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........

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