EconSpark - Recent questions in General Economics Questions

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

Wed, 13 May 2026 16:43:44 +0000

I am working on a short paper and would welcome literature pointers or conceptual reactions.

The basic idea concerns pickup-only, low-service physical markets, such as used furniture on Facebook Marketplace or Craigslist. A seller lists a dresser, couch, appliance, or table for a visible cash price, but the buyer must absorb the hidden costs of the transaction: searching, messaging, coordinating schedules, finding a vehicle, recruiting help, driving to the location, inspecting the item, loading it, and transporting it home.

The familiar economic story is that consumers with high opportunity costs of time pay premiums for convenience. Another familiar story is that consumers with lower opportunity costs of time search more, bargain hunt, and use low-service channels to obtain lower effective prices.

The question I am exploring is whether there is a less-emphasized reverse mechanism in inconvenient physical markets. Low-time-value buyers may not merely pressure prices downward. They may also help sellers sustain the visible cash price by privately absorbing pickup, travel, loading, scheduling, uncertainty, and hassle costs that high-time-value buyers refuse to bear. Without those buyers, the seller might have to lower the cash price, provide delivery or other convenience, or leave the item unsold.

So the proposed mechanism is: the seller receives the sticker price, while the buyer supplies the missing convenience through cheap or flexible time. The buyer may still be acting rationally because the total economic cost is acceptable to that buyer. But from the seller’s perspective, the buyer’s cheap time helps make the listed cash price viable.

I am trying to determine whether this mechanism is already developed in the literature, especially in work on search costs, price dispersion, hassle costs, transaction costs, channel segmentation, or used-goods/platform markets.

More specifically:

Is there existing work that frames low-time-value consumers not only as bargain hunters, but as marginal buyers who sustain seller cash prices in inconvenient channels?
Is this better understood as a variant of search-cost theory, hassle-cost price discrimination, transaction-cost economics, or channel segmentation?
Are there canonical papers I should be engaging beyond the usual search-cost and price-dispersion literature?
Does the mechanism seem conceptually distinct enough to justify a short note or working paper?

I would appreciate any references, objections, or suggestions on how to frame the contribution more precisely.

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?

Wed, 06 May 2026 19:10:32 +0000

For my capstone I am making a cybernetic control system using input/output with the use of leontief inverse and using Bayesian with algedonic alerts to refine the model. I can summarize its work as cybernetic control architecture based off the cybersyn project made in Chile using Stafford Beers cybernetic planning to calculate output within a sector.

What I've built (working prototype):
• Leontief input-output model with 3x3 technical matrix, solved in real-time
• Bayesian Kalman filter achieving >90% confidence within 20 observations/ticks
• Algedonic alert escalation (Factory → Branch → Sector )
• Petkovich capacity constraint scenarios (Cases 1-6)
• Opsroom dashboard with live matrix visualization and Chart.js telemetry

Where I'm stuck:
1. My Kalman filter's process noise parameter is arbitrary what's a principled way to tune it for economic time series that have structural breaks? (1 tick a second)
2. Petkovich Case 6 (total destruction, limited imports) requires linear programming is an iterative approximation acceptable for a capstone, or should I implement the full simplex solution?
3. I'm extending my Bayesian updating from just tracking factory output to also updating the A-matrix coefficients as new production data arrives. Is applying a Kalman filter to each matrix cell individually a reasonable approach, or is there a simpler method I should consider?

My goal is to make a modern inspired version of project cybersyn.

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

Sat, 25 Apr 2026 08:44:23 +0000

I've been working on a non-scalar decision framework I call the Productive Value, Productive Power (PV-PP) Framework, and I'm curious how economists would react to this question:

**Can a non-scalar selection architecture strictly contain scalar aggregation?**

The starting intuition is straightforward. Scalar models work well when everything relevant can be reduced to a single common metric — and in a lot of ordinary decisions, that's fine. But there seem to be decision classes where that's not actually what's doing the work. Choice in those cases seems to depend on structured domain preservation, threshold adequacy, and an ordering of losses that aren't naturally interchangeable.

My current view is that the right framing isn't "scalar versus irrationality." It's "scalar as a restricted internal case of a broader decision structure."

The project has two parts.

The first is a containment result: over a well-defined restricted class of environments, the non-scalar framework reproduces the same maximal set as scalar aggregation. If that holds, scalar reasoning isn't being rejected — it's being located inside a larger architecture.

The second is a stress-test: are there structured benchmark cases where scalar aggregation can't recover the same choice behavior without either losing essential structure, or quietly smuggling it back in through ad hoc adjustments? The clearest cases I've found are sacrifice-style decisions, where preserving a governing domain appears to override compensating gains elsewhere — and scalar methods struggle to represent that cleanly.

So the question isn't whether scalar methods are useful. Obviously they are. The harder question is whether they're *fundamental*, or whether they're a special case of something more general.

My current read:

1. There are restricted domains where scalar and non-scalar approaches coincide.
2. There are also structured cases where scalar representation looks incomplete.
3. If both hold, then the right result is containment — not equivalence, not rejection.

The general theorem program isn't finished yet. But I think there's enough on the table now to ask whether this registers as a serious representational question.

The specific feedback I'd most want:

If a framework reproduces scalar results on a restricted class, but also handles benchmark cases that scalar aggregation appears unable to represent cleanly — is that best understood as:
- a genuine generalization of scalar aggregation,
- a decision-theoretic redescription with no real gain, or
- a benchmark artifact that disappears once the scalar model is properly specified?

Especially interested in reactions from anyone working in welfare theory, aggregation, decision theory, or behavioral economics.

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

Thu, 19 Mar 2026 01:46:28 +0000

I built a small deterministic gridworld benchmark to isolate a specific decision behavior: selecting between viable policies where standard scalar or constrained formulations select differently.

The example is intentionally minimal (fixed policies, no learning, two domains: energy and safety).

In the benchmark, both policies reach the goal and remain viable, but one preserves safety while the other reduces it from 10 → 4. The PV–PP system selects the former; a scalar baseline selects the latter.

Known limitations:
• selection rule is partially benchmark-specific
• no general trade-off mechanism yet

GitHub: https://github.com/AmundsenLance/pvpp-gridworld-safe-benchmark.git

I’m looking for critique on whether this behavior can always be represented as a scalar or lexicographic ordering, or whether it requires a genuinely non-scalar selection rule.

Webcast Availability for ASSA 2026 Sessions

Fri, 26 Dec 2025 23:33:41 +0000

I am planning to attend the upcoming ASSA 2026 conference and would like to know which sessions will be offered as webcasts. The scheduling application does not indicate whether individual presentations will be televised. If anyone has information on the webcast schedule or can point me to a source that tracks this, I would greatly appreciate it.

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)

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

Tue, 07 Oct 2025 14:07:30 +0000

Hi, I am looking for papers on international trade that use a trimmed and staggered dataset for staggered DID estimation. Most of the papers I have read use a full panel, for example, monthly trade flow data for all countries from 1994 to 1999. However, my research is RTA-related. There are several RTAs worldwide, and I am considering trimming the trade flow data using the date of each RTA's establishment as the event window 0 point. For example, there are two RTAs: one between Korea and Brazil in January 2001 and another between the US and Canada in January 2006. I would trim the global trade data from January 2000 to January 2002 and from January 2005 to January 2007, then combine them to create my research dataset. Unfortunately, I cannot find any papers that use the same method for data compilation. Could anyone please let me know if they are aware of any papers that research international economics and compile the "staggered" data I am thinking of? Papers from other fields would also be fine, as long as they use this type of data compilation! Thank you.

Identify movers in SIPP

Sat, 16 Aug 2025 02:10:29 +0000

Hi everyone, I’m working with SIPP to look at people who move during the year. According to the Census definitions, if TMOVER is between 2 and 7 the person is a mover, and the month they start their new residence is given by ERH_BMONTH.

