And yet, inside the ivory towers, the rituals continue: papers are being published, PhDs awarded, conferences convened, Nobel medals polished. Meanwhile, in the world outside academia, productivity has flatlined, global debt has surged beyond 300% of GDP, and AI is rewriting the rules of labor, value, and capital. The gap between what economics produces and what society needs is no longer a gap at all. It’s a chasm.
This is the Great Digital Decoupling — a two-stage crisis in which intellectual output soars while practical impact collapses. Between 2013 and 2023, the volume of economics papers, patents, and graduates increased by nearly 80%, yet the field’s policy influence dropped sharply: citations of academic economics in IMF and World Bank reports fell by 38% over the same period. In other words, the more economists spoke, the less anyone cared to listen.
The cause of death is hardly mysterious. Economics has clung to zombie models that assume equilibrium, rational agents, and stability, even as the real economy has been overtaken by algorithms that make credit decisions before breakfast and platforms that create trillion-dollar monopolies overnight. Its sacred metric, GDP, still counts oil spills as “growth,” ignores unpaid care, and values free digital services at zero. As the OECD and Stiglitz Commission have shown, this blind devotion to GDP systematically underestimates well-being, sustainability, and inclusion. If GDP were a doctor, it would measure cancer as proof of a healthy metabolism.
The statistics bear it out. In the post-crisis decade, productivity growth in advanced economies fell from ~1% per year to barely 0.5%, while youth unemployment rates hovered stubbornly above 12–15%. Global debt levels ballooned to record highs, even as the world produced more economists than ever before. Most damning of all, the empirical analysis confirms that rising research output correlates not with economic health, but with its opposite: a weak negative association between more publications and growth, and a statistically significant decline in policy relevance as academic output expanded.
The digital revolution has only sharpened this irrelevance. Data is not the new oil — it is gravity itself, bending markets, warping institutions, and creating value ex nihilo. Yet mainstream economics still treats it as a secondary input, a footnote in outdated Cobb–Douglas functions. Platforms, networks, algorithms — the defining forces of our age — remain invisible to the models still taught in top PhD programs. In fact, by 2025 only 25% of leading economics departments had integrated courses on AI, complexity, or network science into their curricula. The rest continue producing graduates trained to model a world that no longer exists. This is not oversight. It is epistemological malpractice.
The tragedy is that the profession continues to talk about “reform.” Add a Python course here, sprinkle in an ethics module there, maybe tweak the DSGE model for good measure. But these are not solutions; they are cosmetic. It is brass-polishing on the Titanic, while the iceberg is made not of ice but of blockchain, ChatGPT, and algorithmic capital. The ocean itself has changed, and the ship was never designed for these waters.
The only credible path forward is not reform but replacement. Dr. Shalaby’s Digital Sustainable Growth Model (DSGM) offers precisely that: a new operating system for economics, built for what he calls a 3D Economy —
one that is dynamically complex, digitally native, and developmentally sustainable. Instead of forecasting a mythical equilibrium, DSGM embraces agent-based modeling and network analysis to simulate how households, firms, regulators, and algorithms actually interact. Instead of worshipping GDP, it builds dashboards that prioritize sustainability, inclusion, and resilience. Instead of insulating itself in journals, it values code, data, and transparency, aligning incentives toward relevance and solutions.
This is not abstract theory. Denmark’s experiment with a “talent stock market”, where AI dynamically matches workers’ evolving skills with market demand, is a live example of DSGM’s principles at work. Central banks are beginning to simulate digital currencies before unleashing them on the system. Regulators are waking up to the fact that algorithmic bias must be audited like financial risk. These are glimpses of an economics that designs adaptive, ethical, and resilient institutions rather than describing a world that no longer exists.
So let’s state the truth plainly: economics, as we know it, is dead. Teaching it unchanged is intellectual malpractice. Funding it without transformation is policy negligence. Clinging to it as a career strategy is professional suicide. The elephant is not just in the room — it is stomping through lecture halls, trampling policy briefs, and screaming through the data. The evidence is here. The model is ready. The only missing variable is courage.
References:
- Shalaby, Ahmed, The Great Digital Decoupling: An Existential Challenge for Economics and Economists (August 29, 2025). Available at SSRN: https://ssrn.com/abstract=5420136or http://dx.doi.org/10.2139/ssrn.5420136
- Shalaby, A. The end of labor economics as we know it: DSGM and the shift to a 3D economy- a case study of Denmark’s transformation into a talent stock market. Digit. Econ. Sustain. Dev. 3, 17 (2025). https://doi.org/10.1007/s44265-025-00066-5
- Shalaby, Ahmed, The 2D Economy Is a Dead Horse-The Digital Sustainable Growth Model is Disrupting the Traditional Macro-Microeconomics in the 3D Economy (February 03, 2025). Available at SSRN: https://ssrn.com/abstract=5160079or http://dx.doi.org/10.2139/ssrn.5160079
- Shalaby, A. (2025c). Moving Beyond the Old Economic Models – A Response to Daron Acemoglu’s ‘The Simple Macroeconomics of AI’. SSRN: https://ssrn.com/abstract=5077217.
- Shalaby, A. (2025d) The 2D Economy Is a Dead Horse-The Digital Sustainable Growth Model is Disrupting the Traditional Macro-Microeconomics in the 3D. SSRN: https://ssrn.com/abstract=
- Shalaby, A. (2024a). New Model for Digital Sustainable Growth: Insights from Human Biology and Surgical Approach – A Retrospective Analysis of 15 Years of Socio-Economic Innovations at the Human Information Technology Lab, Finland. DESD, 2, 14. DOI: https://doi.org/10.1007/s44265-024-00038-1.
- Shalaby, A. (2024b). Digital Sustainable Growth Model (DSGM): Achieving Synergy Between Economy and Technology to Mitigate AGI Risks and Address Global Debt Challenges. Journal of Economy and Technology. DOI: https://doi.org/10.1016/j.ject.2024.08.003.
- Shalaby, A. (2024c). Classification for Digital and Cognitive AI Hazards: Urgent Call to Establish Automated Safe Standards for Protecting Young Human Minds. DESD, 2, 17. DOI: https://doi.org/10.1007/s44265-024-00042-5.
- Shalaby, A. (2024d). Leveraging the Digital Sustainable Growth Model (DSGM) to Drive Economic Growth: Transforming Innovation Uncertainty into Scalable Technology. Journal of Economy and Technology. DOI: https://doi.org/10.1016/j.ject.2024.09.003.