Many critiques of both Real Gross Domestic Product and The Consumer Price Index have been written. The Bureau of Labor Statisics has responded in defense of the critiques. Having evaluated the critiques and responses, I will argue for the following points:
- Numbers such as GDP or CPI should be treated as subjective judgements, produced by political actors subject to biases and pressure. They are not as objective facts about the world. Regard the GDP number as having the same truth-value as an opinion survey of government economists.
- GDP numbers are the beginning of an argument. If GDP numbers conflict with someone’s subjective judgement, one must consider whether the GDP numbers are fudged or leave out some important aspect of quality of life. Debates over the “real” value of GDP or CPI are silly, because quality of life judgements cannot be reduced to a number.
- For all the practical purposes for which GDP is used, better numbers exist or could be devised.
The Bureau of Economic Analysis calculates Nominal GDP by totaling the dollar expenditures of every person and organization in the United States. Note that the Nominal GDP number is a measure of the supply and velocity of money – it has nothing to do with the production of goods.
The government adjusts changes in Nominal GDP (the total expenditures/income of the nation) by the change in a price index to create a number known as Real GDP. This is the number that supposedly measures economic growth.
The first problem with Real GDP is the composition of the price index. This problem alone is big enough to invalidate use of GDP as a metric. To create a price index, the statisticians create a basket of goods, then track changes in the prices of those goods. This basket changes over time as consumers buy different products over time.
The trouble is that the basket excludes a) all goods that are produced but not traded and b) all goods that the economy can no longer produce at all, for whatever reason.
There is a famous example from Paul Samuelson who noted that if a man married his maid, then, all else being equal, GDP would fall. Or if a nanny has a child and quits her nanny job to take care of that child, GDP falls, despite the total amount of child care being produced remaining the exact same.
The most glaring absence from the “goods basket” is leisure time. And in fact any non-economic good is excluded: working on the house, taking care of children, doing private research, writing a book to distribute for free over the Internet. Nor is the quality of goods measured. Every time I walk down the main street of my city, I lament how every new building is so ugly and drab, compared to the gorgeous ornamental work of the buildings 100 years ago. GDP does not tell us how much we have lost in our ability to create beautiful buildings.
Futurists in the 1800s used to imagine that as society grew richer, people would work short weeks and dedicate most of their time to leisure, learning and the arts. In such a scenario, GDP would actually be stagnant or declining, as GDP statistics would not measure increased leisure. In policy circles, officials think that greater GDP is always good. But we have no idea if that is actually the case – we might be better off under scenarios where GDP is falling.
The astute reader may object, “But GDP is not trying to be a measure of well being, it is supposed to be a measure of output, to be weighed in policy decisions against other factors.” But this retort is incorrect. GDP does try to measure of well being because there is entire system of “hedonics” and quality adjustments built into the price index. These hedonic measure try to measure how much the good has improved well being.
GDP does not measure actual output of real goods. It just measures money flows and changes in a price index. If the entire industrial base atrophies, manufacturing disappears, and a country survives off of exporting its currency like 16th century Spain, the GDP and CPI statistics will not reveal the problem until it is far too late to fix.
Finally, economists and policy wonks do in fact unthinkingly focus on raising GDP without considering whether it ought to be raised. Just pick up a random academic economics paper or read a Federal Reserve report to Congress. These documents mostly discuss what factors or policies will raise Real GDP. They never discuss the scenarios in which raising GDP is actually desirable. The policy papers rarely concern the trade-offs with other factors such as leisure time, commute time, community, environment, etc. These cannot be measured, and thus get excluded from policy considerations.
Exports and Imports
The price index used by GDP excludes all imported goods. This has some logic to it. The U.S. GDP number is supposed to measure the output of the U.S. If the U.S. imports all its wool, and the price of wool rises due to a sheep epidemic in Australia, then the rising cost of wool does not represent a decline in American output.
