For Pakistan, this is not an academic dispute. Political leaders and planners repeatedly make choices about taxation, subsidies, privatisation, trade, interest rates and public investment under severe fiscal constraints and weak institutions. Policies imported from richer economies can fail when they assume administrative capacity, competitive markets or accountable institutions that do not exist. Equally, invoking “local conditions” can become an excuse for protecting powerful interests from reform. Pakistan needs economists who can distinguish evidence from doctrine, examine who gains and who pays, and test prescriptions against the country’s political economy not merely reproduce models or cite international consensus.
The central failure of economics education is not the use of unrealistic assumptions. Every science simplifies reality. The deeper failure is institutional: the profession has too often failed to distinguish useful abstractions from assumptions that acquire authority through repetition, prestige and policy adoption. Models are indispensable, but a model built to isolate one mechanism can mislead when treated as a description of the whole economy. A conditional proposition becomes a universal rule; a benchmark becomes a prescription; and a prescription survives evidence that should have forced its revision.
John Maynard Keynes understood the political force of economic ideas. In The General Theory (1936), he wrote that “the ideas of economists and political philosophers, both when they are right and when they are wrong, are more powerful than is commonly understood.” Economists do more than interpret events: they shape which choices governments consider legitimate, which costs unavoidable and whose interests take priority. Dani Rodrik offers a necessary corrective to blanket attacks on theory. “Models are never true; but there is truth in models,” he wrote in Economics Rules (2015). The task is to identify which model illuminates which problem, under what conditions and with what limits. Trouble starts when those conditions vanish from policy debate.
As Cambridge economist Jostein Hauge argues, orthodox economics often mistakes a variety of subjects for a diversity of thought. A curriculum may cover labour markets, trade, monetary policy and development while interpreting them through much the same lens. Orthodox economics has tended to privilege mathematical formalism and the claim, explicit or implicit, that analysis can be neutral and insulated from politics; heterodox approaches admit a wider range of methods and schools. This is a distinction, not a verdict: neither orthodoxy is monolithic nor heterodoxy automatically sound. But the claim that heterodox economics is simply a political project begs a question: what common programme unites a Marxist, a Schumpeterian and an Austrian economist? Their disagreements are profound. Pluralism does not mean treating every school as equally persuasive. It means testing competing explanations against evidence rather than excluding them because they fall outside the dominant curriculum. The question is how certain ideas become authoritative, why their limits are neglected, and why failure prompts marginal adjustments rather than reconsideration.
How models acquire professional authority
Economics education is shaped by more than debate. Curricula, journal rankings, doctoral training, promotion criteria and professional networks determine which questions matter and which methods confer status. Mathematical formalisation and econometrics have improved precision, but they also reward questions that fit established techniques over problems whose historical, political or institutional complexity resists them. Paul Romer’s criticism of “mathiness” addresses this danger. In a 2015 American Economic Review paper, he warned that “Mathiness lets academic politics masquerade as science.” His target was not mathematics itself, but the use of formal language to blur the boundary between a mathematical result and the substantive claims built upon it. A model can be internally consistent yet ill-suited to the question; statistical significance alone does not establish causation. Technical sophistication can conceal these gaps from non-specialists, especially when backed by institutional prestige.
Marion Fourcade, Étienne Ollion and Yann Algan have documented the economics profession’s hierarchy, relative insularity and institutional influence. This does not invalidate its findings. It raises a harder question: what happens when the same institutions define acceptable analysis and control the careers of those who challenge it? This need not involve deliberate suppression. Ordinary incentives can produce the same result: researchers pursue publishable questions, teachers rely on established texts, policymakers want clear answers and institutions favour advice that can be communicated and implemented. A contingent approach can gradually acquire the appearance of consensus.