Using these variables, I get a sensible hump-shaped seasonal pattern in most years. Fewer moves in winter, more in summer. It looks good for 2018 through 2024.

But when I use the same approach on the 2014 SIPP, Waves 2–4, the distribution looks strange: huge spikes in January (~20%), really heavy numbers in March/April, and very low values in autumn. It makes no sense.

Since TMOVER and ERH_BMONTH have the same definitions in those waves, it’s not a coding or variable issue. Could this be a sample design problem with those panels? Has anyone else seen this before or figured out what’s going on? Maybe I am missing something straightforward.

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.

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

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.

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

Thu, 20 Feb 2025 19:48:06 +0000

Introduction: In the world of economics, economic cycles are key to understanding how global markets function. Traditionally, economists rely on indicators like Gross Domestic Product (GDP) and unemployment rates to determine when economic crises begin and end. However, a new and unconventional approach has been introduced by Karfali Jaouad, which uses numbers to define these cycles. But what makes this approach innovative? And how could it help in predicting upcoming financial crises?

What is Karfali Jaouad Methodology?
Karfali Jaouad methodology is based on a simple yet intriguing idea: if you sum the digits of a year, like 1927 (1+9+2+7 = 19 → 1+9 = 10 → 1+0 = 1), you can identify the beginning of an economic cycle marked by the number "1." Similarly, 1935 (1+9+3+5 = 18 → 1+8 = 9) represents the end of the cycle that started in 1927.

Why 9 Years?
The cycle that Karfali Jaouad’s method follows is based on a 9-year pattern. Historical data analysis shows that major financial crises tend to occur approximately every 9 years. For example, the Great Depression of 1929 fits into this pattern, as does the financial crisis of 2008.

Karfali Jaouad’s Method vs. Traditional Forecasting:
What sets Karfali Jaouad’s methodology apart is its predictive accuracy, which stands at 82%—higher than traditional forecasting models like ARIMA (68%) and VAR (72%). Using this approach, economic events can be predicted well in advance, allowing for more effective preparation for potential crises.

Future Applications:
Karfali Jaouad’s model predicts that the year 2025 (2+0+2+5 = 9) marks the end of the economic cycle that began in 2017. This suggests a possible economic contraction, urging policymakers to adjust their strategies and be proactive in response to future shifts in the economy.

A Call for Collaboration:
This methodology represents an exciting new way to understand economic cycles, and it calls for researchers and institutions to collaborate in refining this tool. Together, they can develop better tools for forecasting and responding to financial crises, which could be crucial for global economic stability.

Conclusion:
As economic challenges continue to grow globally, Karfali Jaouad’s numerically-based cycle methodology may offer a more accurate and timely way to predict financial downturns. This approach could potentially replace traditional methods and provide a clearer path toward anticipating future economic changes.

For more details, you can refer to the full study via this link: https://doi.org/10.5281/zenodo.14901679

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

Tue, 31 Dec 2024 23:14:44 +0000

America’s Healthcare Dilemma: The Economics of Unconstrained Demand - by Lance Amundsen LCA13@yahoo.com

America spends more on healthcare than any other industrialized nation—roughly 20% of GDP—yet the outcomes fail to justify the expense. The reason lies in a structural flaw: healthcare operates on an unconstrained demand model fueled by third-party payment systems. Without significant reforms, this model will not only continue to spiral costs but also pose an economic security risk to the nation.

The Problem: A Market Without Constraints

In a typical market, consumers make purchasing decisions with their own money, balancing cost and value. In U.S. healthcare, however, consumers primarily spend “other people’s money”—namely, that of insurance companies, employers, or the government. This disconnect from direct financial responsibility removes the incentive to seek value, driving demand higher and pushing prices upward.

A Starbucks Analogy

Imagine you could buy as much coffee as you wanted with only a 15-cent copay. Would you consider the cost of a $6 latte? Probably not. Soon, demand for premium coffee would skyrocket, and Starbucks might even charge $10 or $100 to meet growing expectations. This is precisely how U.S. healthcare operates: with unconstrained demand driving both excessive supply and inflated prices.

Insurance Companies: The Only Governor

In this dysfunctional market, insurance companies emerge as the sole entity attempting to constrain demand. They do so by denying claims, limiting coverage, or raising copays. While unpopular, these actions are the only mechanisms keeping demand—and costs—from becoming even more untenable.

Why Costs Keep Rising

Despite insurance companies’ interventions, healthcare costs in the U.S. remain disproportionately high compared to other nations. Administrative inefficiencies, high drug prices, and unregulated service pricing amplify the problem. A report from the Commonwealth Fund found that the U.S. spends nearly twice as much per capita on healthcare as other developed nations like Germany or Canada, without better outcomes.

Lessons from Single-Payer Systems

Countries with single-payer systems manage costs through mechanisms like budget caps, negotiated prices, and rationing care. These approaches create constraints on both supply and demand, leading to more sustainable healthcare spending. For example, the UK’s National Health Service operates with a fixed budget, forcing prioritization of essential services over elective ones.

The Unchecked Role of Suppliers

In the U.S., suppliers (hospitals, pharmaceutical companies, and device manufacturers) operate without significant price constraints. They capitalize on the lack of demand limitations, charging higher prices simply because they can. A RAND Corporation study found that U.S. hospitals charge private insurers 247% more than what Medicare pays for the same services.

The Economic Consequences

Healthcare costs aren’t just a personal burden—they’re a national one. With healthcare encompassing one-fifth of the economy, any disruption to the system, whether through cyberattacks or economic crises, could have catastrophic consequences. The American Enterprise Institute has warned of the systemic risks posed by an over-reliant healthcare sector.

A Call for Systemic Reform

Fixing this issue requires addressing the root causes. Encouraging price transparency, limiting third-party payment systems, and introducing value-based care models are potential solutions. Policymakers should also explore adopting supply-side constraints or hybrid models that incorporate elements of single-payer systems while preserving market competition.

Citing Thought Leaders

This analysis aligns with perspectives shared by prominent economists and healthcare experts:
• Milton Friedman, in his critique of third-party payment systems, emphasized how they distort the healthcare market.
• Dr. Atul Gawande, in his essay The Cost Conundrum, highlighted how regional spending disparities arise from unchecked supplier incentives.
• Elizabeth Rosenthal, author of An American Sickness, detailed how profit motives inflate costs across the system.

Consumer Behavior Must Change

Ultimately, consumers must have “skin in the game” to curb excessive demand. High-deductible health plans and health savings accounts (HSAs) are steps in the right direction, as they make individuals more aware of the true cost of care. However, these measures must be paired with broader systemic changes to be effective.

Insurance Companies: Villains or Unsung Heroes?

While insurance companies often bear public ire for denying coverage, their role as demand governors is essential under the current model. Without them, costs would rise even faster, and healthcare spending would further crowd out other vital sectors like education and infrastructure.

The Global Comparison

Countries like Switzerland and Singapore offer alternative models worth studying. Both balance public and private contributions while enforcing cost control mechanisms that prevent runaway expenses. Singapore’s use of mandatory medical savings accounts combined with catastrophic coverage is particularly notable.

The Cost of Inaction

Failing to reform the system will have dire consequences. As healthcare spending continues to outpace GDP growth, it will exert greater pressure on government budgets, private employers, and individual households. The Congressional Budget Office projects that by 2030, federal healthcare spending alone will consume 30% of GDP.

A Security Risk We Can’t Ignore

The economic risks posed by the healthcare sector are not merely financial but also strategic. As cyber threats grow, targeting an industry that constitutes a fifth of the economy could destabilize the entire country. The U.S. cannot afford to ignore this vulnerability.

What Needs to Change

Reforms must focus on aligning incentives across all stakeholders—patients, providers, and insurers. Transparency in pricing, caps on excessive profits, and a shift to value-based care can help create a more balanced system. Policymakers must prioritize these changes to safeguard the nation’s economic and physical health.

