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Economics for an uncertain world

October 2023
World Development Online first(5)

DOI:10.1016/j.worlddev.2023.106426

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Authors:

Ilene Grabel

University of Denver

Ian Scoones

Institute of Development Studies

Uncertainty, where we do not know the likelihood of future events, dominates our world. This article examines how economics as a profession and discipline can address uncertainty. From Frank Knight to John Maynard Keynes to Friedrich von Hayek to George Shackle, economics has highlighted the importance of uncertain knowledge and distinguished this from calculable risk. In this article we show how such insights were lost through the rise of narrow neoclassical thinking and were excluded through the emergence of a dominant economics of control that rose to prominence during the twentieth century and especially in the neoliberal era. However, through a range of perspectives in economics that emphasise the importance of complexity, informality , positionality and narratives, uncertainty is once again being embraced within an increasingly heterodox economics. In many ways, this chimes with the work of Albert Hirschman who, starting from the mid-1960s, emphasised the importance of addressing uncertainty in development theory and practice. Through two examples on pastoral development and global financial governance, we highlight the continued relevance of Hirschman's thinking on the importance of adaptation, flexibility and learning-by-doing as responses to uncertainty and for the development of reliable, robust approaches to development policy and practice. In conclusion, we argue that economics theory, methodologies, professional practice and training need to change, recovering some of the insights from previous generations of economic thinkers and practitioners, in order to reinvent an economics appropriate for our uncertain world.

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World Development 173 (2024) 106426

Available online 11 October 2023

Economics for an uncertain world

George DeMartino

, Ilene Grabel

, Ian Scoones

Josef Korbel School of International Studies, University of Denver, Denver, CO 80208, USA

Institute of Development Studies, University of Sussex, Falmer, Brighton, BN1 9RE, UK

ARTICLE INFO

Keywords:

Economics

Uncertainty

Irreparable ignorance

Pastoralism

Global nance

Albert Hirschman

ABSTRACT

Uncertainty, where we do not know the likelihood of future events, dominates our world. This article examines

how economics as a profession and discipline can address uncertainty. From Frank Knight to John Maynard

Keynes to Friedrich von Hayek to George Shackle, economics has highlighted the importance of uncertain

knowledge and distinguished this from calculable risk. In this article we show how such insights were lost

through the rise of narrow neoclassical thinking and were excluded through the emergence of a dominant

economics of control that rose to prominence during the twentieth century and especially in the neoliberal era.

However, through a range of perspectives in economics that emphasise the importance of complexity, infor-

mality, positionality and narratives, uncertainty is once again being embraced within an increasingly heterodox

economics. In many ways, this chimes with the work of Albert Hirschman who, starting from the mid-1960s,

emphasised the importance of addressing uncertainty in development theory and practice. Through two exam-

ples on pastoral development and global nancial governance, we highlight the continued relevance of

Hirschman’s thinking on the importance of adaptation, exibility and learning-by-doing as responses to un-

certainty and for the development of reliable, robust approaches to development policy and practice. In

conclusion, we argue that economics theory, methodologies, professional practice and training need to change,

recovering some of the insights from previous generations of economic thinkers and practitioners, in order to

reinvent an economics appropriate for our uncertain world.

1. Introduction

Four moments; four challenges for economics. On 15 September

2008, bankers emerged from Lehman Brothers in New York City car-

rying boxes of their possessions; a massive nancial crash was unfolding

with impacts that reverberated across the world. In November 2019, a

novel coronavirus was identied in Wuhan, China; soon a global

pandemic was declared, which resulted in a huge number of deaths,

widespread illness and massive economic damage globally. On 9 August

2021, the rst report of the International Panel on Climate Change’s

sixth assessment was released; the UN Secretary General declared ‘code

red for humanity’, as climate chaos wreaked havoc from droughts,

oods, wildres and more. On 24 February 2022, Russia invaded

neighbouring Ukraine, confounding predictions from most pundits, with

the war resulting in major shifts in the global economy and a devastating

international food crisis.

What characterises each of these moments (and many more), and

why is this a challenge for economics? The short answer is ‘uncertainty’.

Uncertainty arises whenever the future cannot be predicted owing to the

ontological properties of the domain under consideration or when

knowledge about such properties is lacking.

When the relevant

domain—whether the social or natural world—is dened by complex,

non-linear systems, the consequences of any intervention are indeter-

minate (Stirling, 2010; Scoones, 2019; Scoones & Stirling, 2020; Stirling

& Scoones, 2020). While in some respects, all these events were foretold,

the details of what would happen, where and to whom could not be

predicted. As a result, they all unleashed a questioning of what can be

forecast and managed and what cannot, highlighting the importance of

* Corresponding author. Address: University of Sussex, Falmer, Brighton, BN1 9RE, UK.

E-mail addresses: George.DeMartino@du.edu (G. DeMartino), Ilene.Grabel@du.edu (I. Grabel), i.scoones@ids.ac.uk (I. Scoones).

Aleatory uncertainty refers to unpredictable variability in the system and is a fundamental property of the system. Epistemic uncertainty arises from a lack of

knowledge of the system, meaning its properties cannot be predicted (Walker et al., 2003). Ontological uncertainty is where there is a fundamental lack of knowledge

about what exists in the world, making modelling and statistical analysis impossible (Spiegelhalter, 2017). In practice all types of uncertainty co-exist and interact. In

this article, we dene uncertainty as the condition when there is lack of knowledge about the likelihood of outcomes, while ignorance is when we don’t know the

likelihoods nor the range of possible outcomes (Stirling, 2010).

Contents lists available at ScienceDirect

World Development

journal homepage: www.elsevier.com/locate/worlddev

https://doi.org/10.1016/j.worlddev.2023.106426

Accepted 1 October 2023

World Development 173 (2024) 106426

taking uncertainty seriously.

Pushing back against the conventional wisdom of development

economists of his day, Albert Hirschman recognised the problems (and

opportunities) presented by ontological complexity and uncertainty. He

warned his colleagues in both policymaking and academia that neither

the economies of the Global North nor the Global South were simple

systems that could ever be adequately represented by standard para-

digmatic thinking (Hirschman, 2013 [1970]; see below). In arguing for a

reappraisal of the importance of uncertainty in today’s world, in this

article we highlight the many important insights of Hirschman and, in

turn, argue for a revived and recast economics for an uncertain world.

2. What is uncertainty and why is it important?

Following Frank Knight (1921), uncertainty is distinguished from

risk, where the full range of possible outcomes are accessible and can be

assigned known probabilities. Risk presumes that the social world is

characterised by ergodic systems, such as at the casino where all possible

outcomes are dened in advance, along with the odds. But what if,

instead, Douglass North (1999:3) is correct in claiming that “the world

we live in is not an ergodic world… For an enormous number of issues

that are important to us, the world is one of novelty and change; it does

not repeat itself.” What if uncertainty and not risk is “written into the

script of life” (Nowotny, 2015:1)? Epistemic insufciency, where we

cannot know all that will or even can happen, we argue, must be central

to economic enquiry. As Brian Loasby (1991:1) puts it, “the foundation

for useful economic theory must be incomplete knowledge, or partial

ignorance.”

Uncertainties take on different forms of what is termed ‘irreparable

ignorance’ (DeMartino, 2022:77-8). In the future we might come to

know some things we don’t know now but only after the moment when

the knowledge was needed to make a consequential decision. George

Shackle (1972/1992: 86) put it this way, “[The] validity of knowledge of

general principles is independent of the historical calendar,” he writes,

“but the question: What is the best action? Is wholly dependent on the

unique historical situation; and any knowledge of that situation, which

is lacking when it is needed, is effectively lacking forever and is forever

too late.” Alternatively, knowledge required to make the right decision

can sometimes only be learned by making the decision, when it is too

late to reverse course. The famished hiker asks, “are these berries food,

or are they poison?” Only the act of eating will answer the question.

Finally, there is the domain of the in-principal unknowable—the sort of

ignorance that John Maynard Keynes referred to when he spoke of “the

prospect of a European war … the price of copper and the rate of interest

twenty years hence, or the obsolescence of a new invention …”. As

Keynes famously put it, “about these matters there is no scientic basis

on which to form any calculable probability whatever. We simply do not

know …” (1937: 213–14; emphasis added). Irreparable ignorance is to

be distinguished from what US Defence Secretary Donald Rumsfeld

referred to as the “unknown unknowns – the ones we don’t know we

don’t know”.

Awareness of the presence of unknown unknowns war-

rants intensied research to discover what is not yet known, on the

presumption that it can in fact be discovered. But if ignorance is irrep-

arable, then further research cannot solve the epistemic problem.

Instead, the practice of searching for the unknowable can end up

generating fake knowledge that can badly mislead.

Uncertainties of different kinds are a challenge for both theory and

methodology in conventional economics, especially the mainstream

neoclassical-Keynesian synthesis that has predominated in textbooks

and policy advice for much of the twentieth century and since.

Complicating matters further, uncertainties can also obscure our

knowledge of the future, present and even the past, owing to irresolvable

epistemological challenges in discerning causality./

The standard approach of much economics however relies on as-

sumptions about equilibrating mechanisms, stability, well-behaved

probabilities, predictability, rational expectations and the achiev-

ability of control (Davidson, 1982; Colander, 2011; Kay & King, 2020).

