assume that the currency is gold-based. We look at the number of hours of labour to mine an ounce of gold, and we can then get a fair value for an hour’s labour. We observe that mine owners should be able to mine gold with a profit, as otherwise no gold will enter the system. Once we determine the income split between miners and mine owners (which is either based on power relationships, or magical marginal thinking, depending upon ideological preferences), we get a fair value for an hour’s wage. We then can pin down wages in other industries via the level of gold miners’ pay, and then can back out other prices. The key is that real parameters within the model — productivity — pin down the price level for a commodity currency.

For a fiat currency, there are no real factors associated with the currency creation. We could multiply all prices by the same factor, and preserve all relative value relationships between all real goods. From a modelling perspective, this implies that the solution to the model is indeterminate: the set of prices implied by the model is the set of all scalings of any price vector that works as a solution.

We need something to pin down the set of solutions to the model, and the MMT solution is the government to fix a key price that forces a single solution.

Although this discussion refers to an abstract problem in economic model building, the argument is that price level instability in models is related to inflation control. That is, can governments set key prices to help stabilise prices? The MMT argument is that is exactly what a Job Guarantee can do.

Levey’s Levy Paper

Sam Levey’s paper steps through a sequence of models of increasing complexity. They are discrete time models in which the government is a monopoly supplier of money, and examines “the price of money” (ratio at which labour is exchanged for money).

He examines what happens when the government sets a price for labour via a Job Guarantee, competing against private sector demand for labour. Using his reversed definition of price, this can be thought of as the government having one price of money versus the private sector (when expressed in labour hours).

This framing then leads to the debate whether a fiat currency issuer truly has a “monopoly” on “money,” given that a lot of “money” are private sector liabilities (mainly bank deposits, but we get wackier credit instruments in broad aggregates). Levey writes:

An analogy can be drawn to the study of “durapoly,” a situation noted in mainstream antitrust and industrial organization literature in which there is a monopoly producer of a durable good and, once sold, this durable good can be “recycled” or resold by other suppliers back into the market (Orbach 2004). Of particular interest is the 1945 antitrust case of United States vs. Alcoa, concerning whether Alcoa, which controlled 90 percent of the production of new aluminum, in fact lacked monopoly power due to the existence of a competitive market in recycled aluminum.

There is significant mainstream literature on durable goods markets in general (Waldman 2003) and the Alcoa case in particular (Gaskins, Jr. 1974; Swan 1980; Suslow 1986). We need not delve deeply into the topic, but we can borrow a general result that a monopoly producer can retain pricing power over a durable good if there is some reason why outstanding units of the commodity become insufficient for meeting the community’s demand. This can happen if units are lost or otherwise unavailable for recycling, or if demand is growing.[3] One or more of these conditions, if continued indefinitely, will eventually force buyers of the good back to the producer, granting the producer bargaining power. For our model this will be taxation: in the absence of government spending, taxation would eventually drain the supply of state money to zero, creating “shortages” in the “secondary market,” forcing demanders of fiat money back to the government and thereby imparting it with pricing power.[4]

The argument is that setting the Job Guarantee wage alone does not fix the price level by itself, rather it operates in conjunction with the monetary drain of taxation.

I looked at the paper relatively quickly, but the models looked clean and seemed well laid out. Since I am supposed to be working on my own agent-based version of a similar model, I do not want to get too side-tracked on going through the details of Levey’s work just yet.

The true challenge with modelling the Job Guarantee is trying to pin down how private sector wages would be set versus the Job Guarantee wage. The standard belief is that private wages would be set as a markup to the Job Guarantee wage, with the markup varying with the cycle. Although that is reasonable (and somewhat non-falsifiable), the trick is modelling the markup. Given the lack of full scale implementations of Job Guarantee programmes, we do not have much in the way of empirical data to work with.

I might return to this paper later, but I just wanted to let everyone know that it is out.

Postscript: Agent-Based Version?

I am plugging away at my agent-based framework, which is an open source Python project. At this point, I have something resembling a closed loop model running. However, I am refactoring it heavily, so I do not consider what I have to be in any sense a completed model.

The problem with a complex agent-based model (like the one I am attempting to build) is that sensible looking decision rules require agents to have a lot of input data to work with, and they need to interact with other many other agents.

For example, the simplest production firm hires workers and then attempts to sell its output. Modelling this requires a few steps.

  • The production firm needs to get the posted market prices for its output, and have an idea what market wages are for setting hiring offer wages.

  • It needs to look at prices and wages (at least) and decide how many workers to hire. (Realistically, they would need more data to make more sensible decisions.)

  • It needs to interact with the worker agents to pay them salary, and with the government to pay withheld income tax.

  • The production event needs to follow its production function.

  • It needs to interact with the market to sell its output.