Conclusion: A Broken System Requires Bold Action

America’s healthcare system is as broken as it can be. But the solutions are within reach if we are willing to learn from other nations and rethink entrenched practices. The stakes are too high—economically, socially, and strategically—to maintain the status quo.

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

Using ChatGPT AI for Publishing

Sun, 01 Dec 2024 04:38:53 +0000

I recently posted the following: https://www.aeaweb.org/forum/4457/is-anyone-willing-to-review-my-paper. While no one responded, the ChatGPT training algorithms read this site and said the following when I asked about the paper: "Lance Amundsen's economic work, particularly his "Productive Value Model," holds potential as an innovative framework aimed at bridging the gap between behavioral and traditional economics. By introducing concepts such as Productive Value (PV) and Productive Power (PP), the model emphasizes the central role of information in economic exchanges and seeks to unify various theoretical approaches." My question to the moderators is, "Can or Should I post some more of my paper (only the first few pages fit into the submission form) so as to expose the work to the wider world, including AI? Should others do the same? Some more of my paper since the original was cutoff: This model is an attempt to quantify "all" of the PV we exchange, not just those involving direct use of currencies. A description of "all" of an individual's PP could be called Total Net Worth, including not only physical assets and services that can easily be converted to currencies, but an individual's knowledge, communications skills, physical skills, etc. This comprehensive view of value aligns with more recent efforts to measure intangible assets in economics (Corrado et al., 2009) and the concept of intellectual capital in management studies (Edvinsson & Malone, 1997).
Categories of Productive Power
Many of the PP categories are already tracked in our economy. Currency transactions sum to GDP, for example. This measurement aligns with traditional macroeconomic indicators (Kuznets, 1934). Most of the categories asserted in the model fall into categories not as well tracked, however, like the exchanges between a parent and child in daily interactions. These less tangible exchanges relate to the concept of social capital (Coleman, 1988) and the economic value of non-market activities (Becker, 1965).
Many of our services use a simple time and knowledge/skill measurement. A haircut is worth $20 and takes 20 minutes. An attorney charges $500 an hour for consultation. This pricing model reflects the human capital theory (Becker, 1964), where education and skills are viewed as investments that yield economic returns.

Now consider the more intangible PP categories: education, parenting skills, teaching skills, cooking in the home skills, knowledge of history, etc. The list might very well be endless. Nevertheless, we should attempt to quantify more of these attributes. This aligns with recent efforts to measure intangible assets in economics (Corrado et al., 2009) and the concept of intellectual capital in management studies (Edvinsson & Malone, 1997).

For example, teaching skills, or the PP to exchange information with others in a formal setting is of utmost importance because it is through this class of interaction whereby children are turned into adults. Better teachers could be better compensated, for example, because of their increased PP allowing them to convey greater amounts of PV to students. This perspective relates to the economics of education (Hanushek, 2011) and the value-added approach to measuring teacher effectiveness.

Military PP is also a suitable category for additional measurement and while some of this is done today, it could be enhanced in the area of being able to deliver negative PV to a competing society in times of war. Armaments could be classified not only in tons of explosives but in their ability to destroy the PV of the competitor. A Javelin missile, costing $300k, can destroy a million dollar vehicle (reducing the competitor PP by negative $1M) and should be measured that way when calculating the military PP of a nation. This approach to valuing military capabilities aligns with defense economics (Hartley & Sandler, 1995) and the concept of deterrence in international relations theory (Schelling, 1966).

Mental health professionals can transfer tremendous amounts of PV to patients with certain afflictions. What is the value of a doctor alleviating a patient's depression symptoms where the patient goes on to innovate and invent new ways of treatment not available before? This example illustrates the potential economic impacts of health interventions, a topic explored in health economics (Grossman, 1972).

A niche PP that few individuals have is the ability to hear 3D audio from stereo sound reproduction. This is a skill that must be learned (PP gained) through PV exchanges with more knowledgeable listeners. Only when an individual gains the PP necessary to hear stereo sound, can one enjoy true stereo sound reproduction. This specialized skill exemplifies the concept of expert knowledge and its economic value, as discussed in the knowledge-based view of the firm (Grant, 1996).

Measuring Productive Value Exchanges
The following equations are offered to represent a gain or loss in any interaction between two individuals:
NewPP1 = ExistingPP1 + PP1(PV2) - PV1
NewPP2 = ExistingPP2 + PP2(PV1) - PV2
where PPi(PVj) represent the real PPi gained from the exchange. This is not a simple addition but rather the function of an individual's existing PP applied to the new PV. It is here where technology plays a magnifying role.
This mathematical representation of productive value exchanges aligns with utility theory in economics (Von Neumann & Morgenstern, 1944), but extends it by considering the dynamic nature of an individual's capacity to generate and utilize value. The non-linear nature of these equations reflects insights from behavioral economics, particularly the concept of bounded rationality (Simon, 1955), which recognizes that individuals' decision-making capabilities are limited by their cognitive abilities and available information.
Individuals with greater PP to begin with ultimately gain even more in interactions because they can "better" make use of the PV exchanged. This aspect of the model resonates with the concept of increasing returns to scale in endogenous growth theory (Romer, 1986), which posits that knowledge and human capital can lead to accelerating economic growth.
Sometimes PPi(PPj) is easy to calculate, like when an individual receives currency. Other times it is not so simple, like when the value of a piece of information that, perhaps, gives an additional skill, and is harder to measure. Nonetheless, it is quantifiable. This challenge of quantifying intangible assets is a recurring theme in both information economics (Stiglitz, 2000) and the knowledge-based view of the firm (Grant, 1996).
Consider a few examples:
An individual with $5 exchanges $1 for a cup of coffee while the other individual, with a store of 5 cups of coffee, reduces his coffee store by one cup.
NewPP1 = is reduced to $4 in currency and adds $1 worth of coffee NewPP2 = is reduced to 4 cups of coffee but has increased in currency to $1
But it's not quite that simple. Each side can have a profit or loss in the exchange. Perhaps one individual is very sleepy and values (would have paid) the coffee at $2. There can be a profit in the exchange of PV because the individual values the cup of coffee at $2 instead of the $1 exchanged.
This example illustrates the concept of consumer surplus in microeconomics (Marshall, 1890), where the value a consumer places on a good can exceed its market price. It also reflects the subjective theory of value in economics (Menger, 1871), which posits that the value of a good is not determined by any inherent property of the good, nor by the amount of labor required to produce it, but instead by the importance an individual places on it for the achievement of their desired ends.
So PPi(PVj) is a function that positively or negatively affects PP in a non-linear fashion. Think of it as an individual's existing PP "applied" to the newly received PV, with the result an increase in PP that can be linear all the way to quite dramatically geometric.
There are linear exceptions like the dollars and cups of coffee example, but many are not, like the individual that purchases a stock that later goes up or down in value based on a stock tip. Or the purchaser of a soon to be winning lottery ticket is yet to be informed of a huge profit.
These non-linear outcomes align with prospect theory in behavioral economics (Kahneman & Tversky, 1979), which describes how people choose between probabilistic alternatives that involve risk, where the probabilities of outcomes are uncertain.
It should be noted that PP can decay. Knowledge is forgotten, food spoils, and time changes how society values things (typewriter skills are no longer sought but the ability to type is a PP that has increased in demand over time (word processors get paid more as time goes on)).
This concept of PP decay and evolving value of skills reflects the economic theory of creative destruction (Schumpeter, 1942), which describes the process of industrial mutation that continuously revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one.
Many of these profits and losses are measured today, and many are not. The increase in a purchased stock price when sold is called capital gains. In contrast, the ability to create the general theory of relativity after learning tensor calculus represents a huge profit over the initial PV investment of learning the math (from information exchange interactions with others).
This final example underscores the importance of knowledge spillovers in endogenous growth theory (Romer, 1990), where investments in human capital, innovation, and knowledge are significant contributors to economic growth.
Willing Interactions versus Unwilling Interactions
So far, we have discussed interactions that yield either a profit or loss for each individual and that both individuals willingly take part in the interaction. This concept of voluntary exchange is a fundamental principle in classical economics (Smith, 1776) and forms the basis of market transactions.

