Productivity: Do Low Real Wages Explain the Slowdown?

GDP per Worker, 1947Q1 to 2016Q2,rev

A.  Introduction, and the Record on Productivity Growth

There is nothing more important to long term economic growth than the growth in productivity.  And as shown in the chart above, productivity (measured here by real GDP in 2009 dollars per worker employed) is now over $115,000.  This is 2.6 times what it was in 1947 (when it was $44,400 per worker), and largely explains why living standards are higher now than then.  But productivity growth in recent decades has not matched what was achieved between 1947 and the mid-1960s, and there has been an especially sharp slowdown since late 2010.  The question is why?

Productivity is not the whole story; distribution also matters.  And as this blog has discussed before, while all income groups enjoyed similar improvements in their incomes between 1947 and 1980 (with those improvements also similar to the growth in productivity over that period), since then the fruits of economic growth have gone only to the higher income groups, while the real incomes of the bottom 90% have stagnated.  The importance of this will be discussed further below.  But for the moment, we will concentrate on overall productivity, and what has happened to it especially in recent years.

As noted, the overall growth in productivity since 1947 has been huge.  The chart above is calculated from data reported by the BEA (for GDP) and the BLS (for employment).  It is productivity at its most basic:  Output per person employed.  Note that there are other, more elaborate, measures of productivity one might often see, which seek to control, for example, for the level of capital or for the education structure of the labor force.  But for this post, we will focus simply on output per person employed.

(Technical Note on the Data: The most reliable data on employment comes from the CES survey of employers of the BLS, but this survey excludes farm employment.  However, this exclusion is small and will not have a significant impact on the growth rates.  Total employment in agriculture, forestry, fishing, and hunting, which is broader than farm employment only, accounts for only 1.4% of total employment, and this sector is 1.2% of GDP.)

While the overall rise in productivity since 1947 has been huge, the pace of productivity growth was not always the same.  There have been year-to-year fluctuations, not surprisingly, but these even out over time and are not significant. There are also somewhat longer term fluctuations tied to the business cycle, and these can be significant on time scales of a decade or so.  Productivity growth slows in the later phases of a business expansion, and may well fall as an economic downturn starts to develop.  But once well into a downturn, with businesses laying off workers rapidly (with the least productive workers the most likely to be laid off first), one will often see productivity (of those still employed) rise.  And it will then rise further in the early stages of an expansion as output grows while new hiring lags.

Setting aside these shorter-term patterns, one can break down productivity growth over the close to 70 year period here into three major sub-periods.  Between the first quarter of 1947 and the first quarter of 1966, productivity rose at a 2.2% annual pace.  There was then a slowdown, for reasons that are not fully clear and which economists still debate, to just a 0.4% pace between the first quarter of 1966 and the first quarter of 1982.  The pace of productivity growth then rose again, to 1.4% a year between the first quarter of 1982 and the second quarter of 2016.  But this was well less than the 2.2% pace the US enjoyed before.

An important question is why did productivity growth slow from a 2.2% pace between the late 1940s and mid-1960s, to a 1.4% pace since 1982.  Such a slowdown, if sustained, might not appear like much, but the impact would in fact be significant.  Over a 50 year period, for example, real output per worker would be 50% higher with growth at a 2.2% than it would be with growth at a 1.4% pace.

There is also an important question of whether productivity growth has slowed even further in recent years.  This might well still be a business cycle effect, as the economy has recovered from the 2008/09 downturn but only slowly (due to the fiscal drag from cuts in government spending).  The pace of productivity growth has been especially slow since late 2010, as is clear by blowing up the chart from above to focus on the period since 2000:

GDP per Worker, 2000Q1 to 2016Q2,rev

Productivity has increased at a rate of just 0.13% a year since late 2010.  This is slow, and a real problem if it continues.  I would hasten to add that the period here (5 1/2 years) is still too short to say with any certainty whether this will remain an issue.  There have been similar multi-year periods since 1947 when the pace of productivity growth appeared to slow, and then bounced back.  Indeed, as seen in the chart above, one would have found a similar pattern had one looked back in early 2009, with a slow pace of productivity growth observed from about 2005.

There has been a good deal of work done by excellent economists on why productivity growth has been what it was, and what it might be in the future.  But there is no consensus.  Robert J. Gordon of Northwestern University, considered by many to be the “dean in the field”, takes a pessimistic view on the prospects in his recently published magnum opus “The Rise and Fall of American Growth”.  Erik Brynjolfsson and Andrew McAfee of MIT, in contrast, argue for a more optimistic view in their recent work “The Second Machine Age” (although “optimistic” might not be the right word because of their concern for the implication of this for jobs).  They see productivity growth progressing rapidly, if not accelerating.

But such explanations are focused on possible productivity growth as dictated by what is possible technologically.  A separate factor, I would argue, is whether investment in fact takes place that makes use of the technology that is available.  And this may well be a dominant consideration when examining the change in productivity over the short and medium terms.  A technology is irrelevant if it is not incorporated into the actual production process.  And it is only incorporated into the production process via investment.

To understand productivity growth, and why it has fallen in recent decades and perhaps especially so in recent years, one must therefore also look at the investment taking place, and why it is what it is.  The rest of this blog post will do that.

