EconSpark - Recent questions, answers and comments

Someone should do a PHD on how Hazing impacts the health of a nations economy

Thu, 06 Aug 2026 01:28:28 +0000

Someone should do a PHD on how Hazing impacts the health of a nations economy

Answered: Are Ducks good economist

Wed, 05 Aug 2026 21:47:22 +0000

Answered: What models explain how political influence and information asymmetry reinforce gains in money and public claims?

Wed, 05 Aug 2026 21:42:07 +0000

Questioning Academic Manners

Fri, 17 Jul 2026 22:25:41 +0000

Optimistically Even Trump will be a better president of both MIT and HubSpot then their current leadership, LOL

Evolution Logic or logic of economics

Fri, 17 Jul 2026 22:22:35 +0000

The first species that will develop self awareness will be in a jungle with high diversity and density of life and easy availability of food, not in Africa.

Bitcoin is not a currency

Fri, 17 Jul 2026 22:20:17 +0000

Alright lets talk about bitcoin and other similar coins a little bit, Its theoretically a sound currency backed by book keeping, but it will never build wealth in the economy and hence have no value as such other than the agreement between two people, the one that is providing and the one that is receiving it, hence it is completely and in entirety a social contract only, not a real currency. No wonder we now have a horde of stable digital coins like USDT etc. backed by the wealth building assets like bonds and real estate.

When Is a Scalar Utility Function Not Enough?

Wed, 24 Jun 2026 06:06:42 +0000

A simple observation in one of our PV-PP simulations has led to one of the most important results we have produced so far.

The observation was that a single-number model seemed to work when the productive-power relationship was simple and smooth. That raised a larger question: when can a complex economic or decision process really be reduced to one number, and when does that reduction leave out something important?

We have now completed a formal proof program around that question.

A simple analogy

A useful analogy is the relationship between Newtonian mechanics and special relativity. Newtonian mechanics works very well at ordinary speeds, but as speeds become extremely high, the broader theory of special relativity is needed.

The same general idea applies here. Scalar models work well when the things being compared can be reduced to one measure without losing anything important. But when history, changing circumstances, hard limits, or different kinds of value start to matter, the broader PV-PP framework is needed.

What we found

The result is not that scalar models are wrong. It is also not that PV-PP must always remain non-scalar.

The result is that scalar aggregation can be used as a valid subroutine inside PV-PP when the conditions are right. In those cases, a one-number representation can rank the available choices without losing anything essential.

When those conditions are not present, the failure is not vague or philosophical. It can be identified. A single number may no longer preserve the role of past interactions, changing capabilities, non-negotiable limits, or different dimensions of value.

This gives us a clearer answer than either extreme. We do not have to say that everything reduces to one number. We also do not have to reject scalar methods altogether.

Why this matters for economics

Economics depends heavily on scalar tools, especially utility functions. They are useful because they make ranking, comparison, and optimization possible.

PV-PP does not ask economists to abandon those tools. Instead, it places them inside a broader framework and asks a more precise question: what does the scalar preserve, and what does it leave out?

That distinction matters because a scalar can sometimes reproduce a final choice without explaining the process that produced it. Two systems may choose the same option while reaching it through very different histories, constraints, or changes in productive power.

A possible objection becomes a strength

One possible criticism of PV-PP is that any decision could eventually be rewritten as a sufficiently complicated utility function. If that were always enough, the larger framework might seem unnecessary.

The new proof work gives a better answer. Scalarization can succeed, sometimes exactly, but only for a stated problem and under stated conditions. Success in one setting does not prove that the entire process, theory, or social structure has been reduced to one number.

That means scalar aggregation is not a rival to PV-PP. It is a special case that PV-PP can use when appropriate and move beyond when it is not.

What has been completed

The proof materials have now been completed as a controlled internal package. They include the positive case showing when scalar representation exists, the failure cases showing when it does not, and examples that mark the boundary between the two.

The package has been subjected to repeated hostile review, including independent review by more than one advanced AI system. No blocking or major defect remained after the final corrections.

The full proof package has not yet been published or independently peer reviewed by outside mathematicians or economists, so this announcement should not be read as a claim of final external validation. It is, however, much more than an intuition from a simulation. It is now a formal and documented result.

Why announce it now?
This changes how the PV-PP framework can be explained.
PV-PP is not opposed to one-number models. It explains when they work, why they work, and when a broader description becomes necessary.
A simple simulation observation opened the question. The proof work has now established a usable boundary. That is a major milestone for the framework.

Why Do Some Demographic Groups Fall Behind Over Time?

Fri, 12 Jun 2026 08:46:35 +0000

One of the hardest social questions is why some populations fall behind others over time.

The usual explanations tend to become moral or political very quickly. Some people blame culture. Some blame discrimination. Some blame policy. Some blame family structure. Some blame markets. Some blame schools. Each explanation may capture part of the story, but none of them fully describes the mechanism.

The Productive Value–Productive Power (PV-PP) framework gives us a different way to look at the problem.

It begins with a simple distinction.

Productive Value is what moves between individuals: goods, services, information, money, protection, instruction, care, discipline, opportunity, tools, and other useful inputs.