Given our daily experience of unexpected, even shocking, events in the

world, such assumptions are surprising. But for over a century, the

pursuit of mathematical tractability and the use of deterministic models

relegated discussions of uncertainty to the periphery of the economics

profession. Economists have too often presumed that risks are calcu-

lable, and that predictions about policy outcomes can be made. Uncer-

tainty, where neither the range of potential future outcomes nor their

likelihoods are known, has been repressed in much economic analysis

(Kay & King, 2020).

This article therefore points to the necessity of recognising uncer-

tainty in development economics theory and practice. Doing so, we

suggest, requires reclaiming earlier strands of thinking that have become

obscured by the predominant versions of economics over the past cen-

tury, while highlighting contemporary conceptual and methodological

innovations that break with the orthodoxy. In particular, we focus on the

insights of Hirschman, who, perhaps more than any other twentieth

century development economist, grappled with the limits to knowledge,

and to expert control. As a journal length piece, all sections are neces-

sarily short and much, much more could be said, but we hope that the

article sufces to provoke, inspire and encourage a re-centring of un-

certainty in development theory and practice, reviving some of the key

insights from Hirschman and others.

3. The illusion of control

The emerging neoclassicals of the late nineteenth century discovered

a general equilibrium framework, borrowing heavily from physics, that

would guide standard economics throughout the next century (Mir-

owski, 1989). The architects of the approach were prepared to make

whatever assumptions were required to sustain it. In Leon Walras’

general equilibrium framework competition between rational actors

with full knowledge of all possibilities conducted frictionless exchange and

generated determinate prices and quantities for all goods (Walras, 2014

[1900]). Arthur Pigou later published The Economics of Welfare (2017

[1920]), which laid the foundations of a more quantitative, equilibrium-

centred welfare economics that enabled policy assessment (Colander &

Freedman, 2018). The ‘moral geometry’ that subsequently emerged in

the New Welfare Economics of the 1930s took the form of unambiguous

decision rules (DeMartino, 2022). Combined with the general equilib-

rium framework, the Kaldor-Hicks potential Pareto test, cost-benet

analysis and social welfare functions all generated denitive policy

conclusions, where uncertainty was treated as nothing more than

calculable risk (DeMartino, 2022). In the face of risk, policy aimed to

maximise ‘expected utility’—typically dened as the sum of all potential

policy payoffs weighted by their respective known probabilities. Even in

contemporary welfare economics this strategy continues to predominate

(Adler, 2019).

Macroeconomics followed suit. The exploration of questions of in-

dustrial production, employment, income distribution and the like

https://www.youtube.com/watch?v=REWeBzGuzCc.

The ‘fundamental problem of causal inference’ (Holland 1986) arises from

the fact that discerning causality would require the ability to run history twi-

ce—once with the event we probe for causal impact included in the ow of

events, and a second time with that event excluded. But of course, history runs

just once—and that fact requires researchers to simulate multiple runs of his-

tory through counterfactual analysis. Research methods seek to discover the

right counterfactual, so as to be able to infer the right causal relation. But the

certainty of causal claims is undermined by the inevitable ctional nature of all

counterfactuals (see DeMartino, 2021).

G. DeMartino et al.

World Development 173 (2024) 106426

employed computable general equilibrium and dynamic stochastic

general equilibrium models. These “post-real” (Romer, 2016) ap-

proaches largely banished questions of uncertainty, yielding deeply

inadequate predictions. Macroeconomics failed regarding the crisis of

2008 not because it did not predict the crisis, but because its most so-

phisticated models did not countenance even the possibility of a crisis

(Krugman, 2009).

Twentieth

century economists went to extraordinary lengths to sus-

tain the idea that they could make dependable predictions of policy

effects. The required epistemic presumptions were heroic. By the 1950s

Milton Friedman announced the emergence of a ‘positive economics’,

which could be “an ‘objective’ science, in precisely the same sense as any

of the physical sciences” (1953: 4), where generalisable laws could be

elaborated through careful modelling and quantitative analysis of

assumed ‘subjective probabilities.’ In Price Theory, Friedman explicitly

dismissed as ‘invalid’ Knight’s distinction between risk and uncertainty,

claiming that “we may treat people as if they assigned numerical proba-

bilities to every conceivable event” (Friedman, 2007, 282; quoted by Kay &

King, 2020: 74; emphasis added; see also Friedman & Savage, 1948). By

mid-century Kenneth Arrow had adapted the then standard competitive

equilibrium model to account for the fact that individuals and com-

panies do not know what the future holds. For a competitive equilibrium

to exist he showed that everyone must prepare a list of all future states

that might occur, and that everyone must hold the same beliefs about all

future states (Arrow & Debreu, 1954). Domesticating uncertain knowl-

edge that would otherwise disrupt modelling in the analysis of

competitive equilibria therefore required making wildly unrealistic as-

sumptions (Ormerod, 1994: 89-90).

For those entrenched in the predominant neoclassical-Keynesian

synthesis, the fact that the models were laden with unrealistic assump-

tions was not seen as a deciency, as long as the models appeared to

provide convincing guides for policymaking (Friedman 1953/66). As

Friedman’s colleague at Chicago, Gary Becker (1976: 5), put it, “The

combined assumptions of maximizing behavior, market equilibrium,

and stable preferences, used relentlessly and uninchingly, form the

heart of the economic approach.” Here there was no room for Knightian

uncertainty. The result was a severely reductionist equilibrium thinking

centred on an abstract version of the economy where stick-gure eco-

nomic agents make decisions based on preferences that are pre-

determined, with no transaction costs or externalities (Coyle, 2021: 38),

and with considerations of uncertainty excluded or domesticated

(Hodgson, 2011).

This ‘objective’ science of economics that reduced uncertainty to

calculable risk was advocated by the most inuential economists from

the UK (such as John Hicks (1939) and Nicholas Kaldor (1939))

and the

US (such as Abba Lerner (1944)). Lerner in particular was instrumental

in persuading economists that dependable policy assessment based on

scientic rules derived from economic theory could guide policy

(Colander, 2003: 201-2; Colander & Rothschild, 2010). Lerner’s key

book, The Economics of Control, set the tone for many decades, becoming

entrenched for example in Paul Samuelson’s inuential textbook

(Samuelson & Nordhaus, 1985). The title of Lerner’s book was apt. The

hunt for control was central to the economic project. Economists sought

to create and sustain a theoretical architecture that could yield unam-

biguous policy assessment and clear direction to policymakers. If

correctly applied, it was thought, the economy could be directed to-

wards benecial outcomes—static and dynamic productive efciency,

full employment and social betterment dened in terms of rising

welfare.

The idea of a universal, unimpeachable science of economics that

could inform policy, without worrying overly about uncertainties and

complexities, was as important for economic practice and economists’

inuence in the Keynesian-planning era of the post-war years as it was

throughout the subsequent neoliberal era, from the 1970s into the early

2000s. However, the control project was always threatened by a latent

recognition of uncertainty. Control presumes epistemic adequacy—the

economist could not control what the economist could not know. And

therefore a fundamental choice had to be made—between representa-

tions of the economy as a site of irreparable ignorance and a represen-

tation that repressed uncertainty in order to facilitate tractability. For a

profession craving policy inuence, the choice was obvious. Knightian

uncertainty was displaced by the presumption of calculable risk,

allowing the profession to exploit the appearance of adequate knowl-

edge to extend its inuence over public affairs.

Nowhere was this strategy more apparent than in the eld of

development economics. From the post-war period through the neolib-

eral revolution, economists purported to have the authority to dene

‘development’ in low-income countries and sufcient knowledge to

ascertain which interventions to pursue to achieve it. As Robert Nelson

(2001: xx) put it, “Correctly understood, [economic] messages [were]

seen to be promises of the true path to a salvation in this world—to a

new heaven on earth.” At a speech at the World Bank-IMF annual

meeting in 1991, Larry Summers, then Chief Economist at the World

Bank, argued that “the laws of economics, it’s often forgotten, are like

the laws of engineering…. There’s only one set of laws and they work

everywhere.” He continued, “One of the things I’ve learnt in my short

time at the World Bank is that whenever anybody says, ‘but economics

works differently here,’ they’re about to say something dumb” (cited in

Hardy, 2019: 18). This kind of hubris fueled the fervent closed-

mindedness of the neoliberal reformers across the Global South and in

the post-Soviet transition economies of the 1990s too (Murrell, 1993).

4. Dissenting voices—then and now

Many self-aware economists have of course wrestled with the

epistemic problem and the challenge presented by uncertainty. For

example, Herbert Simon (1990) offered the useful concept of ‘bounded

rationality,’ which stems from a related recognition that the social world

is inherently complex and only partly intelligible. Even some of the ar-

chitects of the marginal revolution of the late 1800s recognised the

challenge uncertainty presented to the emerging science. William

Stanley Jevons wrote, “If we wished to have a complete solution of the

[economic] problem in all its natural complexity, we should have to

treat it as a problem of motion – a problem of dynamics.” But Jevons

recognised that that kind of knowledge was unavailable. To make

analysis tractable, he opted for a “purely statical” approach to the

analysis of the “action of exchange,” rather than attempting a more

difcult analysis of the economy as a complex system (quoted by Keen,

2021: 138).