B.  The Slowdown in the Pace of Investment

The first point to note is that net investment (i.e. after depreciation) has been falling in recent decades when expressed as a share of GDP, with this true for both private and public investment:

Domestic Fixed Investment, Total, Public, and Private, Net, percentage of GDP, 1951 to 2015, updated Aug 16, 2016

Total net investment has been on a clear downward trend since the mid-1960s.  Private net investment has been volatile, falling sharply with the onset of an economic downturn and then recovering.  But since the late 1970s its trend has also clearly been downward. Net private investment has been less than 3 1/2% of GDP in recent years, or less than half what it averaged between 1951 and 1980 (of over 7% of GDP).  And net public investment, while less volatile, has plummeted over time.  It averaged 3.1% of GDP between 1951 and 1968, but is only 0.5% of GDP now (as of 2015), or less than one-sixth of what it was before.

With falling net investment, the rates of growth of public and private capital stocks (fixed assets) have fallen (where 2014 is the most recent year for which the BEA has released such data):

Rate of Growth In Per Capita Net Stock of Private and Government Fixed Assets, edited, 1951 to 2014

Indeed, expressed in per capita terms, the stock of public capital is now falling.  The decrepit state of our highways, bridges, and other public infrastructure should not be a surprise.  And the stock of private capital fell each year between 2009 and 2011, with some recovery since but still at almost record low growth.

Even setting aside the recent low (or even negative) figures, the trend in the pace of growth for both public and private capital has declined since the mid-1960s.  Why might this be?

C.  Why Has Investment Slowed?

The answer is simple and clear for pubic capital.  Conservative politicians, in both the US Congress and in many states, have forced cuts in public investment over the years to the current low levels.  For whatever reasons, whether ideological or something else, conservative politicians have insisted on cutting or even blocking much of what the United States used to invest in publicly.

Yet public, like private, investment is important to productivity.  It is not only commuters trying to get to work who spend time in traffic jams from inadequate roads, and hence face work days of not 8 1/2 hours, but rather 10 or 11 or even 12 hours (with consequent adverse impacts on their productivity).  It affects also truck drivers and repairmen, who can accomplish less on their jobs due to time spent in jams.  Or, as a consequence of inadequate public investment in computer technology, a greater number of public sector workers are required than otherwise, in jobs ranging from issuing driver’s licenses to enrolling people in Medicare.  Inadequate public investment can hold back economic productivity in many ways.

The reasons behind the fall in private investment are less obvious, but more interesting. An obvious possible cause to check is whether private profitability has fallen.  If it has, then a reduction in private investment relative to output would not be a surprise.  But this has in fact not been the case:

Rate of Return on Produced Assets, 1951 to 2015, updated

The nominal rate of return on private investment has not only been high, but also surprisingly steady over the years.  Profits are defined here as the net operating surplus of all private entities, and is taken from the national account figures of the BEA.  They are then taken as a ratio to the stock of private produced assets (fixed assets plus inventories) as of the beginning of the year.  This rate of return has varied only between 8 and 13% over the period since at least 1951, and over the last several years has been around 11%.

Many might be surprised by both this high level of profitability and its lack of volatility.  I was.  But it should be noted that the measure of profitability here, net operating surplus, is a broad measure of all the returns to capital.  It includes not only corporate profitability, but also profits of unincorporated businesses, payments of interest (on borrowed capital), and payments of rents (as on buildings). That is, this is the return on all forms of private productive capital in the economy.

The real rates of return have been more volatile, and were especially low between 1974 and 1983, when inflation was high.  They are measured here by adjusting the nominal returns for inflation, using the GDP deflator as the measure for inflation.  But this real rate of return was a good 9.6% in 2015.  That is high for a real rate of return.  It was higher than that only for one year late in the Clinton administration, and for several years between the early 1950s and the mid-1960s.  But it was never higher than 11%.  The current real rate of return on private capital is far from low.

Why then has private investment slowed, in relation to output, if profitability is as high now as it has ever been since the 1950s?  One could conceive of several possible reasons. They include:

a)  Along the lines of what Robert Gordon has argued, perhaps the underlying pace of technological progress has slowed, and thus there is less of an incentive to undertake new investments (since the returns to replacing old capital with new capital will be less).  The rate of growth of capital then slows, and this keeps up profitability (as the capital becomes more scarce relative to output) even as the attractiveness of new investment diminishes.

b)  Conservatives might argue that the reduced pace of investment could be due to increased governmental regulations, which makes investment more difficult and raises its cost.  This might be difficult to reconcile with the rate of return on capital nonetheless remaining high, but in principle could be if one argues that the slower pace of new investment keeps up profitability as capital then becomes more scarce relative to output. But note that this argument would require that the increased burden of regulation began during the Reagan years in the early 1980s (when the share of private investment in GDP first started to slow – see the chart above), and built up steadily since then through both Republican and Democratic administrations.  It would not be something that started only recently under Obama.

c)  One could also argue that the reduced investment might be a consequence of “Baumol’s Cost Disease”.  This was discussed in earlier posts on this blog, both for overall government spending and for government investment in infrastructure specifically.  As discussed in those posts, Baumol’s Cost Disease explains why activities where productivity growth may be relatively more difficult to achieve than in other activities, will see their relative costs increase over time.  Construction is an example, where productivity growth has been historically more difficult to achieve than has been the case in manufacturing.  Thus the cost of investing, both public and private, relative to the cost of other items will increase over time.  This can then also be a possible explanation of slowing new investment, with that slower investment then keeping profitability up due to increasing scarcity of capital.