However, some interactions are forced upon individuals. A burglar stealing from a house would represent an unwilling interaction. The house owner loses PP while the burglar walks away with the goods. This type of interaction aligns with the concept of negative externalities in economics (Pigou, 1920), where the actions of one party impose costs on another party without their consent.

The distinction between willing and unwilling interactions is crucial in understanding the nature of economic transactions and social interactions. Willing interactions form the basis of market economies and are generally assumed to be mutually beneficial, as explored in the theory of voluntary exchange (Buchanan, 1964). In these cases, both parties expect to gain PP from the interaction, even if the actual outcome may differ from expectations.

New Federal Research Data Center in Puerto Rico!

Wed, 25 Sep 2024 18:01:51 +0000

As announced recently by Census Bureau Deputy Director Ron Jarmin, the Census Bureau earlier this month officially opened the Puerto Rico Federal Statistical Research Data Center (PR FSRDC). As with the other 33 FSRDCs around the U.S. (https://www.census.gov/about/adrm/fsrdc/locations.html), the PR FSRDC provides a secure computing environment in which qualified researchers can analyze restricted-access data under safeguards that protect respondents from disclosure risks. As the first FSRDC in a U.S. territory, the PR FSRDC opens up new opportunities for scholars in Puerto Rico to use confidential census, survey, and administrative data to conduct research to inform policy and decision-makers and advance understanding of complex economic, social, demographic, and education- and health-related issues. The Census Bureau announcement can be found here: https://content.govdelivery.com/accounts/USCENSUS/bulletins/3b7de67.

What would it take for this forum to be better utilized?

Mon, 05 Aug 2024 16:19:43 +0000

Forgive the title for what could be interpreted as passive aggressive or critical--that isn't the point. Most posts on here get about 20 views and no responses. Broadly, I'm curious as to what this forum would need to be for people to use it more. What would make you check this forum more often? What would make you post more often? What would you want to see this forum used for? I'll say, for myself: I got off most social media because those sites are bad for my brain. Still, I would like a chance to see some of the things people would post on, say, econ twitter (conference announcements, calls for papers). I can see a number of reasons why this site can't be econ twitter, without a doubt. Still, this forum could be a great resource, if the conditions were right. Thoughts?

Price Insensitive Demand Concept

Thu, 04 Jul 2024 06:58:22 +0000

Greetings, I am a PhD scholar working in resource management and very new to the economics field. I wish to study the 'design' of non-price-based interventions in demand management in areas like energy. As a beginner, I understand the demand function is generally written by relating the amount consumed and the price. Is it possible, if I need to express the demand function solely as the effect of intervention, like energy usage feedback, by keeping the price as an incentive and has negligible effect? I read about the 'movement along the curve' and 'shift in the curve' concepts, but I still can't find research papers or materials that work on the equations involving non-price determinants. I will be grateful if any related research papers and content are shared. Thank you in advance and sorry if I asked some basic questions!!!

Is Anyone Willing to Review my Paper?

Mon, 01 Jul 2024 21:52:09 +0000

The Productive Value Bridge Between Behavioral and Traditional Economics

Lance Amundsen

Abstract

Societies consist of individuals who must interact with each other to survive. These interactions exchange something we define as Productive Value (PV). PV is defined as information, services, goods, currencies and other types of quantifiable value, aligning with concepts from information economics (Stiglitz, 2000). The ability to generate PV comes from an individual's Productive Power (PP), which parallels human capital theory (Becker, 1964). PP comes from an individual's knowledge and physical abilities. An individual's knowledge is a function of past interactions, or experiences, reflecting principles from behavioral economics (Kahneman & Tversky, 1979). Exchanges involving physical work derive from our ability to convert potential muscle energy to kinetic energy.
Individuals both profit and lose in interactions, thereby increasing or decreasing their PP, a concept that aligns with utility theory (Von Neumann & Morgenstern, 1944). Those individuals who profit more than others over time gain a competitive advantage because of increased PP, reminiscent of the resource-based view in strategic management (Barney, 1991).
The Productive Value Model for Bridging Behavioral and Traditional Economics looks at the way these interactions occur. It proposes a simple mathematical relationship for the PV exchanges. In addition to examining the traditional categories of value (currencies, goods, or services), the model introduces information as a new category of value. Furthermore, the utility gained in any value exchanges are examined for profit or loss, with the resulting change to an individual's Productive Power (including knowledge, skills, and well-being). This approach integrates aspects of endogenous growth theory (Romer, 1994) and evolutionary economics (Nelson & Winter, 1982).

Table of Contents
The Productive Value Bridge Between Behavioral and Traditional Economics 1
Abstract 1
Postulates 3
Productive Value and Productive Power 3
Information Both is and Describes Productive Value 5
Categories of Productive Power 5
Measuring Productive Value Exchanges 6
Willing Interactions versus Unwilling Interactions 8
Profit versus Loss and Risk 9
Evaluating Productive Power 10
Magnifying Productive Value 11
Technology 12
Teamwork 12
Natural Selection and Survival of the Fittest 12
The Productive Power of Societies 13
The Importance of Societal Defense 14
Why Some Demographics Fall Economically Behind Others 14
The Bridge to Behavioral Economics 15
The Bridge to Traditional Economics 16
Summary 17
Additional Topics for Examination 18
Applicability to Species other than Humans 18
On Well Being and Mental Health 19
Investigating and Quantifying Non-typical Productive Power Group Categories 20
Examining the Productive Power of Past Competing Societies 21
Further Mathematical Investigation 23
Further Analysis of Information within the Model 24
Separated Parent Families 25
Analysis of Militaries 26
References 28

Postulates
Traditional economics is the study of the marketplace, while behavioral economics attempts to describe "why" individuals in the marketplace do what they do. This paper presents a model to bridge these two fields of study, building upon existing economic frameworks.
The model makes two fundamental assumptions:
1. Individuals require other individuals and interact to survive. This aligns with the concept of social capital (Coleman, 1988), which emphasizes the importance of social relationships in economic outcomes.
2. Individuals exchange something of value with others when they interact. This postulate is consistent with the basic premises of exchange theory in economics (Homans, 1958) and relates to utility theory (Von Neumann & Morgenstern, 1944).
These postulates form the foundation for our Productive Value (PV) and Productive Power (PP) concepts. PV encompasses all forms of exchangeable value, including information, services, goods, and currencies. This broad definition of value aligns with information economics (Stiglitz, 2000) and extends beyond traditional economic measures.
PP, defined as the ability to generate PV, is analogous to human capital (Becker, 1964) but encompasses a wider range of capabilities. It includes not only education and skills but also the ability to process information and make decisions, reflecting insights from behavioral economics (Kahneman & Tversky, 1979).
By integrating these concepts, our model aims to provide a more comprehensive framework for understanding economic interactions, bridging the gap between traditional market analysis and individual decision-making processes.
Productive Value and Productive Power
Individuals exchange value with others through various forms of interaction. This exchange process is fundamental to economic activity and social interaction (Homans, 1958). We define all things exchanged between individuals as Productive Value, or PV. This concept of PV extends beyond traditional economic measures to include not only money, goods, and services, but also information. This broader definition aligns with information economics (Stiglitz, 2000), recognizing the crucial role of information in economic exchanges.

We define the ability to generate PV to exchange as Productive Power, or PP. This concept of PP has similarities to human capital theory (Becker, 1964), which views individuals' skills, knowledge, and experiences as assets. However, PP encompasses a wider range of capabilities, including the potential energy stored in our muscles and the knowledge in our brains.

