The Structural Factors Behind the Steady Fall in Labor Force Participation Rates of Prime Age Workers


I would like to acknowledge and thank Mr. Steve Hipple, Economist at the Bureau of Labor Statistics, for his generous assistance in assembling data on labor force participation rates used in the blog post below.  This post would not have been possible without his help.

A.  Introduction

Increasing attention has recently been directed to the decline in labor force participation rates observed for men over the last several decades, and for women since the late 1990s.  The chart above tracks this.  It has indeed been dubbed (for men) a “quiet catastrophe” in a new book by Nicholas Eberstadt titled “Men Without Work”.

The issue has been taken up by those both on the right and on the left.  Even President Obama, in one of the rare “By invitation” pieces that The Economist occasionally publishes, has highlighted the concern in an article under his name in last week’s issue (the issue of October 8).  President Obama treats it as one of “four crucial areas of unfinished business” his successor will need to address.  A chart similar to that above is shown.  President Obama notes that in 1953, just 3% of men between the ages of 25 and 54 were not working, while the figure today is 12% (that is, the labor force participation rate fell from 97% to 88%).  The share of women of the same age group not participating in the formal labor market has similarly been falling since 1999.

While Obama is careful in his wording not to say directly that all of this increase in those not working was due to “involuntary joblessness”, he does note that involuntary joblessness takes a devastating toll on those unable to find jobs.  This is certainly correct. The fundamental question, however, is to what degree do we know whether the rise has been involuntary, and to what degree has it risen due to possibly more benign factors with rational choices being made.

Nick Eberstadt, who is perhaps the person most responsible for raising the profile of this issue, is a senior researcher at the conservative American Enterprise Institute.  He sees it as a major problem.  And a recent piece by the conservative columnist George Will, which is essentially a review of Eberstadt’s new work, appeared in the journal of conservative opinion the National Review, where it was subtitled “American men who choose not to work are choosing lives of quiet self-emasculation”.

On the left, Larry Summers praised Eberstadt’s book in a review published in the Financial Times (see this blog post of his for a non-paywalled summary), as did Justin Fox in this post at Bloomberg View.  But both emphasize factors beyond the worker’s control, in particular that “good” jobs are disappearing because of technological change (as well as, perhaps, international trade), and that America’s high prison incarceration rates have made it impossible for many men to be hired for the jobs there are.

Alan Kreuger, a Professor of Economics at Princeton and a former chair of President Obama’s Council of Economic Advisers, suggests a different factor in a recent carefully done academic analysis.  (See also this piece by Peter Coy for a non-technical summary of Krueger’s work.)  He found that poor health may well explain the high level for men, and found from independent data that nearly half of prime age men not in the labor force are taking pain medication daily.  As with the others, Krueger stresses that the issue is an important one. He concludes his paper by noting that “The decline in labor force participation in the US over the past two decades is a macroeconomic and social concern”, and that addressing it for “prime age men should be a national priority”.

While both sides have praised Eberstadt’s work, it is probably not surprising that they stress different underlying causes.  Those on the right blame individuals for becoming increasingly unwilling to work, abetted by foolish government policies that have enabled them to stay at home rather than get a job.  Those on the left emphasize instead that “good” jobs are disappearing because of technological change (as well as, perhaps, international trade), and that America’s high prison incarceration rates have made it impossible for many men to find jobs.  Professor Krueger’s conclusions are somewhere in between:  Individual factors (health) may explain what is being seen, but the health issues may be getting worse due to factors beyond the individual’s control.

It is not clear to me that any of these explanations really suffice.  But to develop an understanding of what might be going on, it is important first to examine more closely the underlying data for those who are not in the labor force and the reasons they give for this.

A first step is to separate the male and female rates, such as in the chart above.  It is an update of a chart that appeared in a post on this blog from last March (which in turn updated a similar chart from an even earlier post, from August 2014).  It tracks the monthly rates since 1948, with male and female rates shown separately as well as for everyone together.  Since demographic factors will affect labor force participation rates, particularly as a consequence of the increasing share of the baby boom generation who are now moving into their normal retirement years, the chart controls for age distribution by including only those aged between 25 and 54, the prime working years.

As the chart shows, the overall labor force participation rate (for men and women together) has been falling since the late 1990s.  The overall rate rose prior to then, but solely because the female rate was then rising strongly, as women increasingly entered into the formal, paid, job market. This peaked for women in the late 1990s, after which their rate as well as the overall rate began a slow fall.

The male rate, in contrast, started from a high level, of around 97% in the mid-1950s, after which there has been a slow but more or less steady fall.  It is now around 88%. Interestingly, since 1999 the female rate has moved almost exactly parallel to the male rate (at 83 to 84% of it, as discussed in the earlier blog post), suggesting that the underlying causes of the declines in both since 1999 might be similar.