Productive Power is the capacity an individual has to generate, preserve, receive, or use Productive Value in the future.

A child is not born into the market as a fully formed economic individual. A child passes through years of Productive Power formation before reaching adulthood. During that period, the child is shaped by household conditions, language exposure, nutrition, safety, discipline, emotional stability, schooling, peer groups, neighborhood conditions, institutional trust, and access to capable adults.

Those inputs do not merely affect the child’s current comfort. They shape the child’s future interaction possibilities.

This leads to the key concept:

Interaction corridor quality.

An interaction corridor is the path of possible exchanges available to an individual. A high-quality corridor exposes the individual to better information, better schools, safer relationships, stronger mentors, more reliable institutions, better job networks, lower predation, and more recoverable mistakes. A low-quality corridor exposes the individual to weaker instruction, unstable relationships, unsafe environments, predatory offers, low-trust institutions, poor networks, harsher consequences, and fewer recovery paths.

This means lower Productive Power does not merely make an individual “poorer” in a static sense. It can route the individual into lower-quality interaction corridors.

That is the mechanism.

Low early Productive Power leads to weaker childhood corridor access. Weaker childhood corridor access leads to weaker school readiness, weaker behavioral regulation, weaker language development, and weaker institutional navigation. Those weaknesses then affect adolescent corridors: peer groups, school tracks, discipline systems, mentor access, work habits, confidence, and exposure to risk.

By adulthood, the individual does not enter the marketplace from nowhere. The individual enters after years of corridor formation.

The adult market then sees an outcome that looks individual: this person has lower skills, weaker credentials, poorer networks, less savings, less confidence, worse judgment, or more legal exposure. But the PV-PP view says those adult traits are often the downstream result of earlier corridor sequences.

The time path matters.

Early household environment shapes early Productive Power.

Early Productive Power shapes childhood corridor quality.

Childhood corridor quality shapes school readiness.

School readiness shapes educational placement and feedback.

Educational placement shapes adolescent peer and opportunity corridors.

Adolescent corridors shape credentials, habits, risks, and networks.

Those shape adult labor-market entry.

Adult labor-market position shapes the starting conditions of the next generation.

This is how demographic divergence can persist without assuming that any group is permanently fixed, biologically destined, or morally defective. Populations can diverge because they are exposed at different rates to Productive Power-forming or Productive Power-damaging conditions over time.

This also clarifies the role of parenting.

Poor parenting is not just a moral category. In PV-PP terms, it is a weak early Productive Power formation environment. A child may receive less language, less discipline consistency, less emotional regulation, less structure, less modeling, less institutional guidance, less protection from harmful corridors, and less transmission of productive norms.

That does not mean parenting is the only cause. It is one corridor-forming mechanism among many. Neighborhoods, schools, health, safety, violence exposure, family stability, peer groups, institutional trust, and local labor markets all matter.

The point is not to blame one factor. The point is to model how the factors connect.

The framework also explains compounding.

Individuals with higher early Productive Power are more likely to enter better corridors. Better corridors produce better Productive Value transfers. Better transfers increase future Productive Power. Higher future Productive Power opens still better corridors.

Individuals with lower early Productive Power face the reverse pattern. Lower Productive Power leads to weaker corridors. Weaker corridors produce lower-quality transfers. Lower-quality transfers reduce future Productive Power formation. Future corridor access narrows.

This is cumulative advantage and cumulative disadvantage, expressed in PV-PP terms.

It also explains why late intervention is harder than early intervention.

If a child is given strong Productive Power early — language, nutrition, safety, structure, instruction, discipline, care, and access to productive adults — that child may enter better school and peer corridors from the beginning. If the same support arrives much later, it may still help, but it must overcome years of prior corridor formation.

In other words, early Productive Power insertion can change the path before the corridor narrows.

This is where the framework is descriptive, not moralistic.

PV-PP does not say society must intervene. It does not contain a fairness command. It does not say weak individuals must be protected, or that disparities must be corrected. Those are value judgments that must come from outside the framework.

What PV-PP does say is more limited and more structural:

If individuals are left to compete with unequal Productive Power, weaker individuals will often be routed into lower-quality corridors. Those corridors will tend to produce weaker future Productive Power. Over time, the system will prune, sort, stratify, and compound differences.

That is what happens in nature. Weak animals are often pushed out, preyed upon, denied resources, or left behind. Human society differs because it can choose to interrupt that process. It can artificially insert Productive Power through parenting, education, nutrition, safety, healthcare, mentoring, training, capital access, and institutional design.

But the framework does not tell us whether to do that.

It tells us what such actions do.

They change corridor access.

They change future Productive Power.

They change the probability that an individual can compete.

This is why the concept matters. It gives us a way to discuss demographic stratification without reducing the discussion to slogans. It shows how early differences become adult differences. It shows why some interventions work better when applied early. It shows why market outcomes often reflect long pre-market histories. And it shows why the same society can contain groups moving through very different economic realities.

The core claim is simple:

People do not merely differ in resources. They differ in the quality of the interaction corridors available to them. Those corridors shape future Productive Power, and future Productive Power shapes the next set of corridors.