Teasing out the distinction between uncertainty and risk, Chicago

economist Knight emphasised in 1921 that “It is a world of change in

which we live, and a world of uncertainty” (Knight [1921] 2014: 199).

In his view, the economic actors about whom economists theorise face

interminable and irresolvable epistemic constraints. They must rely on

“images of a future state of affairs,” “common sense,” “intuition,” “su-

perstitions,” “hunches,” the “subconscious” and “convictions or opin-

ions” ([1921] 2014, 201, 229– 30). Keynes agreed, while Shackle

provided one of the most thorough analyses of the epistemic problem,

arguing that economic agents confronting the future face “the void of

unknowledge” (1992[1972]: xi). This insight led Shackle to advance the

radical claim that economics must be understood not as the study of

objective facts about the world, like prices and quantities, but of ideas

about that world. “Economics is about thoughts,” he wrote. “It is

Like many leading economists of the period, Kaldor did not have a xed

view over time. In the period from the early 1930s until the later establishment

of a narrow neoclassical-Keynesian consensus view there was much debate

about the value and limits of equilibrium perspectives. For example, before

moving to Cambridge, Kaldor was engaged in intensive debates between Hayek,

Myrdal and Knight during the 1930s (Telles, 2023). He later reected on the

limits of an equilibrium perspective (Kaldor, 1972).

G. DeMartino et al.

World Development 173 (2024) 106426

therefore a branch or application of epistemics, the theory of thoughts”

(Shackle, 1972/1992: xx). Dani Rodrik (2017: 159, 163) emphasises the

same point today: “Yet without ideas… the concept of self-interest is

empty and useless… In truth, we don’t have “interests.” We have ideas

about what our interests are” (cf. Knight, 2014[1921]: chapter 7). As

Rodrik (2007, 2015) argues, there are many models from which to

choose when confronting particular economic problems. Unfortunately,

such is the inuence of the mainstream view that side-lines consider-

ations of uncertainty, the pursuit of optimality continues as if the world

were adequately knowable - as if we can know which model to apply in

any particular context.

However, countering such condence, various leading economists

have highlighted the epistemic challenges of economic science. Nearly a

century ago, Lionel Robbins noted, “What precision economists can

claim at this stage is largely a sham precision. In the present state of

knowledge, the man who can claim for economic science much exacti-

tude is a quack” (1927: 176). Almost fty years later, Friedrich von

Hayek remarked in his 1974 Nobel lecture, “I prefer true but imperfect

knowledge, even if it leaves much indetermined and unpredictable, to a

pretence of exact knowledge that is likely to be false” (Hayek, 1975:

438). As he explained in his famous article, ‘The use of knowledge in so-

ciety’, economists must recognise ‘unorganised’ knowledge, “the

knowledge of the particular circumstances of time and place” (Hayek,

1945: 521; see also Hayek, 1978). In this context Hayek emphasised the

importance of the tacit knowledge that individuals glean from and apply

to their worlds. Tacit knowledge comprises know-how, craft, sensibil-

ities and other forms of dispersed knowledge that are not easily articu-

lated, conveyed and appropriated by central authorities. This form of

knowledge cannot be codied in textbooks that convey abstract prin-

ciples, but instead must be discovered through trial and error. The

acquisition of tacit knowledge falls into the second category of irrepa-

rable ignorance: it can be gleaned only by taking decisions the effects of

which depend on the missing knowledge, and then facing the conse-

quences. It is knowledge that does not reveal itself easily; it must be

hard-earned through practice that is fraught with uncertainties.

De-

cades later, the famous Cambridge economist, John Hicks argued that,

“economic knowledge, though not negligible, is so extremely imperfect.

There are very few economic facts we know with precision” (1980: 1).

Today control economics is in turmoil. The orthodoxy has been

called into question by a new generation of micro- and macro-

economists who eschew the theory-laden axiomatic deductive models

and ‘blackboard proofs’ of assumed realities that dominated economic

thinking for many decades. Indeed, the profession has experienced a

critically important empirical turn over the past few decades (Angrist

et al., 2017). The new empiricism features ‘big data’-driven research,

‘natural experiments’ that arise as a consequence of actual events in the

world and ‘randomised control trials’ (RCTs), whereby researchers

apply a treatment in the eld to some groups but not to other similarly

situated control groups (Banerjee & Duo, 2011). In the same vein, in

lab experiments behavioural economists test the assumptions and logic

of economic propositions, while exploring how real human beings make

actual economic decisions (Kahneman et al., 1982; Ariely & Jones,

2008). At its best, the new empiricism has unsettled received wisdom

across policy domains by demonstrating just how wrong-headed are

models of the economy and society that reduce all processes and out-

comes to the simple workings of a small number of variables that can be

captured adequately in theory (Resnick & Wolff, 1987; Rodrik, 2015).

In addition, the empirical turn has encouraged engagements with

sociology, anthropology and psychology—elds that the mainstream in

the profession had long ignored, and that emphasise the salience of

factors that standard economics had frequently overlooked. Indeed, it is

increasingly unclear just where the boundaries that distinguish eco-

nomics from other elds now lie.

All this is to the good. But much of the new empirical work is aimed

at discovering causal connections in the very same way that the

axiomatic deductive methods did before. The mapping of assumed

causal laws via empirical methods can be exploited by control-oriented

economists and policymakers, reproducing the epistemic and policy

errors of previous generations. For instance, behavioural economists

often look to ‘nudge’ economic actors into making the ‘right’ decisions

by taking advantage of predictable biases in decision-making (Thaler &

Sunstein, 2019). Here, the economist is assumed to know best what

kinds of outcomes individuals should value (DeMartino, 2022: chapter

2). The problem of course is that, if the world is itself complex and if

inscrutable individuals hold distinct, evolving values as they negotiate

unpredictable and changing worlds, then the new control methods are

apt to generate substantial unintended and unforeseeable consequences,

some of which may be deeply damaging to those whom economists

purport to serve.

If we confront irreparable ignorance of the sort discussed above, then

we cannot ever know the uniquely correct counterfactual that is

required to ascertain the causal effect of any particular intervention

(Donavan, 2018; van der Meulen Rodgers et al., 2020). RCTs warrant

particular attention in this regard. RCTs are sometimes thought to

demonstrate directly the causal effects of a policy intervention through

careful stratication in the construction of the treatment and control

groups. Provided one nds a statistically signicant difference between

the average outcome of a treatment and no treatment, the inference is

drawn that the policy intervention caused the observed outcome. As

Deaton and Cartwright (2018:2) put it,

[RCTs] are taken to be largely exempt from the myriad problems that

characterize observational studies, to require minimal substantive

assumptions, little or no prior information, and to be largely inde-

pendent of ‘expert’ knowledge that is often regarded as manipulable,

politically biased, or otherwise suspect.

However, RCTs of course suffer the same challenges of inferring

causality in complex and uncertain settings as other methods, where

issues of both internal and external validity remain (Deaton, 2020).

There should be no automatic hierarchy of preferred method, but

diverse, complementary methods must be used when knowledges are

always plural and conditional under conditions of uncertainty.

In terms of dissenting voices, many heterodox traditions in eco-

nomics, especially those inspired by Knight, Keynes and Hayek, have

taken far better account of uncertainty and irreparable ignorance. Those

working broadly in the Austrian tradition have been amongst the most

strident critics of the epistemological assumptions of mainstream

These insights about complexities of knowledge and ignorance were

informed the Austrian contributions to the socialist calculation debate of the

1920s through to the 1940s (Adaman & Devine, 1996). They were famously

opposed by Oscar Lange, Abba Lerner, Maurice Dobb and other economists who

sought to justify ‘market socialism’ and other forms of economic planning.

Dobb, for example, argued against the ‘atomistic’ approach of neoclassical so-

cialist economists as this would, he suggested, result in short-termism and fail

to address uncertainties, which could only be accommodated through state-led

planning and coordination to facilitate investment in the economy. This posi-

tion however assumed that uncertainties could be objectively known and

addressed through planning, something that the Austrian school rejected.

Hayek instead focused on the relationships between knowledge and uncer-

tainty, highlighting tacit economic knowledge in particular (Adaman & Devine,

1996). In emphasising the distinction between a ‘taxis’ and a ‘cosmos’, he noted

how a taxis is a constructed order, “rationally designed to serve a particular

purpose” (Burczak, 2006: 40) but, by contrast, a cosmos is a spontaneously

emerging order; it arises “from regularities of the behavior of the elements

which it comprises” (Hayek 1978:74). Hayek challenged control-minded

economists – such as Dobb and others - to recognise that not all orders arose

from or required rational design. Instead, efforts to impose a taxis threatened a

naturally evolving cosmos, with damaging effects. His insights were discovered

anew in the context of the failure of Soviet planning and came to inform late

twentieth century efforts to transform planned economies into hyper-liberalised

market economies in which, it was hoped, tacit knowledge would lead actors to

pursue experiments that would promote economic development.

G. DeMartino et al.

World Development 173 (2024) 106426

economics. For example, Deidre McCloskey (1990) advances the Hay-

ekian point that economists cannot begin to know all that they presume

to know. In place of genuine knowledge, they too often sell “snake oil.”