A critical question is why.  The breakdown into separate male and female rates is a first step, but only a first step.  One wants to go beyond this.  The purpose of this blog post will be to take that next step, using BLS data I recently became aware of which reports on the survey responses of individuals on the primary reasons they are not in the labor force. This post will first review those results, and will then discuss some of the reasons that might explain the declining rates, especially for men.

B.  Non-Participation in the Labor Force by Prime-Aged Males

We will look at the rates for males first.  The chart below provides the reasons given (as a share of the male population aged 25 to 54) for why they were not participating in the labor force over the years from 1991 to 2015:

males-reasons-for-not-participating-in-the-labor-force-1991-to-2015The data was assembled by Mr. Steve Hipple, an economist on the staff of the Bureau of Labor Statistics (BLS) of the US Department of Labor.  He authored a Beyond the Numbers article of the BLS in December 2015 titled “People who are not in the labor force:  Why aren’t they working?”, which provided a first look at the reasons given by respondents for why they are not participating in the labor force, focusing on data for 2004 and for 2014.  The chart above is based on data assembled by Mr. Hipple for the full period from 1991 to 2015.

The data is derived from responses to queries made in the Annual Social and Economic Supplement to the Current Population Survey (CPS-ASEC).  This is a joint effort by the BLS (which conducts the Current Population Survey monthly, from which the official unemployment rate, among many other measures, is derived) and the US Census Bureau. The CPS-ASEC survey is undertaken once a year, each Spring, and asks a larger national sample a broad range of questions focused on conditions (such as on employment and household incomes) in the previous calendar year.  Among the questions it asks is whether each adult member of the household was in the labor force (where the labor force is defined as all those employed and all those unemployed who were actively seeking employment at some point in the year), and if not, what the reason was.  The possible responses are those listed in the chart above.

Several points should be noted:

a)  The numbers ultimately come from a survey of individuals, and hence will have the shortcomings of any survey.  There will be statistical error simply from the size of the sample, but more importantly also non-statistical error from how people choose to respond.  The reasons why an individual may not be participating in the labor force may be interpreted differently by different individuals, and multiple factors may apply (for example, they may be somewhat ill, have had difficulty in finding a job, and are at an age where early retirement is possible).  While such inherent limitations should be recognized, they also may not so much affect the trends, and the trends are of most interest here.

b)  The CPS-ASEC survey asks the respondents on their status in the previous calendar year, and covers the status over the entire year.  Hence if they were employed for part of the year but not for the full year, they would still be counted as part of the labor force.  The CPS survey, in contrast, is monthly, and asks for the status at that point in time (or, to be more precise, in the preceding week).  For this reason, one should expect to find that the share of the population counted as in the labor force to be higher in the annual figures than in the monthly figures, since they will be included in the annual numbers if they were in the labor force at any point in the previous year and not simply at the point in time of the monthly survey.  And one does see this in the results reported.  Conversely, the share not in the labor force will then be lower in the annual figures than in the monthly estimates.

The annual and monthly figures will, however, move similarly.  But note that the chart at the top of this post is based on the monthly estimates from the CPS, while the charts here for the reasons for not participating in the labor force are drawn from the annual CPS-ASEC estimates. The totals for those not in the labor force will differ for this reason.

c)  Participation in the labor force is defined as anyone in a paid job for as little as one hour in a week, plus those unemployed (defined as those actively looking for a job but do not have one). Thus to be counted as not in the labor force but “retired” or “going to school” is quite strict.  If one is retired but working for pay a few hours a week, or in school but working in the school cafeteria for some extra income, one is counted as part of the labor force and hence will be excluded from those not in the labor force.

d)  One must similarly be careful in the interpretation of the “could not find work” category.  The CPS-ASEC questionnaire asks whether the respondent had spent “any time trying to find a job” in the previous year.  If they had, they would be included in the unemployed.  If not, they would then be asked why they were not in the labor force that year, from this list of possible reasons.  Those who responded that they “could not find work” would be saying that they could not find work during this period even though they also say they had not actively searched for a job in this period.  It is possible, however, that they had looked before, could not find anything suitable, and believed this still to be the case even though they had given up actively looking.

e)  Only data going back to 1991 could be readily assembled.  While this covers a significant period, 25 years, it would be interesting if results further back were available.  The downward trend in the male participation rate started in the mid-1950s, and it would be of interest to see whether the causes prior to 1991 were similar to those since then.  I suspect they probably were, but this is speculation and one would like to see if that is indeed true.

The CPS-ASEC goes back to 1959 I believe (although initially under a different name), the monthly CPS goes back further, and a CPS questionnaire I found from 1978 asks a similar question (although without “retired” as a separate category).  The older data is not easy to access, however, and requires special software as well as expertise that I do not have.