That is the mechanism by which small starting differences can become large social differences over time.

It is also the mechanism by which artificial Productive Power insertion can change a life trajectory.

The Productive Value–Productive Power framework does not replace the existing research on early childhood development, social capital, neighborhood effects, education, family structure, or intergenerational mobility. It organizes those findings into a single process model.

Early conditions shape Productive Power.

Productive Power shapes corridor access.

Corridor access shapes future exchange.

Future exchange shapes future Productive Power.

And across time, those paths become demographic outcomes.

Are Elite Universities Solving Inequality—or Just Rearranging the Final Sorting Gate?

Thu, 11 Jun 2026 08:10:37 +0000

Elite Universities Don’t Just Educate. They Concentrate Productive Power
A Productive Value–Productive Power view of education, cumulative advantage, and social mobility
LANCE AMUNDSEN
JUN 09, 2026

One way to understand education is to stop thinking of it as merely schooling.

Education is one of the main ways a society creates, concentrates, certifies, and distributes productive capacity. In the Productive Value–Productive Power (PV-PP) framework, that productive capacity is Productive Power: the stored knowledge, skill, resources, relationships, habits, institutional fluency, and practical capability that allow a person to generate future value.

Once viewed this way, universities become more than places where students take classes. They become institutional machines for selecting and accelerating Productive Power.

The compounding problem

People do not enter the education system with equal Productive Power. Some children arrive with books in the home, stable housing, educated parents, safe neighborhoods, good schools, tutoring, extracurricular development, expectations of success, and adults who know how institutions work. Others do not.

Those differences matter because Productive Power compounds. A child who reads early can use reading to acquire more knowledge. A student with strong preparation can enter harder classes. A student who understands institutions can find better opportunities. A family that knows how college admissions work can help a teenager package prior achievement into future access.

The result is a familiar cycle: early PP advantage leads to better development opportunities; better opportunities create stronger credentials; stronger credentials open access to better networks and higher-value exchanges; those exchanges then create still more Productive Power.

This is not a moral claim that advantaged students are better people. It is a structural claim about cumulative capability.

Elite universities as Productive Power concentrators

Elite universities are usually described as engines of excellence, opportunity, research, or leadership. They can be all of those things. But they are also Productive Power concentrators.

They generally do not create high-capability students from nothing. They select students who already show strong indicators of accumulated PP: academic performance, writing ability, test performance, discipline, family support, institutional knowledge, social confidence, and the ability to operate inside formal systems.

Then they add more PP. They provide advanced instruction, elite peer groups, faculty access, research opportunities, alumni networks, career placement, institutional prestige, and a powerful credential. The student enters with an advantage and leaves with a larger one.

That is the snowball effect. Prior Productive Power helps secure entry. Entry adds additional Productive Power. The added Productive Power improves access to future exchanges. Future exchanges then increase Productive Power again.

This is one reason elite education has such strong social persistence. It does not merely reward merit at a single moment. It captures prior advantage, intensifies it, and returns it to the economy with institutional certification.

The college debate starts too late

Most public debate about fairness in education begins near college admissions. That is too late.

By the time students are applying to universities, large PP differences have already accumulated. If one student is reading fluently by age eight and another is still struggling to read in high school, the second student is not simply behind in English class. That student is behind in the main channel through which modern Productive Power is formed.

Reading is not just a school subject. It is a multiplier. It allows self-instruction, abstraction, technical learning, institutional participation, and access to accumulated human knowledge. A student who cannot read well by the middle of high school has already been cut off from many future PP-formation pathways.

So the question is not merely who should get into Harvard, Stanford, MIT, or the top state universities. The harder question is why so many students arrive at the sorting gate without the Productive Power needed to compete there.

Standards, diversity, and a better question

Modern universities face several competing obligations. They are asked to preserve academic excellence, widen access, correct inherited disadvantage, support diversity, conduct research, prepare workers, generate leaders, and remain socially legitimate. These goals are not identical.

A weak version of the debate collapses everything into one fight over standards versus inclusion. That framing is too crude.

A better PV-PP question is: which Productive Powers are being selected for, which are being missed, which can be developed after admission, and which institutional outputs must be preserved?

A student with lower conventional credentials may still possess high latent Productive Power if placed in the right developmental environment. Another student with impressive credentials may have strong test-taking ability but weaker practical, creative, moral, adaptive, or social capability. The problem is not diversity itself. The problem is bad diagnosis of Productive Power.

Universities get into trouble when they confuse symbolic correction with actual PP formation. Admitting someone into a high-demand environment does not by itself supply the missing Productive Power. If the institution expands access but does not also build the missing capability, it has not solved the underlying problem. It has only moved the failure point downstream.

Credentialed PP versus actual PP

Employers have long used elite degrees as shortcuts. A selective university credential signals that a candidate passed through a difficult filter. But a credential is not the same thing as productive capability. In PV-PP terms, a credential creates perceived Productive Power. The workplace tests actual Productive Power.

When the gap between perceived PP and actual PP becomes visible, employers adjust. Some employers still value elite degrees heavily. Others increasingly look for demonstrated skill, project history, technical competence, apprenticeship experience, or evidence that the person can actually produce value in the job.

