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Mental Models

The State Can Help—When Incompetent

State incompetence, such as inefficiency and lack of optimization, can sometimes prevent catastrophic failures by creating redundancies and local self-sufficiency, as seen in Soviet agriculture and housing. This contrasts with over-optimized systems that become fragile and prone to collapse during disruptions.

THE IDEA

THE STATE CAN HELP—WHEN INCOMPETENT

The famine in China that killed 30 million people between 1959 and 1961 can enlighten us about the effect of the state "trying hard." Xin Meng, Nancy Qian, and Pierre Yared examined its variations between areas, looking into how the famine was distributed. They discovered that famine was more severe in areas with higher food production in the period before the famine began, meaning that it was government policy of food distribution that was behind much of the problem, owing to the inflexibility in the procurement system. And indeed, a larger than expected share of famine over the past century has occurred in economies with central planning.

But often it is the state's incompetence that can help save us from the grip of statism and modernity—inverse iatrogenics. The insightful author Dmitri Orlov showed how calamities were avoided after the breakdown of the Soviet state because food production was inefficient and full of unintentional redundancies, which ended up working in favor of stability. Stalin played with agriculture, causing his share of famine. But he and his successors never managed to get agriculture to become "efficient," that is, centralized and optimized as it is today in America, so every town had the staples growing around it. This was costlier, as they did not get the benefits of specialization, but this local lack of specialization allowed people to have access to all varieties of food in spite of the severe breakdown of the institutions. In the United States, we burn twelve calories in transportation for every calorie of nutrition; in Soviet Russia, it was one to one. One can imagine what could happen to the United States (or Europe) in the event of food disruptions. Further, because of the inefficiency of housing in the Soviet state, people had been living in close quarters for three generations, and had tight bonds that ensured—as in the Lebanese war—that they stayed close to each other and lent to each other. People had real links, unlike in social networks, and fed their hungry friends, expecting that some friend (most likely another one) would help them should they get in dire circumstances.

When to use it

  • Evaluating economic policies for unintended fragilities, especially those that optimize one metric at the expense of resilience.

  • In business management, considering the value of slack resources and decentralized decision-making to absorb shocks.

  • In urban planning, preserving local food production and community bonds as buffers against supply chain disruptions.

  • In personal finance, avoiding over-optimization (e.g., extreme efficiency in budgeting) that leaves no room for unexpected expenses.

FROM THEORY TO EVERYDAY LIFE

In practice

01

Chinese Famine (1959-1961)

The famine was more severe in regions that previously had higher food production due to inflexible government procurement policies, showing how state intervention can exacerbate disasters.

02

Local redundancy after the Soviet collapse

In Orlov’s account, local agriculture kept food accessible during institutional breakdown, while shared housing had created relationships through which people supported one another.

✳

A MOMENT TO REFLECT

Put it to work.

  1. Can you think of a situation in your life or work where incompetence or inefficiency provided a buffer against failure?

  2. What are the risks of over-optimizing a system, and how can you build in beneficial redundancies?

  3. How might a top-down policy that seems efficient actually create hidden fragilities? Relate to the Chinese famine example.

Connected ideas

Another lens can bring the same problem into focus.

Often confused with

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Source texts

  • Antifragile (Nassim Nicholas Taleb)
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