Wassily Leontief: A General Manager For The American Economy

With the draft under 24 hours away, general managers of football teams are doing their research, trying to figure out what kind of player will best fit their needs for the upcoming year. Should they focus on the battle of the trenches, selecting an offensive or defensive lineman? Perhaps picking up a wide receiver or cornerback could help combat on the perimeter? Some team managers will look for a franchise quarterback, bringing peace and stability to the team for years to come. There are a number of ways in which a manager can pick up and arrange players into positions that will be optimal for the team. Regardless of who the team selects, the player will be beholden to the rest of the 53 man squad that he will go to games with on any given game day.

The New York Football Giants Lining up against the defensive line of the New York Jets. Photo taken from artika.info

The Pick Is In!

Nobel winning economist Wassily Leontief was the GM of America in his time, taking part in making decisions in an attempt to plan out the American economy with the use of his input-output model of analysis.

Wassily Leontief was awarded the Nobel prize in economics in 1973 “for the development of the input-output method and for its application to important economic problems.” In essence, the dude wrote the fricken book on how to look at the numerous transactions that go down in the various industries of an economy.

At age 19, he laid the foundations of input-output analysis by showing how Leon Walras’s general equilibrium theory, considered abstract at the time, was actually quantifiable. Leon Walras was an economist whose general equilibrium theory would allow for a government to potentially plan out the economy by solving a system of simultaneous equations. What were you doing at 19?

In 1941, as a professor at Harvard, Leontief showcased his expertise. Like a football team manager, he used the U.S. Census of Manufacturers data, to figure out how to call the play for the country. However, while the census certainly contained a lot of the data, it was a rough collection with many missing data points. The missing data had to be compiled through arduous sifting through countless trade journals and a mixture of sources from across the spectrum.

Unlike a football team manager, Leontief finally overcame this issue by compiling a 44 sector input-output table, containing over 2000 numbers explaining the relationships between different industries. Using this table, he was able to take the 44 sectors and consolidate them into 10 and solve the simultaneous equation coinciding with it. Keep in mind, at this point in time there was no calculator; he just had his good ‘ole brain.

Everyone in the economics community recognized the significance his work almost instantaneously, as he served as a consultant for the U.S. Bureau of Labor Statistics. He assisted them in constructing a 400-sector table that would help predict employment for major industries after WW2, when all our boys came back to the states. His goal was to ensure that we had a smooth transition from the production of tanks to the production of Chevy’s. However, input-output analysis could also be used in understanding flow of trade between countries.

Taken from Pintrest

While seeking to understand how countries trade with each other, he found a surprising trend that contradicted what most economists believed. Many economists thought that the United States traded capital-intensive goods, like planes, cars, etc. — goods that require a ton of money to produce. However, Leontief discovered that we were actually exporting wheat, sugar, and other goods that are labor intensive. What’s more is that other countries that were thought to be exporting labor intensive goods were actually trading the expensive stuff! This became known as the Leontief paradox.

Applications Of The Game Plan:

In football, each player on the team is dependent on one another: they need each other to play well to succeed. The quarterback will perform better if he has good protection. If the quarterback can play well, this is a major component on whether or not wide receivers can produce in the form of receptions, yards and touchdowns. A defensive end can flourish if his fellow linemen can command double teams, leaving him with one on one match-ups to exploit. Like the Leontief paradox, knowing what everyone is actually bringing to the table is pretty important.

The input-output model is regarded as a staple for major institutions such as the World Bank, the United Nations and the United States Department of Commerce. None of these institutions would be able to conduct their “inter-industry” analysis without Leontief’s framework.

The USSR also used this method of analysis in the foundations of their five year plans. They would use the model to set goals they would like to see the industries meet five years down the road. Though, more often than not, those objectives were never met. On the tail end of the era of the USSR, research showed that the revered input-output model needed a lot of fixing to better suit the state’s industry goals.

In 2010, the U.S. Congressional Budget Office (CBO) used inter-industry analysis to look at the effects of pricing carbon dioxide emissions. Results from the analysis revealed that if a $20 tax is placed on CO2 emissions, consumers of energy commodities such as natural gas, electricity, and gasoline would see prices go up by 10 percent. But, most other commodities would see prices go up by only one percent.

The Importance Of Data Collection

Throughout his life, Leontief campaigned against “theoretical assumptions and non observed facts.” Hence, the Leontief paradox. So obvious was his campaign that it was the title of his acceptance speech when he became the president of the American Economic Association.

Wassily Leontief, aka the General Manager Of The Planned Economy. Photo taken from Encyclopedia Britannica

He was a critic of economists that were reluctant to “get their hands dirty” by working with raw empirical data. He started the craze by bringing data to the top of the toolkit when practicing economics. Leontief did his part to rectify that err in the economist way, making quantitative data more accessible, more indispensable and advancing the study of economics. His mouth would be watering at the amount of accessible “big data” we have at our fingertips today.

The Complexity of the Game

Leontief’s model had his fair share of critics, though. His input-output matrices gave a good rough estimate of the inputs required, but failed to account for changing proportions. For example, when the cost of an input increases, producers reduce using that particular input and substitute in a cheaper alternative. This changing behavior of the producer can lead to Leontief’s matrices giving wrong answers.