One problem with each of the possible explanations described above is that they all depend on capital investments becoming less attractive than before, either due to higher costs or due to reduced prospective return.  If such factors were indeed critical, one would need to take into account also the effect of taxes on investment returns.  And such taxes have been cut sharply over this same period.  As discussed in an earlier blog post, taxes on corporate profits, for example, are taxed now at an effective rate of less than 20%, based on what is actually paid after all the legal deductions and credits are included.  And this tax rate has fallen steadily over time.  The current 20% rate is less than half the effective rate that applied in the 1950s and 1960s, when the effective rate averaged almost 45%.  And the tax rate on long-term capital gains, as would apply to returns on capital to individuals, fell from a peak of just below 40% in the mid-1970s to just 15% following the Bush II tax cuts and to 20% since 2013.

Such sharp cuts in taxes on profits implies that the after-tax rate of return on assets has risen sharply (the before-tax rate of return, shown on the chart above, has been flat).  Yet despite this, private investment has fallen steadily since the early 1980s as a share of GDP.

Such explanations for the reason behind the fall in private investment since the early 1980s are therefore questionable.  However, the purpose of this blog post is not to debate this. Economists are good at coming up with models, possibly convoluted, which can explain things ex post.  Several could apply here.

Rather, I would suggest that there might be an alternative explanation for why private investment has been declining.  While consistent with basic economics, I have not seen it before.  This explanation focuses on the stagnant real wages seen since the early 1980s, and the impact this would have on whether or not to invest.

D.  The Impact of Low Real Wages

Real wages have stagnated in the US since the early 1980s, as has been discussed in earlier posts on this blog (see in particular this post).  The chart below, updated to the most recent figures available, compares the real median wage since 1979 (the earliest year available for this data series) to real GDP per worker employed:

Real GDP per Worker versus Real Median Wage, 1979Q1 to 2016Q2, rev

Real median wages have been flat overall:  Just 3% higher in 2016 than what they were 37 years before.  But real GDP per worker is almost 60% higher over this same period.  This has critically important implications for both private investment and for productivity growth. To sum up in one line the discussion that will follow below, there is less and less reason to invest in new, productivity enhancing, capital, if labor is available at a stagnant real wage that has changed little in 37 years.

Traditional economics, as commonly taught, would find it difficult to explain the observed stagnation in real wages while productivity has risen (even if at a slower pace than before). A core result taught in microeconomics is that in “perfectly competitive” markets, labor will be paid the value of its marginal product.  One would not then see a divergence such as that seen in this chart between growth in productivity and a lack of growth in the real wage.

(The more careful observers among the readers of this post might note that the productivity curve shown here is for average productivity, and not the marginal productivity of an extra worker.  This is true.  Marginal productivity for the economy as a whole cannot be easily observed, nor indeed even be well defined.  However, one should note that the average productivity curve, as shown here, is rising over time.  This can only happen if marginal productivity on new investments are above average productivity at any point in time.  For other reasons, the real average wage would not rise permanently above average productivity (there would be an “adding-up” problem otherwise), but the theory would still predict a rise in the real wage with the increase in observed productivity.)

There are, however, clear reasons why workers might not be paid the value of their marginal product in the real world.  As noted, the theory applies in markets that are assumed to be perfectly competitive, and there are many reasons why this is not the case in the world we live in.  Perfect competition assumes that both parties to the transaction (the workers and employers) have complete information on not only the opportunities available in the market and on the abilities of the individual worker, but also that there are no costs to switching to an alternative worker or employer.  If there is a job on the other side of the country that would pay the individual worker a bit more, then the theory assumes the worker will switch to it.  But there are, of course, significant costs to moving to the other side of the country.  Furthermore, there will be uncertainty on what the abilities of any individual worker will be, so employers will normally seek to keep the workers they already have to fill their needs (as they know what these workers can do), than take a risk on a largely unknown new worker who might be willing to work for a lower wage.

For these and other reasons, labor markets are not perfectly competitive, and one should not then be surprised to find workers are not being paid the value of their marginal product.  But there is also an important factor coming from the macroeconomy. Microeconomics assumes that all resources, including labor resources, are being fully employed.  But unemployment exists and is often substantial.  Additional workers can then be hired at the current wage, without a need for the firm to raise that wage.  And that will hold whether or not the productivity of those workers has risen.

In such an environment, when unemployment is substantial one should not be surprised to find a divergence between growth in productivity and growth in the real wage.  And while there have of course been sharp fluctuations arising from the business cycle in the rate of unemployment from year to year, the simple average in the rate since 1979 has been 6.4%.  This is well in excess of what is normally considered the full employment rate of unemployment (of 5% or less).  Macro policy (both fiscal and monetary) has not done a very good job in most of the years since 1979 in ensuring there is sufficient demand in the aggregate in the economy to allow all workers who want to be employed in fact to be employed.

In such an environment, of workers being available for hire at a stagnant real wage which over time diverges more and more from their productivity, consider the investment decision a private firm faces.  Suppose they see a market opportunity and can sell more. To produce more, they have two options.  They can hire more labor to work with their existing plant and equipment to produce more, or they can invest in new plant and equipment.  If they choose the latter, they can produce more with fewer workers than they would otherwise need at the new level of production.  There will be more output per unit of labor input, or put another way, productivity will rise if the latter option is chosen.