But the logic of excluding import prices collapses upon further inspection. Imagine a nation has a thriving export industry making airplanes. The U.S. manufactures and exports the planes to Saudi Arabia, Saudi Arabia ships back oil. Now let us say that due to bad management the quality of American airplanes declines. Saudi Arabia switches to buying European made Airbus planes, and the American companies go out of business. What will happen? Nominal national income (NGDP) in dollars of the U.S. will be the same (remember, nominal national Income is simply a measure of the supply of dollars and people’s desire for cash balances, it has nothing to do with goods produced). The price of oil will rise significantly. The U.S. has fewer desired export goods to exchange for oil and thus the dollar must weaken against Saudi’s currency. The price of other goods will rise a bit due to increased oil costs, but not as much. Thus if you exclude oil from the price index, you would miss out on a huge huge drop in the production of quality export goods. And in fact, this has happened over the last decade as GDP continues to climb despite the relative lagging of the U.S. manufacturing base.
So we have good reasons for excluding imports from the price index, and good reasons for including imports. Which is correct? The economist at the Bureau of Economic Analysis tries to patch it up the best they can, and kludge a number together.
The reasonable person must admit: “We do not know.” We cannot reduce a nations output to a single number. Any attempt to do so will simply combine dozens of different assumptions that will react or cancel each other out in weird ways, giving you a resulting number that is completely useless.
And we are still not done yet.
If the price of steak rises, consumers will shift their consumption to another good, perhaps ground beef, chicken or tofu. This will in turn change the weightings used by the CPI and GDP, so that the more expensive good, now being consumed less, will get weighted less. The CPI allows limited substitution, while the GDP is a full substitution index. These different assumptions can have dramatic differences in the resulting numbers.
The various indexes attempt to correct for these substitutions, but these corrections are impossible. Any attempt to do so is just making up numbers. If, for instance, steak consumption declines as steak prices rises, it is impossible to determine why steak consumption declined and what people switched to. Maybe steak consumption declined because it was found that red meat caused heart disease, and thus peoples quality of life has improved as they are healthier. Perhaps tofu is a perfectly adequate substiute and people are just as well off as before. Or perhaps consumers stopped eating steak because they could no longer afford steak, and quality of life has in fact declined. No numbers can tell us the answer.
During a general economic decline, society will gradually lose the ability to produce the goods it once used. For instance, modern buildings lack the gorgeous decorative art of older buildings. Such masonry and art is too expensive to produce, since we sent all our young workers into college to learn how to be businessmen and lawyers instead of being artisans. This decline has made us poorer. But this will not show up in the numbers, since the price of ornamental masonry work will not show up in the GDP deflator calculations.
The GDP calculation measures the dollar value spent on infrastructure, but does not measure the amount actually produced. If the government pours money down the drain into wasteful and corruption-ridden projects, this will show up in the figures as net production.
The GDP numbers do not include depreciation. So if existing infrastructure is crumbling faster than it gets replaced, GDP might show the country as actually growing while in reality things are falling apart.
If the entire city of Detroit gets destroyed in riots, fires, crime waves, and ethnic cleansing, and is left in ruins, this catastrophe not show up in GDP numbers. In fact, GDP might actually increase since the destruction would spur the creation of new housing (which does show up in the numbers) and the average home price might actually fall (reducing the GDP deflator) due to violence making the neighborhoods unlivable.
Quality and Hedonic Adjustments
Both the Consumer Price Index and GDP deflator rely on adjustments for quality. On the surface, there is some plausibility to these adjustments. Cars have risen in price since 1970, but they have also improved greatly in quality. We now have air bags, crunch zones, better mileage, greater durability, etc. If you just look at price, you may think that purchasing power has dropped when in fact it has risen.
But few of these improvements can be quantified. Try answering for yourself: How much better is a 2010 desktop computer than a 2002 computer? 4.3 times better? 1.7 times better? 20% worse? If you cannot answer this number numerically, for yourself, how can anyone answer it, especially for the entire country?
The 2010 computer has three times the processing power, so is it three times better? But most people will never use this processing power, so for them the quality is the same. Those who hate the latest Windows and swear by Windows XP might argue that the quality has actually declined. The answer is entirely subjective.
The BEA uses several methods for adjusting price indexes based on quality. All of these methods have a surface plausibility, but upon a deeper examination they are completely invalid.