Hence, policymakers following economists’ dictates cannot exert the

kind of control over economic affairs that many economists have pro-

moted. The ‘post-Keynesian’ tradition has been equally critical of the

epistemic framing of mainstream economics. They have taken up

Keynes’ own insights and pushed back with particular intensity against

any neoclassical-Keynesian synthesis, with its promise of guiding the

economy along stable, predictable growth paths. They argue that the

approach represses Keynes’ chief epistemic insight: that we cannot know

how private market actors will respond to stimuli. Some post-Keynesians

infer that the state cannot eliminate cycles and crises under a liberal

market order (Crotty, 2019) linked to long waves of often unpredictable

Schumpeterian innovation (Perez, 2003), while others emphasise the

sometimes epoch-shaping uncertainties that emerge in production pro-

cesses (Chang & Andreoni, 2020).

Ecological economics takes a different approach to addressing un-

certainty, highlighting how non-linear ows of resources, energy and

waste must be conceptualised within complex systems subject to

pressing local and planetary constraints (Common & Stagl, 2005; Raw-

orth, 2017). The approach goes beyond the narrower extension of neo-

classical presumptions in the eld of environmental economics, which

less ambitiously seeks to theorise and internalise externalities in eco-

nomic calculus. Ecological economics, by contrast, challenges the way

we think about the relationships between economy, ecology and human

values, examining interactions between domains with complex causal

relations where uncertainties emerge (Cartwright, 1980). Echoing ideas

from ‘post-normal science’ (Funtowicz & Ravetz, 1993, 1994), when

uncertainties prevail, values are plural, stakes are high and decisions are

urgent, ecological economics offers an opportunity to engage with sys-

tem complexity under uncertain conditions, where singular expert

models are insufcient and deliberation among ‘extended peer com-

munities’ is needed. An economics that accepts that there are plural

values associated with different ethical positions must accept that such

deliberation, enhanced by a range of methods such as disaggregated

multi-criteria approaches, is essential (Spash, 2013). Ecological eco-

nomics in this mode therefore offers a route to addressing the urgent

questions concerning sustainability (Daly, 2007; Kallis, 2019), (de-)

growth (Hickel & Kallis, 2020) and wider well-being (Brand-Correa

et al., 2022) in ways that are attuned to system complexity and

uncertainty.

The eld of complexity economics (and more recently, quantum

economics; see Orrell, 2018) presents a particularly stiff challenge to

standard, deterministic economics. Instead, complexity economics of-

fers insights into how non-linear systems operate. Here, instability is the

norm; any apparent equilibria are illusory and unstable, and dynamic

paths exhibit breaks, jumps and unpredictable behaviours (e.g.,

Ormerod, 1994; Beinhocker, 2006; Colander & Kupers, 2014; Gr¨

abner &

Kapeller, 2015; Arthur, 2015, 2021). For complexity economists, viable

models of the economy must reckon with “black swans” (Taleb, 2007) of

all sorts, recognising that the presence of unpredictable and even un-

imaginable events render useless attempts to predict economic futures

or to control economic ows and outcomes. Indeed, the approach calls

into question the very idea of economic causality, upon which standard

models depend. In Brian Arthur’s (2015: 1) words,

Complexity economics thus sees the economy as in motion, perpet-

ually “computing” itself—perpetually constructing itself anew.

Where equilibrium economics emphasizes order, determinacy,

deduction, and stasis, complexity economics emphasizes contin-

gency, indeterminacy, sense-making, and openness to change.

Further, narrative economics recaptures the insights of Shackle on

the epistemic nature of economics advanced decades before. From this

perspective, economic models construct narratives, replete with meta-

phors and imaginaries, which provide the basis for making sense of

complex, uncertain worlds (McCloskey, 1998; Bronk, 2009; Beckert,

2016; Akerlof & Snower, 2016). Narratives are essential as economic

actors look to navigate the economy, and yet they are irreducibly cti-

tious. Competing narratives are conditioned by emotions, collective

thinking, fads and fashions (Shiller, 2011; Tuckett, 2011), what Karin

Knorr-Cetina (2007) refers to as ‘epistemic cultures.’ The narrative

approach emphasises the tentative nature of economic modelling and

the reexivity of economic analysis (Sutton, 2002; Bronk, 2013; Beckert

& Bronk, 2018). Recognition of the existence of epistemically insecure

competing narratives undermines the hunt for one ‘optimal’ policy op-

tion, and instead provides the basis for making judgements about how to

act responsibly in an inescapably uncertain world.

What might be called post-structuralist economists have perhaps

gone furthest in highlighting that economic narratives are con-

stitutive—shaping the worlds we inhabit—rather than merely explana-

tory (e.g., Resnick & Wolff, 1987; Ruccio & Amariglio, 2003). From this

perspective, the misguided impulse to control can itself create unpre-

dictable disruptions. Meanwhile, feminist economists have challenged

the standard conception of ‘homo economicus’ as the universally appro-

priate model of economic identity and behaviour (e.g., Kabeer, 1994;

Nelson, 2004; Ghosh, 2012; Kuiper, 2022). Feminist perspectives

emphasise how positionality and social difference affect how we un-

derstand economic actors, the world they act in, and the goals they do

and should pursue. Like ‘stratication economics’ (Chelwa et al., 2022),

feminist analysis seeks to reveal biases that inform economic theory,

policy design, market interactions and economic outcomes and so

problematises standard claims to certainty.

In the wake of the 2008 nancial crisis – and in direct confrontation

with unexpected empirical realities - some mainstream macro-

economists have come to accept the severe epistemic limits under which

they work (e.g., Krugman, 2009). For instance, Kenneth Rogoff (2018)

writes that, “As any academic macroeconomist will tell you, the global

economy never ceases to be uncertain and unpredictable.” In the same

vein, Peter Orszag, Robert Rubin and Joseph Stiglitz (2022: 2) argue

that, “In our collective experience, scal policy should… be informed by

copious amounts of humility, particularly given the role of impossible to

predict events (including pandemics, wars, and bubbles).” These and

other macroeconomists are coming to recognise that deriving strong

claims of causality from econometric models of the economy is highly

problematic (Coyle, 2021: 100-1).

5. Uncertainties, development economics and the

“Hirschmanian mindset”

By the late twentieth century, some inuential economists had come

to dismiss the “need for development economics because, in the new

order, the laws of economics had universal validity without regard for

structural or historical difference” (Polanyi Levitt, 2022: 15).

Among the prominent dissenters to this view was Hirschman. He

worked across many disciplines and lived and conducted research in

many national contexts, although he is perhaps best known as a devel-

opment economist. His oeuvre provides a bridge between the array of

epistemic dissent emerging across economics discussed in the previous

section – with his work often preceding the blossoming of heterodox

economics by decades - and the eld of development economics and

practice.

While most development experts repressed uncertainty as they

crafted ambitious development plans, Hirschman chose to embrace it.

While his colleagues looked to infer policy strategy from blackboard

proofs, Hirschman’s mindset led him to celebrate the “possibilism” that

arises when we just cannot know what strategies will and will not work

(Hirschman, 2013 [1971]; see Lepenies, 2008). For Hirschman,

Grabel (2017: chapter 2) develops the idea of a Hirschmanian mindset in

greater detail than we can present here; see also Grabel (2019, 2022, 2023).

G. DeMartino et al.

World Development 173 (2024) 106426

epistemic limits provided a “bias for hope,” while his concept of the

“Hiding Hand” emphasised the vital role of experimentation and prag-

matic problem solving in response to unforeseen or underestimated

challenges.

In his view, learning (imperfectly) from others—what

Charles Lindblom (1959) referred to as “muddling through”—provided

the right approach to development implementation (Hirschman and

Lindblom (1971 [1962]).

For Hirschman, the development economist confronts an obscure

world that cannot ever be ‘known’ via universal theories, let alone

domesticated through social engineering. Hirschman embraced the

virtues of theoretical messiness and complexity - what Grabel (2017)

calls “productive incoherence” - over contrived coherence and parsi-

mony. He urged development practitioners to look at the “development

process in the small” and “immersion in the particular,” seeking spaces

for opportunistic interventions and innovation, and to push back against

seductive visions of grand institutional change (Hirschman, 1969: ix,

1967: 2). Hirschman emphasised modest, mid-range theories and em-

pirics, managing to combine intellectual boldness with humility. Against

the “development experts” (Hirschman, 1965; 1967: chapter 1) who

aspired to control, Hirschman embraced the autonomy and self-

determination of the communities that development economists pur-

ported to serve. Hirschman (2013 [1970]: 144) even wondered whether

expert meddling was “inspired primarily by compassion or by contempt”

for the lot of poorer countries.