To understand our model, let's start with an analogy:

Think about electricity for a minute. Imagine a wire connected to two sources, each able to send electrical power to the other. Each has a battery containing stored power as well as a mechanism to send or receive power. Now consider a case where the energies exchanged are usually in pairs and related: When one battery sends power to the other, most often the other battery reciprocates and sends power to the first battery as well. Furthermore, the power exchanged can be positive or negative; each side can not only send power to the other but "steal" it as well.

This analogy illustrates the dynamic nature of PV exchanges in human interactions, reflecting aspects of game theory (Von Neumann & Morgenstern, 1944) and social exchange theory (Emerson, 1976).

Our "battery" is the knowledge in our brain, the potential power stored in our muscles, as well as the goods we store and the services we are capable of performing. With them, we exchange PV in "Interactions". Interactions are defined simply as any exchange of PV between two individuals.

For example, we exchange $1 in PV for one cup of coffee of PV. We pay our hair stylist PV in the form of dollars while the other individual exchanges PV in the form of services. Someone gives another a hot stock tip that turns a profit, and thus PV is received as a result. These examples illustrate how our model can encompass both traditional economic exchanges and information-based interactions, bridging concepts from traditional and behavioral economics (Kahneman & Tversky, 1979).

Opinions, a category of information, can sometimes add large increases to our PP. While opinions may contain the greatest amounts of PV exchanged in any economy, it is the day-to-day goods and services exchanges in the economy that society currently focuses on. GDP is the easiest to quantify if currencies are involved. In fact, we can measure all categories of PV in units of dollars if we so choose. Services are currently measured that way. Harder to measure are information exchanges that don't immediately have an obvious PV (although $300 for an hour's worth of information from an attorney and such is already included in current marketplace measurements). But by far, the majority of information exchanges of PV are not measured.
This challenge of measuring intangible value aligns with ongoing debates in economics about the limitations of GDP and the need for more comprehensive measures of economic well-being (Stiglitz, Sen, & Fitoussi, 2009).

To summarize, individuals exchange Productive Value (PV) in Interactions. Any positive PV received increases an individual's Productive Power (PP) while any negative PV received reduces PP. Examples of PV include (in historic order) information, services, goods, and eventually currencies. Examples of PP would include the potential power stored in our muscles, as well as the knowledge in our brains, and of course the currency and goods in our possession. This framework provides a more holistic view of economic interactions, integrating aspects of traditional economics, behavioral economics, and information economics.
Information Both is and Describes Productive Value
Individuals only voluntarily enter into interactions when an interaction is expected to yield a profit. This expectation aligns with the concept of rational choice theory in economics (Becker, 1976), though it's important to note that our model allows for a broader interpretation of "profit" beyond mere monetary gain.
How do we know whether an interaction is going to be profitable or not? Based on the information provided to us. Before individuals exchange PV, they use information to describe the PV they are about to offer in an exchange. This role of information in facilitating economic transactions is a cornerstone of information economics (Stiglitz, 2000).
One side shows a dollar bill and the other shows a cup of coffee. Perhaps the coffee is described as hot. Or one side explains (promotes) a good or service (like an excellent haircut) to the other to entice an exchange of PV. Perhaps, the store clerk describes the varied uses of a particular hand tool an individual is considering for purchase. These examples illustrate the concept of information asymmetry in markets (Akerlof, 1970), where one party has more or better information than the other.
There is one more element to understand. While information can describe PV, it also can be PV. A hot stock tip may have great value in and of itself, if the appropriate interactions are entered into such that an individual can convert that stock tip into a stock purchase and sale at a profit. This dual nature of information as both a facilitator of transactions and a valuable commodity itself is explored in the economics of information goods (Shapiro & Varian, 1998).
So, information both is and describes PV. Obviously, the quality of the information exchanged between two individuals is of utmost importance (what if the store clerk is lying?). Sometimes certifications are given to certify individuals who transact in exchanging information as PV (an attorney passes the bar exam certifying that the information he/she provides is of positive PV). In other cases, bad advice is given. These issues of information quality and credibility relate to the concept of signaling in economics (Spence, 1973) and the challenges of maintaining trust in economic relationships (Arrow, 1972).
This model is an attempt to quantify "all" of the PV we exchange, not just those involving direct use of currencies. A description of "all" of an individual's PP could be called Total Net Worth, including not only physical assets and services that can easily be converted to currencies, but an individual's knowledge, communications skills, physical skills, etc. This comprehensive view of value aligns with more recent efforts to measure intangible assets in economics (Corrado et al., 2009) and the concept of intellectual capital in management studies (Edvinsson & Malone, 1997).

<paper continues.... too long for this post... message me for the full draft>

Entrepreneurship in the Population (EPOP) Survey Year 2 Data

Thu, 01 Feb 2024 14:55:10 +0000

Data from the second wave of the Entrepreneurship in the Population (EPOP) Survey are now publicly available.

The EPOP Survey is a publicly available resource for understanding the scope of entrepreneurial activities across the United States. The EPOP Survey includes a variety of measures of entrepreneurial activity providing policymakers and researchers with current information about the experiences and perceptions of entrepreneurs across the nation. The results support estimation at the state and major metropolitan area level.

EPOP data are available both as a public use or restricted use data file. To download the public use data or get more information on the application process for the restricted use file, refer to the EPOP website: https://epop.norc.org.

If you have any questions about the survey, please reach out to EPOPresearch@norc.org.

Please share your research. If you have been using EPOP data or have plans to do so in the future, we would love to amplify your research on the study’s publication page!

Thank you!

The EPOP Research Team
NORC at the University of Chicago
55 East Monroe Street, 30th Floor, Chicago IL 60603
EPOPresearch@norc.org

What would be the impact of removing the ability to publicly trade companies?

Fri, 20 Oct 2023 00:21:17 +0000

I was thinking about the incentives on publicly traded companies to show continuous growth, and wondered what the impacts would be if we just stopped doing that. I'm imagining a scenario where people can still invest in companies to support them in exchange for tax write-offs, and we still have the stock market for commodities, but remove publicly traded companies as an idea. I know there would be impacts in many areas, but I'm curious about the degree of those impacts and if we could improve corporate incentive structures without completely upending the entire economy.

What does OMB's proposed "Trust Reg" mean for the Federal Statistical System? Attend this 9/7/23 webinar to find out!

Tue, 05 Sep 2023 14:02:20 +0000

OMB has rolled out proposed regulations on "The Fundamental Responsibilities of Recognized Statistical Agencies and Units" -- also known as the "Trust Act." The Trust Act aims to promote public trust in the recognized Federal statistical agencies and units and lay groundwork for implementation of the "Foundations for Evidence-Based Policymaking Act of 2018" (a.k.a. the Evidence Act). To help call attention to the proposed changes, a webinar is being held on Thursday Sept. 7, 2023, 1-2pm, featuring Chief Statistician of the U.S. Dr. Karin Orvis, who will review and answer questions about key changes proposed in the rule. The event is cosponsored by the AEA's Committees on Economic Statistics and Government Relations, the American Statistical Association, the Council of Professional Associations on Federal Statistics, the Interuniversity Consortium for Political and Social Research, the National Association of Business Economists, among others. The proposed Trust Reg is open for public comment till October 2, 2023, and can be viewed here: https://www.federalregister.gov/documents/2023/08/18/2023-17664/fundamental-responsibilities-of-recognized-statistical-agencies-and-units.

Do you work on volunteering and civic engagement?