GMs are not perfect. They often make many mistakes and bad picks along the way; just ask the Dallas Cowboys GM and owner Jerry Jones. In fact, only one GM can pick the best combination of players in any given year. We find out which one when the team wins the Super Bowl. Nonetheless, with all the complexities of finding the best combination of 53 people, Giants Head Coach Ben McAdoo has nothing on the hubris of Leontief in trying to find the best combination of an entire national economy.

J. R. Hicks: Lizard Monsters, Twix Bars, and Welfare Economics

The government’s radical changeover has come with some controversial changes. One of these is reducing the powers of the EPA, which some argue will be detrimental to our environment. More and more headlines fly across the screen, from the praising of the coal industry by EPA director to a call to exit from international climate defense accords.

Let’s say that a factory is pumping goop into a river, killing off some of the wildlife and turning others into giant lizard monsters.


How should a government respond? Should we stop all goop being pumped into the river entirely, should we tax the goop, or just leave it alone?

Unsurprisingly, economists are split on how to answer this question.

A lot of economists argue that their role is not to tell people what to do, but to figure out why people act in certain ways. Everybody values goods differently. So, since value is subjective, we have to be objective economists; free from any kind of moral bias. These type of economists of in the field of economic positivism.

For example, a positivist economist would likely share this particularly solution-less economic insight to our river pollution problem: “Restricting the amount of goop a factory can pump into the river will reduce competition as the costs of reducing pollution will be too high for smaller factories. On the other hand, it will also lead to cleaner rivers.”

John R. Hicks helped pioneer another camp known as welfare economics. He was the Nobel Prize winner in 1972, along with Ken Arrow, “for their pioneering contributions to general economic equilibrium theory and welfare theory.”

So what is welfare economics? They share the first step with positivists in that they would figure out why people are doing what they’re doing. The difference is that they would go a step further and prescribe the solutions to problems in our economy.

You may have seen welfare economists talking on the news, saying that in order to improve our economy we need to stop losing to China, that minimum wage needs to be raised, or that stopping a factory from pumping goop into the river is bad. They are called welfare economists because they argue for what is best for the welfare of our society.

John R. Hicks contributed heavily to welfare economics. In order to explain how, I’m going to have to throw a few more definitions in.

Before Hicks came along, economists held fast to something called the Pareto efficiency model. An economy is “Pareto efficient” if no one can become better off without making someone else worse off.

To illustrate: Let’s say you and I are an economy. I have $2 and you have a delicious Twix bar. I like Twix much more than I like $2, and you’d much rather have $2 than a Twix. If we don’t trade, we aren’t Pareto efficient. We can both be better off without making anyone worse off by trading the $2 for the Twix.

However, once we make that trade, I’m not giving you the Twix back for $2. If you start craving a Twix and want it more than the $2, we can’t trade without making me worse off and Twixless. This is Pareto efficient.

Pay me for advertising in Twix please

This is a really strict rule though. What if something makes a million people better off, but one person worse off? We’re already Pareto efficient, and with that model we shouldn’t go any further.

With this scenario in mind, J.R. Hicks created the Kaldor-Hicks efficiency criterion.

So instead of Pareto efficiency, we can use the Kaldor-Hicks efficiency. In order to discover if something is KH efficient, we use something called the “compensation test”. The test determines whether the gains to those who benefit from a proposed policy, for example, compensate the losses to those who must incur the costs, and still have gains left over. If this is the case, then the policy is worth implementing.

Instead of going back to the Twix example, it might be better to use the factory example to see the benefits of using the KH model. When measuring the factory, let’s say in this case the benefits of the factory pumping goop outweigh the costs to the river. After all, Godzilla protects us from other giant beasts like King Kong.

With the Pareto efficient model, we would refuse to allow the factory pump goop because the benefits happen at the cost of others. However, with the KH model, we can state that the factory should pump goop because of the benefits.

The EPA attempts to figure this out by doing cost-benefit analyses on proposed regulations. Although these analyses are imperfect, they are useful tools to measure the economic and social impact of EPA regulations. Should we exit from the international environmental treaty? What benefits does adhering to that treaty bring, and does it outweigh the costs?

John Hicks wasn’t so easy to pin down as a pure welfare economist, as he constantly contradicted himself. He would write in broad support of welfare economics, but then turn around and say things like this quote from his Nobel autobiography:

“I have been reluctant to pronounce on larger issues of practical economics since I am convinced that one should not pronounce unless one knows the facts; and to keep abreast of changing facts on a world, or even on a nation scale, is more than can be done by one whose main concern is with principles. A mere familiarity with statistics that have been prepared and digested by others is not sufficient.”

This seems to claim that an economist shouldn’t make broad policy judgements because we shouldn’t claim to know the right policy unless we know all the facts in a changing world. Furthermore, a mere familiarity with the statistics won’t save us either.

In the end, we’re left with a better model for understanding and trying to change the world of economics, but words of caution about hubris. Economists face the tempting danger of thinking we can know enough to solve all the worlds problems.

Pulled from nobel.org

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The industry is ripe for the harvest. Opportunities are everywhere, and in an effort to close the ever-widening skills gap prevailing in the modern economy, marijuana industry members and training schools have joined forces. Continue reading “Weed Schools Are Preparing Folks For The Modern Cannabis Industry”