Hirschman accepted Hayek’s view that much knowledge is tacit,

partial and dispersed. He accepted equally Knight’s, Keynes’ and Hay-

ek’s views that the future is fundamentally uncertain (Hirschman, 2013

[1970]; see Alacevich, 2014, 2021). For Hirschman, the outcome of any

intervention is unknowable in advance since it is always confounded by

the “balance of the contending forces that are set in motion” and the

totality of contextual circumstances at the time of the intervention,

neither of which was accessible to the researcher (Hirschman, 2013

[1970]: 150). In Hirschman’s view, the failure of development experts to

appreciate the severe “limits to ‘intelligibility’ of our complex world”

(Adelman, 2013: 238) led them to treat poorer countries as essentially

simple, manipulable systems that invited expert control (Hirschman,

2013 [1970]: 144). This orientation led him to an appreciation of

backward and forward linkages (associated with non-deterministic

structuralism and the virtues of unbalanced growth) often tied to un-

predictable side-effects that can induce new capabilities (Hirschman,

1969 [1958], 1967, 1973). In this and many other respects, Hirschman

anticipated a paradigm shift, just now under way, towards under-

standing the economy as a ‘complex adaptive system’ that features

constant evolution and abrupt shifts and, notably, the absence of suf-

ciently powerful equilibrating mechanisms (such as the Walrasian

auctioneer) that can be relied on to bring an economy in a disequilib-

rium state back into equilibrium (Kirman, 2016).

The recognition of uncertainty is especially crucial in settings where

informal, parallel, second, real, hustle or creole economies dominate (e.

g., MacGaffey, 1991; Browne, 2002; Meagher, 2010; Jones, 2010;

Thieme, 2018). This is the ‘indigenous capitalism’ of much of the world,

where uncertainty reigns. Here the standard Western market models do

not apply. Various attempts have been made to provide an alternative,

‘Southern’ perspective on economic thinking, including the Havana

Charter and the UNCTAD approach to economic development (see,

Reinert et al., 2016; Nissanke & Ocampo, 2019), as well as economics

approaches emanating from Ghandian or Islamic traditions, for example

(cf. Pani, 2001; El-Ashker & Wilson, 2006), or rooted in African contexts

(Mkandawire, 2001; Nasong’o & Ikpe, 2022). Emerging from different

settings, some of these have embraced uncertainty more centrally than

the mainstream Western canon.

The notorious failure of Gross Domestic Product measures to reect

the reality of economic activity especially in such contexts, for example,

is well known (Jerven, 2013); the result of inadequate and poorly

framed economic statistics, often the inheritance of colonial era thinking

and practice (Serra, 2014; Nyamunda, 2017). The Western gaze on so-

called developing economies misses important dimensions, as noted

long ago by Dudley Seers (1962) and Polly Hill (1986). Such framings

miss the ingredients for economic success as crucial aspects remain

hidden, as Deepak Nayyar found when revisiting the 1968 analysis by

Gunnar Myrdal in Asian Drama in the light of the Asian growth story

since (Nayyar, 2019; Myrdal, 1968).

As Hirschman argued, a more respectful approach that embraces the

complexity of actually-existing economies—as opposed to simplistic

model economies—is required, where uncertainty is always central. This

requires a different starting point, one rooted in the always contradic-

tory and transient economic practices and institutions – including the

pragmatic getting by and making-do of ‘debrouillardise’, a term used to

describe economic behaviour in the Democratic Republic of Congo and

elsewhere (Wild-Wood, 2007).

Immersed in these types of contexts, Hirschman’s epistemic com-

mitments and diverse experiences informed his distinct vision of

development. He advocated a development approach that would “stress

the unique rather than the general, the unexpected rather than expected,

and the possible rather than the probable” (Hirschman, 1971: 28). In the

words of his biographer Jeremy Adelman, Hirschman’s work is marked

by the view that “the study of social change, if it is to be helpful… should

rethink the typical reliance on predictions according to laws of change

and consider instead the analysis of possibilities and alternatives for

social change” (Adelman, 2013: 137). With Lindblom he argued that “It

is clearly impossible to specify in advance the optimal doses of… various

policies under different circumstances. The art of promoting economic

development… and constructive policymaking… consists, then, in

acquiring a feeling for these doses” (Hirschman & Lindblom, 1971

[1962]: 83–84).

In 1994, Paul Krugman took stock of the state of development eco-

nomics. He argued that the eld had only recently been “rescued” from

Hirschman and other like-minded thinkers. We argue the opposite: the

need to reclaim such thinking for a world of uncertainty. As others are

demonstrating across a range of heterodox and dissenting perspectives

discussed briey above, embracing uncertainty does not require aban-

doning economic methods, analysis and advice. It involves instead

searching for strategies that prove to be robust in the face of highly

variable, indeterminate, uncertain settings. In the spirit of Hirschman’s

inuential work, this requires breaking with approaches that are overly

prescriptive and deterministic – whether neoclassical models of indi-

vidualised economic actors in idealised markets; mechanistic Keynes-

ianism purporting to be able to map policy interventions onto

determinant outcomes; narrow forms of causal experimentalism and

paternalistic behaviourism, along with simplistic deterministic, struc-

turalist perspectives on capitalist development. As we discuss further

below, this shift has major implications for economics training, ethics

and professional practice, perhaps especially in the context of the

practice of ‘development’. To get at this we explore briey two very

different empirical sketches – pastoral development and global nancial

governance – from our own empirical research that both feature stra-

tegies that reect awareness of uncertainty, each drawing rmly on the

Hirschman tradition.

6. Navigating uncertainties in the worlds of pastoralism and

high nance

In the two sketches that follow, we focus on two very different sets of

actors that would certainly not be categorised together in most social

science research. The rst are East African pastoralists, seeking reli-

ability in highly variable dryland environments; the second are

The capitalisation is Hirschman’s The Hiding Hand has been the subject of

lively debate (e.g., see the collection in World Development, 2018, volume 103;

see also Alacevich, 2021: chapter 4); Grabel (2017: chapter 2) and Gasper,

1986.

G. DeMartino et al.

World Development 173 (2024) 106426

policymakers from the Global South who look to protect themselves

from global nancial instability. Their worlds are of course wildly

different. What they share is the fact that they face and must respond to

challenges posed by the ineradicable uncertainties they confront in

volatile, complex environments, where the stakes, though very different,

are high. In both cases we nd actors, who might be taken to have

limited agency, utilising many of the principles and practices discussed

by Hirschman. We therefore highlight the role of local knowledges, ad

hoc experimentation and innovation, learning-by-doing and learning

from others, along with pragmatic problem solving as a route to

increasing resilience and exercising autonomy. Finally, both sketches

highlight the initiatives of less powerful actors who entertain no illu-

sions that they can control their worlds.

6.1. Pastoralists and drought in East Africa

Drought is a recurrent feature of dryland areas, and pastoralists –

mobile livestock keepers who make use of extensive rangelands for their

livelihoods – are frequently heavily affected. From mid-2022 into 2023,

a drought across southern Ethiopia, northern Kenya and into Somalia

resulted in the loss of huge numbers of livestock, with major impacts on

food security for dryland populations.

Over the years, many development programmes have invested in

mechanisms for drought early warning and disaster response, including

offering a range of social protection and insurance programmes to

mitigate the effects of drought disasters. These solutions make use of

sophisticated satellite-based monitoring systems linked to climate

models to predict drought impacts, with early action responses based on

a range of anticipatory models. Such risk management approaches as-

sume that drought is a calculable risk that can be predicted and so

managed, with disasters averted (Johnson, Mohamed, Scoones, & Taye,

2023). However, investments in risk-based early warning and humani-

tarian and disaster response have often been found wanting (Buchanan

Smith & Davies, 1995; Caravani et al., 2021). Information derived from

such predictions are frequently not followed, as such information sys-

tems are not embedded in people’s day-to-day lives and practices

(Buchanan-Smith et al., 1994; Mohamed & Scoones, 2023a).

As the experience in 2022–23 has shown – along with many other

examples before – predicting drought is not straightforward; there are

many uncertainties involved. The much-improved large-scale climate

models may not ‘down-scale’ easily, making precise predictions for

particular places impossible (Ericksen et al., 2012). Many disasters

emerge through the compounded, cascading effects of multiple factors –

locust attacks, inter-ethnic conict, economic downturns and so on –

and context-specic responses are required. In 2022-23, pastoralists in

the Greater Horn of Africa had to deal with drought on the back of the

major impacts of the COVID-19 pandemic (Simula et al., 2021). Pasto-

ralists living in such settings are however well-practised in confronting

droughts, as part of a suite of other uncertainties.

Such responses, aimed at increasing reliability, include the redistri-

bution of animals through loans, splitting herds and ocks between

different sites, changing the species composition, ensuring supplemen-

tary feeding and watering, negotiating access to fodder in farmland or

protected areas, sales of certain animals and livelihood diversication to

gain other income sources (Mohamed & Scoones, 2023b). This is not just

a pattern of passive ‘coping’, but a deliberate, well-planned set of re-

sponses, all of which are central to ‘living with uncertainty’ in the dry-

lands (Scoones, 1994). These strategies may not always be successful, as

the terrible toll on livestock populations during 2022–23 showed, but

disasters are frequently offset or at least ameliorated though a range of

practices. Pastoralists must always live with and from variability, and so

must continuously navigate uncertain conditions (Kr¨

atli & Schareika,

2010). Unexpected droughts – variable across time and space – are in

this sense ‘normal’.