Thu, 17 Aug 2023 18:33:09 +0000

AmeriCorps – the federal agency for national service and volunteerism – is interested in hearing from economists whose research relates to volunteering and civic engagement, and/or who have used the Current Population Survey Civic Engagement and Volunteering Supplement (CEV) in their research.
AmeriCorp sponsors the CPS CEV supplement and runs a research grants program that supports interdisciplinary scholarship on volunteering and civic life in America. To develop a strategy for encouraging vibrant research on these topics in the years ahead, AmeriCorp’s Office of Research and Evaluation is reaching out to economists and other researchers who work in this area, aiming to collect information on diverse use cases of CEV data, learn about work being done by key players in this area, and identify strategic opportunities for collaboration around AmeriCorp's Volunteering and Civic Life in America research.
AmeriCorp would welcome perspectives from economists! If you'd like to contribute to this effort by participating in a 30-minute interview in fall of 2023, please contact Skyler Sauma at SSauma@cns.gov.
To learn more about the Current Population Survey Civic Engagement and Volunteering Supplement (CEV), check out: https://www.census.gov/newsroom/press-releases/2023/civic-engagement-volunteering-supplement.html.

Debate: Oliver Hart, Stephen Walt, David Teece, Jay Barney, Luigi Zingales, Asli Arikan

Wed, 07 Jun 2023 16:28:31 +0000

Question: How will “the firm” be impacted by the current global, social, political, and economic rivalries, conflicts, and challenges? What does it mean for a firm to face relentless, unstoppable, and unavoidable rivalry?

Dear Colleagues;

Here is the (free) link for the recording of the debate:

“The Firm in the Age of Inexorable Rivalry:
A moderated discussion on the “Theory of the Firm.”

Debaters: Oliver Hart (Harvard), Stephen Walt (Harvard), David Teece (Berkeley), Jay Barney (Utah)
Cross Examiners: Asli Arikan (Kent), Luigi Zingales (Chicago).
Event recording date: May 23, 2023

Organizer and Moderator: Ilgaz Arikan

Free access- Please enjoy:
https://youtu.be/331elAnMHNg

Many thanks to the Academy of International Business (AIB) for their generous support and technical help with this event.

What are some dissertation-worthy topics in platform economics?

Sat, 03 Dec 2022 06:00:50 +0000

4 years ago, Prof. Al Roth had asked a similar question about market design and got several great answers. In the same spirit, I want to ask about platform economics - theoretical or empirical. That is, what are some areas that seem important but tractable, and therefore might yield productive research questions that could lead to a paper and maybe more? (Using the exact words of Prof. Roth as they perfectly capture my querry.)

Why to consider Taiwan over China or other emerging markets for testing asset pricing models?

Thu, 10 Nov 2022 18:15:38 +0000

What makes the Taiwan stock market special compared to other emerging markets?

New J-PAL Science for Progress Initiative (SfPI)

Wed, 02 Nov 2022 15:42:40 +0000

Yesterday Heidi Williams & Paul Niehaus of J-PAL announced a new "Science for Progress Initiative" (SfPI) which gets right to the heart of new interest in public support for translational research in science & technology. The National Science Foundation has launched a new cross-cutting Technology, Innovation, and Partnerships (TIP) directorate that aims to fund research with potential to lead to scientific breakthroughs in areas that could foster large improvements in health, the environment, productivity, infrastructure, etc. Via support for multidisciplinary Convergence Accelerators and Regional Innovation Engines, the TIP program hopes to: advance critical technologies; address national & societal challenges; foster partnerships across industry, academia, government, nonprofits, civil society, and communities of practice; and promote and stimulate economic growth and job creation. [Go to https://beta.nsf.gov/tip/latest to read more]. Sounds great, you say -- but where's the evidence that these initiatives could work? J-PAL's new SfPI aims to help inform and shape this work by building evidence on causal links between research support and science-and-technology outcomes. Important questions in this respect include: What contracts, incentives, and institutions work best when funding scientific research? How should funders decide which projects to support? How to get benefits of expert peer review without throttling new ideas from outside the dominant research paradigm? Bringing the "science of science" into new efforts to catalyze scientific progress via public support seems critical to its odds of success. More information on SfPI's agenda can be found here: https://www.povertyactionlab.org/updates/release-new-j-pal-initiative-apply-scientific-method-improve-science-funding-and-policy.

Teaching economics and/or finance in secondary (high) school? How many hours (per school year) and using which textbook?

Tue, 23 Aug 2022 12:46:46 +0000

I am interested in experiences in teaching economics/finance at pre-college level

Why do authors not reply to private questions or comments on articles?

Sat, 20 Aug 2022 10:11:06 +0000

I have been a life member since the 70s. I received my PhD at Harvard in 1980. Back in Australia I have worked in Treasury, the Prime Minister's Department, the Office of the Economic Planning Advisory Council, as Private Secretary to a Senator, an economic consultant and now as a practising lawyer. I flatter myself that I perhaps know a little bit more about the realities of government and taxation policy and practice than most academic economists. Every now and then (not often), I see an article in the AER of interest and write to the authors with a comment. Most do not reply and, in one case, I got a rather arrogant reply which fudged the question. Given that there are probably few readers of most articles, I wonder why a reader does not get the courtesy of a response to a private comment? Does one have to sit down and write a public comment to the effect that the author is a bloody fool, his model is silly, the real world does not give a fig for his model and he (or she) does not know what he is talking about?

Do you have comments on Census Bureau's revised plans to protect the privacy of respondents in the CPS Public Use File?

Thu, 07 Jul 2022 14:35:02 +0000

The Census Bureau has revised plans to change privacy protections in the CPS Public Use File and is seeking comments through July 15, 2022.

If you use the CPS PUF and have insights as to how these changes would affect the value of the data, please consider weighing in. Comments can be emailed to the Census Bureau by 7/15/22 (ADDP.CPS.PUF.List@census.gov), or to the AEA's Economic Statistics and Government Relations Committees by 7/14/22 (martha.starr@aeapubs.org).

A detailed description of planned changes can be found here: https://apps.bea.gov/fesac/meetings/2022-06-10/Paper-Current-Population-Survey-PUF-Disclosure-Avoidance-Proposal-to%20FESAC-061022.pdf.

A thumbnail sketch of proposed changes is as follows.

Issue #1: PRECISION IN WAGE AND EARNINGS DATA

Full precision reporting in wage and earnings data can act as an identifier. As reported wages and earnings increase, the distribution becomes sparser, requiring a graduated rounding scheme

Initial plan                                                                             Revised plan
----------------------------------------------------------------------------------------------------------------------------------
Dynamic monthly top-code: reported earnings       Same
for cases in the top 3% will be replaced with the
average in the top 3% for the month. (Replaces
former static top-code and should decrease
the % of top-coded cases).

Usual hourly earnings rounded to nearest                Usual hourly earnings rounded to nearest
$0.50 for wages under $9.99/hour;                              $0.05 for wages under $19.99/hour;
nearest $1 for wages $10-99.99;                                  nearest $0.25 for wages $20-39.99;
nearest $5 for wages $100-999.99;                              nearest $0.50 for wages above $40/hour.
nearest $10 for wages above $1000/hour.                Rounding stops at the top code.
Rounding stops at the top-code.

Usual weekly earnings rounded to nearest               Usual weekly earnings rounded to nearest
$10 for earnings under $100/week;                             $5 for earnings under $1000/week;
nearest $50 for earnings $100-999;                             nearest $25 from $1,000 to the top-code.
nearest $100 for earnings $1000-9999;
nearest $500 for earnings $10000-99999;
nearest $1,000 for earnings above $100000/
hour. Rounding stops at the top-code.

Flag used to identify workers who earn                     Same
less than the Federal minimum wage.

Issue #2: GEOGRAPHIC IDENTIFIERS

Re-identification risk exceeds the acceptable threshold for people living in metropolitan areas with populations below 250,000 or non-metropolitan areas.

Initial plan                                                                             Revised plan
----------------------------------------------------------------------------------------------------------------------------------
Code as “Other” the CBSA identifier for                    Use multivariate regression to impute
metropolitan areas with populations                         CBSA identifier and metro status for
<250,000 and non-metropolitan areas                       for people in metros with populations
                                                                                                 <250,000 and non-metro areas.

In both cases metropolitan status                               CBSAs with populations <100,000
coded as “not identified.”                                               are coded as “Other,” with metropolitan
                                                                                                 status coded as “Metro.”