Method one is overlap pricing. For a brief period of the year, an appliance company might sell both the 2009 microwave model and the 2010 model at the same time. The price difference between the models can be used as the hedonic adjustment. This method is complete absurd. New products often sell for more even if they are not really any better. New game consoles sell for huge premiums upon release, but quickly fall in price. A new release movie costs more to see than a movie in a second run theater, that does not mean the new movie is better, it is just novel. With overlap pricing, it is impossible to determine how much of the increased prive is due to the novelty premium and how much is due to real quality improvements. Overlap pricing strategies actually measure the how the producer is extracting profits by charging more to people who show-off their status by buying the latest thing. There is no predictable relationship to overall increase in quality.
Method two is the explicit quality adjustment method in which the government tracks the amount spent on improvements. For instance, if a car company spent $100 per model adding a new support beam for safety, that would be counted as $100 worth of quality improvements. Again, this is invalid. Just because a company spent $x dollars on improvement does not mean it actually increased quality that much. This number also has the potential to exclude various items the car company might subtract from the car. The new oven might have a slick digital interface, but perhaps some of the internal parts have been replaced by plastic. Nor it is easy to distinguish improvements that are marketing gimmicks from actual long term quality improvements. The CPI excludes money spent on cosmetic changes like new paint colors and reshaped bumpers. But take the example of the Lexus that can parallel park itself. Is that a valuable long term quality improvement, or really just a gimmick that allows its rich owner to show off?
Method three is to measure some component of the product - such as processing speed or gas milage – and detect how much it improves. Again, this is often invalid because it is not possible to relate something like processing speed to an overall quality value for the product. Doubling the processing speed of the computer has no hedonic impact on my mother’s ability to send email to her friends.
These problems are not merely academic. Quality adjustments have a dramatic impact on the numbers.
From 1996 to 2010, the average sale price of an American car rose from $16,901 to $23,182 (37%). The Ford Taurus rose in price from $18,545 in 1996 to 25,018 in 2010. The cheapest Ford rose in price from $11,430 (the escort) to $13320 (the Fiesta). The cheapest Honda rose in price from $9,980 (the Civic) to $14,900 (the Fit).
Depending on the measure we use then, the prices of cars rose by 22% to 49%.
Yet from the CPI index for automobiles from January 1996 to April 2010 actually fell’ by 1.5%. In other words, the government decided that the 2011 cars are around 35% better in quality than the 1996 cars.
Compare the 1996 Ford Escort specs to the 2011 Ford Fiesta Specs. The new model has similar gas mileage, no greater trunk space, no more seats. The new model does have more horsepower, but that’s not going to get you to your destination any faster. There of course various improvements – side airbags, antilock breaks, power locks, better crunch zones. But do those advances make the 2011 car 17% better?
What is amazing though, is that if you restricted your price index to using the straight-up price numbers, and use gas milage, car space, and speed to calculate hedonic changes, then that price index would show that there has been no economic growth in the automobile sector. Growth is wiped out. The assumptions used by the BLS thus create the economic growth. Change the assumptions and you get very different growth numbers. When you hear on the news, “the economy grew by 2% annualized last quarter” remember that behind those numbers are a group of government statisticians subjectively deciding that cars got 2% better.
In other areas, the price index calculations may dramatically understate improvements in purchasing power.
A few years back, Google scanned nearly every out-of-copyright book available in the great libraries of the country. A treasure trove of millions of books is now available at my fingertips. As a student of history, this is immensely valuable to me. But such a benefit cannot be quantified, and is not included in the GDP or the CPI.
My ability to enjoy the mass media from any time period is amazing – I have near unlimited quantities of reading material music, and videos to watch all for a tiny fraction of my income.
Should the CPI include this? No. There is no way to quantify the benefit of this media production.
The web site ShadowStats does their own calculation of CPI numbers excluding all hedonics, and using the pre-Boskin commission methodology. They estimate of CPI is nearly double the official number. Is this estimate more correct? No, the entire endeavor is senseless.
