It must be the beginning of the new university year that makes us — once again — think long and hard about our profession, its meaning and what, as economics educators and professionals, we are trying to achieve in the field of economics. Economics should not turn into an ivory tower devoted to beautiful models for their own sake; it should serve practical needs, and that requires a broad skill set grounded in a varied intellectual tradition.
Two recent pieces nudged this reflection into focus: Tim Harford’s latest column in the Financial Times and Aleksandr V. Gevorkyan’s essay, “What does it mean to be an economist?” Harford cautions against the “wrong kind of maths” in economics — technique that dazzles while drifting from the messy world we claim to study. It’s a reminder that elegance without empirical grip or institutional awareness turns into self-referential performance, not analysis. Gevorkyan, for his part, argues for a profession grounded in history, development realities, and ethical responsibility. His call is pragmatic and pluralist: economists should be problem-solvers embedded in real economies, not just model-builders admiring their own assumptions. Taken together, they sketch an agenda for the classroom and the workplace: less ritual, more reality; less ornamental formalism, more engagement with institutions, power, and lived constraints.
After reading Gevorkyan’s Substack, I told him it echoed a question I’d just fielded under the shadow of the “Ivory Tower” at Makerere University in Kampala, Uganda — not the cliché, but the actual main building that bears the name. A student asked a deceptively simple question: What skills do you believe are most critical for young finance professionals in Africa today and how should universities adapt their curriculum to meet future needs? My reply was simple: build on a broad theoretical base rather than a single orthodoxy, and anchor that breadth in the history of economic thought as it developed in Africa as well as elsewhere.
Africa’s own intellectual lineage provides ample examples. Institutions such as Samir Amin’s Dakar circle — Third World Forum and its sister networks around IDEP (African Institute for Economic Development and Planning) and later CODESRIA — consciously cultivated non-mainstream approaches that tied economics to decolonization, structural constraints, and social development priorities. A similar current ran through the University of Dar es Salaam, where a vibrant Marxist tradition shaped debate around policy after the Arusha Declaration. Think of Walter Rodney’s years teaching in Dar (1966-1968), the publication of How Europe Underdeveloped Africa (1972), and Issa Shivji’s class analyses that probed the limits of official “African socialism” in the 1970s. Economics at the University of Ghana leaned into development planning amid intense debates over the role of Marxism and state-led industrialization, with figures like Arthur Lewis in the mix. These weren’t armchair lectures; they informed arguments about production, distribution, and state capacity in newly independent African states.
Over time, that pluralist, developmentalist tradition lost ground to a narrow neoliberal common sense embodied in African neoliberal transformation: markets first, the state as fixer of “business climate,” society measured largely by GDP growth. Policy practice followed suit. Cost-recovery user fees spread in health and education under the Bamako Initiative, only to be partially reversed decades later after well-documented social costs. And when ”private sector” use is cited as proof of success (as the recent IFC report does), it typically bundles retail drug shops and non-profits with clinics; disaggregated data from fifteen countries show that once shops are excluded, private clinical care for the poorest collapses, and only about 3% of the bottom quintile saw a private doctor.
Privatization and PPP orthodoxy marched through utilities and water, with mixed to poor results in several African cases (Tanzania, Ghana, Gabon and Nigeria), prompting rethinks and reversals. Meanwhile, “ease of doing business” benchmarking shaped reform scripts long after the flagship index was scrapped for data manipulation, its deregulatory logic lingering in successor exercises and domestic scorecards. Add the persistent tilt toward austerity-first fiscal consolidation and inflation-targeting orthodoxies, often amid shallow capital markets and external shocks, and you get policy toolkits that prioritize formal indicators over social development content, leading to what Joseph Stiglitz and colleagues termed “growth without quality and development.”
Range before doctrine
So my answer began here: don’t let any single school of thought trap your horizons. Standard curricula supply useful tools, but they rarely capture the structural realities of late-industrializing economies. Add depth with post-Keynesian macro, Marxist political economy, dependency and world-systems analysis, and institutional economics. That isn’t ideology shopping; it’s context. Each lens spotlights different frictions — market power, external constraint, unequal exchange, institutional capacity — and you need the full spectrum to diagnose real problems and to see who wins and who pays when policies are sold as “neutral.”
This is exactly where I converge with Gevorkyan. The cure is curricular: give students a guided tour across traditions, then insist they connect macro frameworks to actual institutions and test claims with data that reflect African structures rather than borrowed templates. From there the skills list writes itself: theoretical range anchored in African debates; applied political-economy literacy; serious quantitative competence; and sectoral fluency in how finance really works in health systems, utilities, municipal investment, and trade logistics. Rebuild that mix and you recover economics’ social-development drive while staying rigorous enough to change policy rather than merely comment on it.
Math used properly
This is also where I converge with Harford, who ends his critique with a simple plea: don’t turn our backs on mathematics. The issue isn’t math; it’s using the right math, in the right way, for the right problems.