That does not mean elite universities no longer matter. They do. But it does mean the signal is being questioned. Institutional prestige is strongest when it maps reliably to actual productive capability. When the mapping weakens, the market searches for better signals.

So how do we fix it?

The answer is not to punish high-PP students. It is not to pretend selection can disappear. Complex societies will always sort people by some combination of capability, credential, trust, performance, network, and institutional fit.

The real question is how to increase the rate at which lower-PP students can acquire the Productive Powers needed for viable participation before the major sorting points arrive.

That means the repair has to start early. Literacy cannot be treated as one subject among many. Numeracy cannot be allowed to drift for years. Attention, discipline, health, sleep, nutrition, safety, family support, mentoring, and institutional navigation all matter because they affect the student’s ability to accumulate future PP.

A serious education system would identify PP deficits early and intervene before they compound. It would create multiple high-quality pathways: academic, technical, vocational, entrepreneurial, and apprenticeship-based. It would treat reading, writing, math, digital fluency, and practical problem-solving as foundational Productive Powers. It would create re-entry paths for students who mature late or whose early environments failed them.

Most importantly, it would stop pretending that late-stage admissions policy can repair fifteen years of unequal PP formation.

The reduced claim

The reduced claim is simple: education is society’s main Productive Power formation system. Elite universities historically concentrate and certify already-advantaged PP, then add more through training, networks, and institutional prestige. That produces cumulative advantage.

The social challenge is not to deny excellence or weaken standards. The challenge is to build earlier, better, and more varied PP-acceleration systems so that more people can reach high-functioning maturity before the decisive sorting moments arrive.

If we want a fairer society, the goal cannot be merely to rearrange who receives elite credentials at the end of the pipeline. The goal has to be to increase the number of people who actually possess the Productive Power those credentials are supposed to represent.

Commented: Do low-time-value buyers sustain cash prices in pickup-only markets?

Fri, 05 Jun 2026 16:10:59 +0000

Is it time to rethink scalar utility as a special case of a broader decision framework?

Thu, 04 Jun 2026 13:29:07 +0000

I’m looking for a technically serious reviewer for a proof package I’ve been developing around what may be a boundary problem in standard utility/scalar aggregation.

The question is this:

Can scalar utility be treated not as the whole decision architecture, but as a restricted subroutine that works only when specific structural conditions are met?

The proof package comes from the Productive Value–Productive Power (PV-PP) framework. The basic claim is not that scalar utility is useless. It is not that economics is wrong. The claim is narrower:

Scalar comparison appears to be locally recoverable inside PV-PP under certified structural conditions, but scalar comparison does not appear to globally contain the full PV-PP decision architecture in classes involving staged selection, governing-domain conflict, changing state, viability thresholds, recovery constraints, and execution authority.

In plain language: one score may be valid when the decision problem has the right structure. But in other cases, the decision is not just “which option has the highest score?” It is “which options are viable under the domains that currently govern the decision, and which stages of the decision process are being collapsed if we force everything into one ranking?”

If this holds, the implication is not anti-utility. It is more like an expansion of the textbook treatment of utility: scalar utility would remain important, but as a special case inside a broader architecture that can identify when scalar compression is valid, merely diagnostic, or structurally misleading.

The current proof package has been reduced to a finite review set. The live theorem packet is V3.25; V3.26 is only a status-and-boundary layer. The package has already gone through adversarial AI-assisted file-control and claim-scope review, but that is not a substitute for a human technical reviewer.

I am looking for someone with strength in one or more of:

mathematical economics
decision theory
utility theory
optimization
formal methods / proof verification
multi-criteria decision theory

The review I need is adversarial. I do not need encouragement. I need someone to look for theorem defects, hidden assumptions, overclaims, condition drift, and places where a proof-control note may be doing more work than the theorem actually supports.

If you know someone who would be willing to review this kind of proof package, or if you think there is a better venue for finding such a reviewer, please contact:

amundsenlance@gmail.com

The review question is simple:

Is scalar utility best understood as the whole decision model, or as a powerful but structurally limited subroutine inside a broader decision architecture?

Answered: What are the chances that the Cave drawing are the first human written ledgers of info. (tracks) traded between tribes

Mon, 01 Jun 2026 23:20:57 +0000

Commented: Can a non-scalar selection architecture strictly contain scalar aggregation?

Tue, 26 May 2026 00:13:53 +0000

Answered: The Broken Demand/Supply Model of US Healthcare - How to Fix?

Mon, 25 May 2026 14:36:56 +0000

Commented: Minimal benchmark: non-scalar policy selection in gridworld (seeking critique)

Mon, 25 May 2026 14:26:22 +0000

Answered: Using ChatGPT AI for Publishing

Mon, 25 May 2026 14:07:13 +0000

Answered: Is Anyone Willing to Review my Paper?

Mon, 25 May 2026 14:04:23 +0000

Commented: is it important to apply kalman filter in each cell of the matrix for my input ouput model, what the best way to do it?

Mon, 25 May 2026 13:13:02 +0000

Answered: Any paper constructs trimmed+stacked data to do Staggered DID?