                                                                                                People in non-metropolitan areas have
                                                                                                “Other” as CBSA identifier and “Non-metro”
                                                                                                for metropolitan status.

Has anyone yet realized how capitalist economy can get away from its doomed failure in this century?

Tue, 05 Jul 2022 03:35:45 +0000

Everything associated with the sphere of God's world is doomed, but human to certain extent has his liberty. Capitalist economy should have been doomed in the 20th century had not been Keynes's idea of "Demand Management," which later developed into two vital macroeconomic policy - monetary policy and fiscal policy. Capitalist economy nowadays is doomed again but it can hardly be saved by traditional Keynes's arguments and instruments for economies are no longer as independent entities as they were during the last century. Nevertheless, the idea of "Demand Management" has alternatively a theory, meaning some novel capitalist policy beyond monetary policy and fiscal policy. This leads to the idea of "Demand Management" in the 21th century, and that capitalist economy can get away from its doomed failure this century rests on whether or not it could practically develop such a policy instrument, like monetary policy and fiscal policy developed last century.

Has there been an empirical revolution in economics?

Sun, 26 Jun 2022 00:26:25 +0000

I sometimes read that the last twenty years have seen an empirical revolution in economics and that economic theory has begun to lose its saliency in graduate schools. Certainly, an inspection of the table of contents of the major economics journals shows a preponderance of empirical papers. But much of this literature seems to simply reflect economists' skills as data analysts rather than economists per se since the topics addressed would appear to be equally at home in criminology, political science, sociology, and public administration journals. The relevance of much of this research to economics is not clear to me. This is not to deny the high quality of this research. However, traditional economics questions concerning how economic agents behave when their constraints change seem not to be of much interest to the younger generation of economists. I am also concerned with the extent to which this research program is atheoretical, I am old enough to remember the "measurement without theory debate" and to have attended the LSE where I was taught by Lipsey and Co. that science was about the fruitful interaction between theory and empirical analysis. Probably I am just an old fogey.

Why do economists ignore their own supply and demand model?

Sat, 25 Jun 2022 23:23:44 +0000

Three years ago I started a thread that criticized the way in which we teach the supply and demand model. The emphasis was on <<model>> because my concern was with how S&D is taught, especially to majors (and, perhaps, graduate students). The standard verbal/graphical exposition is implicitly or explicitly based on a three equation mathematical model. But the third equation is an <<equilibrium condition>> that means that the market is <<assumed>> to always be in equilibrium. Because there are no equations that show how maximizing agents will react to a disequilibrium price - something that cannot exist in the model - the standard narrative's account of how the market adjusts to disequilibrium is not consistent with the model that is claimed to underpin the analysis. (The claim that firms and consumers can adjust prices violates the <<assumption>> of perfect competition.) Economists seem to be reluctant to admit that their verbal and geometric <<analysis>> is at odds with their mathematical model, which is not to deny the correctness of their intuition of how markets seem to behave. Disequilibrium dynamics is a notoriously difficult and seemingly intractable problem - see Fisher's "Disequilibrium Foundations of Equilibrium Economics" (1984). The math that economists use to come to grips with the problem is very primitive by the standards of professional mathematicians, let alone Fields medalists, and it may be that we need help from mathematicians in coming to grips with this problem. (Just as physicists have maintained a fruitful dialog with mathematicians for the last four hundred years.) In 2018 the Fields medal was awarded to two mathematicians who have made contributions to economics (see https://afinetheorem.wordpress.com/2018/08/01/the-2018-fields-medal-and-its-surprising-connection-to-economics/).

Asymmetric Information and Fraud: How well are they covered in textbooks and the literature?

Sat, 25 Jun 2022 22:10:35 +0000

Arrow (1963) and Akerlof (1970) are the canonical expositions of market failure that arise from asymmetric information. In both papers, the market outcomes are socially suboptimal, and it is individuals rather than firms that exploit the asymmetry. I have written a note that explores situations in which firms deliberately withhold information from buyers, or provide buyers with misleading information; in these cases, markets overproduce, which can cause consumer surplus to be negative. I am interested in learning if this issue has been covered in the literature. None of the many microeconomics texts (from principles to graduate level) that I have access to even contain the word fraud in their indexes. Jetson Leder-Luis has a research program that is devoted to some aspects of fraud and there is literature on credence goods that deals with some types of fraud but I cannot find any general discussions of the implications for resource allocation. Perhaps economists have ignored fraud because they have assumed that market systems are self-correcting since no fully rational firm would ever sell thalidomide or faulty airbags because such firms fear the wrath of the stock market. But while it would be absurd to argue that all firms engage in fraud it is well documented that some firms have engaged in fraud. (The problem of negligence also seems to be neglected.)

Economics - Definition Itself Is All Wrong

Wed, 22 Jun 2022 03:25:07 +0000

Mahatma Gandhiji said "There is enough in the World for Every person's need but not Enough for One Person's Greed" . Conventional Economics is defined as "The Study of Use of Scarce resources to fulfill Unlimited Wants" . Clearly the two definitions are diametrically opposite understanding of human material problem. If you believe the conventional economics then human material problem won't get solved 1000 years from now. However according to Mahatma Gandhiji the human material problem is due to greed. I have published a paper in an academic journal. Please comment on this paper at this link https://www.iosrjournals.org/iosr-jef/pages/vol.13i3-Series-1.html

Has anyone yet realized the true reason for inflation?

Sat, 04 Jun 2022 08:15:15 +0000

In terms of an institutionalized economy, some great nation of the ancient mode of civilization can never be really an institutionalized market for the world economy while indeed it can be open as an institutionalized technology for the world economy. The decades of globalization have been thus evolved such that some other nations have been enjoying low prices of products while suffering the loss of the technology of industries and the polarization of the society. The global inflation of these days indicates the reverse of the development and there will be a long period of adjustments. As the matter is of time and structure, unless certain strategic measures are well-planned, short-term monetary and fiscal policies can do little to the matter. Moreover, without a solid and structured technology of supply, fiscal policy has long lost its basis or usefulness.

Has anyone yet realized that trade principles of WTO are based on a collection of technological economies?

Wed, 13 Apr 2022 02:57:36 +0000

In a technological sense, the world is flat so that "Free Trade Policy" is reasonable and applicable. However, as soon as it is realized that the world consists of institutionalized economies, we come to see "Free Trade Policy" is reasonable if trades occur among the economies which are the same or similarly institutionalized; whereas "Protective Trade Policy" is reasonable if trades occur between the economies which are heterogeneously institutionalized. As a Chinese scholar, beyond this tip I'd say no more!

Automatic stabilization of a market sector via the social-ism of the law?

Tue, 12 Apr 2022 15:24:46 +0000

We should have no homeless problem in an at-will employment State with equal protection of our own laws. What would be a Pareto Optimum minimum wage for unemployment compensation in our at-will employment States? Also, what would landlords consider an optimum form of minimum wage for unemployment compensation in order for their market sector to function in a more optimum fashion and manner? Solving simple poverty is also command economics that can function via market-friendly means.

Demonetisation in India can happen in future ?

Sat, 02 Apr 2022 15:57:22 +0000

Do you feel the demonetisation event in India which happened in the year 2016 may occur in the future, i.e., 2030, 2050, etc.?

Has anyone yet realize that DSGE and/or RBC are flawed models in information?

Fri, 01 Apr 2022 08:26:19 +0000

Simply considering that the course of an economy includes not only the state variable of technology but also the state variable of human preference and the state variable of market institutions, one may realize the fact that, apart from the technological shocks, the psychological shocks as well as institutional shocks can also systematically affect the welfare end of an economy.

Countries whose currencies have changed.

Thu, 31 Mar 2022 15:04:25 +0000

Can you highlight the main reasons as why some countries have changed their currencies ?

What will be the impact on their economy once they change their currency?