The point is not that GDP numbers are overstating growth or understating growth. The point is that GDP numbers have no objective meaning whatsoever. The GDP calculation is basically a very fancy and obfuscated way of doing a subjective survey or poll of the BEA statisticians. The numbers are very sensitive to the assumptions you make, and a wide range of plausible assumptions can be used, each producing a very different GDP number. The GDP flunks a sensitivity analysis and is therefore useless. If the number seems close to your intuitive sense of how fast the economy has grown, it is because the calculations were fitted to match your intuitive sense.
Adjusting the data
Every year the BEA makes adjustments and revisions to previous years GDP data. For instance, the growth numbers for Q3 2002 were revised downward in three successive revisions. The end result was changing the growth rate from 3.3% to 2.2%. In the 2009 comprehensive revision, the growth rate for 2008 was changed from 1.1% to .4%.
Economist Jeremy Nalewaik has pointed out that GDP tends to be adjusted in the direction of the GDI estimates (GDP and GDI should be identical, GDP is calculated by adding up expenditures while GDI is calculated by adding up incomes).
Again, the point is not that these adjustments are right or wrong. The point is that the results are extremely sensitive to the assumptions and adjustments made. The end result is that GDP numbers will simply replicate what the people doing the adjustments think it should look like.
Composition problems with the Consumer Price Index
The CPI excludes the price of housing. Instead they use owner-equivalent rent. The claim is that since money paid for a home is actually income for another person, it is not necessary to include the home price in the index. But this claim applies to the price of every good. Money you pay for oil goes to the shareholders of the oil company. Money you pay for services is someone else’s income. The net result of excluding housing was creating a much lower inflation estimate for the past decade.
We all know that from 2006 to 2010 the housing market crashed. Across the nation housing prices dropped dramatically. The Case-Shiller index reported that home prices fell by 31.5%. Yet the CPI index for housing costs (based on equivalent rent) actually ‘‘rose’’ by 7.7%. Again, by using a different methodology, the CPI produces a wildly different number.
The issue becomes even more complicated when you include foreign investment. Imagine China is implementing a mercantilist policy. An American spends cash to buy goods exported from China. The Chinese recycle the money earned from exporting goods to America into buying mortgage backed securities. The American takes out a big mortgage to buy a house, mortgage bought by the Chinese. The American is effectively borrowing from the Chinese in order to fund current consumption. The net result is that America is a net seller of home equity and in return has recieved goods. The price of homes will be pushed up. In the GDP statistics this will actually show up as economic growth (since the cheap Chinese goods will push down the GDP deflator). But in reality, there has been no growth, the U.S. is simply selling off its own wealth and getting poorer.
“Give me four parameters, and I can fit an elephant. Give me five, and I can wiggle its trunk”
To recap, we have identified a half-dozen different ways in which subjective and arbitrary model changes dramatically alter the GDP number, and even change its direction. Yet still we have this intuitive sense that the GDP numbers look correct.
I do not know exactly what goes on in the minds of those at the BEA. But I assume it is no different than what goes on with a college social science major trying to write a thesis, or a marketing department trying to figure out product ROI numbers for marketing reports. That is, they keep adjusting until the numbers look plausible.
As we noted, there are huge range of adjustments that go into making the GDP. Everything from excluding oil imports, to including paid child care but not household child care, to the various hedonic adjustments are all subjective fudges. The art of model construction is that you keep tweaking these adjustments until you get something that “feels right”. While this sounds nefarious, and it is nefarious, the economist might not think so. For he assumes that it is possible to boil down the economic output to a number. He also assumes that the plausible adjustments are the best possible. Therefore, any tweak to those adjustments to make it “feel right” is a tweak towards greater accuracy, it is fine tuning.
One analyst at a government agency in Canada writes:
Much of our time is spent “forecasting,” which basically means making a common-sense appraisal of what some indicator or variable will do in the coming years, and creating a statistical model that confirms it. The second step adds nothing of value to the prediction - the math is just there for show, a means of impressing the innumerate by camouflaging shot-in-the-dark guesses in rigorous clothing.
Forecasting is a different field than compiling GDP statistics, but this quote shows the general mindset that exists.