Sun, 24 May 2026 21:43:52 +0000

Answered: Identify movers in SIPP

Sun, 24 May 2026 21:41:10 +0000

Answered: What professional economists have served as national leaders, cabinet secretaries, or members of the legislature?

Sun, 24 May 2026 21:38:52 +0000

Answered: Does any body know how to carry out simulation analysis with GTAP 12 database?

Sun, 24 May 2026 21:27:44 +0000

Answered: Call for Papers: Special Issue of Macroeconomic Dynamics in Honor of Frank Ramsey

Sun, 24 May 2026 13:46:07 +0000

Transitioning from MBA to IO PhD

Thu, 12 Mar 2026 19:49:17 +0000

Hello! I’m an MBA in finance with 8+ years advising on market power and platform strategy. I’m preparing to apply to IO PhD programs (with Yale IO at the top of my list). I’d love pointers on:

1. Finding paid or volunteer RA roles to build my econometrics and theory skills
2. Connecting with mentors in IO research (I would love to send you some of my research to get feedback!), I am actively looking to connect with Professors that I could work for, have sessions with, and learn about how to build the best profile for this goal.
3. Crafting a PhD-level research agenda before applying. Any sample outreach templates or leads to active job boards would be hugely appreciated. Thank you!

Economics Internships/Research for a incoming High School Senior

Sun, 01 Mar 2026 05:36:53 +0000

Hi everyone! I’m an incoming high school senior with a strong interest in economics, finance, and research, and I’m currently looking for internships, research opportunities, or mentorship programs for this upcoming year/summer. I have written a research paper under the guidance of Dr. Andrew Foley of NYU Stern in Narrative Economics, but I am looking to deepen my involvement.

Commented: Webcast Availability for ASSA 2026 Sessions

Sun, 18 Jan 2026 04:29:12 +0000

Commented: 2Q data is wrong (again)

Thu, 08 Jan 2026 19:17:29 +0000

In a volatile global economy, should policy success be measured by short-term stability or institutional readiness?

Mon, 29 Dec 2025 22:34:21 +0000

This question aims to encourage discussion on how economic policy success should be evaluated in environments characterized by recurring volatility, with particular attention to institutional capacity and policy implementation under pressure.

Answered: Should central banks change their inflation targets?

Mon, 22 Dec 2025 21:24:49 +0000

Answered: How can the Federal Reserve stop inflation without causing a recession?

Mon, 22 Dec 2025 21:18:30 +0000

Adam Smith and the colonial origins of institutions

Mon, 20 Oct 2025 19:25:13 +0000

While reading Adam Smith's, Wealth of nations (Wordsworth editions, Ware, Hertfordshire, UK, 2012), I was amazed by the fact that he can be regarded as a distant predecessor of the theory of colonial origins of institutions and cross-country differences in economic growth. Specifically, I found these passages in which Smith argues that thinly inhabited European colonies had set better political institutions and, consequently, witnessed more rapid growth.

The colony of a civilized nation which takes possession either of a waste country, or of one so thinly inhabited that the natives easily give place to the new settlers, advances more rapidly to wealth and greatness than any other human society. (Book 4. Of systems of political economy, Chapter 7. Of colonies, p. 560)

Plenty of good land, and liberty to manage their own affairs their own way, seem to be the two great causes of the prosperity of all new colonies. In the plenty of good land, the English colonies of North America, though no doubt very abundantly provided, are, however, inferior to those of the Spaniards and Portuguese, and not superior to some of those possessed by the French before the late war. But the political institutions of the English colonies have been more favourable to the improvement and cultivation of this land, than those of the other three nations. (Book 4. Of systems of political economy, Chapter 7. Of colonies, p. 567)

Answered: What resources do you use to teach international trade?

Tue, 30 Sep 2025 19:30:35 +0000

Why are ICAO statistics the only paid statistics in the United Nations system? Is there an alternative?

Wed, 13 Aug 2025 17:15:40 +0000

I'm conducting economic research on the civil aviation industry in Latin America, but I'm surprised to find significant restrictions on data access, particularly from the United Nations. I'm looking for open-access data sources on this industry. I appreciate your collaboration.

How do rule changes impact market equilibrium?

Tue, 12 Aug 2025 23:52:37 +0000

I am eager to explore this question and welcome thoughtful discussion. My current understanding is as follows: When institutions change—throughnew rules, regulations, or policies—skills that were valuable under previous institutional frameworks can become obsolete, as they were specifically tailored to those earlier conditions. Consequently, demand for different skills is reconfigured. Because institutional change often occurs faster than the workforce can adjust its skills, this creates a mismatch between labor supply and demand, resulting in market disequilibrium. This disequilibrium persists as the adjustment of skills lags behind the pace of institutional change. The reconfiguration of demand and the ensuing disequilibrium lead to a reordering of marginal returns to skills and a redistribution of welfare. Some groups bear the costs associated with skill devaluation, while others benefit from the new rules.

I have developed these ideas further in a working paper posted on SSRN:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5335021

Answered: Teaching in Corona times: useful examples for an undergrad micro-economics course?

Fri, 11 Jul 2025 13:12:06 +0000

Answered: What are issues that arise in advising grad students and young colleagues, or about which you have sought advice?

