The Big, Bad Natural Catastrophe Wolf

The fable of the three little pigs and the big, bad wolf can serve as a metaphor to help us to understand how better to mitigate climate risks.

In most of its many iterations, each of three little pigs make themselves homes, one of straw, one of sticks, and one of bricks. The big, bad wolf huffs, puffs, and blows the first two down but he cannot destroy the third.

Most Americans today follow the example of the second pig, building their homes with 2 by 4 “sticks.” They ain’t cheap but prove no match for the big, bad national disaster wolf, who sometimes blows the houses down (derechos, hurricanes, tornadoes), sometimes burns them down (wildfires), sometimes floods them out (avalanches, floods, mudslides), and sometimes swallows them whole (earthquakes, sinkholes). 

Time was, many Americans who lived in areas frequented by natural disaster wolves followed the example of the first pig, living light and cheap in trailers or “shacks.” They often suffered complete losses but if the wolf didn’t kill them, they recovered because they hadn’t invested much.

The third pig seems like the smart one but not every little pig can afford to make its house impervious to the entire pack of natural disaster wolves. And if a wolf doesn’t appear, pig three looks foolish because it could have consumed more or invested in something else instead of those under used bricks.

In a perfect, fairytale world, the little pigs would be able to buy wolf insurance at a price representing the risk that a particular wolf would appear. They could still self-insure by building with straw or brick if they wanted, but they could also build with sticks and, most importantly, get price signals on what type of stick house to build.

If the flood wolf is the biggest threat, the insurance premium would be lowest for a stick house on stilts not too close to any body of water. If the fire wolf is likely to come around, the premium would be highest for a stick house built like a cub scout tinder bundle (as many in southern California are). In the territory of the huff and puff wolf, a house with a robust roof tied to structural footers would have a lower premium than a house with an asphalt shingle roof near the end of its service life.

To ensure that the little pigs paid sufficient attention to the state of their stick homes, insurance contracts in fairytale land would say they have to pay some of the costs of any damage the wolf might cause.

America never had a perfect fairytale insurance system, but it long had one where premiums pretty closely reflected risks, and insureds and insurers both suffered when the big, bad wolf came around. The availability of actuarially fair insurance explains why so many Americans built stick homes.

The problem is that America’s insurance system degraded into a nightmare for insurers and homeowners, especially those in low-risk areas. Due to regulations, premiums on houses in many risky areas are too low. Because regulated premiums often subsidize risk-taking, few build with straw or brick anymore. Worse, many build stick houses of the wrong type, in the wrong places, and do nothing to mitigate risks. They know that if the wolf does its worst, regulators will either force insurers to make them whole or public or private assistance will do so.

Meanwhile, the little pigs who built out of sticks correctly or who live where wolves seldom roam suffer. Their risks remain the same but their premiums increase faster than inflation, or their day-to-day claims face unexpected scrutiny, because their insurers have big bills due to California’s wildfires or Florida’s hurricanes.

Because of the problems in the insurance market, some Americans can no longer afford a mortgage and the mandatory insurance that goes along with it. Insurance costs are also reflected in rents so there can be no American Dream or affordable housing without property insurance reforms.

Beyond the Quotidian: The Real-World Impact of Economic Analysis

 Individuals or small teams can move markets or persuade policymakers with incisive economic analysis.

Economic analysis melds models, data, and experience to prognosticate broad market movements or to steer policy discussions. It is empirical but not exclusively quantitative, giving both numbers and words their due weight. It synthesizes large swathes of information while searching for big picture patterns that can help businesses, investors, or policymakers to foresee the next big crisis or innovation before it overwhelms positions outflanked by an inherently volatile world.

Economic analysis differs from financial price data dissemination and post-market narration, which date from the 16^th century. It offers less precise predictions than forecasting, which in modern form began in the 1920s, because it tries to capture sea changes, not middle run trends or short-term fluctuations. Its scope far exceeds that of securities or even industry analysis.

Warren Buffett and Alan Greenspan both exemplify the power of economic analysis. The former made billions for stockholders through extensive reading and contemplation rather than relying on technical signals or trading hunches. The latter’s understanding of macroeconomy conditions proved largely ineffable but almost infallible as he guided U.S. monetary policy for the almost two decades now called The Great Moderation.

This post surveys three older but no less important economic analyses, Economist editor Walter Bagehot’s (1826-1877) lender of last resort rule, Brian Anderson’s (1886-1949) case for free trade in the Chase Economic Bulletin at the apex of American protectionism, and Wilma Soss’s (1900-1986) empirically based campaign to put women on the board of directors of America’s largest corporations.

Bagehot (pronounced badge ut), longtime editor of The Economist, explicated the lender of last resort trigger rule employed by the Bank of England during the periodic financial crises that struck the City of London in the Victorian Age. Sometimes called Bagehot’s Dictum, the rule, laid bare by Bagehot in his 1873 book Lombard Street, stated that to stave off panic and contagion central banks should lend freely to all borrowers with sufficient collateral at a rate of interest high relative to pre-panic levels.

Implemented but left unarticulated by U.S. Treasury Secretary Alexander Hamilton (1757? - 1804) during financial panics in 1791 and 1792, Bagehot’s Rule ensured that solvent firms could borrow from the central bank when needed but had incentive to do so only when no private lender would provide better terms. The collateral requirements minimized moral hazard while also protecting the central bank from losses. In the aftermath of the 2008 global financial crisis, central bankers, including the Fed’s Brian F. Madigan, pointed to the continued overall usefulness of Bagehot’s Rule when “interpreted in the context of the modern structure of financial markets and institutions.”

A Ph.D. economist, Anderson wrote economic analyses for the Chase Economic Bulletin for much of the 1920s and 1930s. One of his themes was that America thrived due to trade, not tariffs. Policymakers ignored his analysis until America’s high tariff regime exacerbated the Great Depression and helped foment the Second World War. As nineteenth century French political economist Frederic Bastiat (1801-1850) put it, “Barriers result in isolation; isolation gives rise to hatred; hatred, to war; war, to invasion.”

Especially relevant for policy discussions today, Anderson warned against what he termed “the balance of trade bogey.” Americans fetishized a “favorable balance of trade,” but “the fear” of imports, he explained, “is an idle one” because “Europe will not merely send us goods, but will also provide us with funds with which to pay for them.” “A rich capitalist country,” he concluded, “can afford to import more than it exports.”

Financial journalist and notorious corporate gadfly Soss used her weekly NBC radio show, Pocketbook News, to push for corporate governance reforms like cumulative voting and independent audits.

Importantly, Soss leveraged her empirical studies of widespread female stockownership to induce many major U.S. corporations in the 1950s, 60s and 70s to put qualified women, like Alice E. Crawford of the Corn Exchange Bank, on their boards. Women remain underrepresented in C-suites but, thanks in large part to Soss’s trenchant analysis and promotional efforts, female directors are no longer anomalies.   

Economic analyses require information acquisition but also the ability to process data and news as rationally as possible given the natural constraints of the human brain. Many of the best models are mental, incapable of being explicitly shared because they form from embodied human capital, or what was once known as wisdom.

To gain an edge over competitors, economic analysts think opportunistically and flexibly, like a fox, hunter, or natural intelligence, not in well-worn rows, like a hedgehog, farmer, or artificial intelligence. Like Anderson, Bagehot, Buffett, Greenspan, and Soss, the best economic analysts read widely and critically, selecting readings based on their perspicacity rather than reputation or popularity. Then, they write.