The problem is that one cannot boil the economy down to single number. The result of this entire process is numerology. They are data mining a pre-determined conclusion. Numerology is when people calculate numbers from the Bible to get results. Since the Bible is so big, you can get pretty much any number you want. Similar with GDP. The space in which you can make adjustments and tweak variables is so great, you can get any result you want. So the fact that the numbers say GDP grows 2% a year is not adding any new knowledge about the world. The GDP calculation is a deeply complicated model that simply spits back the assumptions of the model’s creator.
In the 1990s, Congress felt that social security payments were too high, and they wanted to balance the budget, so they assigned the Boskin commission to redesign the formula. Now there is some validity to this. In my unbiased opinion as younger, working-age person, retirees were getting too much. But this was not because the CPI was “overstating” inflation. It was because a) the components of inflation that were rising the fastest affected seniors the least. Healthcare premiums were rising, but seniors get covered by Medicare. Housing costs were shooting up, but far more seniors are sellers than buyers. But in changing the CPI numbers to stop overpaying seniors, the statisticians demonstrated that the CPI is a political number that is simply adjusted until it produces the desired result.
GDP and developing countries
The use of GDP statistics becomes even more ridiculous when studying developing countries. Yale economist Chris Blattman writes:
Doesn’t it strike you as odd that the World Development Indicators have annual infant mortality data for most countries in Africa for most years? It should. Most of that data is interpolated, and the rest is (as often as not) close to made up. It’s not just the human development indicators. You wouldn’t want to be inside the sausage factory that is the GDP calculation in Chad.
A commenter on his blog, Mona follows up:
As someone who, another lifetime ago, worked on the World Development Indicators, I can corroborate the claims in that last paragraph!
Often GDP numbers for developing countries look plausible. But that could just because the number was fitted to be plausible. If the GDP number counters your intuition, you certainly cannot treat the GDP number as authoritative. Since we cannot trust the GDP number over simpler statistics and our own subjective observations, there is no reason to use the GDP number at all.
What is the overall bias in the “Real” GDP number?
To review, the Real GDP number derives from nominal national income adjusted by a price index. Nominal income is a measure of monetary inflation – it is a measure of the supply and velocity of money. Thanks to excluding certain classes of goods such as oil imports and real estate, and thanks to including hedonics, the price index is less sensitive to growth in the money supply than is national income. So in any period of monetary inflation, the economy will appear to be growing, while in periods of monetary stability the economy will appear to be shrinking. What this means is that the Real GDP number has a built in bias that makes policy makers confuse inflation with growth. Policy makers might think the economy is growing – as in 2006. But in reality the purchasing power of the average worker is eroding as the newly created money and credit is going to the well connected, while the price of oil and food rises.
Futhermore, due to the mechanics of the modern business cycle, inflation will be associated with high utilization of economic resources (ie, low unemployment) while deflation will be associated with recessions. This is another nasty problem in economics whereby there are several orthogonal forms of “economic growth” get badly mixed up. There is the “growth” that occurs when exiting a downturn – this “growth” is an increase in utilization as idle resources go back to work. This kind of “growth” can in certain circumstances be stimulated by printing money. Then there is the growth due to the invention of new technologies and products. This growth has very little to do with monetary inflation. Unfortunately all these mixed definitions leads to smart people writing hopelessly confused essays where they mistakenly try to apply policies to stimulate technological growth toward the goal of stimulating utilization growth.
Is the GDP statistic good for anything?
As we said, “GDP” refers to either Nominal GDP’ or ‘Real GDP’. ‘Nominal GDP’ is a misnomer. It is a measure of the flow of dollars, not of production. However, comparing the Nominal GDP’ of Country A in 2010 to the Nominal GDP’ of country B in the same year can be useful. Because there is an exchange rate between the two countries, comparing any cross section of income – whether that be nominal GDP, median income, wage of the average McDonald’s worker, or total taxable – will give a reasonable comparison of quality of life. Of course, there is still much room for fudge, such as purchasing power parity adjustments or potential double counting in the GDP calculations.
The so-called Real GDP number is nearly useless in all circumstances. Real GDP attempts to put a dollar price on the change of output overtime. But since there is no exchange of goods between 2010 and 1970, this can only be calculated via the tortuous statistics that I discussed above. These statistics simply replicate what the economists want to find, they do not add any information, and only create opportunities for being misled.