But in an economy where labor is available at a flat real wage that has not changed in decades, the best choice will often simply be to hire more labor.  The labor is cheap.  New investment has a cost, and if the cost of the alternative (hire more labor) is low enough, then it is more profitable for the firm simply to hire more labor.  Productivity in such a case will then not go up, and may indeed even go down.  But this could be the economically wise choice, if labor is cheap enough.

Viewed in this way, one can see that the interpretation of many conservatives on the relationship between productivity growth and the real wage has it backwards.  Real wages have not been stagnant because productivity growth has been slow.  Labor productivity since 1979 has grown by a cumulative 60%, while real median wages have been basically flat.

Rather, the causation may well be going the other way.  Stagnant and low real wages have led to less and less of an incentive for private firms to invest.  And such a cut-back is precisely what we saw in the chart above on private (as well as public) investment as a share of GDP.  With less investment, the pace of productivity growth has then slowed.

As a reflection of this confusion, conservatives have denounced any effort to raise wages, asserting that if this is done, jobs will be lost as firms choose instead to invest and automate.  They assert that raising the minimum wage, which is currently lower in real terms than what it was when Harry Truman was president, would lead to minimum wage workers losing their jobs.  As a former CEO of McDonalds put it in a widely cited news report from last May, a $15 minimum wage would lead to “a job loss like you can’t believe.”   Fast food outlets like McDonalds would then find it better to invest in robotic arms to bag the french fries, he said, rather than hire workers to do this.

This is true.  The confusion comes from the widespread presumption that this is necessarily bad.  Outlets like McDonalds would then require fewer workers, but they would still need workers (including to operate the robotic arms), and those workers would be more productive.  They could be paid more, and would be if the minimum wage is raised.

The error in the argument comes from the presumption that the workers being employed at the current minimum wage of $7.25 an hour do not and can not possess the skills needed to be employed in some other job.  There is no reason to believe this to be the case.  There was no problem with ensuring workers could be fully employed at a minimum wage which in real terms was higher in 1950, when Harry Truman was president, than what it is now.  And average worker productivity is 2.4 times higher now than what it was then.

Ensuring full employment in the economy as a whole is not a responsibility of private business.  Rather, it is a government responsibility.  Fiscal and monetary policy need to be managed so that labor markets are tight enough to ensure all workers who want a job can get a job, while not so tight at to lead to inflation.

Following the economic collapse at the end of the Bush administration in 2008, monetary policy did all it could to try to ensure sufficient aggregate demand in the economy (interest rates were held at or close to zero).  But monetary policy alone will not be enough when the economy collapsed as far as it did in 2008.  It needs to be complemented by supportive fiscal policy.  While there was the initial stimulus package of Obama which was critical to stabilizing the economy, it did not go far enough and was allowed to run out. And government spending from 2010 was then cut, acting as a drag which kept the pace of recovery slow.  The economy has only in the past year returned to close to full employment.  It is not a coincidence that real wages are finally starting to rise (as seen in the chart above).

E.  Conclusion

Productivity growth is key in any economy.  Over the long run, living standards can only improve if productivity does.  Hence there is reason to be concerned with the slower pace of productivity growth seen since the early 1980s, and especially in recent years.

Investment, both public and private, is what leads to productivity growth, but the pace of investment has slowed since the levels seen in the 1950s and 60s.  The cause of the decline in public investment is clear:  Conservative politicians have slowed or even blocked public investment.  The result is obvious in our public infrastructure:  It is overused, under-maintained, and often an embarrassment.

The cause of the slowdown in private investment is less obvious, but equally important. First, one cannot blame a decline in private investment on a fall in profitability:  Profitability is higher now than it has been in all but one year since the mid-1960s.

Rather, one needs to recognize that the incentive to invest in productivity enhancing tools will not be there (or not there to the same extent) if labor can be hired at a wage that has stagnated for decades, and which over time became lower and lower relative to existing productivity.  It then makes more sense for firms to hire more workers with their existing stock of capital and other equipment, rather than invest in new, productivity enhancing, capital.  And this is what we have observed:  Workers are being hired, but productivity is not growing.

An argument is often made that if firms did indeed invest in capital and equipment that would raise productivity, that workers would then lose their jobs.  This is actually true by definition:  If productivity is higher, then the firm needs fewer workers per unit of output than they would otherwise.  But whether more workers would be employed in the economy as a whole does not depend on the actions of any individual firm, but rather on whether fiscal and monetary policy is managed to ensure full employment.

That is, it is the investment decisions of private firms which determine whether productivity will grow or not.  It is the macro management decisions of government which determine whether workers will be fully employed or not.

To put this bluntly, and in simplistic “bumper sticker” type terms, one could say that private businesses are not job creators, but rather job destroyers.  And that is fine.  Higher productivity means that a firm needs fewer workers to produce what they make than would otherwise have been needed, and this is important for ensuring efficiency.  As a necessary complement to this, however, it is the actions of government, through its fiscal and monetary policies, which “creates” jobs by managing aggregate demand to ensure all workers who want to be employed, are employed.

The Highly Skewed Growth of Incomes Since 1980: Only the Top 0.5% Have Done Better Than Before

Piketty - Saez 1947 to 2014, June 2015, log scale

A)  Introduction

The distribution of the gains from growth have become terribly skewed since around 1980, as the chart above shows and as has been discussed in a number of posts on this blog (see, for example, here, here, here, here, and here).  From 1980 to 2014, the bottom 90% of households have seen their real income fall by 3%, while the top 0.01% have enjoyed growth of 386%.  This was not the case in the post-war years up to 1980:  Over those decades the different income groups saw similar increases in their real per household incomes:  By 87% for average income for the period between 1947 and 1980. But that ended around 1980.