Sat, 05 Jul 2025 21:44:58 +0000

Karfali-VAR 9-Year Cycle: Historical Patterns Forewarning Current Headwinds?

Sat, 05 Apr 2025 15:21:07 +0000

Following up on my previous posts about the Karfali-VAR model and its economic cycle analysis, with its hybrid methodology (30% cycle / 70% VAR), I want to emphasize that the model's discovery of a robust 9-year economic cycle, and its prediction of a potential slowdown or contraction phase around 2025, was established based on historical data analysis (since 1954) using strong statistical tools (like spectral analysis, Augmented Dickey-Fuller test with P=0.01, Granger causality test with P=0.03, plus out-of-sample testing) before the specific global economic frictions and events we see today escalated.

This prediction was not merely an abstract statistical result but was based on recurring patterns observed directly in the historical economic data. This data showed a repeated tendency towards slowing economic growth, manufacturing sector weakness (with the ISM index often nearing or falling below 50), and the appearance of other characteristic pressures of the late stages of the cycle.

Based only on recognizing these recurring historical rhythms, the methodology indicated that the 2024-2025 period represents a late and sensitive phase of the current cycle. Today, we observe that recent developments:

Heightened global discussions on trade policies and tariffs.

Notable volatility in commodity prices (like oil recently).

The ISM manufacturing index falling below 50, signaling contraction.

...strikingly align with the economic environment the model anticipated in advance, making the model serve as an analytical "warning" based on recurring patterns in the data.
ORCID :https://orcid.org/0009-0002-9626-7289
(Statistical details, data, and charts are available via the application: https://preview--cycle-insight-analyzer.lovable.app/ )

This alignment raises a question for discussion: Since the systematic analysis of these historical patterns enabled the model to signal potential economic weakness for the current period before the latest global events fully manifested, does this highlight the foresight value that can be gained by integrating statistically validated, medium-term cycle analysis into our economic monitoring and forecasting tools? Can these approaches offer critical foresight that complements short-term analyses? We invite your opinions on the value of integrating these cyclical approaches into economic monitoring and forecasting.

Solving simple poverty on an at-will basis in our at-will employment States through equal protection of laws?

Fri, 28 Mar 2025 20:20:49 +0000

Why not solve simple poverty on an at-will basis in our at-will employment States through the equity and equality of equal protection of the laws?

Anyone not officially living in poverty should be able to pay taxes, afford insurance, and avoid homelessness—this is the goal of addressing official poverty.

The current welfare system is inefficient, expensive, and prone to abuse, fraud, and waste because it tackles complex forms of poverty rather than focusing on simple poverty.

Why not solve simple poverty on an at-will basis in our at-will employment states, leveraging the equal protection clause to ensure fairer employment practices? The necessary legal and physical infrastructure already exists and only requires modernization to meet contemporary economic needs. Unemployment compensation in our at-will employment States that solves for official poverty could be the new 'minimum wage' instead of the current minimum wage that employers are subject to. In my opinion, that should mean that wages would be more responsive to inflationary pressures since anyone who feels they are not making enough, could simply quit on an at-will basis and collect unemployment compensation that solves for official poverty. We should also have no homelessness due to unequal protection of the laws.

Under capitalism, circulating capital is essential. Increased circulation benefits the economy, as seen with the full employment of capital resources. What could be more Efficient than that?

The karfali-var model identified the nine-year cycle using spectral analysis, ADF test, and Granger causality

Thu, 27 Mar 2025 21:09:19 +0000

The Carvali-Farr model developed a robust methodology to identify recurring patterns in economic data over a nine-year period, supporting the hypothesis of a nine-year economic cycle. By applying a range of advanced analyses, such as spectral analysis, the Augmented Dickey-Fuller (ADF) test, and Granger causality testing, we were able to demonstrate that this cycle is not random but follows statistical patterns with clear significance in the historical data.

Spectral analysis showed a peak at the nine-year cycle, supporting the hypothesis that the economic cycle follows a fixed, periodic pattern rather than a random one. The Augmented Dickey-Fuller (ADF) test confirmed that the data contains non-random patterns, with a p-value of 0.01, reinforcing the hypothesis that there is a predictable economic cycle. The Granger causality test revealed a causal effect between the nine-year economic cycle and economic variables such as economic growth and employment, with a p-value of 0.03, indicating that the cycle has a significant impact on economic outcomes.

Out-of-sample tests were crucial in validating the model, where it was trained on data from 1954 to 1998 and successfully predicted the major recession of 2007. The model also forecasted another recessionary cycle in 2025, reflecting the accuracy of its future predictions.

Gross Domestic Product (GDP) growth: There is strong growth in the early years of the cycle (1-3), followed by a slowdown in the middle of the cycle (4-6), with a significant weakening in the later years (7-9), where a recession is expected.
https://preview--cycle-insight-analyzer.lovable.app/pattern-detection
Unemployment rate: It begins to decline in the early years (1-3) with economic recovery, reaches its lowest levels in the middle of the cycle (5-6), but starts to rise as the cycle nears its end (7-9).