Variability is the basis of pastoral production, involving mobile

grazing across extensive landscapes, with careful herding (FAO, 2021;

Scoones & Nori, 2023). Given the contingencies and uncertainties

involved, even with sophisticated dynamic and stochastic approaches, it

is impossible to model such practices effectively and precise prediction

is futile. Agent-based and Bayesian approaches may offer some insights,

focusing on how individual pastoralists respond to complex, fast-

changing settings and uncovering how decisions are made sequentially

in response to unfolding conditions (e.g., Yu, Evans, & Malleson, 2019;

Lybbert et al. 2007). However, in the end, an economic understanding of

pastoralism must embrace uncertainty and confront irreparable

ignorance.

This means focusing not on predicting or anticipating actions but

building on existing practices to improve reliability (Roe et al., 1998),

very much in the Hirschman tradition. As with other ‘critical in-

frastructures’, this means reducing high input variation, so as to ensure a

reliable, low-variability ow of system services – milk, meat, hides and

so on, at the same time as assuring the viability of the asset (Roe, 2016,

2020). As ‘high reliability professionals’, pastoralists – working with

others in wider networks – must actively manage uncertainties and

avoid sources of ignorance where the real dangers lie (Scoones, 2023),

deploying the strategies of experimentation, learning-by-doing and

adaptive responses highlighted by Hirschman.

Pastoralists use movement to gain access to pasture and water

(although some may move fodder and water to animals instead of

moving the animals themselves). This requires timely knowledge about

resource availability, prices of commodities, the exible mobilisation of

labour and transport, networking among different groups, scouting for

information and real-time communication to allow responsive action

(Maru et al., 2022). Flexible mobilities are not amenable to prescriptive

plans or regulations and must rely on adaptive exibility, responsive to

highly variable conditions (Scoones & Nori, 2023). Unsurprisingly, these

are features all central to the operation of development projects that

Hirschman observed in the 1960s (Hirschman, 1967).

Central to pastoralists’ responses are social networks – among pas-

toralists, across ethnic groups, with government ofcials, politicians and

others. Mobilising knowledge requires investing in networks and re-

lationships and building both formal and informal institutional capac-

ities (Mohamed, 2023). For example, in response to uncertainties about

animal disease, pastoralists in northern Kenya connect different

knowledge networks, with brokers acting to mediate between them

(Tasker & Scoones, 2022), and so echoing perspectives from institu-

tional and complexity economics.

In facilitating mobility as a response to uncertainty, pastoralists must

galvanise the group, learn the route, nd out about conditions in other

areas and be attuned to changing temporal and spatial patterns in key

resources. Animals must be well-trained and skilled herding is essential

(Kr¨

atli, 2008). This is above-all a social process, with particular

gendered and age-specic roles. Movement is embedded in culture,

associated with songs, poems and sayings and movement – so much a

part of daily life – and is an emotional, affective experience, not simply a

rational, scripted response (Maru, 2020).

In extensive, dryland pastures, making use of common resources is

vital. Maybe combined with private sources of fodder, shared resources

managed through communal institutions are essential (cf. Ostrom,

1990). In times of drought, ‘key resources’ – riverbanks, wetlands,

forested hills – are especially important (Scoones, 1991), as they provide

a level of redundancy in a complex landscape and are crucial when

droughts strike. Yet such resources are easily encroached, subject to land

or green ‘grabs’ that appropriate such ‘unused’ land, and so undermine

the overall resilience of the system (White, Borras, Scoones, & Wolford,

2012).

https://www.thenewhumanitarian.org/News/2022/31/05/A-country-by-

country-guide-worsening-drought-in-the-Horn-of-Africa.

G. DeMartino et al.

World Development 173 (2024) 106426

Pastoralists’ responses to uncertain contexts are thus very different

to rationalist, predictive risk management with anticipatory responses

to a singular shock or event. Instead, rmly in the tradition of Hirschman

and suggesting a different type of economic analysis, pastoralists must

embrace uncertainty through much more emergent, adaptive responses,

embedded in local networks, institutions and cultures, while providing

exibility and the possibility of exit through redundancy and the mobile

use of common resources (Scoones, 2021).

6.2. Responding to nancial crises in the global South

The nancial crises of the 1990s and then 2008 presented a costly

refutation to the idea that practices informed by economic theory had

eliminated uncertainty and so provided dependable guidance for policy

and institutional design. While in the rst instance these crises solidied

the International Monetary Fund’s (IMF’s) role in enforcing neoliberal

responses (Grabel, 2017: chapter 3), they ultimately induced irreparable

cracks in the neoliberal consensus. By the early 2000s, policymakers in

the Global South had come to understand what economists had long

repressed—that they operated in a world of epistemic insufciency. That

insight inaugurated a period of extraordinary institutional experimen-

tation, centred on pragmatic problem solving (successful and not),

innovation and learning-by-doing.

Two features of these dynamics are particularly notable and reect

Hirschmanian sensibilities. First, the wide-ranging institutional experi-

ments were unscripted. They were not deduced from blackboard dem-

onstrations of optimal institutional congurations; nor did they target

economic efciency. Instead, they represented pragmatic responses to

pressing challenges that were not driven by a grand theoretical frame-

work. Key actors looked to establish institutions and policies that would

prove to be robust in the face of enduring uncertainty. Second, although

some important early initiatives failed to take root, they laid the

groundwork for later initiatives that succeeded in altering the landscape

of global nancial governance in ways that provide some measure of

protection of Global South economies from global nancial vicissitudes.

The range of new initiatives in nancial governance that followed

the crises of 1997–98 and 2008 is striking, especially in comparison with

the institutional stagnation of the neoliberal period when rigid thinking

dominated, rather than the sort of pragmatic innovation that Hirschman

advocated. For Hirschman, the tendency to pronounce policy failure in

advance of its application reected a grievous error involving the pre-

narration of history that doomed what might otherwise be viable ini-

tiatives (Hirschman, 2013 [1970]). The crises ipped the script,

inducing a new appreciation of uncertainty in nancial affairs, which

opened the oodgates to policy and institutional experimentation. The

new pragmatism ultimately even inuenced the thinking of the IMF.

Most notably, perhaps, was a new-found appreciation of the utility of

capital controls, which as recently as 1997 the IMF had sought to ban via

a change in its Articles of Agreement. Countries of the Global South

learned through experience how to employ capital controls to inuence

the disruptions associated both with rapid capital inows and outows.

In the light of these experiences, the IMF switched its position,

rebranding capital controls during the crisis of 2008 as prudential

nancial management, and began to consider them a “legitimate part of

the policy toolkit” (Grabel, 2017: chapter 7).

Equally importantly, new institutions were created to ensure

counter-cyclical crisis support and long-term project nance. Many of

these institutions signed cooperation agreements with one another,

establishing new networks that facilitated their capacity to adjust in the

face of changing conditions. Some of these institutions comply with the

established IMF model of surveillance and conditionality, but others

deploy entirely different approaches to disbursement and surveillance,

while also extending loans in local currencies (Grabel, 2017: chapter 6).

Initial excursions by countries across the Global South into nancial

governance have not all been successful. But, as Hirschman would have

expected, some initial failures provided opportunities for learning and

adjustment (as per his concept of the Hiding Hand), bearing fruit in new

forms and in new settings. For instance, as the East Asian nancial crisis

emerged in 1997, Japan proposed the formation of an Asian Monetary

Fund. The Fund was to be independent of the IMF; its mission was to

provide liquidity that protects policy autonomy in times of economic

turbulence. The initiative was killed immediately on political grounds

by the US, China and the IMF. But the initiative catalysed pragmatic

thinking across the Global South about institutional innovation that has

continued to this day (Grabel, 2017: chapter 3).

Another important site of innovation in nancial governance is

taking place among the BRICS countries— Brazil, Russia, India, China

and South Africa, a grouping that has now signicantly expanded. The

BRICS have evolved from an acronym created by a nancier (initially

BRICs since South Africa was not an original member), to an informal

group that met on the margins of a G-8 meeting in 2006 to a formal

network with ministerial meetings. It is now an important network with

an evolving institutional architecture that includes, for example, the

New Development Bank, which is beginning to make loans to members

in currencies other than the US dollar (so far only the RMB, with plans to

disburse in other currencies). The BRICS also have a nascent liquidity

support arrangement (the Contingent Reserve Arrangement) and China

has established the Asian Infrastructure Investment Bank (AIIB) in 2015,

along with a raft of other lending, investment and aid facilities.

These developments do not reect a new coherent theoretical vision;

instead, there are deep inconsistencies and unevenness in the emergence

of disparate, overlapping and interconnected institutions that look to

manage dangerous nancial ows in the context of deep uncertainty.

The initiatives are diversifying the nancial governance landscape,

dispersing power within it and inaugurating a more complex, decen-

tralised, pluri-polar global nancial and monetary system that is likely

to be far more robust in the face of an unknowable and uncontrollable

future.

Is the resulting ‘disorder’ disconcerting? For those of us trained in

economics to seek guidance in parsimonious theory and institutional

coherence, it surely is. But we propose instead that we follow Hirschman

in not rushing to judgement, keeping in view the value of experimen-

tation and continuous pragmatic adjustment. With Hirschman, we

interpret the current incoherence as productive, allowing for the dis-

covery of effective institutional arrangements and policy strategies that

cannot be inferred from standard models, but which must arise from

doing, failing and adjusting (Grabel, 2017).