The data underlying these figures were recently updated to include estimates for 2014, and this may be an opportune time to look at them again and more closely.   Specifically, most analyses (as well as the chart above) focus on the incomes of the top 10%, the top 1%, and so on, even though these are overlapping groups.  The top 10% includes the top 1%, and an open question is the extent to which the gains of the top 10% reflects gains primarily in the top 1% or also gains of those in the 90 to 99% income range.  This will be examined below.  Finally, the post will look at the question of what share of the growth in overall incomes over the full 1980 to 2014 period went to the various groups.  As one would expect, the gains were highly concentrated for the rich.  What one might find surprising is how concentrated it was.

B)  Real Income Growth (or Decline) Between 1980 and 2014 

As seen in the chart above, the rich got far richer in the period since 1980, while not just the poor but even those making up fully 90% of the population, got poorer.

The data in the chart come from Professor Emmanuel Saez of UC Berkeley, who has for some years been providing the figures from which the incomes of the very rich can be calculated, often in collaboration with the now better known Thomas Piketty.  In late June, Saez released data updated through 2014:  See his June 29 post at the Washington Center for Equitable Growth website, with links there to an Excel spreadsheet from which the data used here was downloaded.  The basic data are now also available at the World Top Incomes Database, of Facundo Alvaredo, Tony Atkinson, Thomas Piketty, and Emmanuel Saez.  Note that this data for 2014 reflects initial estimates.  They may change as more detailed figures are released by the IRS (the ultimate source for the data).

The chart covers the 1947 to 2014 period, indexed to 1980 = 100 for each of the groups. A logarithmic scale is used as equal proportional changes will then show as equal distances on the vertical axis.  That is, the distance between index values of 50 and 100, between 100 and 200, and between 200 and 400, will all be equal as all represent a doubling on income.  This makes it easier to see and track relative changes in values across different periods, for example between 1947 and 1980 in comparison to 1980 to 2014.

The data through 2014 confirm the trends discussed before in this blog, with a sharp increase in inequality since 1980 but also with large year to year fluctuations.  The year to year fluctuations are especially large for the very richest.  The incomes reported here come from anonymized tax return data, and hence reflect incomes by tax reporting units (generally households) with incomes as defined for tax purposes.  The income figures include income from realized capital gains, and hence one sees peaks (especially among the very rich) around 2000 (due to the dotcom bubble) and again in the middle of the first decade of the 2000s (coinciding with the housing as well as stock market bubbles of those years). The fluctuations between 2012 and 2014 can also be explained, at least in part, from tax law changes.  The Bush tax cuts were allowed to expire for the very rich in 2013 (they were made permanent for everyone else), which created an incentive for the rich to bring forward their taxable incomes into 2012.  This increased reported income in 2012 (when their tax rates were lower) while reducing it in 2013.  There was then a return to more normal levels in 2014.

Average household incomes rose only by 27% over 1980 to 2014, a sharp slowdown from the 87% growth achieved on average between 1947 and 1980 (with one less year as well in that period, compared to 1980 to 2014).  An earlier post on this blog discussed the immediate factors that led to this sharp deceleration in growth for average incomes (at least for wages).  But I want to focus here on the growth in incomes of the higher income groups, where there was no such slowdown.

Between 1980 and 2014, the top 10% saw their average incomes rise by 82%.  This was far better than the 27% growth in overall average household income in the period, and even more so than the 3% fall in incomes for the bottom 90%.  But it is actually similar to the growth seen for most income groups between 1947 and 1980, when average incomes rose by 87%.  One could reasonably argue that the top 10% did not do especially well over this period, but rather only saw a continuation for them of the previous trend growth.

The ones who undisputedly did especially well post 1980 were the top 1%, top 0.1%, and especially the top 0.01%.  The richer you were, the greater the increase enjoyed in the post-1980 economy.  Note there is no necessity in this:  The households are stratified by their rank in income in each year, but the growth in incomes over the period could be greater for the top 10%, say, than the top 1%.  Indeed, this was the case over the 1947 to 1980 period.  But between 1980 and 2014, the higher your income, the higher your growth in income:  The average income of the top 1% rose by 169% between 1980 and 2014, by 281% for the top 0.1%, and by 386% for the top 0.01%.

It should not be surprising that the extreme rich are pleased with how their incomes have grown since 1980, which many have not unreasonably attributed to the election that year of Ronald Reagan.  But you have not done well if you are in the bottom 90% of the population – your real income has stagnated over this period of more than a third of a century, and indeed even fell slightly.

C)  Real Income Growth of Non-Overlapping Groups

As noted above, there is a potential issue when figures are provided for the top 10%, top 1%, top 0.1%, and top 0.01%.  Even though commonly done, the figures for the top 10% include the incomes of the top 1% (and the top 0.1% and top 0.01%).  That is, these are overlapping groups, and one cannot determine just from figures presented in such a way whether the share of the top 10% increased because of higher incomes for most of those in the group, or because those in the top 1% saw an especially sharp increase.  Similarly for the top 1% and top 0.1%.  Since the very richest enjoyed such a sharp increase in their incomes, one cannot say with certainty from just these figures whether the widening distribution reflected higher incomes for most of those with higher incomes, or just for the extremely rich.