From a programming point of view, this means that the firm needs to interact with a lot of different other software entities — each of which also needs to interact with others. This turns into what is known as “spaghetti” in software engineering jargon.

I am in the process of creating a standardised interface so that all of the agents can make their decision process in a structured fashion. The agents just indicate what input data they need, and then when that data is supplied, they give a list of actions to be taken. The software framework then processes those actions, which means that decision-making code does not need to know how interactions between agents are implemented.

Going with this more elegant solution slows down adding new features. However, once it is in place, it should be easier to add new decision rules, which is ultimately the most interesting part of the project.

I write more about this project on my Patreon.


Email subscription: Go to https://bondeconomics.substack.com/ 

(c) Brian Romanchuk 2021

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Aldoro Resources covering all bases with rubidium, lithium, nickel, copper, gold and more in rock chip samples

Special Report: Aldoro Resources is covering all bases across its diverse prospects in WA, posting high-grade rock chip assays for … Read More
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Aldoro Resources is covering all bases across its diverse prospects in WA, posting high-grade rock chip assays for a suite of metals including gold, copper, nickel, lithium and rubidium.

Junior explorer Aldoro (ASX:ARN), is using grassroots exploration techniques to improve the surface geochemical knowledge of its tenements across the Wyemandoo pegmatite, Narndee Igneous Complex, and Quandong Well target, collecting 20 rock chip samples.

Evidence of mineralisation across pegmatite, magmatic nickel-copper gossan and VMHS gold-copper targets was uncovered at all three targets.

Samples from the Wyemandoo pegmatite returned top grades of 0.80% rubidium and 0.81% lithium.

A high-grade rubidium-lithium lepidolite pegmatite sample from Wyemandoo. Pic: Aldoro Resources

The results are exciting after Aldoro recently identified world-class rubidium potential of its nearby Niobe project, and warrant drilling investigation.

At Narndee, top results from samples included up to 0.37% nickel, 0.15% copper, 0.09% cobalt, 27ppb palladium and 22ppb gold.

That included two samples taken from gossans within a couple of kilometres of the VC1 target, where Aldoro struck magmatic sulphides in the first drilling undertaken at Narndee in a decade.

Aldoro Resources
Gossan 2, exposed in a historical exploration pit 1000m SSW of the significant VC1 drill hole. Pic: Aldoro Resources

Meanwhile, sampling at Quandong Well returned best results of 1.93g/t gold and 0.45% copper.

BHP subsidiary Dampier Mining explored Quandong Well in the 1970s, drilling 31 holes for 1731m that are yet to be compiled and validated by Aldoro.

The old timers reported significant copper, zinc, and gold results in oxide phases close to the surface, grading into a sulphide assemblage of pyrrhotite and chalcopyrite at depth.

Next steps

The rock sampling program was an important step for Aldoro, which noted the surface geochemical dataset is inadequate over most of its tenement package.

Initial results have enabled the company to develop an industry-standard database as a launchpad to future exploration success at Wyemandoo, Narndee and Quandong Well.

Aldoro plans to complete systematic rock chip and soils sampling programs and detailed mapping over the Wyemandoo pegmatite swarm.

This will identify the most prospective zones for drill targeting and locate pegmatite strike extensions and occurrences under soil cover.

The company said field reconnaissance and field mapping will continue to locate and assess all prospective areas of the tenement package for LCT pegmatites, nickel gossans, and copper-gold gossans.

 


 

 

This article was developed in collaboration with Aldoro Resources, a Stockhead advertiser at the time of publishing.

 

This article does not constitute financial product advice. You should consider obtaining independent advice before making any financial decisions.

The post Aldoro Resources covering all bases with rubidium, lithium, nickel, copper, gold and more in rock chip samples appeared first on Stockhead.

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Cannindah up 21pc on gigantic copper hit

Special Report: First assays from an ongoing drilling program at the historic Mt Cannindah copper-gold-silver project in central Queensland are … Read…

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First assays from an ongoing drilling program at the historic Mt Cannindah copper-gold-silver project in central Queensland are in – and they look very good.

The recent increase in copper prices has underlined the significant value of Cannindah Resources’ (ASX:CAE) brownfields ‘Mt Cannindah’ copper-gold-silver project, which boasts an existing JORC resource of 5.5 million tonnes @ 0.93% copper and significant exploration upside.

The company is currently undertaking a 1,450m drilling program to explore both new and existing areas.

Mt Cannindah project: location of identified resources & known targets.

 

Success has come quickly, with the top portion of hole two hitting 117m at 1.01% copper, 0.39g/t gold and 28g/t silver from 34m to 151m.

Assays are pending for the subsequent 180m interval from 150m to 330m. This bottom portion “contains visual primary copper mineralisation, many metres of which looks similar in tenor to the 34m-151m interval”, the company says.