When a benchmark becomes a description
Perfect competition illustrates the process. The model assumes many buyers and sellers, adequate information, free entry and no individual firm able to influence prices. Under specified conditions, it yields important results about allocation and efficiency. As a benchmark, the model is useful. The distortion begins when students absorb it as the normal state of markets and treat monopoly or market power as exceptions, often attributed chiefly to government interference. Real markets are shaped by scale economies, patents, brands, network effects, control of distribution and unequal information. Firms influence prices and wages and can use political connections to shape market rules. Jan De Loecker, Jan Eeckhout and Gabriel Unger estimated a substantial rise in US markups between 1980 and 2016, although both measurement and interpretation remain contested. This does not mean every large firm is a monopoly or concentration is always harmful. It means private power deserves the same scrutiny as public power. If market failure is framed chiefly as a consequence of government intervention, corporate rent extraction and influence over policy disappear from view. A model shows what follows from assumptions; it cannot prove they describe reality. Claims about trade, taxation or regulation mislead when stripped of their conditions. The crisis that did not transform the profession
The efficient-market hypothesis, associated especially with Eugene Fama, holds that asset prices reflect available information, though its implications depend on which information set is assumed. It does not prove that bubbles are impossible or regulation unnecessary. Yet influential readings of market efficiency reinforced confidence that markets allocate risk well and that sophisticated institutions could manage exposures through mathematical models. Warnings existed. Robert Shiller questioned whether stock-price movements could be explained by subsequent changes in dividends. Sanford Grossman and Joseph Stiglitz showed that perfect informational efficiency creates an incentive problem: if prices already reflected all costly information, investors would have little reason to acquire it. Long-Term Capital Management, the dot-com boom and the 2007–09 crisis exposed different vulnerabilities. Leverage, correlated behaviour, fragile balance sheets and the interaction of mortgage lending with securitisation could turn losses into systemic distress. The Queen’s question at the London School of Economics in November 2008—why had nobody seen the crisis coming?—captured a failure of professional judgment. Some economists had warned of danger; influential institutions and policymakers gave those warnings too little weight.
The lesson is not to abandon mathematical finance. It is to model institutions, shifting expectations, balance-sheet constraints and the possibility that individually rational choices produce collectively disastrous outcomes.
Hyman Minsky’s financial-instability hypothesis offered a different account. During prolonged stability, borrowers and lenders grow more confident, financing becomes more fragile and leverage accumulates. Stability can therefore generate instability. The lesson is not to abandon mathematical finance. It is to model institutions, shifting expectations, balance-sheet constraints and the possibility that individually rational choices produce collectively disastrous outcomes. The crisis did change economics: financial frictions, credit and systemic risk gained attention. The stronger criticism is that reform often added mechanisms to existing frameworks without confronting why professional practice had underweighted them. Accountability is elusive when a model fails: responsibility can be assigned to assumptions, data, policymakers or supposedly exceptional circumstances. Each explanation may contain truth, but together they make it hard to specify what failure would justify abandoning a framework.
Money, inflation and the limits of technical advice
Monetary economics shows the gap between simplified teaching and banking practice. Elementary accounts often depict banks as intermediaries lending deposits supplied by savers. Related textbook explanations imply that central-bank reserves generate loans and deposits through a stable multiplier. The Bank of England’s 2014 paper Money Creation in the Modern Economy challenged this account: “Whenever a bank makes a loan,” it explained, “it simultaneously creates a matching deposit.” Lending is constrained by capital, liquidity, regulation, funding costs, creditworthiness and demand—not mechanically determined by a reserve ratio. In March 2020, the Federal Reserve reduced reserve requirements to zero. The textbook multiplier then ceased to be a useful guide, exposing how poorly it described actual lending.
Quantitative easing after 2008 exposed the same weakness. The Fed’s balance sheet grew from about $850 billion before the crisis to about $4.5 trillion; bank reserves rose from under $50 billion to about $2.8 trillion by 2014. A crude multiplier story implied that this should drive a surge in broad money and prices. Inflation instead remained below the Fed’s 2 per cent target for most of the 2010s. The Bank of England had bought £375 billion of assets by 2012, yet UK inflation fell to 0.0 per cent in 2015, among the lowest readings on record. The 2021–23 inflation surge reflected interacting demand, supply, energy and monetary forces. US inflation peaked at 9.1 per cent in June 2022; UK and euro-area inflation reached 11.1 and 10.6 per cent that October. Pandemic bottlenecks and the energy shock after Russia’s invasion of Ukraine were major triggers. Money growth also mattered: US M2 rose 26.9 per cent in the year to February 2021. Ben Bernanke and Olivier Blanchard concluded in 2023 that price shocks accounted for much of the initial US surge, while labour-market pressures persisted longer. Neither episode can be explained by one variable.