Thus it is of interest to break down the population categories into non-overlapping groups:

Piketty - Saez 1947 to 2014, by exclusive categories, log scale, June 2015The bottom 90% is as in the chart at the top of this post (decline of 3% in their real per household incomes between 1980 and 2014), and growth was 27% for average household incomes over this period.

But then it is of interest to note that those with incomes in the 90 to 99% range of households saw real income growth over this period of just 47%.  While better than the overall average of 27%, it is worse than the average growth achieved of 87% in the third of a century before 1980.  It would be difficult to argue that they have done especially well in the period since 1980.  They did worse than what average growth for everyone was before.

The group in the 99 to 99.5% percentile of income (in red in the graph) saw their incomes over the 1980 to 2014 period as a whole rise by 89%.  This was almost exactly what their growth in incomes would have been had they grown at the same rate as average incomes grew between 1947 and 1980.  Thus they did not do worse post-1980, but also not better than what the average for everyone was before.

The groups that did do better post-1980 were those in the top 0.5% of the distribution. Those whose income put them in the top 99.5 to 99.9% of the population saw income growth of 127% over this period; those in the top 99.9 to 99.99% of the population saw income growth of 219%; while those in the top 0.01% enjoyed income growth of 386%. These groups did extremely well in the post-1980 economy.

Thus the slogans about the top 1% should perhaps be refined.  It is really the top 0.5%.

D)  The Share of Growth Going to the Rich

Finally, one can calculate what share of the growth in the economy over this period accrued to the different income groups.  The measure used here is the one the Professor Saez has used in his work, and has applied to various periods (although not to the 1980 to 2014 period).  It shows what share of the growth in the overall economy was captured, in per household terms, by the group identified:

Bottom 90%

Top 10%

Top 1%

Top 0.5%

Share of income in 1980

65%

35%

10%

7%

Share of 1980-2014 growth

-7%

107%

63%

54%

Share of income in 2014

50%

50%

21%

17%

Difference in Share 1980 – 2014

-15%

15%

11%

10%

The top 10% of households accounted for a little over a third (35%) of overall household incomes in 1980.  But between 1980 and 2014, they captured 107% of the gains in overall growth, raising their share of overall incomes to 50%.  The bottom 90%, in contrast, saw their per household real incomes fall.  They “gained” a negative share of the income growth, of -7% (the mirror image of the top 10%).  Their share of overall incomes fell from almost two-thirds (65%) in 1980 to just one-half (50%) by 2014.  These are huge changes in national income shares over such a period.

Breaking this down further, it is the top 1% and even more the top 0.5% that accounted for the bulk of this worsening in distribution.  The top 1% captured 63% of the gain in overall incomes between 1980 and 2014 (in per household terms), and saw their share of overall income more than double to 21% in 2014 from “just” 10% in 1980.  But the top 0.5% captured 54% of the gains, and saw their share rise from 7% to 17% over this period, or an increase of 10% points.  That is, the increased share of the top 0.5% accounted for, by itself, fully two-thirds of the 15% point increase for the top 10%.  Yet there are only one-twentieth (1/20) as many households in the top 0.5% as the 10%.

The distribution of the gains from growth have become extremely concentrated.  Just the top 0.5% (five-thousandths of the population) captured more than half of income growth generated by the economy over this 34 year period.

E)  Conclusion

The gains from growth have accrued overwhelmingly to the very rich since 1980.  And it is not really the top 10% who have done so well, nor even the top 1%, but rather the top 0.5% .  At the same time, the bottom 90% have seen their real incomes fall.

Something changed around 1980.  Growth before then (in the period since 1947) had been much more evenly distributed, with the rich as well as the bottom 90% doing similarly well, with growth of 1.9% per annum in average household incomes (a cumulative 87%).  To be fair, one cannot say with certainty that the turning point was in 1980 rather than a few years before or a few years after.  Incomes in any given year will depend a good deal on whether the economy is growing strongly or is in recession, and (especially for the rich) whether the stock market and other asset prices are booming or in a bust. The economy was also already struggling in the 1970s.  It is therefore difficult to mark when there has been a change in trend as opposed to fluctuations caused by year to year factors.  But something happened to the economy in either 1980 or in the years surrounding it.

Ronald Reagan was of course elected president in 1980.  He launched a broad set of policies that conservatives like to praise as the “Reagan Revolution”.  There is no doubt that a deterioration in distribution resulted from many of the policies that Reagan won (large tax cuts focussed on the rich, attacks on labor unions, a focus of macro policy on inflation rather than unemployment, deregulation of financial markets and other sectors, changing wage norms which led to giant compensation packages for CEOs and others at the top, and so on).  But to be fair, one should add that other structural changes in the economy in recent decades have also had an impact on distribution, such as changes in technology, from globalization, and following from these, an increasing number of “winner-take-all” markets.

But whether due to policy or structural changes or (almost certainly) a combination of both, it is clear that policy did not counteract the resulting extreme concentration in the benefits of growth accruing to very rich.  And that is a challenge that needs to be addressed.

