I got a wonderful gift from Thomas Reardon, a volume of Thomas Kuhn’s classics.
I should have read it before, but I didn’t, and reading it, I
understood why it’s a “great” book. It presents a convincing conceptual
framework, compelling narrative without excessive jargon, and presents
interesting and clear examples. The book presents an original vantage
point to understanding scientific progress. Rather than assuming that
science advances through smooth accumulation of knowledge, it suggests
convincingly that science advances through periodic revolutions that
shake the scientific fields.
Paradigm is a key concept in Kuhn’s
analysis. It is a shared framework that defines problems, methods,
standards, and exemplars within a scientific community. Once a paradigm
exists, most of the scientific work within this paradigm is part
of normal science, where scientists solve “puzzles” rather than question
fundamentals, refine measurements, extend applications, and articulate
theory. Normal science is conservative by design; it aims at precision,
not novelty. Over time, anomalies arise. They are empirical findings or
conceptual problems that cannot be fully explained within the prevailing
paradigm. For a while, these anomalies are ignored, explained away, or
treated as measurement errors. But over time, when anomalies accumulate
and become persistent, the field may enter a crisis, where confidence in
the existing paradigm erodes, competing ideas emerge, and
methodological and conceptual disputes intensify. This crisis may lead
to a paradigm shift. This is a scientific revolution where a new
paradigm replaces the old one. This change is discontinuous, as all the
new paradigms may use different concepts, standards, and questions, and
the choice between paradigms is influenced not only by data, but also by
judgement, persuasion, and community dynamics. Classic examples of
shifts are: in physics from Newton’s world to Einstein’s relativity, and
the big shift in astronomy from traditional to Copernican.
With new paradigms, the same data can be
interpreted differently, and standards of explanation vary, but there is
a strong conviction that you’ll get closer to the truth. Every new
paradigm has some holes and therefore, normal science tries to fill
them. Paradigms generally tend to explain the range of issues that
science can analyze and explain and increase the capabilities of
scientific communities. Fascinatingly, Kuhn argues that scientific
change is a social process sustained by scientific communities – and
therefore persuasion is crucial for a scientific revolution that may
take a long time. Education is crucial in establishing paradigms because
textbooks that reflect paradigms train new generations of scientists.
Frequently, marginal groups in scientific communities play a major role
in introducing a new paradigm. Younger members of disciplines tend to be
earlier adopters of new paradigms and subscribers to the older paradigm
tend to either convert or die :-). Nevertheless, people may believe in
and act according to concepts of multiple paradigms. For example,
accepting Newtonian mechanics and Einstein relativity.
Religion is a paradigm
My perspective on religion comes from my
familiarity with Judaism. Prior to the emergence of Judaism, there were
multiple ancient religions in the Middle East believing in multiple
specialized gods responsible for rain, wars, etc. The gods were part of
nature and there were ritual activities including sacrifice to satisfy
the gods. These religions have their own priesthoods and the religions
and priesthoods were supposed to provide insurance (against droughts),
healthcare, education, and political legitimacy, among others[1].
Judaism provided a paradigm shift. It introduced the notion of a
universal god, separating between gods and nature. It prescribed a moral
law and rituals (Mitzvot), which are the core of religious life.
Judaism has the equivalent of “normal science”, which is a continuous
scholarly activity, refining and expanding the paradigms. It has a
social structure (scholars, teachers, certifiers) that provides multiple
services to its adherents.
While initially, Judaism was linked to
Israel and the temple in Jerusalem, the destruction of the temple by the
Romans, led to significant paradigm modifications where sacrifice was
replaced with prayers and the religion became more global and can be
practiced everywhere. Christianity, in my view, is a paradigm shift that
retained monotheism and ethics, introducing Jesus as a mediator between
God and humanity. It also emphasizes the role of faith vs. the pursuit
of practices and emphasizes a pursuit of universal membership. Modern
secularism is a paradigm shift compared to the monotheistic religions,
but people can hold beliefs and practices associated with both. While
with religion, outcomes are governed by the gods, in secularism it’s
governed by impersonal laws and much of the content and beliefs are
constructed by humans. While religious opinions and actions are governed
by faith, tradition, and authority of the church; in secularism
perspectives are based on science and evidence, and the truth is
revisable. In secular systems, science replaced theology for explaining
nature, secular law provides guidance and enforcement, and states
replace churches for governance.
Religion and science are Incommensurable,
namely, ask different questions, and use standards of evidence.
Therefore, people should be able to subscribe to both in different
aspects of life. One of Kuhn’s major contributions is the emphasis of
the social aspect of the paradigm. Both religion and modernity lead to
institutions, and organizations, and professionals that provide multiple
services. They include centers of education, healing and welfare, some
are competing, and some are cooperative. Conflicts among religions and
modernity led to multiple conflicts. The Peace of Westphalia,
initiated a process that ended religious war in Europe and ushered a
separation and coexistence of state and church (at least in some
countries). So, history, religion, and politics evolved, but Kuhn’s
notion of paradigms is really crucial to understand them.
