I used to think I had a handle on the basic theoretical debates between mainstream (or neoclassical) economics and urban planning institutions and practices, but a recent book opened my eyes to the realization that scenario planning’s focus on non-quantitative uncertainty is yet another area where planning conflicts with ideas from economics. Although my research does not engage deeply with economic theory, I thought I would outline these ideas since economics is a social science field whose ideas carry outsized influence in political and policy conversations.
Planning theorists have long observed that urban planning–and government attempts to plan more generally–have been controversial in the US and other capitalist societies, since according to conventional economic theories governmental regulation and planning are often unnecessary and impose costs on the economy. A classic analysis of this position is contained in Richard E. Klosterman’s 1985 article, “Arguments for an against planning,” where he argues that within the perspective of conventional neoclassical economic theory, planning can be justified since it provides public goods, addresses negative externalities, responds to prisoners’ dilemma conditions, and addresses unequal distributions of resources. These defenses are still taught in planning schools today, and these arguments provide one explanation for the begrudging acceptance of some forms of planning across politically diverse communities, and among even ardent free-market advocates.
A somewhat related debate centers around the appropriate management of urban land. Many have observed that urban land doesn’t act like a normal economic good: the total amount of land is finite, each property has a unique location and attributes, and there are many positive and negative externalities between adjacent properties. All of these reasons justify planning activities like the creation of land-use plans and adoption of various regulations like zoning and pollution controls. Furthermore, the writer Henry George famously pointed out that increases in land value are due to the growth of cities and public investments in infrastructure, and therefore argued for adopting taxes on land value to prevent speculation and allow this wealth to be shared. Modern planning instruments like tax increment financing, land banks, and value capture around transit stations are all influenced by George’s ideas, and an institute founded to promote his ideas thrives to this day.
Think you are ready to defend planning with the economist at the cocktail party? Not so fast! In their fascinating recent book Radical Uncertainty: Decision-Making Beyond the Numbers, economists John Kay and Mervyn King take on another aspect of neoclassical economic theory that I found eye-opening. As they tell it, in the early 20th Century, economic theorists like John Maynard Keynes and Frank H. Knight promoted analyzing economies through the separate concepts of risk and uncertainty. Risk describes situations where future events are known, and therefore can be represented quantitatively and be managed through insurance, cost/benefit analysis, and other quantitative techniques. In planning for example, flooding is managed primarily as a risk: flood zones are areas that, statistically speaking, will flood during a given time period given climate assumptions. Uncertainty, on the other hand, refers to a deeper, more fundamental uncertainty about the future. As they describe it, neoclassical economists preferred to focus exclusively on risk, to the exclusion of uncertainty. Kay and King illustrate how through a quote from Milton Friedman’s book Price Theory, a key work forming the Chicago School of economics (where all economic actors are men, apparently):
“just as we can suppose that an individual acts as if he attached a definite utility to every possible event if it were to occur, so we can suppose that he acts as if he attached a definite probability to each such event. These ‘personal probabilities’ are assumed to obey the usual laws of the mathematics of probability.”
What’s the problem with this view? First, it only applies to what Kay and King call small worlds, where interactions are limited by fixed rules that define a set of possible outcomes. Second, even for small world situations where outcomes are finite and defined, it makes unreasonable assumptions about the rationality of individuals. A library of research into behavioral economics has undermined the myth of rational calculation assumed by neoclassical theory. Overall, the problem with this perspective is that in the real world, uncertainty dominates over risk, and therefore economists–and the quantitative models they create–are continually blindsided by asset bubbles, recessions, pandemics, political events, etc. Instead of fixating on risk, Kay and King promote engaging uncertainty by creating multiple narratives that can be used to prepare for alternative futures and pursue resilience. In fact, they write approvingly (if briefly) about scenario planning in particular as a valuable tool for coping with uncertainty: “Scenarios are useful ways of beginning to come to terms with an uncertain future. But to ascribe a probability to any particular scenario is misconceived.” (p. 223).
What to make of all of this? On the one hand, the preeminence of economic ideas has been on the decline, due not only to recent events like the Great Recession that highlighted the limitations of their theories, but also to longstanding intellectual shifts such as the growing maturity of behavioral economic research. In politics, the tone has noticeably changed from the Obama years where mainstream economists like Timothy Geithner and Larry Summers held sway. On the other hand, economic ideas holds deep resonance in our society, illustrated by a renaissance in interest in figures like Hayek. Being well versed in how planning aligns (or doesn’t) with economic ideas seems useful to empower planning practitioners to engage with economic thinking wherever it pops up, whether across the seminar table or in the halls of power.