“In Guidelines for the Responsible Practice of Economics, Dr. Steven Payson provides a thoughtful, constructive framework for navigating the modern analytical landscape. Drawing on extensive experience across both academia and the federal government, he offers 36 practical guidelines designed to strengthen empirical research, enhance methodological transparency and scientific integrity, and bridge the gap between abstract theory and effective public policy.” amazon

Dr. Steven Payson is a Senior Lecturer and Program Coordinator in Applied Economics at Johns Hopkins University. He holds a Ph.D. in economics from Columbia University and has an
extensive professional background spanning major academic institutions—including
Georgetown University, the University of Maryland, and Virginia Tech—as well as leadership roles as a senior economist across multiple U.S. federal agencies. A widely published author on economic measurement, technological change, public policy analysis, and the scientific integrity of economic methods, Dr. Payson brings decades of rigorous, real-world experience to
examining the foundational practices of the profession.

LINK to the book paperback EUR 6.94

The Interview

With Steven Payson spoke GLO President Klaus F. Zimmermann.

1. What sparked your interest in research and publication ethics, and why does economics need explicit ethical guidelines?

My interest in this general topic began when I was a graduate student in economics during the 1980s, as I observed the extent to which graduate-level economic theory had become overly reliant on mathematical showmanship rather than the advancement of useful knowledge. I have pursued this area throughout my career, addressing it partially in my dissertation, through founding the nonprofit Association for Integrity and Responsible Leadership in Economics and Associated Professions (AIRLEAP), and in prior publications leading up to this book. These efforts were fueled by a personal desire to see economics improve, believing it can do much better for the benefit of society.

However, that initial focus on “research and publication ethics” does not fully capture the scope of my new book, Guidelines for the Responsible Practice of Economics. While responsibility certainly includes ethical behavior, it also encompasses a leadership commitment and professional actions that extend well beyond research and publishing—and which most people, and economists in particular, do not typically associate with ethics.

For example, if you asked most economists whether they are ethical, the vast majority would immediately answer yes. In their minds, they are ethical because they have never abused a relationship with a coworker, taken a bribe, or falsified data. Responsible leadership, however, has a much wider scope. Suppose an economist in a position of great authority upholds a public policy simply because it aligns with an esoteric model—one they may not even fully understand or care to study—driven by the sycophantic assumption that the model must be correct because its developer is a famous, highly acclaimed economist. If that model has the potential to cause real societal harm, but the authority figure dismisses any concerns simply because those concerns were raised by sources with lower professional prestige, then that would be deeply irresponsible. Yet, few people would view that failure as a violation of traditional research and publication ethics. The word “ethics” narrows the scope too much, masking real-world problems of professional responsibility that go far beyond conventional definitions.

As for why economics needs guidelines for responsible practice, Guideline #3 provides the most vital answer: “do no harm”—a fundamental directive that every profession requires. The absence of such guidelines causes genuine harm to society, alongside losses in economic efficiency and basic human dignity, but the primary issue is avoiding the very real damage that bad economics can inflict.

2. Why has economics been more resistant than other social sciences to professional ethics, and where is that resistance most visible?

To frame this question constructively, I prefer to substitute the term “responsibility” for “ethics,” restructuring the query as: “Why has economics been slower than other social sciences to embrace professional responsibility, and where is that hesitation most apparent?”

While this question is surely posed in good faith rather than as a trap, it carries an inherent paradox. My writings do not declare that economics is uniquely insular compared to sister social sciences—a proposition whose factual basis is far from certain, given that professional blind spots and ethical lapses surface everywhere. To brand economics as the absolute worst offender would cast me as an isolated, uncharitable alarmist; conversely, to claim it is no worse than any other field would undermine the very premise for examining its unique institutional failures. Navigating this dilemma has required a consistent approach across decades of work.

Even under the most generous assumption that the vast majority of economic research is conducted honorably, a dangerous complacency takes root. Presuming the system functions smoothly allows widespread professional oversight to be swept aside by institutional apathy. At the same time, sliding into pure defeatism—the belief that the entire apparatus is hopelessly compromised—merely breeds a cynicism that defenders of the status quo can easily dismiss.