While the worlds of pastoralism and nance are wildly different in

almost all respects, we nd striking similarities in the ways uncertainties

have been confronted via adaptive, exible responses. If the aim is to

design robust, reliable practices to support development in highly un-

certain settings—by which we mean practices that generate a reasonably

stable stream of services (as with meat or milk from animals or nancial

ows that serve development objectives or quell liquidity crises)—then

More recent initiatives include China’s 2015 programme to develop a Cross

Border International Payments System (CIPS) as an alternative to SWIFT (So-

ciety for Worldwide Interbank Financial Telecommunication), the West’s

dominant international nancial messaging system used widely for cross-border

payments. While CIPS remains extremely small relative to SWIFT, sanctions in

Iran and now the war in Ukraine have provided Chinese and other policymakers

with incentives to push it forward as a workaround to US nancial power.

Others, such as Russia, have sought to reduce dependence on the dollar and to

provide some protection from the weaponisation of nance and trade relations

by the US and other nancial powers. Before the war, Russia was already

developing an alternative to SWIFT, with the hope that it would connect to

China’s CIPS and that India would join the Russian alternative (Grabel 2022,

2023).

G. DeMartino et al.

World Development 173 (2024) 106426

certain principles are central. Following Hirschman, these include un-

scripted pragmatic exibility and adaptability, learning-by-doing,

continuous monitoring, organisational redundancy, social networking,

sharing of common resources and the preservation of exits from strate-

gies that go wrong. All of these entail some loss of ‘efciency,’ as

economists dene it, while pursuing such strategies requires rejecting

once-and-for-all standard models that presume to tell us what will and

won’t work or what are the uniquely ‘optimal’ strategies to control the

world through our interventions.

7. Confronting uncertainty with new methods

Some of these vital lessons from Hirschman are accepted by a new

eld – decision-making under deep uncertainty (DMDU) – where un-

certainty is explicitly embraced (Marchau et al., 2019). DMDU fore-

grounds Knightian uncertainty and therefore rejects entirely the ‘predict

then act’ model of policy analysis that has dominated economics and

other elds for a century (Lempert et al., 2013). It rejects equally the

pursuit of efcient policy design and outcomes on the grounds that the

hunt for efciency is far too dangerous in an unpredictable world; not

least, because it runs the risk of imposing grave harms on affected

communities, especially on the most vulnerable and those lacking po-

litical voice. In its place, the approach seeks ‘robust’ policy, by which is

meant policy that stands to do well enough across a very large number of

possible futures (Lempert, 2019). Such an approach is as relevant to

questions of global nance as it is to issues faced by pastoralists in

dryland Africa.

The DMDU approach starts from the assumption that social and

natural systems are non-linear and interrelated. In this context no model

can tell us what will happen next; none can dependably map policy

interventions onto outcomes. Instead, DMDU generates thousands of

possible futures, without weighting them by probabilities, and then

empowers stakeholders—especially those who stand to be most seri-

ously harmed, and those who are typically excluded from policy delib-

eration—to decide which risks to take in pursuit of which valued ends

(Hallegatte et al., 2011). The approach recognises, in Hirschmanian

fashion, that all policy interventions are experiments. But with Hirsch-

man, and contrary to most RCT practitioners, here the experts experi-

ment with rather than on those they seek to serve. The approach also

dethrones the detached economist and arms-length policy analyst who

lacks what Nassim Nicolas Taleb calls “skin in the game” (Taleb, 2018).

Instead, what is required is meaningful, ongoing involvement of econ-

omists (and other experts) with stakeholders in decision-making pro-

cesses, deliberation on the ambiguity of outcomes, assessment of

uncertainties and negotiation around different versions of contested

knowledges.

Building on the core principles of experimentation, improvisation,

incremental learning and local level adaptation, the goal is to inform

rational, responsible decision support, where those most directly and

deeply affected by the consequences of policy decisions themselves play

central roles in collaborative policy deliberation and policy choice.

This is inevitably a social process that embraces enduring collaborations

with diverse participants to confront problems that have no end date.

The transformation in economic practice is also ethical - away from a

paternalistic vision in which the economist-knows-best to a vision in

which the economist recognises the integrity and autonomy of those

they hope to serve; something that Hirschman passionately argued for

many decades ago.

8. Conclusion

The standard economic framing that represses uncertainty has

generated dangerously over-condent assertions about what to do to

promote ‘development.’ In contrast, self-awareness about the assump-

tions we make about complex processes, expected outcomes and future

dynamics opens the door to more robust economic analysis. We

emphasise that “uncertainty (of whatever kind) is by denition not a

condition that is simply ‘out there’ in the world; uncertainty is a prop-

erty of relations between what is known and who is doing the knowing”

(Scoones & Stirling, 2020: 11). Both private economic actors and public

decision-makers operate under epistemic insufciency—there is simply

no escaping the problem. As a consequence, and following Shackle,

economics must study the construction and transmission of economic

stories and beliefs rather than seek grounding in rational calculation of

‘optimal’ strategies as determined by ‘objective’ data. Navigating the

future requires negotiating narratives, informed by different imaginaries

(Bronk, 2009; Beckert, 2016). Edward Leamer (2009: 3) conveys much

of what the new thinking alludes to when he writes in his inuential

textbook,

You may want to substitute the more familiar scientic words “the-

ory and evidence” for “patterns and stories.” Do not do that… The

words “theory and evidence” suggest an incessant march toward a

level of scientic certitude that cannot be attained in the study of a

complex, self-organizing human system that we call the economy.

The words “patterns and stories” much more accurately convey our

level of knowledge, now, and in the future as well. It is literature, not

science.

What approaches might help recast an economics of control for

make-believe model economies to one appropriate to the uncertain

world we inhabit? Perhaps from a surprising provenance, given the long

history of ve-year plans, the Indian government has recently proposed

an ‘agile’ approach to managing the economy, based on the experience

of the COVID-19 pandemic. In the preface to the 2021–22 Economic

Survey – and quoting Hayek’s views on the ‘pretence of knowledge’ – the

ministry of nance argues, “This framework is based on feed-back loops,

real-time monitoring of actual outcomes, exible responses, safety-net

buffers and so on. Planning matters in this framework but mostly for

scenario analysis, identifying vulnerable sections, and understanding

policy options rather than as a deterministic prediction of the ow of

events….…”.

Following the central ideas of Hirschman and aligning

with the ideas now being explored under the umbrella of DMDU, this is a

major shift from the standard approach that denes a plan from prior

analysis or model and then has a strict approach to implementation. The

ministry argues that an alternative approach is now possible thanks to

the availability of real-time data on all aspects of the economy and the

ability to monitor, learn and react adaptively as circumstances change.

The common response to uncertainty by the economics profession

and the decision-makers they serve is to demand more knowledge: if

only we could parameterise each variable, then a risk model could be

tted, and we could predict what will happen and plan the future. More

economic knowledge is expected to shrink the domain of our ignorance,

yielding better predictions and a heightened ability to plan and control.

RCTs, increasing computing power, ‘big data’ analysis, articial intel-

ligence, machine learning and geographic information systems certainly

add to our knowledge, but gaining new knowledge can expand rather

than contract the domain of uncertainty and ignorance. New knowledge

brings new capacities to act, and those capacities necessarily make

salient new areas of ignorance (DeMartino, 2022). The nancial crisis of

The DMDU approach draws inspiration from some strands of ecological

economics that highlight ‘strong’ versions of sustainability and ‘deep’ versions

of ecological economics (Spash 2013). These emphasise the importance of

participatory deliberation around different options, informed by plural values

and different ethical positions (¨

Ozkaynak et al. 2004), as well as a wider

argument around ‘economic democracy’ requiring a challenge to mainstream

approaches that ignore complexity and uncertainty (Akbulut and Adaman

2020).

https://www.indiabudget.gov.in/economicsurvey.

G. DeMartino et al.

World Development 173 (2024) 106426

2008 was the result of more (not less) information; faster (not slower)

processing power and newer (not archaic) models that promised control

in the face of hyper-liquid nancial markets. For this reason, we are not

surprised that enormous investments in predictive early warning sys-

tems supported by satellite imaging have not reduced uncertainty either

in the pastoral drylands or in nancial systems.

That said, we fully accept Des Gasper’s (2018) argument that an

emphasis on uncertainty can open the door to the disavowal of re-

sponsibility for harm by those whose behaviour harms others. Uncer-

tainty does not provide moral cover for those making decisions with

ruinous consequences on the grounds that they could not have known

that things would go so badly. Recognition of uncertainty instead im-

plies a duty to support decision-making processes that help stakeholders,

including the most marginalised and vulnerable, to discover robust

strategies as they confront so-called ’wicked problems’ in an often

dangerous, opaque world. The DMDU approach discussed above, for

one, provides a way forward in contexts where more data and more

knowledge cannot sufce to ensure good policy outcomes.

Recognition of uncertainty implies a change in economic training.

Uncertainty-aware instructors present economic practice as imperfec-

tible art rather than perfectible science, emphasising where the world

will always overwhelm the cognitive capacity of the very best econo-

mists armed with the most sophisticated techniques. Policy and insti-

tutional innovations are therefore always experimental - the n always

equals 1 - and all stakeholders must be incorporated as key actors in the

policy-making enterprise since they and not the economist will bear the

costs of the decisions taken.