Why Wages Have Stagnated While GDP Has Grown: The Proximate Factors

Real GDP per Capita & Median Weekly Earnings, 1980-2013

A.  Introduction

A healthy debate appears to be developing in the run up to the 2016 elections, with politicians of all parties raising the issue of stagnant wages.  Republicans have charged that this is a recent development, and the fault of Obama, but that is certainly not the case.  As the diagram above shows, real median wages have been stagnant since at least 1980, despite real GDP per capita which is 78% higher now than then.  Real median wages are only 5% higher (and in fact unchanged from 1979).  In a normally developing economy, one would expect real GDP per capita and real wages to move together, growing at similar rates and certainly not diverging.  But that has not been the case in the US since at least the early 1980s.

Why has such a large wedge opened up between worker earnings and GDP per capita?  This blog post will look at the immediate factors that lead from one curve to the other.  This will all be data and arithmetic, but will allow one to decompose the separation into several key underlying factors.  A future blog post will look at policies that would address those factors.

B.  Moving from Growth in GDP per Capita to Stagnant Real Wages

The progression from GDP per capita to real wages, with intermediate steps shown, looks as follows:

Going from GDP per Capita to Median Wage, 1947 to 2013:14

The chart here goes back further, to 1947, to show the divergence in recent decades in a longer term perspective.  The data come from the Bureau of Economic Analysis (BEA) or the Bureau of Labor Statistics (BLS).  As one sees, the curves moved together until around the mid-1970s, after which they began to diverge.

1)  Real GDP per Capita

Starting at the top, real GDP per capita (the curve in blue) measures the progression, in real terms, of GDP per person in the US.  GDP captures the value of all goods and services produced in the economy.  Its price index, the GDP deflator, is a price index for all those goods and services.  Although there have been temporary dips with periodic recessions, real GDP per capita has in fact grown at a remarkably stable long term rate of about 1.9% per annum going back all the way to 1870.  The growth rate was in fact a bit higher, at 2.0%, from 1947 to 2014, as the 1947 starting point was somewhat below the long term trend.  With this growth, real GDP per person was 3.75 times higher in 2014 than what it was in 1947.

2)  Real GDP per FTE Worker

But wages are paid to individual workers, and the share of workers in the population can change over time.  The share has in fact grown significantly over the post-war period, and in particular since about the mid-1960s, principally due to women entering the labor force.  There will also be demographic effects leading to changes in the shares of the very young and of retirees.

With a growing share of the population in the labor force, real GDP per full time equivalent (FTE) worker (the measure of the labor force used by the BEA) will grow by less than it will per person in the population.  The path of real GDP per FTE worker (the curve in green in the chart above), will rise more slowly than the path for real GDP per capita.  The curves start to diverge in the mid-1960s, when large numbers of women began to enter the labor force.

It should also be noted that the divergence in the two paths will not necessarily continue forever.  Indeed, the paths have in fact grown broadly in parallel from around 1997 until 2008 (when GDP per capita dipped in the downturn that began in the last year of the Bush administration).  The number of women entering the labor force reached a peak as a share of the labor force around 1997, and a decade later the first of the baby boomers started to retire.

Thus while such demographic factors and labor force participation decisions led to a significant divergence in the two paths (between GDP per capita and GDP per FTE worker) from the mid-1960s to the late-1990s, the impact since then has been broadly neutral, and might in fact go the other way going forward.

3)  Average Real Wages using the GDP Deflator

Next, workers are paid wages, not units of GDP.  Wages and salaries made up roughly half of GDP in 1947, with most of the rest accounted for by profits to capital.  And it stayed in the narrow range of 49 to 51% of GDP continuously until 1974.  The share then fell to 48%, where it held until 1981, and then began to deteriorate much more sharply, to just 42% as of 2013 (the most recent year with this data).

If the share of wages in GDP had remained constant, then the growth of wages per FTE worker would have exactly matched the growth of GDP per FTE worker.  But with a declining share of wages in GDP (with a growing share of profits as the mirror image), the curve (shown in brown in the chart above) of wages per FTE worker will rise by less than the curve of real GDP per FTE worker.

4)  Average Real Wages using the Consumer Price Index

The curves so far have been measured in real terms based on the GDP deflator.  The GDP deflator is a price index that takes into account all goods and services produced in the economy, and the weights in the price index will be in accordance with the shares of each of the goods or services in the overall economy.  But to an individual, what matters is the prices of goods and services that he or she buys.  This is measured by the consumer price index (cpi), where the weights used are in accordance with the expenditures shares of households on each of the items.  These weights can be significantly different than the weights of the items in GDP, as GDP includes more than simply what households consume.

The curve in orange in the chart above is then the average real wage but with the cpi rather than the GDP deflator used to account for inflation.  From 1978 onwards, the average real wage based on the cpi grew by significantly less than the average real wage measured in terms of the GDP deflator.  That is, inflation as measured by the items that make up the cpi grew at a faster rate, from 1978 onwards, than inflation as measured by the items (and their weights) that go into the GDP deflator.  Up until 1978, the cpi and the GDP deflator grew at remarkably similar rates, so the two curves (brown and orange in the chart) follow each other closely up to that year.

What happened after 1978?  The prices of several items whose weight in the cpi is greater than their weight in the GDP deflator began to rise more rapidly than other prices.  Especially important was the rise in medical costs in recent decades, but also important was the rise in housing costs as well as energy (with energy increases already from 1974).

Thus wages expressed in terms of what households buy (the cpi) rose by less, from 1978 onwards, than when expressed in terms of what the economy produces overall (the GDP deflator).