However, it should be noted that the model does not handle external economic shocks, such as the COVID-19 pandemic, perfectly, which may lead to short-term forecasting errors. But in the long term, the model remains strong in predicting economic patterns.We look forward to discovering the model from your side

https://orcid.org/0009-0002-9626-7289

Dude, Where's My Nobel Prize?

Sat, 15 Mar 2025 18:59:33 +0000

See title and read https://drive.google.com/file/d/1ieKMaZnt_kFk66_vnpnIPvrdAy7g5Oh4/view

The oliGARCHy

Tue, 11 Mar 2025 16:32:26 +0000

This is not really a question, but rather an invitation to a new type of economics and a new way of economic thinking. Read the papers ( https://drive.google.com/file/d/1ZFYY9VhSF1IVdPsYtqtRcK6lIyNEZW1C/view ), the code ( https://drive.google.com/file/d/1IasW7WyXM8BWOoVq7zeYuWTLsR3uNuvY/view ), the AI analysis I ( https://chat.jaay.fun/obfo29 ) and the AI analysis II ( https://chat.jaay.fun/kgjmfe ) using password 'TheGr8oliGARCH'. I hope this thread turns into a well-rounded discussion of the oliGARCHy.

Commented: Could Numerically-Based Economic Cycles Be the Key to Predicting Future Financial Crises?

Fri, 28 Feb 2025 22:00:40 +0000

Business Cicles and Trade cycles

Fri, 28 Feb 2025 02:36:30 +0000

Hello I'm Ryan Mcconnell. After the papers we published and the settle of full employment in the US and the EU, and solving the OLS problem with the MDMR, I want to contact someone* to write an essay about trade cycles, comercial crisis and of course business cycles. I want to make a review of all the phenomena and all possible solutions. I would like to emphasize about the "Great Moderation" period, but even knowing the system used I can't make a full dissertation. More knowledge is needed.

How do economic cycles contribute to explaining financial crises and predicting future global economic trends?

Wed, 05 Feb 2025 23:17:27 +0000

Understanding the Role of Time Cycles in Shaping the Global Economy is a crucial step toward improving future financial and economic policies. Through this research, I aim to enhance and develop this science for the greater good, encouraging researchers and relevant institutions to collaborate in exploring and analyzing the deeper impact of these cycles. Your valuable contributions could help provide practical solutions to global economic challenges."

"Economic Time Cycles" rely on analyzing the numbers associated with years to determine the beginning and end of each cycle. For example, if we look at the year 1927, we sum its digits (1 + 9 + 2 + 7 = 19) and then reduce the result to a single digit (1 + 9 = 10, and 1 + 0 = 1). Thus, we identify the start of a new cycle with the number "1".

On the other hand, if we take the year 1935 as an example, summing the digits (1 + 9 + 3 + 5 = 18) and reducing it (1 + 8 = 9) indicates the end of the cycle that began in 1927. This process reveals that each economic cycle repeats periodically, and major economic crises tend to follow similar patterns based on these numerical cycles.

"Analyzing Global Economic Patterns" shows how these time cycles repeatedly affect the global economy, where major financial crises occur cyclically based on these patterns. History demonstrates that major financial crises often occur at similar intervals, following mathematical patterns linked to years.

"Future Predictions" indicate that the upcoming cycle in 2026 may mirror the patterns of previous economic transformations, including significant shifts towards sustainable economies, the influence of technology, digital currencies, and changes in financial policies.

"Economic Policies" highlight how these cycles impact economic decisions, including government and financial institutions’ responses during periods of recession and recovery. The study also shows that global financial institutions play a vital role in adapting to these cycles and developing new solutions to economic crises.

"The Role of Technology": The research emphasizes the growing role of technology in shaping financial markets. Innovations such as artificial intelligence and digital currencies could reshape traditional financial systems, changing how transactions are processed and financial data is analyzed.

"Call for Collaboration": This research is a call for active participation in analyzing and improving this science for the public good, so that we can develop economic and financial strategies that contribute to the stability of the global economic system and solve future challenges more effectively.

"For more details on the research, please refer to the full study via the following link:
https://doi.org/10.5281/zenodo.14805665
By understanding these economic time cycles and their patterns, we can pave the way for more effective financial policies and crisis management. If you have any further thoughts or need additional modifications, feel free to ask!

Has the Phillips Curve been proven true for all countries?

Wed, 18 Dec 2024 22:22:27 +0000

I found in one research that there is a direct relation between inflation and unemployment in india in year 1960 to 2020

Answered: Survey: Is Economics a Science?

Mon, 09 Dec 2024 06:55:52 +0000

Answered: What are some dissertation-worthy topics in market design?

Fri, 06 Dec 2024 01:44:29 +0000

Answered: Is the prime directive of economcs to maximize net social benefits?

Fri, 06 Dec 2024 01:34:18 +0000

Economics is Physics?