Technological Paradigms
The notion of paradigms is useful in
explaining technological evolution and change. Technological paradigms
can be viewed through the Kuhnian prism to understand how technological
waves can change the problems that are being solved, provide new
solutions, and lead to the establishment of skills, institutions,
practices, and evolve into a supply chain.
The printing revolution in the 15th-16th century
is a paradigm shift. Before, knowledge was transmitted by hand-copied
manuscripts or orally, and literacy was scarce. After a long transition,
printing allowed a mass reproduction of information, standardization of
knowledge, and rapid diffusion of ideas and technologies. Similarly,
the industrial revolution in the 18th and 19th century,
was a shift from old paradigms that relied on artisan production, human
and animal power, and localized manufacturing to industries that rely
on mechanized production, fossil fuels, and factories and economies of
scale. In the 19th and 20th century, electrification and mass production were significant paradigm shifts, and in the late 20th century,
we had digital computers and the information revolution. We are now in
the midst of artificial intelligence and data-centric revolution, which
are based on new learning systems and pattern recognition at scale, and
probability decision-making. While we are aware of the occurring
transition, we are less aware of its implications. Personally, I
realized that if you cannot beat them, join them and this blog post was
written with the assistance of AI. From my minimal experience with AI, I
learned that you need to be very well-informed to produce useful
prompts and to check the reliability of the results. I am also concerned
about the capacity of humans and the future of employment in an AI
world.
As an economist, I am particularly
interested in the transition from a fossil-based, linear throughput
economy to a circular one. In the prevailing paradigm, the central
objective has been to maximize output efficiently, with environmental
impacts treated largely as externalities. The emerging paradigm instead
focuses on how to meet human needs and aspirations within planetary
limits.
Under this framework, performance can no
longer be evaluated solely by profits or GDP. Assessment must also
account for life-cycle emissions, system resilience, and net present
value at the whole-system level. The transition entails moving from
fossil-based technologies to modular renewable energy systems, and from
linear extraction and disposal to circular material flows.
This shift creates value in technologies
for recovery, recycling, and reuse; in bio-based materials; and in
designs that enable disassembly. It also points toward integrated
bio-industrial systems and symbiotic innovation and product supply
chains that jointly consider economic, environmental, and resilience
attributes.
Such a paradigm shift requires a policy
environment that de-risks innovation, coordinates infrastructure, and
sets dynamic standards, while preserving space for entrepreneurship and
experimentation.
The Evolution of Economics’ Paradigms
Economics’ paradigms have evolved in
response to changing technologies, institutional complexity, and
societal objectives. While early economic thought focused on markets and
efficiency, successive paradigms progressively incorporated
uncertainty, institutions, innovation, and governance.
Classical political economy, associated
with Adam Smith and David Ricardo, focused on production,
specialization, and long-run growth constrained by land and resources.
Analysis emphasized aggregate outcomes rather than the mechanisms
through which new technologies emerged and diffused.
The neoclassical paradigm associated
Alfred Marshall shifted attention to marginal decision-making, prices,
and allocative efficiency. It provided powerful tools for analyzing
markets, but innovation remained largely exogenous, and economic success
was evaluated primarily through static efficiency. This framework
offered limited insight into technological change, scale-up, or long-run
adaptation.
Major disruptions—the Great Depression and
later stagflation—motivated macroeconomic paradigms centered on
stabilization and expectations, most notably Keynesian and New Classical
economics. While these approaches advanced understanding of business
cycles and policy credibility, they did little to explain how innovation
is generated, financed, and commercialized, or why many socially
valuable technologies fail to scale.
From the late twentieth century
onward, economics increasingly turned toward innovation and
institutions. Economic growth theory, led by Robert Solow, Daron
Acemoglu, Paul Romer and Philippe Aghion, made technological change
central to growth and showed that incentives and policy shape innovation
rates. Induced innovation models demonstrated that the direction of
technological change responds to relative prices, scarcity, and
regulation, an insight especially relevant for agriculture, energy, and
environmental technologies.
At the same time, institutional and
organizational economics expanded the analytical scope. Ronald
Coase and Oliver Williamson explained how transaction costs,
uncertainty, and asset specificity shape the governance of innovation,
while David J. Teece showed why firm capabilities, complementary assets,
and business models determine whether innovations capture value.
Another recent paradigm is behavioral
economics. It represents it relaxes the neoclassical assumptions of
fully rational, self-interested agents with stable preferences,
replacing them with empirically grounded models of bounded rationality,
heuristics, and systematic biases. It integrates insights from
psychology and neuroscience, shifting economics from a purely deductive
framework to one that is increasingly experimental and evidence-based.
This paradigm explains persistent anomalies—such as under-saving,
inertia, and loss aversion—that standard models cannot reconcile. As a
result, it changes both positive analysis and policy design, justifying
interventions like nudges that improve welfare without relying solely on
prices or mandates. The transition among paradigms in economics is not
stark and several coexist, yet over time, the new paradigms tend to be
adopted.