Uncertainty should not be seen solely or even principally as a

constraint, but also as an opportunity: “Instead of inventing numbers to

ll the gaps in our knowledge, we should adopt business, political and

personal strategies that will be robust to alternative future and resilient

to unpredictable events… uncertainty can be embraced, because it is the

source of creativity, excitement – and success.” (Kay & King, 2020:

cover). Today there is an acute need to displace perilous prediction,

assertive causality in the service of control and the narrow calculus of

risk and expected utility. Following Hirschman, this means shifting to a

stance of pragmatic practice in economic analysis and policy advice for

development - and indeed in other elds - whereby ‘productive inco-

herence’ can be a positive feature of negotiating an uncertain world, in

the context of what Zygmunt Bauman (2013) has termed our chal-

lenging, turbulent ‘liquid modernity.’

Funding sources

For IS, the writing of the paper has been supported by the UK Eco-

nomic and Social Research Council through the STEPS Centre (Grant

number: ES/R008884/1), as well as the European Research Council

through an Advanced Grant (PASTRES, www.pastres.org, Grant num-

ber: 74032).

Declaration of Competing Interest

The authors declare that they have no known competing nancial

interests or personal relationships that could have appeared to inuence

the work reported in this paper.

Data availability

No data was used for the research described in the article.

Acknowledgements

This article emerged out of conversations that started during 2019 as

part of the ESRC STEPS Centre’s ‘uncertainty’ year (www.steps-centre.

org/uncertainty). We would like to thank participants at the symposium

and seminar series for stimulating this writing project. The empirical

work on pastoralism was carried out by IS and colleagues as part of the

European Research Council PASTRES project (pastres.org), while the

empirical case on global nancial governance is based on the work of IG.

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The study of addressing socio-environmental challenges through sustainability transitions inherently considers the future in various ways, although these considerations are often only implicit. In this essay, we argue that it is crucial to engage more explicitly in understanding how imagined futures are enacted and comprehended within research on sustainability transitions. This endeavour is necessary to navigate both the uncertainty and complexity of the future and to avoid perpetuating cognitive path dependencies and unsustainable modes of production and consumption that uphold existing injustices. Our paper discusses characteristics of futures and future-making that are relevant to transition studies. Given the spatial contingency of futures, the social construction of time, and the tendency to reproduce incumbent futures in transitions research, we outline contours of diverse futures through which we can not only analyse but actively engage in diverse future-making. Finally, we discuss the limitations of our approach for the study and community of sustainability transitions.

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The relevance of effective mentoring of doctoral students in the chemical sciences is now widely recognized. However, the scholarly literature on the topic is virtually non‐existent, and most approaches to faculty education on mentoring are based on “tips” and “guidelines. Following the analysis of current mentorship practices, we suggest a new approach based on evidence resulting from surveys of doctoral students, and on theory derived from studies in social and human sciences.

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Book

Full-text available

Oct 2023

Ian Scoones

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May 2023

Amidst climatic and economic volatility, agricultural development and climate adaptation policies have increasingly turned to weather microinsurance to manage uncertainties, particularly in dryland pastoral and agricultural settings. While the political embrace of insurance has been cause for concern amongst those who fear insurance will undermine embedded coping mechanisms and moral economies, economists have puzzled over low insurance adoption rates amongst target populations. This article argues for an approach that scrutinizes insurance in relation to dynamic social practices and norms for responding to uncertainty. We employ this approach to investigate pastoralists’ encounters with index-based livestock insurance in Northern Kenya and Southern Ethiopia. Drawing on interview, ethnographic, and survey data, we demonstrate how insurance is understood within larger moral economies and collective imaginaries for living with and managing uncertainty in the drylands. Relational understandings shape pastoralists’ participation in risk-sharing arrangements, collective and individual decisions about livestock insurance purchase, and eventual uses of insurance payouts. Payouts also support a broad array of social reproductive purposes and investments in social and political life. As we conclude, these findings upset the binary between formal and informal insurance, revealing how “formal” index insurance must be negotiated with embedded social affiliations, rights, obligations, and understandings of uncertainty.

Climate Change in Sub-Saharan Africa

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Full-text available

May 2013

From Austrian theory of capital to dissent: Nicholas Kaldor, Friedrich A. Hayek and the way to disequilibrium

Article

Apr 2023

Keanu Telles

Purpose In the early 1930s, Nicholas Kaldor could be classified as an Austrian economist. The author reconstructs the intertwined paths of Kaldor and Friedrich A. Hayek to disequilibrium economics through the theoretical deficiencies exposed by the Austrian theory of capital and its consequences on equilibrium analysis. Design/methodology/approach The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials. Findings The integration of capital theory into a business cycle theory by the Austrians and its shortcomings – e.g. criticized by Piero Sraffa and Gunnar Myrdal – called attention to the limitation of the theoretical apparatus of equilibrium analysis in dynamic contexts. This was a central element to Kaldor’s emancipation in 1934 and his subsequent conversion to John Maynard Keynes’ The General Theory of Employment, Interest, and Money (1936). In addition, it was pivotal to Hayek’s reformulation of equilibrium as a social coordination problem in “Economics and Knowledge” (1937). It also had implications for Kaldor’s mature developments, such as the construction of the post-Keynesian models of growth and distribution, the Cambridge capital controversy, and his critique of neoclassical equilibrium economics. Originality/value The close encounter between Kaldor and Hayek in the early 1930s, the developments during that decade and its mature consequences are unexplored in the secondary literature. The author attempts to construct a coherent historical narrative that integrates many intertwined elements and personas (e.g. the reception of Knut Wicksell in the English-speaking world; Piero Sraffa’s critique of Hayek; Gunnar Myrdal’s critique of Wicksell, Hayek, and Keynes; the Hayek-Knight-Kaldor debate; the Kaldor-Hayek debate, etc.) that were not connected until now by previous commentators.

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Article

Jun 2023

While acknowledging the absence of a single definition or theory of sustainability, this paper argues that a discussion of sustainability which refers only to definitions is pointless without an understanding of how the definitions are operationalised. In this context, the paper considers the operationalisation of strong sustainability. The definitions and operationalisation of strong sustainability most closely associated with (i) neoclassical environmental economics and (ii) ecological economics are discussed and compared. This analysis raises questions about the extent to which ecological economics has been able to influence real-world decisions and policy. The paper ends by considering whether the economic and political power structure taken as given by ecological economics is compatible with its policy perspective.

The War in Ukraine and the End of the American Financial Order?

Article

May 2023

Ilene Grabel

The crises of 1997–98, 2008, and the pandemic accelerated contradictory changes in global financial governance. Taken together, the change and stasis propelled by these crises is coalescing around a fragmented “post-American financial order.” The war in Ukraine represents another inflection point. The war has facilitated the reassertion of American financial power and cooperation among rich nations. However, like previous crises, the war is creating fissures in financial governance. The landscape offers risks and opportunities against a backdrop of heightened financial fragilities, authoritarianism and fascism, inequalities, devastation associated with the pandemic and war, and climate crisis. In such moments, Hirschman’s “possibilism” is both elusive and necessary. In this context, we might aspire to “permissive multilateralism s” rather than nostalgia for a new Bretton Woods. JEL Classification: F02, F51

Complexity and the Economy

Chapter

Jul 2007

W.B. Arthur

The use of knowledge in society

Chapter

Sep 2009

Friedrich Hayek

This book brings together classic writings on the economic nature and organization of firms, including works by Ronald Coase, Oliver Williamson, and Michael Jensen and William Meckling, as well as more recent contributions by Paul Milgrom, Bengt Holmstrom, John Roberts, Oliver Hart, Luigi Zingales, and others. Part I explores the general theme of the firm's nature and place in the market economy; Part II addresses the question of which transactions are integrated under a firm's roof and what limits the growth of firms; Part III examines employer-employee relations and the motivation of labor; and Part IV studies the firm's organization from the standpoint of financing and the relationship between owners and managers. The volume also includes a consolidated bibliography of sources cited by these authors and an introductory essay by the editors that surveys the new institutional economics of the firm and issues raised in the anthology.

The Tragic Science: How Economists Cause Harm (Even as They Aspire to Do Good)

Book

Jan 2022

George F. DeMartino

Fiscal resiliency in a deeply uncertain world: The role of semiautonomous discretion

Article

Mar 2022

This Policy Brief argues that embracing the deep uncertainty about interest rates and other key parameters determining a country’s fiscal position requires a new approach in fiscal policy. It proposes retaining fiscal discretion exercised after making the budget adjust more automatically and rapidly in areas where there is broad consensus that doing so is consistent with achieving broader societal goals. For such a semiautonomous discretionary fiscal architecture five elements are emphasized: stronger automatic stabilizers, a new infrastructure program, extension of debt maturities, indexation of long-term fiscal programs to their underlying drivers, and more emphasis on residual fiscal discretion. The goal is to provide a framework better adapted than our current budgetary structures to deep uncertainty, thus freeing up a discretionary fiscal policy to focus more on adjusting to the unanticipated.

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