Two long-standing cautions apply. First, results are hostage to assumptions: as Dani Rodrik argues in Economics Rules, with a convenient premise, even an undergraduate student can generate a convincing model and “prove” almost anything. Second, there’s often a mismatch between the technical complexity of the mathematics employed and the payoff, where elaborate proofs certify what common sense already suspected for a long time. Neither is an argument against math (nor against questioning common assumptions!); both are arguments for using it on the right questions with transparent premises.
So, my advice to students was straightforward: policy is a knife fight carried out with numbers. Build deployable fluency in statistics and econometrics: causal identification basics; panel methods; forecasting and scenario analysis; risk modeling; cost-benefit and cost-effectiveness frameworks. Keep clean data, reproducible code, and versioned workflows. If you can’t interrogate a result, you can’t defend it or overturn it. The point isn’t the toolset itself but how tools become policy: what phenomenon you measure, for whom, and to what end.
Which leads to a more uncomfortable question. Who would object to better tools for measuring economic phenomena? Almost no one. The real argument is about the choice of phenomena and purposes. As Branko Milanović quips when he wonders whether even Lenin might endorse parts of IMF surveillance if they foster sound policy, the issue isn’t “discipline” itself but its aim: financial discipline for what, and for whom? Does the fiscal space created expand broad-based welfare or mostly protect the top decile’s claims?
Know the plumbing
Whether it tilts one way or the other depends on institutions and implementation. It’s important to know the plumbing: how banks in your region actually price risk; how credit registries and collateral laws shape lending; how FX regimes and shallow capital markets steer real investment; how public-investment management, guarantees, and blended-finance structures crowd risk in or out. In many African financial systems, pervasive credit rationing is the norm: with thin information, weak collateral, and high monitoring costs, lenders cap quantities rather than raise prices, systematically underprivileging entire classes of investment — especially SMEs — regardless of their social return. This is where method meets reality. Broaden the toolkit beyond brittle comparative statics to approaches that fit institutional thinness and fat-tailed shocks: simulation, network analysis, agent-based models, and experimental or behavioral evidence. The goal isn’t fancier math; it’s understanding how systems behave when data are noisy, incentives misaligned, and frictions are everywhere.
Then add political-economy literacy. Balance sheets sit inside power structures, so debt sustainability is not just a ratio but a negotiation over who absorbs adjustment. Understand how IFIs, conditionalities, credit-rating dynamics, and the politics of state capacity shape the feasible set. Ask the uncomfortable questions: do IFI-promoted (or imposed) policies serve longer-term development interests or merely clear short-term bottlenecks? To what extent do they reflect aid conditionality rather than real national needs? Is it possible that well-intentioned “good Samaritans” are steering us into a trap? As Hansen and Twaddle asked of Uganda’s 1990s reforms, to what extent did donor demands reflect donors’ interests rather than Ugandans’? And as Branch argues, some World Bank projects in the country’s north enabled the construction of a security state. I develop this risk from a peripheral perspective elsewhere.
Policies that seem to work in rich, high-capacity settings often misfire where enforcement is patchy, informality is large, and external dependency rewires incentives. Read incentives, map veto players, and trace distributional effects up front; otherwise you design elegant policies for imaginary countries.
Advice with money attached
Which brings us to the obvious follow-up: what to do with advice that arrives attached to financing? The question I received was blunt: should young finance professionals challenge recommendations from the IMF and the World Bank when money rides on compliance? Short answer: engage critically, not reflexively. Much of what these institutions propose is technically sensible and can support better cash management, debt transparency, and macro stability (to make even Lenin happy). But uncritical adoption can entrench pro-cyclical austerity or deepen external dependence.
Track records underscore why a salt shaker is mandatory: over 2000–2014, an analysis reported in The Economist found that the IMF’s two-year-ahead global growth forecasts were off by about 2.8 percentage points on average, only marginally better than wide-range guesswork and roughly comparable to assuming a constant 4% growth each year. If that’s the hit rate on something as central as growth, treat glossy diagnostics and model-based packages from the IMF, World Bank, or AfDB as inputs, not instructions. The task is to translate generic templates into country-specific strategies that widen domestic fiscal and financial space while protecting investment, employment, and basic services.
Habit of inquiry
Finally, my advice was to develop and maintain a habit of inquiry. Modern economics and finance are so specialized that even well-meaning colleagues can talk past each other, and it’s easy to stay in a comfortable niche. Try, deliberately, to step outside it. Keep a running file of puzzles from your own economy: why SME credit stalls despite guarantees; why FDI clusters without deep supply-chain linkages; why inflation prints diverge from the headline narrative. Build small models, test with local data, talk to practitioners, iterate. Treat tidy claims as hypotheses to be checked rather than truths to be repeated. Curiosity and evidence should outvote habit.
That, to me, is the compact: less ritual, more reality. If we refuse the ivory tower in both senses — the metaphor and the building — and train economists who can navigate theory, data, and institutions with equal confidence, we might actually earn our keep.