Discussions with colleagues in the physical and life sciences often surface a comforting yet misleading premise: the notion that maintaining scientific integrity is equally arduous across all intellectual domains. This argument treats integrity lapses as an immutable consequence of human nature, using universal fallibility as an excuse to insulate economics from specific critique. Yet economics occupies a distinct structural position. Its integrity failures are unmistakable, marked by an insular publishing ecosystem that prioritizes methodological abstraction over actual discovery. As I noted in previous investigations of journal metrics, the race for high-impact placements has increasingly converted scholarly publishing into an inward-looking exercise rather than an authentic pursuit of empirical truth. Because the discipline acts as a primary arbiter for how societal resources and incomes are apportioned, the neutrality of its frameworks carries immense weight. When analytical justifications for resource allocation are underwritten by the very beneficiaries of those arrangements, the independence of the science is deeply compromised.

Other fields face analogous pressures—medicine, for instance, operates under a severe “fatality constraint” where flawed clinical claims or dangerous remedies that directly harm patients are quickly exposed by undeniable physical outcomes. Economics lacks such immediate, unambiguous feedback loops; establishing causal links across complex macroeconomic systems is inherently difficult. For example, the severe global downturn of 2007–2008 undoubtedly triggered widespread hardship and elevated mortality across vulnerable populations worldwide, yet because those tragic outcomes are diffused through a complex global economy, the discipline largely shields itself from direct accountability.

Furthermore, locating where “resistance” manifests requires a slight reframing, as true resistance implies a deliberate, active defiance. My critique is not structured as an adversarial campaign, nor is the problem driven primarily by deliberate malice; rather, it stems from institutional inertia and a lack of awareness. Practitioners frequently operate simply by following the established paradigms passed down through their training, adopting conventional norms without critically evaluating their broader societal implications. The primary objective of my work is to illuminate these blind spots so that practitioners can recognize what responsible economic stewardship truly entails.

3. Of your 36 guidelines, which three address the most serious ethical problems in economics today?

While the question presumes that each of the 36 guidelines addresses an entirely isolated problem and that selecting the top three is straightforward, the guidelines are deeply interconnected rather than independent. To answer meaningfully, we can examine importance through three distinct lenses: hierarchical dependency, harm reduction, and the introduction of critical new perspectives that correct major professional blind spots.

When evaluating through the lens of hierarchical dependency, the very first guideline—realizing the need for guidelines—stands out as foundational, because without it, the entire discussion is mute. Dismissing that background premise leaves 35 guidelines, among which numbers 2, 3, and 4 are paramount: recognizing the important responsibility of being an economist, doing no harm, and acting with honor and integrity. All subsequent rules, such as Guideline #27 on confronting institutional deception, logically derive from these foundational principles, as complicity in deception inherently risks causing harm and abandoning integrity.

If we set aside dependency and focus instead on which rules prevent the greatest real-world harm (extending from Guideline #3), three stand out:

• Guideline #25 (Avoiding Alternative Realities Made Possible by Subfield Isolation): Insular academic subfields can generate catastrophic real-world outcomes, such as the financial crisis of 2007–2008, where self-referencing echo chambers insulate analytic models from external reality. When governments treat fringe theoretical models as valid equivalents, it allows policy to be captured by narrow political or corporate agendas at the expense of society.
• Guideline #28 (Distinguishing Between Science and Running Experiments): The broader issue here is the deep-seated methodological misunderstanding that simply running an experiment automatically confers scientific validity—a form of “experimental-scientist cosplay”. While the uncritical contemporary obsession with randomized controlled trials (RCTs) in development economics is a major corollary of this delusion (a topic I also explored in my recent book, Nobel Laureates Caring about Poverty), the overall problem is much larger, carrying a massive opportunity cost that diverts analytical energy and resources away from more productive and holistic forms of structural observation.
• Guideline #30 (Eliminating “Hategoatism” and Upholding Analytical Objectivity): This guideline addresses a pervasive distortion where complex economic difficulties are falsely blamed on targeted groups rather than undergoing rigorous systemic evaluation. To justify coining the term “Hategoatism,” we rely specifically on the less common term “scapegoatism” rather than “scapegoating,” pairing it with dehumanization on the basis that these two behaviors most often coincide and reinforce each other.

Alternatively, if we evaluate importance through the lens of unique intellectual contributions that challenge industry blind spots, other critical areas emerge: Guideline #8 regarding the bibliometric citation-count and journal-ranking ecosystem, which impedes the accumulation of genuinely useful knowledge; Guideline #14 on scholastic escapism and the “nice bartender” mentality at the academic apex, which explains how the profession often lacks true, responsible leadership at the very top; and Guideline #34 on grounding technological change and economic models in scientific literacy to keep pace with the ongoing artificial intelligence revolution.

4. You criticize the “prestige engine” of top journals, citations, and rankings. Are these metrics fundamentally corrupting, or simply imperfect measures of research quality?