Coming next – hole 3 (21CAEDD003) — completed for 762.2m vs the planned 250m — has also encountered significant copper, the company says. The exciting visuals of the core has driven the significant increase in meterage.

The hole was drilled to the drill rig’s capacity and ended in copper-rich sulphidic breccia.

It is now the deepest hole drilled within the Mt Cannindah mine area, the company says.

“Copper assays are awaited, [but] preliminary tests from visual estimates of chalcopyrite, and PXRF analyses of sludge samples to date, all indicate significant copper values should be returned over large sections of at least the first 500m or so of hole 21CAEDD003,” Cannindah says.

Results received to date underpin potential extension of the current 5.5Mt JORC resource, with the supergene zones offering further grade upside upon incorporation.

“Although assays are needed to confirm the significance of the discovery, CAE are highly encouraged that this strategy has been successful and a major extension to the known Cu-Au-Ag resources at Mt Cannindah mine will likely follow from the drilling of hole 21CAEDD003,” the company says.

“This goal has eluded the major mining houses that have previously explored Mt Cannindah.”

New diamond drilling is yet to occur on other targets such as Cannindah East, where the explorer is also expecting encouraging results. Cannindah East has a non JORC gold resource of 245,000t grading 2.8g/t.

The $77m market cap stock is up 383% year-to-date.

 

Cannindah Resources share price today:


This article was developed in collaboration with Fresh Equities, a Stockhead advertiser at the time of publishing.

This article does not constitute financial product advice. You should consider obtaining independent advice before making any financial decisions.

 

The post Cannindah up 21pc on gigantic copper hit appeared first on Stockhead.

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Precious Metals

UPDATE – Gold:Silver Ratio Suggests Much Higher Future Price for Silver (+30K Views)

Silver is currently greatly undervalued relative to its average long-term historical relationship with gold and, as such, it is realistic to expect that…

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Silver is currently greatly undervalued relative to its average long-term historical relationship with gold and, as such, it is realistic to expect that silver will eventually escalate dramatically in price. How much? This article applies the historical gold:silver ratios to come up with a range of prices based on specific price levels for gold being reached.

By Lorimer Wilson (www.munKNEE.com)  – “ The internet’s most unique site for financial articles! (Here’s why)”.

Gold to Silver Ratio

How both gold and silver perform, in and of themselves, does not tell the complete picture. More important is the price relationship – the correlation – of one to the other over time, the gold:silver ratio.

Let’s look at the gold:silver ratio from several different perspectives:

  • Over the last 50 years, the average value of the gold-silver ratio was approximately 57:1.
  • Over the last 25 years, the average value of the gold-silver ratio was 64:1.
  • Over the last 10 years it was 66:1.
  • since 1985 the mean ratio has been 45.7:1

Let’s now look at the various price levels for gold and the various gold:silver ratios mentioned above, one by one, and see what conclusions we can draw.

First let’s use the price of $1,750 for gold and apply the gold:silver ratios mentioned above in approximate terms and see what they do for the potential % increase in, and price of, silver.

  • Gold @ $1,750 using the 57:1 ratio (50-yr. avg.) puts silver at $30.70
  • Gold @ $1,750 using the 66:1 ratio (10-yr. avg.) puts silver at $26.51

Now let’s apply the projected potential parabolic peaks of $2,000, $3,000, $5,000 and $10,000 to the various gold:silver ratios and see what they suggest is the parabolic top for silver.

Silver’s Potential Price Range With Gold At $2,000

  • Gold @ $2,000 using the ratio of 57:1 puts silver at $35.09
  • Gold @ $2,000 using the ratio of 66:1 puts silver at $30.30

Silver’s Potential Price Range With Gold At $3,000

  • Gold @ $3,000 using the ratio of 57:1 puts silver at $52.63
  • Gold @ $3,000 using the ratio of 66:1 puts silver at $45.45

Silver’s Potential Price Range With Gold at $5,000

  • Gold @ $5,000 using the gold:silver ratio of 57.1 puts silver at $87.72
  • Gold @ $5,000 using the ratio of 66:1 puts silver at $75.76

Silver’s Potential Price Range With Gold at $10,000

  • Gold @ $10,000 using the gold:silver ratio of 57:1 puts silver at $175.44
  • Gold @ $10,000 using the ratio of 66:1 puts silver at $151.52

It would appear that, any way we look at it, physical silver is currently undervalued compared to gold bullion and is in position to generate substantially greater returns than investing in gold bullion.

Gold to Silver Ratio Conclusion

This fiat currency experiment will end badly in a currency crisis and when that happens, as it surely will, gold will go parabolic and silver along with it – but even more so – as the gold:silver ratio adjusts itself to more historical correlations.

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The post UPDATE – Gold:Silver Ratio Suggests Much Higher Future Price for Silver (+30K Views) appeared first on munKNEE.com.

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