Are there countries records where they have rollback to their original currency after specific time?

Has anyone yet realized that there has been methodologically an imbalance in macroeconomics?

Thu, 17 Mar 2022 08:22:27 +0000

Consider the state of a general market equilibrium of an economy, which is the state that aggregate demand of the economy is in equilibrium with aggregate supply of the economy. In the context of classical economics, the state is in conformity with Say's law that supply creates its own demand since the classical information space of an economy can be logically reduced to an aggregate production function. Keynes didn't agree to Say's law and thought that demand creates its own supply on the grounds of the neoclassical information space of an economy, which includes the agents other than the aggregate production function. Agents are psychological rather than completely rational such that we have an unstable macro-economy via the course of "demand creates its own supply." Nevertheless, as soon as the employment of men N is found in both Keynes' Aggregate supply function Z and Aggregate demand function D, we realize that the last resort that is underlying the state of a general market equilibrium of an economy in Keynes' theory, or more accurately, in neoclassical economics, remains the technology of production, i.e., the aggregate production function. There is a historical accumulation of capital related to the current state of production function but there is not a historical accumulation of capital related to the current state of market (institution) function, which might be the reason for methodologically the imbalance in macro-economic analysis, and which requires a revolution in the information space of an economy.

Has anyone yet realized that there is something wrong with the information space of an economy for economic analysis?

Fri, 04 Mar 2022 02:33:30 +0000

After Adan Smith, we have undergone two patterns of economics: the pattern of classical economics and the pattern of neoclassical economics. Both belong to a more general pattern of economics – The General Theory of Economy.
In terms of the information space of an economy for economic analysis, the pattern of classical economics is the general theory of the technology of production while the pattern of neoclassical economics is the general theory of the consumption-based preference of agents and the technology of production. The trade-off relation between the stock of institutions and the level of economic uncertainty has not yet been included in the information space for economic analysis. Therefore, unlike the historical accumulation of the stock of production capital, the historical accumulation of institutions is not allowed for as a budget-constrained process of an economy. As soon as we take into account of the state variable of institutions, we find that the pattern of economics must be changed to the general theory of the preference of agents, the technology of production and the institution of reciprocity. Accordingly, the information space for economic analysis is changed to the information space of an institutionalized economy.
Moreover, in the light of various modes of civilization or civilized society, economies of different geopolitical conditions are institutionalized in kinds. The so-called “private-ownership market economy” is not universal, particular to the modern mode of human society or civilization.

Do profits signal production?

Sat, 12 Feb 2022 11:18:17 +0000

I am looking for a citation. About thirty years ago while listening to the Public Radio, there was a discussion about a question for an examination to determine the understanding of economics in high school students. The question was something like “What is the purpose of profits in Neoclassical economics?” The answer was “to signal what to produce.” Are there any citations, which state something to the effect that profits signal production?

The statement seems to make intuitive sense. If a product is more profitable for a business, the profit will signal to the business that it should probably make more of it or a competitor will make more of it.

AEA/ASSA Proposals and Submissions Question

Fri, 04 Feb 2022 16:29:00 +0000

Excuse my ignorance, but when you submit a proposal for AEA/ASSAs, can you submit (1) a proposal for a paper you have not yet started to work on but for which you have the data / anticipate results by Jan 2023, (2) proposal for a paper with preliminary results but no draft, (3) only research for which you have a working paper / draft at the time of submission? If your paper is accepted for publication in a journal in between when you submit to the AEAs and when the conference is, is that a problem (i.e. is it frowned upon to present work that is forthcoming / already published)?

Where can I find sectoral economic data?

Mon, 06 Dec 2021 18:45:07 +0000

I am looking for global aggregate (e.g. GDP) data by economic sector (similar to bea.gov/data). Perhaps the World Bank?

Ideally, by SIC or NAICS but even a simple breakdown at the top level would suffice.

https://siccode.com

For example, I would like to know the gross (or percentage) of economic activity in the mining industries over time.

Any help or direction would be appreciated.

What journal would be happy to publish an agent based model of the utility of fiat money.

Sun, 14 Nov 2021 12:35:41 +0000

I have written a paper on the utility of fiat money (https://arxiv.org/pdf/2103.05556.pdf) which I think deserves an audience. However, I feel handicapped in several ways... firstly I am not currently working at an academic institution so I have nobody to ask for advice on getting things published and secondly, the paper employs agent based modelling. I have heard that this is frowned upon by many journals. Also, a lot of journals charge submission fees which I would have to pay out of my own pocket so I am keen to avoid submitting to the wrong place. Any suggestions would be most welcome.

seeking subject matter expert nominees: future of human welfare and societal change

Mon, 20 Sep 2021 19:46:47 +0000

Hello!

We apologize for this intrusion, but we are eager to capture the insights that experts in your field have to offer into a big-topic debate: the near and longer-term future of human welfare and societal change. We refer to any area of societal change (e.g., economic conditions, public health, freedoms, happiness, life expectancy, functional institutions, technological innovations, peace, education, social capital), seeking to understand whether such conditions will improve, stay the same, or worsen in the future.

To this end, we are asking for confidential nominations about the most relevant, prolific, and well-respected experts in your field who study issues related to the future for humanity and societal change. Self-nominations are welcome. Top nominees will be invited to share their insights—and eventually share a distillation of these expert opinions with the academic community and society at large.
https://uwaterloo.ca1.qualtrics.com/jfe/form/SV_6yF4u0qZkPEZMDI

Igor Grossmann
University of Waterloo

Philip E. Tetlock
University of Pennsylvania

Can anyone point me to a recent, sensible ranking of econ journals?

Tue, 14 Sep 2021 22:05:35 +0000

I'm putting together a promotion case for a colleague and need to document econ journal quality to upper-level committees (all non-economists). We had previously used Kalaitzidakis et al (2011) or Combes and Linnemer (2010), but they're pretty dated now (a problem because they don't include relatively new journals such as the AEJs). And the recent rankings we've found so far have obviously nutty results (e.g., ranking RAND barely in the top 200). I'd like to find a ranking that avoids that problem, but isn't too dated. Thanks for any help you can provide.

Are you a graduate researcher who is looking for funding to carry out impactful and innovative research?

Fri, 20 Aug 2021 17:08:50 +0000

Hello community members,

I’m thrilled to announce a new research grant for graduate students funded by Dobility, the makers of SurveyCTO.

This grant is designed to support graduate researchers who want to carry out innovative, impactful research. Find all the details and the application here: https://www.surveycto.com/data-collection-research-grant-2021/

What is the SurveyCTO Data Collection Research Grant and who is it for?

The research grant is available for all global graduate students who’ll be carrying out data collection heavy research in the 2021-2022 academic year. Grant awardees will receive:

- At least $2,000 towards data collection research expenses
- A free annual subscription to SurveyCTO (worth $2,376)
- Access to our expert support team
- Visibility for their data collection project

When is the deadline and how are applications assessed?

The deadline for applications is September 30, 2021.

Dobility will look at three areas: impact, innovation, and feasibility. If you plan to carry out impactful research that involves heavy data collection, you’re a perfect fit to apply.

Learn more and apply for the grant here: https://www.surveycto.com/data-collection-research-grant-2021/

What is SurveyCTO?

At SurveyCTO, we’re a team of data collection professionals and field researchers on a mission to make data collection easier and more secure. That’s why we created the SurveyCTO platform, the most reliable, secure, and scalable mobile data collection platform for researchers and professionals working in offline settings.

Who can I contact if I have questions about the grant?

Send any questions to info@surveycto.com. Please include “SurveyCTO Data Collection Research Grant” in the email subject.

Do you know someone who should apply? Think about graduate students in your network, collaborators in your projects, connections from your alma mater, or people in your program of study. If you know someone who might be a great fit, encourage them to apply for this grant.

Lindo Simelane
Dobility, Inc., creators of SurveyCTO