Milton Friedman’s claim that inflation is “always and everywhere a monetary phenomenon” should not be caricatured as saying every episode has the same immediate cause. The 1963 formulation specifies that inflation can be sustained only by money growing faster than output. Monetary conditions and expectations matter to persistent inflation, but the initial impulse may come from supply disruption, energy prices or exchange rates. Interest rates can restrain demand and second-round effects; they cannot produce energy or repair supply chains. Interest rates affect employment, investment, borrowing and public debt service, while benefiting some creditors and savers. Policy should be judged by likely effects, alternatives and the costs of inaction—not conformity to a model.
The politics hidden in economic advice
Universal prescriptions are especially hazardous in developing economies. Property rights, courts, tax administration, infrastructure and bureaucratic competence shape whether markets encourage investment or facilitate rent extraction. Institutions are not details that can always be fixed after liberalisation; they help determine whether reform works, who acquires assets and who pays. John Williamson coined “Washington Consensus” in 1989 for reforms he believed broadly supported in Washington for Latin America. The term later became shorthand for a wider market-oriented programme. Williamson’s original list was more qualified than many later versions, but subsequent experience exposed the limits of applying common prescriptions to economies with different financial systems, political structures and state capacities.
The 1997–98 Asian financial crisis showed the danger of capital flows meeting fragile balance sheets and weak supervision. IMF-supported programmes imposed demanding monetary and fiscal measures, whose design and effects remain contested. Malaysia introduced capital controls in 1998 alongside other stabilisation measures, challenging the claim that unrestricted capital mobility is always desirable. The IMF later accepted that capital-flow management measures can have a role in specific circumstances. Russia’s transition in the 1990s offered another warning. Privatisation amid weak law and regulation helped concentrate formerly state-owned assets in powerful private hands. The lesson is not that privatisation always fails, but that changing ownership does not itself create competition or effective institutions.
Economic advice also allocates risks and rewards. Mariana Mazzucato’s critique of innovation policy captures the issue as “socializing the risks and privatizing the rewards.” Public investment has helped create technologies and markets from which private firms later capture substantial gains. Whatever one makes of her wider programme, the political-economy question is unavoidable: who bears the risk, who receives the return and under what rules? Fiscal responsibility cannot be judged by a deficit ratio alone, detached from how public money is used and what productive capacity it creates. Nor is all public investment worthwhile: state intervention can protect inefficient firms, encourage corruption and waste resources. The test is whether institutions can set objectives, enforce conditions, measure results and withdraw support when it fails. Market reforms can support growth, but their effects depend on sequencing, state capacity and power. Models cannot settle these questions without evidence and institutional analysis.
From technical competence to intellectual accountability
A better economics education would not replace market orthodoxy with an anti-market creed. It would teach students to distinguish a model’s internal logic from its empirical performance and its suitability for a particular decision. Economic history and the history of economic thought should be core subjects, not peripheral additions. Students should study how theories emerged, which problems they addressed and how crises changed or failed to change the profession’s assumptions. Competing approaches should be tested against evidence, not ranked by their place in an academic hierarchy.
Financial institutions, market power, distribution and development should sit at the centre of core courses. Mathematics and econometrics remain essential, but as investigative tools, not badges of authority. Students should learn to identify assumptions, test causal claims, communicate uncertainty and explain what a model omits. Revision also extends beyond traditional modelling. In Economics in the Age of Algorithms, Sendhil Mullainathan argues that machine learning offers new empirical methods and may require foundational theories to change. New techniques matter only if they improve explanation, not merely novelty or complexity.
Ronald Coase made a related point in How Should Economists Choose? (1981): theory is not merely a device for prediction; it helps organise thought and explain what is happening. This standard demands more than technical competence. Economists must explain why results occur, identify when they may not recur and remain answerable to contrary evidence. The objective is not to abandon the blackboard but to stop a model’s authority substituting for the obligation to explain the world. Economics becomes more rigorous when its abstractions remain open to challenge and when the institutions that confer professional authority learn from failure.