5)  Median Real Wages using the Consumer Price Index

The final step is to note that average wages can be misleading when the distribution of wages becomes more skewed.  If the wages of a few relatively well off wage earners (lawyers, say) rise sharply, the average wage can go up even though the median wage (the wage at which 50% of the workers are earning more and 50% are earning less) has been flat.  And that median wage is what is shown as the red curve in the chart.

[Technical Note:  The median wage series used here is the median weekly earnings of full time workers, adjusted for inflation using the cpi.  The series unfortunately only starts in 1979, but is the only series on the median, as opposed to average, wage I could find that the BLS publishes which goes back even as far as that.  The source comes from the Current Population Survey, which is the same survey of households used to estimate the nation’s unemployment rate, among other statistics.]

Since 1980 (and indeed since 1979, when the series starts), the median real wage has been flat.  This is not a new phenomenon, that only began recently.  But it is a problem nonetheless, and more so because it has persisted over decades.

C.  The Astounding Deterioration in the Distribution of Income Since 1980

Aside from demographic effects (including the impact of women entering the labor force), and the differential impact of certain price increases (medical costs, as well as others), the reason median real wages have been flat since around 1980 despite an increase of real GDP per capita of close to 80% over this period, is distributional.  The share of wages in GDP has been reduced while the share of profits has increased, and the distribution within wages has favored the better off compared to the less well off (leading to a rise in the average wage even though the median wage has been flat).

That is, the US has a distribution problem.  Wages have lost relative to profits (and profits largely accrue to the rich and wealthy), and the wages of lower paid workers have fallen even while the wages of higher paid workers have risen.

There are therefore two reasons for the distribution of income at the household level to have deteriorated since 1980.  And one sees this in the data:

Piketty - Saez 1945 to 2012, Feb 2015

This is an update of a chart presented in an earlier post, with data now available through 2012, and with the period from 1945 to 1980 included on the same chart as well.  The data came from the World Top Incomes Database (now part of the World Inequality Database), which is maintained by Thomas Piketty, Emmanuel Saez, and others.  The data is drawn from individual income tax return filings, and thus the distribution is formally by tax reporting unit (which will normally be households).  The incomes reported are total taxable incomes, whether from wages or from capital.

Over the 33 years from 1947 to 1980, average reported taxable incomes rose in real terms (using the cpi price index to adjust for inflation) by 87%.  The incomes of the bottom 90%, the top 10%, and the top 0.01%, rose by almost exactly the same amount, while the incomes of the top 1% and top 0.1% also rose substantially (by 57% and 63% respectively).  It is amazing how close together all these figures are.

This changed dramatically from 1980.  As the chart above shows, the curves then started to diverge sharply.  Furthermore, the average reported income rose only by 24% over 1980 to 2012, even though real GDP per capita rose by 73% over this period.  The 24% average increase can be compared to the 28% increase over the same years in the average real wage (based on the cpi).  While from two totally different sources of data (income tax returns vs. the national income accounts of the BEA) and measuring somewhat different concepts, these are surprisingly close.

But while average real incomes per household rose by 24%, the bottom 90% saw their real incomes fall by 6%.  Instead, the rich gained tremendously:  by 80% for the top 10%, by 178% for the top 1%, by 312% for the top 0.1%, and by an astounding 431% for the top 0.01%.

The US really does have a distribution problem, and this deterioration in distribution largely explains why real median wages have stagnated since 1980, while real GDP per capita grew at a similar rate to what it had before.

D.  Summary

To summarize, in the post-war period from 1947 to about the mid-1970s, measures of real income per person grew substantially and at similar rates.  Since then, real GDP per capita continued to grow at about the same pace as it had before, but others fell back.  The median real wage has been stagnant.

One can attribute this to four effects, each of which has been broadly similar in terms of the magnitude of the impact:

a)  Real GDP per worker has grown by less than real GDP per capita, as the share of those working the population (primarily women) has grown, with this becoming important from around the mid-1960s.  However, there has been no further impact from this since around 1997 (i.e. the curves then moved in parallel).  It may be close to neutral going forward, but was an important factor in explaining the divergence in the period from the mid-1960s to the late-1990s.

b)  The average real wage (in terms of the GDP deflator) has grown by less than real GDP per worker, as the share of GDP going to wages has gone down while the share going to profits (the mirror image) has gone up, especially since about 1982.

c)  The average real wage measured in terms of the cpi has grown by less than the average real wage measured in terms of the GDP deflator, because of the rising relative price since 1978 of items important in the household consumption basket, including in particular medical costs, but also housing and energy.

d)  The median real wage has grown by less than the average real wage (and indeed has not grown at all since the data series began in 1979), because of increasing dispersion in wage earnings between the relatively highly paid and the rest.

The implication of all this is that if one wants to attack the problem of stagnant wages, one needs to address the sharp deterioration in distribution that has been observed since 1980, and secondly address issues like medical costs.  Medical costs have in fact stabilized under Obama, as was discussed in a recent post on this blog.  But while several of the measures passed as part of the Affordable Care Act (aka ObamaCare) have served to hold down costs, it is too early to say that the previous relentless upward pressure of medical costs has ended.  More needs to be done.

Future blog posts will discuss what policy measures could be taken to address the problem of stagnant real wages and the deterioration in the distribution of income, as well as what can be done to address medical costs.