Mon, 02 Dec 2024 19:49:10 +0000

The Fundamental Law of Economics FLoE: A finitely (not infinitely) converging algorithm addressing simultaneously the dual variables price and quantity represents the mathematical formulation for the Economic Globalization of the Planet. The FLoE has been derived from the Constructal Law and is a complement to this law. Constructal Law: For a finite economic system to persist in time it must evolve with freedom such as to increase access to what flows. The problem with economic systems is that they are not evolving with freedom. There is always a resistance to flow. Therefore, we need a Corollary to the Constructal Law: For a finite economic system to evolve with freedom the resistance to flow must be contained. What is this resistance? Is this resistance significant? Can this resistance be contained? What is this resistance: resistance in economic systems comes from the uninspired involvement of the human factor. Humans are acting on one of the dual variables price or quantity allowing the free variance of the dual variable to create unintended consequences. A businessman is putting his product out on the global market differentiating the prices such as to extract all the value. Market agents are buying this product on low priced markets and are selling it on high priced markets, underselling the producer and taking away some of the producer's revenue; sometimes as much as 50%. This is arbitrage capital and is exploiting price differentials but not creating value. The market arbitrage capital is a nonproductive capital and therefore resistance to flow. Is the resistance to flow significant: economist Nomi Prins estimates global market distortions mainly due to all sorts of market arbitrage to $150 trillions a year. Elon Musk is going after this $150 trillion market. He recently developed a Sofware which is supposed to bring in more revenue than all of his other businesses combined. Can this resistance to flow be contained: Could be contained if we somehow could control both dual variables - price and quantity. Entanglement is the solution. Entanglement is a fundamental property of matter that defines the universe binary and gives rise to time and space. In quantum entangled particles assume instantaneously (zero time, zero space) complementary statuses. You impose a horizontal resonance on one of the particles, the other is assuming instantaneously a vertical resonance. The entangled particles are in equilibrium. My assumption and Niels Bohr assumption in the Correspondence Principle is that entangled dual variables in classical physics behave identical to the entangled particles in quantum. Price and quantity assume complementary statuses only in measurable time and space. Entanglement gives rise to time and space. From zero in quantum to infinity for infinite complex systems. Price goes up, the entangled variable quantity goes down. Quantity goes up, the entangled variable price goes down. We have proven my assumption and Bohr's Correspondence Principle on a market model in geometric programming. Some postulates: 1. Timespace expands directly proportional to the complexity of the system. 2. Timespace expands inversely proportional to advancements in science / technology. 3. Timespace expands to infinity for infinite systems. In an example we reviewed the findings from a study on five medicines commercialized in Europe. We have reported and actual measured parallel trade. Reported parallel trade is always less than actual parallel trade. Reasons could be two - faulty market statistics, more likely intentionally under reporting parallel trade to justify the legality of parallel trade. We resolve the economic equilibrium problem and find parallel trade returned to the producers of the medicines and consumers in percentages and dollar values. $2 billion are returned to the five producers and $800 million to the consumers. This is an important finding. Parallel trade become legal under the claim that it benefits consumers. From our study it turns out that parallel trade is hurting consumers by $800 millions. Has parallel trade been legalized under a false pretense? Conclusions and comments: the finitely converging algorithm we derived from the equilibrium of electrical circuits. The laws that govern the equilibrium of electrical circuits are therefore also governing the economic equilibrium problem. Therefore, ECONIMCS IS PHYSICS. Historically it has been proven that democracy and capitalism are the most effective ways to produce the energy supporting life as we know it. However, capitalism is coming with a problem - polarization of wealth. The buying power is migrating up to the 5% - 10% of rich people who cannot possibly absorb any more the entire aggregate supply and we run into the painful recessions and depressions. The natural function of recessions and depressions is to redistribute wealth restoring the balance of buying power between the rich and the many. Democratic governments are currently attempting to redistribute wealth by fiscal and / or monetary policies with at best questionable results. Redistribution of wealth historically has been also done by violent means - revolutions and Socialism. Socialism is the least effective way to redistribute wealth as it ends up redistributing poverty. The most effective way of redistributing wealth is by the laws of physics. And here comes into play the FLoE. As in the example above the resistance to flow is redistributed to the five producers - $2 billion, and to the consumer $800 million. The balance of buying power is preserved. The economic wave is not cresting anymore and al also not crashing any more - no more recessions and depressions. Economics is an elastic medium that can be studied with the laws of elasticity from physics. ECONOMICS IS PHYSICS.

Why is the ASSA forcing us to cross picket lines in San Francisco?

Wed, 27 Nov 2024 20:10:30 +0000

Several of the hotels where the ASSA meetings are occurring are on strike by their poorly-paid cleaning and maintenance staffs (overwhelmingly women of color). They have asked consumers and organizations to boycott to put pressure on the hotels. The ASSA not only refuses to move the conference, but will not allow allied organizations (IAFFE, URPE, etc.) to hold their sessions in non-boycotted sites or online. Does the AEA/ASSA really want to put economists in a position of crossing picket lines to access our conference and job interviews?

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Dude, Where's My Nobel Prize?

The oliGARCHy

Commented: Could Numerically-Based Economic Cycles Be the Key to Predicting Future Financial Crises?

Business Cicles and Trade cycles

How do economic cycles contribute to explaining financial crises and predicting future global economic trends?

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Economics is Physics?

Why is the ASSA forcing us to cross picket lines in San Francisco?

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