This post may turn out to be unsatisfying, because it will ask some questions to which there are no good answers.  We know that if we want something to improve, we have to measure it.  So we measure the nation’s GDP (Gross Domestic Product) and its growth (or shrinkage in a recession).  And if we divide the GDP by the population, we get GDP per capita.  If it is growing, we say that the standard of living is improving.


GDP is the sum of Consumption spending, Investment spending, and Government spending.  In the relatively short run, measurement of changes in GDP per capita are probably fairly accurate. There are some problems with it, because it measures dollars spent, rather than value received, but one year over another is probably not too far off.  The problem I see is over longer periods, where technological change may deliver far more value than just the number of dollars spent.  Let me give a few examples of what I mean.


If someone spends $40 per month on his cellphone service, and increases it to $50 per month, that will increase GDP by $10 per month.  But if another person, who had no cell phone, cancels a land line that costs $40 per month, and subscribes to a cellphone plan at $40 per month, there is no change in GDP.  However, the increase in value received is enormous.  Free long distance calls (up to some limit), and the mobility of communications all beat the static nature of landlines and extra charges per long distance call.  GDP measurements won’t show this.


If XYZ company had 10 million subscribers at $40 per month each, drops the rate to win new subscribers to $30 per month, and gains 2 million more subscribers here’s what happens.  Before the price cut, they had revenues of $400 million per month, and afterwards, only $360 million per month.  But there was an increase of 20% in the people using cell phones, gaining the value they provide.  GDP went down, value provided went up.


Other key statistics have problems, too.  We like to see a low unemployment rate, below 5%.  But that doesn’t measure the participation in the labor force, which may be dropping at the same time the unemployment rate is dropping, because people give up looking for a job, quit the labor force, take government transfer payments, and are no longer counted as unemployed.


As we know, the government can borrow money long term, and spend it today.  GDP may rise through increased government spending (unless it’s for transfer payments which aren’t counted in GDP).  But we increase today at the expense of the future, when our children or grandchildren have to pay the debt through taxes.  Some will argue that debt can always be increased, we won’t go bankrupt.  That is true only up to a point—remember the problems Greece had with a sudden inability to borrow as lenders lost confidence.


So, what, if anything, is the lesson here?  I think it is that no single statistical measure can really tell us how we are doing.  Several differing measures must be looked at simultaneously, to get a whole picture that is relevant.  Politicians tend to only cite the statistic that bolsters the argument they are making at any given moment.  Policies must be designed that truly make our situation better, not just a single statistic.  As Mark Twain said, “Statistics don’t lie, but liars can use statistics”.

4 thoughts on “Economics–GDP, Measurement, and Standard of Living

  1. You’re right that a number of key indicators help paint a fuller picture. Labor productivity is a very important one you didn’t discuss above which helps temeper or explain some of the examples you mentioned.


  2. In my line of work we call measurements like this “Key Performance Indicators” or KPIs. I think one of the big challenges we face as a society is a lack of alignment on what our KPIs are. How do we know if we are being successful if we don’t know what success is?

    To define success I work with all my constituents and conduct “KPI workshops” where we all sit down together, figure out what our objectives are, and then figure out how we quantify them. Then we can deploy something loosely resembling the scientific method where we gather data, make observations, develop hypotheses, conduct experiments, and measure results.

    We say economics is a science but it’s really quite far from that. Two economists with different initial biases can write about the same topic and the layperson can read both essays/articles and be forgiven for thinking that they are about different planets. Can you imagine this happening with a scientific experiment? When two scientists write about the same thing, they may have different opinions, but the data is the same. Economists cherry-pick their data.

    I believe if we all had the same KPIs and all worked with the same data, we would be a far more “successful” society. You may be the American Centrist, but if I had a party I would call it the “Open Party”. We’d have KPIs, data would be made available (provided it doesn’t compromise security) and analysts would be free to slice and dice, uncover outliers, and develop hypotheses. Government legislation, rather than all-encompassing, would be directed towards smaller-scale tests to see if the KPIs improved, before rolling out to the general public. Building coalitions would be easier because we would have broader alignment on what our goals are and we would have actual evidence that our legislation works, as opposed to the collective “gut” of whatever party happens to be in power in this two-year cycle.


    1. Michael–I just read this. I will reply on the blog, but I want to tell you I was blown away by what you wrote, by its insights and depth. Thank you!

      Love, Dad


  3. While this post started out by saying that it “may turn out to be unsatisfying, because it will ask some questions to which there are no good answers,” actually, there are some very good answers to the questions it posed. In what I could only describe as one of the most interesting and enlightening books I’ve read in quite some time, “The Second Machine Age – Work, Progress, and Prosperity in a Time of Brilliant Technologies,” by Erik Brynjolfsson and Andrew McAfee of M.I.T. (W.W. Norton & Company Ltd., 2014), the authors treat this entire topic in great detail, and their answers are, indeed, eye-opening. Chapter 8, “Beyond GDP,” in particular, is right on point, and is highly recommended!

    Paul Richman


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