It is not even close—they are worse than “fundamentally corrupting”. They have placed a stranglehold on the profession’s ability to identify and accumulate useful knowledge.

Instead of operating as a legitimate science, the metrics turn the discipline into an intellectual sport, much like chess. Furthermore, they contaminate the thinking and culture of economics, making many practitioners proud to be winning an intellectual game rather than having a positive effect on the world. I realize this sounds outrageous and delusional to readers who are seeing these claims for the first time, but reading the book will easily eliminate such skepticism.

5. Economics has made major advances in replication, open data, and reproducibility. Does your book underestimate this progress?

I discuss these advances directly in the book, and I would not call them “major” advances, nor does the book underestimate this “progress”. Instead, the book explains why this progress has been greatly overestimated by the profession and misunderstood as reflecting scientific integrity when it does not.

Replication is merely a bare minimum requirement for any respectable science—the fact that economics has tried to achieve it is nothing for the profession to brag about. In the book, I liken it to a five-year-old child baseball player receiving an award from the coach for “best team spirit” for showing up to practice on time. Major league players do not get team-spirit awards; they are recognized for how well they actually perform on the field. The fact that a model can be reproduced means very little regarding its scientific validity.

In our profession, repetition has been completely misunderstood as scientific validation. For example, in my forthcoming book examining the estimated Value of a Statistical Life (VSL) used for cost-benefit analysis, that estimated value—derived from regressions of wages against safety risk probabilities—has been replicated across several studies. Yet each study repeats the same egregious error of omitted variables and failed robustness: adding just one dummy variable for the airline pilot occupation entirely strips away the statistical significance and value of the estimated parameter in every single replicated study. (While airline pilots earn high wages and face high risks, their higher compensation is driven by factors far beyond a simple personal risk premium that the model must assume.) Subfield isolation has allowed all VSL calculations to ignore this fundamental econometric and statistical inference error. And yet, the VSL subfield continues to announce the “replicability” of its results with pride, as if it attests to the scientific validity of the estimated VSL value.

As this suggests, using replicability as evidence of scientific validity is like rewarding sports players for how often they show up to practice. Economics is not T-ball for kindergarteners. Because economics has major-league effects on our society, it needs to be a major-league science, and that requires, at a minimum, understanding the difference between replication and scientific validity.

6. If, as you argue, reproducibility is only a minimum standard, what should matter more: robustness, external validity, better measurement, or substantive economic importance?

Objective truth is what matters. Are we truly learning how the world actually works, or are we putting on a good show to score points in the citation-publication tournament? It is that simple.

The situation has become so skewed that many economists view the pursuit of objective truth as comical naivete, much like a science fiction writer dismissing someone who points out that their movie violates the known laws of physics—dismissing the critique simply because violating physical laws does not hurt ticket sales. The fundamental question all economists need to ask themselves is: what effect will their work actually have on the world? If that effect is completely peripheral to the impact their work has on their career, then that is the real problem.

7. Your book notes that AI can now generate models, code, text, and references very well calls for greater “post-AI intellectual transparency.” Can you explain this and why one cannot find much about what ethical rules economists’ use of AI in research and publishing should follow?

What I meant by post-AI transparency is the following, quoted directly from the book: “In an era where machine-generated complexity is ubiquitous, individual economists must distinguish themselves not through their ability to produce esoteric notation, but through their ability to look inside the assumptions of a model, validate its variables against physical data, and articulate its relevance to the actual challenges of the global economy.”

This goes beyond the normal scope of discourse on ethical rules for using AI; it addresses the reality that artificial intelligence has eliminated the traditional competition among economists to demonstrate sheer mathematical prowess. Because showcasing complex math is no longer a differentiator—since anyone can generate it—we now need far greater transparency regarding what makes the underlying math scientifically valid or not.

Most current AI ethics discussions focus on authorship credit—specifically, how much credit a writer should receive for work that was assisted by or entirely generated from AI. That is an entirely separate can of worms that could have been discussed in the book, but because so many others are already addressing it, I did not think it would add as much unique value.