When you pull back the curtain behind all the adjustments, the Real GDP number is simply equivalent to a survey asking government staticians, “how much richer does your country feel today than in the past?” So if you know absolutely nothing about a country, reading the results of such a survey or of Real GDP can tell you what the consensus government opinion is. But from the point of view of analysis, or for guiding any policy decisions, the number should always be avoided. It would be much more honest to simply state a subjective opinion than to use a complicated, subjectively calculated number that pretends to be objective.
How to replace GDP and CPI
The last argument of the GDP/CPI supporters is that, “GDP/CPI may be imperfect, but it is the best number available for (insert use case here).”
There are no such use cases. The calculations have become too complicated and twisted to redeem any use out of the resulting number.
In some cases we must accept that the attempt to use any number is fundamentally flawed. But in many cases there is actually a replacement number that is far more sensible for the given purpose. Let us go through each use case one by one.
Measuring changes in well being: the Basic Living Index
Is there any way we can measure well-being numerically?
Creating some sort of “national happiness number” is an impossible task. It will contain all the problems of measuring GDP and then some. It will bury the underlying data and create endless arguments that it is not taking into account x, y, or z.
The best way to measure changes in well being over time is to do the following:
Create an index where you have precisely defined set of goods in the basket that maintain their definition over the time period that you are measuring. For instance, the basket might include:
- 100 dozen eggs
- 200 pounds of ground beef
- 300 pounds of flour
- 350 gallons of gasoline
- enough heating gas for a year
- the cheapest car that can legally drive on the highway, cost amortized over its lifetime
- a home of 1,500 square feet, in median-income metro area, 30 minutes commute from downtown
The goods should be weighted by the actual, typical consumption over the course of the year. Then the total cost of buying one year’s worth of the good should be divided by the median wage of a 30 year old male worker. The basic living index now has a precisely defined definition that is true across the entire time period: “The number of hours you must work to meet your basic needs of food, shelter, clothing, heat, and healthcare.”
Then leave everything else to subjective discussions and interpretations. Do not try to turn subjective things into a number, rather, leave them for the reader to decide. Each person can on their own evaluate subjective claims such “car prices have not fallen but we now have airbags” or “We have more access to music now, but the live music sucks.”
The primary number the government should use for monetary control is total nominal national income. Total income is simply a measure of the supply and demand for money. If the supply of money increases, national income will rise as a person will have more money to spend. If demand money for falls, by definition, the price at which a person is willing to exchange money for goods will rise, and thus national income will rise. The IRS has a very heavy interest in getting an accurate and complete accounting of total income, without double counting. And in theory, national income can be estimated from payroll taxes and corporate earnings reports, thus making it much more up to date and accurate than Nominal GDP (which in theory is the same, but the numbers don’t always track together).
The second number the government should use is an index of the prices of alternative stores of value. If the price of other stores of values are all rising with respect to dollars, that is a good sign that people no longer trust the currency. An index of alternative stores of value would include: central city real estate, farmland, stocks, oil, and gold.
Sometimes you wish to adjust prices for the purpose of illustration. You may be reading a book that cites the price of a movie ticket in 1910. What does that price mean to someone today? The best way to adjust the price is by using a measure of wages. Median wage is good if the number is available. Otherwise use the wage of a typical laborer or artisan. A wage number is less susceptible to fudge factors (although still not perfect), and is more directly aligned with what you actually want to know. If you are adjusting a price for illustration, you are trying to figure out what the price means to you. Showing a price in terms of hours of labor is more meaningful and impactful than adjusting it by some mysterious price index.
Indexing Social Security
Social Security should be indexed to nominal national income. In fact, the way to solve the entire social security crisis is to simply state that 12.6% of national income will go to social security, and whatever that income buys, it buys. If the economy produces fewer goods because seniors retire, there is no inflation adjustment possible that can give those seniors the promised income. If the cost of living increases because the economy is shrinking, everyone must bear the pain. Conversely, if the economy grows really fast, there is no reason to exclude seniors from this windfall by reducing their income.