From Micro and Macro Paradigms to a Supply-Chain Systems Perspective
The evolution of economic paradigms can be
interpreted not only as a sequence of intellectual shifts, but also as a
growing recognition of the limits of narrow analytical lenses. A useful
distinction is between macro paradigms, which focus on aggregate
outcomes such as growth, employment, and inflation, and micro paradigms,
which focus on individual decision-making, market interactions, and
price formation. Much of modern economics has been built on micro
paradigms that abstract from the physical world and treat economic
performance as emerging from a relatively small set of transactions,
prices, and equilibrium conditions.
Traditional neoclassical microeconomics,
and many of its extensions, rely on simplified representations of
production and consumption in which technologies are summarized by
production functions and environmental feedbacks are largely ignored.
Even when uncertainty and expectations are introduced, as in rational
expectations or information economics, the physical transformation of
materials, energy, and biological resources remains peripheral.
Behavioral economics has enriched this framework by relaxing assumptions
of full rationality, introducing bounded rationality, heuristics,
norms, and biases. While behavioral insights improve predictions of
individual and market behavior, they often remain disconnected from
the biophysical systems in which economic activity is embedded.
In contrast, macro paradigms—Keynesian,
growth, and institutional approaches—have focused on aggregate dynamics,
long-run development, and systemic constraints. Yet these paradigms
also tend to treat technology and production structures in highly
aggregated ways, limiting their ability to address coordination
failures, scale-up bottlenecks, and sustainability challenges that arise
at intermediate levels of organization.
This course advances a different
perspective, one that is more closely aligned with real-world economic
and environmental systems. We argue that economies are better understood
as networks of multiple, symbiotic supply chains—both of innovation and
of production—that transform raw materials through successive stages of
discovery, development, processing, distribution, and consumption.
These multistage supply chains explicitly incorporate biophysical
constraints, behavioral responses, and institutional arrangements, and
they generate not only valued goods and services but also residues that
are sources of pollution and environmental stress. Forever, more
than 90% of innovations don’t end up as commercial products and
innovation and product supply chain are subject to random shocks and
uncertainties that have to be considered as we analyze them.
Viewing economic systems through this lens
allows economists to better explain past patterns of technological
change, anticipate future transitions, and design effective policy
interventions. In particular, it provides a way to address classic chicken-and-egg and coordination problems—where
valuable feedstock are not developed because there is no infrastructure
to utilize them. Such problems arise in sustainable energy, bioeconomy
development, and circular material systems—where prices alone fail to
induce efficient outcomes. By embedding economic behavior within
interconnected innovation and product supply chains, this paradigm
offers a more realistic and policy-relevant foundation for analyzing
economic performance in a world facing tight environmental constraints
and rapidly evolving societal demands.
Conclusion
The Kuhnian paradigm perspective provides a
powerful framework for assessing the evolution of human thought and
action systems, including science, religion, technology, and economics.
History reveals recurrent revolutionary patterns in which established
ways of thinking and doing are fundamentally transformed, often
accompanied by profound social and organizational change.
Kuhn provides a powerful lens for
understanding the evolution of economic thought and practice. Periods of
“normal economics,” in which analysis focuses on marginal adjustments
within established frameworks, are periodically disrupted by deeper
transformations driven by technological change, social pressures, and
binding biophysical constraints. Today’s transition from a fossil-based,
linear throughput [רפ4] economy
toward a circular and bio-based system reflects such a moment of
paradigm change. Traditional economic metrics and analytical
tools—centered narrowly on prices, profits, and aggregate output—are
increasingly insufficient for guiding decision-making in a world facing
climate change, biodiversity loss, and heightened demands for resilience
and equity.
Viewing economic systems through this
broader paradigm enables economists to better explain historical
patterns of technological change, anticipate future transitions, and
design more effective policy interventions. In particular, it highlights
the critical role of government initiatives—often characterized as
industrial policies—including investments in research and development,
physical infrastructure, workforce training, and, in some cases,
targeted subsidies. These interventions do not replace markets; rather,
they enable markets to function by empowering the private sector,
overcoming classic coordination failures and chicken-and-egg problems,
and accelerating the emergence of new technologies and supply chains.
Such challenges are especially acute in domains such as sustainable
energy, bioeconomy development, and circular material systems, where
price signals alone frequently fail to induce socially efficient
outcomes.
Embedding economic behavior within
interconnected innovation and product supply chains offers a more
realistic and policy-relevant analytical foundation. This perspective
explicitly links discovery, development, scale-up, and diffusion to
material flows, environmental externalities, and behavioral responses.
It also clarifies how economic and biophysical systems co-evolve,
producing both valued goods and unavoidable residues that must be
managed. By integrating these dimensions, the emerging paradigm moves
economics closer to the physical world it seeks to explain and
influence.
Ultimately, ideas originating in
agricultural, environmental, and resource economics—fields long
considered peripheral—are now central to shaping this transition. Their
multidisciplinary orientation and sustained engagement with climate
change, food security, and biodiversity preservation position them to
contribute to a new economic paradigm. If successfully translated into
policy and institutional change, this paradigm has the potential not
only to enhance sustainable development but also to support greater
global stability, cooperation, and harmony.