One thing I will note, however, is that economic journals are showing their hand lately by asking contributors to specify the extent of their AI use, operating under the assumption that greater AI reliance makes a paper less deserving of publication. If artificial intelligence can be used to expand useful knowledge in economics—which it certainly can, provided glitches are properly addressed—it should be embraced in the same way computers were embraced during my lifetime. Restricting AI merely to preserve the citation tournament as a fairer test of human intellectual ability would mean throwing out the baby of useful scientific discovery with the bathwater of the citation tournament, ultimately reducing science to a mere sport. As I argue in the book, just as the historical idiom regarding the Colt-45 famously captured a shift in physical power during the 1800s—”God created men, but Sam Colt made them equal”—we are witnessing a similar, radical democratization of intellectual labor: “The universities created economists, but AI made them equal.” The profession needs to recognize this, accept it, and move past it, allowing AI to improve economic science, which it has the power to do.

8. Similar: Social media increasingly shapes academic visibility and debate; is its absence from the book a gap? Or are ethical standards when promoting findings, criticizing others, or communicating uncertainty online straightforward applications of your general guidelines?

I do not spend much time in the book tracking how various historical shifts have altered the profession. From my perspective, the effects of social media are peripheral to the core issues discussed, because I assume that social media is simply present as part of the background environment for everything mentioned. The same foundational ethical standards apply regardless of the communication medium used.

9. If unethical research behavior is largely driven by incentives, which institutional reforms in publishing, tenure decisions, or research assessment would matter most?

First, I prefer that we discuss “irresponsible research behavior” rather than “unethical research behavior,” as the former encompasses a much wider and more accurate scope.

I avoid singling out specific institutional reforms as “matter[ing] the most” because it is a trap that implicitly dismisses the factors left off the list and creates an easier target among the ones that are left standing.

In the book, I barely touch upon recommended institutional reforms for one primary reason: until our profession truly embraces these guidelines, any institutional reforms proposed will be rejected out of hand by the academic apex. Instituting those reforms would require admitting that a fundamental problem exists; if the establishment refuses to acknowledge a problem in the first place, their dismissal of suggested reforms will simply be misinterpreted by the broader community as proof that the issue was trivial all along.

I learned this the hard way when I argued in my earlier article, “Cite this Economics Paper!”, that reference lists should categorize citations—differentiating between essential citations, normal citations, citation fodder, and negative citations where authors cite work they are actively criticizing. Such categorization could have made the citation-counting tournament far more meaningful and useful. Yet no one ever adopted this reform in any reference sections other than my own work for a few years, until I gave up as well, realizing I was the only one following my own suggestion.

Meaningful reforms cannot be imposed top-down; they must originate from a fundamental re-examination of the true motivations driving why economists do their work. That internal reckoning is the hard part—once that shift occurs, the rest should follow relatively easily. In other words, before we can begin making structural changes, we must first determine and agree upon what the actual problems are that need to be solved.

10. Why does ethics still play such a limited role in economics education, and how should it be integrated into undergraduate and graduate training?

Again, the title of the book is Guidelines for the Responsible Practice of Economics—not Guidelines for the Ethical Practice of Economics, which would have resulted in a much smaller volume. “Responsibility” plays such a limited role in economic education because the principles of responsibility are not well known or understood by the educators themselves. Frankly, as the book clearly demonstrates, educators, themselves, need a lesson on responsibility before they can teach others about it, especially those who have defined success in their professional lives by how well they have fared in the publication-citation tournament.

With a smile, I dare say that the teaching of responsibility in economics can be easily integrated into undergraduate and graduate training through one simple act: having students assigned to read my book, and having professors cover it in class. I do not see this recommendation as a conflict of interest—I wrote the book for this very purpose.

11. Your book uses strong terms such as “Scholasticism,” “Hagiocracy,” and “citation tournament.” What achievement would make you revise your diagnosis of the economics profession?

There is only one achievement that would revise my diagnosis of the economics profession: the complete elimination of scholasticism, hagiocracy, and the citation tournament from economic discourse.

These terms are not designed to be insults—even though they may function that way in effect—but are simply accurate observations. When those observations change and the underlying practices disappear, the words will no longer apply.

12. What is the single most important piece of advice a young economist should follow who wants to maintain scientific integrity while still performing in the academic system?

Don’t be a coward! Stand up for what you believe. If you find yourself in a situation where your career goals conflict with your moral compass to be responsible, know first that you are not alone.

Of course, you cannot simply dismiss your career—you have to make the tradeoffs that make the most sense to you. But never let your career goals damage your thinking. Being forced to do something irresponsible is a cost you may sometimes have to pay, but do not let the situation distort your understanding of what responsibility actually means. When you can, plan your escape and find a situation where there is no longer a conflict between responsibility and your career. When you get old, you will look back on it and be glad that, whatever you had to do, you did it with full consciousness of your decisions.

Klaus F. Zimmermann: Many thanks for this inspiring exchange.