To the extent that a changing dependency ratio is a problem, the fix should be to make part of social security income come from the tax payments of your own children. So if you had four children you get a larger payout than if you had zero children. This is fair, since social security is not actually an insurance or savings program. It is a socialization of the age-old method whereby children support their elders in retirement. But as with all socialization, it creates an incentive to freeload. The childless retirees are essentially freeloading off of the work of those who raised the next generation. Thus the childless should get less than those with children.
Comparing cross country wealth
Let us say we want to compare the wealth of two countries. The best number to use is some sort of income measure adjusted for exchange rate. One method would be to find the wage of a typical worker – carpenter, taxi driver, factory worker, secretary or whatever – and use that to find an average nominal median wage, and then multiply by the population. If the country has accurate measurements of total income, then that could be used. But for third world nations, where no good national income numbers exist, a typical wage method will give more meaningful numbers.
Simple statistics can also be more illustrative than complex calculations. Good numbers to look at include: the Big Mac index, percent of population with indoor plumbing, percent of population with electricity, or typical income in terms of purchasing gasoline, eggs, flour, or automobiles.
But you must also mix in personal observation. No number will tell you the misery caused by soot-filled air or overcrowding in slums.
Measuring the start and end of a recession
Use the unemployment rate to measure the start and end of recessions. Recessions are fundamentally a crisis of utilization, and thus to measure recessions, measure the utilization of labor. Using the unemployment rate will eliminate the absurdity of people saying the recession is over when the unemployment rate is still at 10% and rising. Any other measure of utilization is also useful, such as automobiles manufactured as a percentage of peak output.
Measuring national output
For some purposes – such as military planning, or studying the history of economic development in a country, or gauging the depth of a depression – it is useful to measure actual physical output. In this case the various industrial outputs should be measured directly. Compile a list of differnt for all industries – miles of railway, tons of steel, cargo containers shipped, KWH of electricity produced, airplane flights made, the total horsepower of all machinery, bushels of wheat, phones per capita, etc. The units on these figures are the unit that you are measuring. There is no way to convert the units to dollars and compare the results across time period. Instead just compare the output directly.
Final thoughts on GDP and the use of metrics
The GDP and CPI numbers are foundational to a vast number of academic papers. The numbers are woven into discussions and assumptions of economics. Thus to denounce the numbers as useless is to put myself in opposition to nearly all of academic economics.
But I believe such a view is justified, as noted for all the reasons above. Academia is not disciplined by external forces that make it truthful. Nobody gets fired for producing papers that are so obscurant that they can never be disproven. In any such situation, we should expect that falsehood will accumulate over time.
In working at a growing software company, we used various numbers for measuring product usage and customer satisfaction. But the numbers that worked best were the simple numbers. One executive, an MBA and former consultant, tried creating a hugely complicated “customer success model” to run the customer support department. It was a mess, it got gamed, and the department improved when that executive was replaced.
While we appreciated good data, we found it important to follow a few rules-of-thumb:
- Focus on simple, objective numbers that measure the really important things. For us it was the cancellation rate, monthly sales, % of people using the product, and overall recurring revenue.
- Subjective, speculative, projections should be done with a spreadsheet or a program. But again, keep it simple, stupid. The art of the program is not to spit out a single answer, but to allow you to model how changes to different assumptions will impact your business. A spreadsheet should be tinkered with in order to give you a holistic understanding of what drives the business.
- Do not be data driven, be data advised. Data works best as a double-check of assumptions or as a way to uncover hidden problems. Numbers should not be the north star. As the Dropbox founder says, “You cannot A/B test your way to the iPhone.” If you push to hard on metrics, people will game them, or they will focus on myopic issues rather than creating a strong product and great brand for the long-term.
- Most of the important things cannot be measured numerically.
The last point is the clincher. Family life, community bonds, the aesthetics of your neighborhood, the stress of a commute, clean air and water, the pleasures of walking through a tree-lined village or a town park, a gaggle of laughing kids running around outside, respect in the workplace, feeling useful at a job – none of this can be measured as part of GDP. And yet these are the most important things. The GDP obsession must end, as it only misguides us, in every single way.