However, the 25 years of data from 1991 to 2015 do show some interesting trends. Specifically, for the male rates (the chart above):

a)  The share of males aged 25 to 54 not in the labor force almost doubled over this period, from 5.9% of the male population in this age group in 1991 to 11.5% in 2013 and 2014 before dipping to 11.1% in 2015.  This was a significant increase.  And as the chart at the top of this post shows, this was a continuation of a similar trend in the decades prior to 1991.

b)  The increase in the total was not due to just one or two causes, but rather to substantial increases in the shares for each of the given reasons other than, interestingly, “could not find work”.  About 0.6% of the prime working age male population responded “could not find work” in 1991, and 0.7% did in 2015.  But the share reporting “could not find work” did fluctuate over the period, bumping higher in those years when the labor market was weak and unemployment high (1992, 2002, and then especially in 2009/10), and being compressed in the mid to late 1990s (the Clinton years) when labor market conditions were strong.  It appears to be capturing that labor market participation rates of prime age males are less when labor markets are weak.  This would be hidden unemployment.  However, the extent is limited.  The difference between the peak rate (in 2010) and the low rates in the late 1990s is only about 1.0% point.

c)  In terms of shares among those prime age males not participating in the labor force, the most important reason given was “ill or disabled”.  Interestingly, this share fell from close to 60% of those not in the labor force in 1991, the first year for which we have data, to 50% in 2015.  There were larger relative increases in the other causes (other than “could not find work”).

d)  The shares that rose the most (in relative terms) were the share of prime age men going full-time to school (rising from 11.0% of those prime age males not in the labor force in 1991 to 15.5% in 2015), the share retired (rising from 5.9% to 9.6%), and the share taking on home responsibilities (rising from 4.6% to 10.8%).  The share of those who could not find work fell from 10.5% to 6.3%, and the share for “other reasons” fell from 8.5% to 7.9%.

We will discuss below some of the possible reasons for these changes.

C.  Non-Participation in the Labor Force by Prime-Aged Females

A similar chart can be drawn for the responses of women not in the formal, paid, labor force.  The huge post-World War II change was of course the entry of women into the paid labor force, almost doubling from 34% of prime working age women in 1948 to 77% in 1999.  The rate then slowly fell, in parallel with the male rate, to 74% in 2015.

What dominates in the share of women not in the paid labor force is the share with home responsibilities.  This came down sharply from 1991 to 1999, as the following chart shows, and almost certainly in the period before then as well.  Since 1999 it has fluctuated, but appears to be on an upward trend (as the male rate is as well, although starting from far lower levels):


Interestingly, over the past two decades the rate fell when the labor market was strong in the mid to late 1990s, rose as the labor market weakened with the recession that began a few months after George W. Bush took office, fell once the labor market recovered (but with a lag), and then turned upward again after 2009 as the labor market weakened again. It then fell in 2015.  This pro-cyclicality may be implying that, for women, the “home responsibilities” reason is being given as the stated reason for not participating in the formal labor force, when in fact it may to some degree reflect hidden unemployment.  But we cannot know for sure.  It might also reflect what kind of jobs, and their wages, that women can get when labor market conditions are weak.  The impact of wage rates will be discussed below.

The share for “home responsibilities” remains high, however, and would dominate all else in a chart if left in.  To examine what is going on it is therefore best to first subtract out the home responsibilities cause, accounting for it separately, and then examining the break-down for all the other reasons given for not participating in the labor force.  The result then is a chart which is remarkably similar to the chart for males:


One finds:

a)  The total rate for women not in the labor force, once one excludes those with home responsibilities, almost doubles between 1991 and 2015, as it did for the males.

b)  Once again, the largest share of women of ages 25 to 54 not in the labor force (and excluding also those with home responsibilities) are those recorded as ill or disabled.  But the share ill or disabled was largely flat between 1991 and 2015, accounting for 55% of the total in 1991 and 57% in 2015.

c)  The second highest share, as with the male rates, was the share going full time to school.  But it was largely flat for this group of women, at 20.2% of the total in 1991 and 20.5% in 2015.

d)  Women, similar to men, saw a relatively high increase in the share retired, rising from 5.7% in 1991 to 12.5% in 2015.  Also similar to men, the share recorded as could not find work fell sharply from 8.2% in 1991 to 4.1% in 2015.  And the “other reasons” share also fell, as it did for the males, from 10.4% to 5.9%.

There appears then to be a similar pattern in the female rates as in the male rates once one removes the effect of home responsibilities.  Furthermore, this similar pattern held prior to 1999 as it did after that; there was not a sharp break in that year.  Indeed, excluding full time home responsibilities for both men and women, one finds that the curves of the shares in the 25 to 54 age group not in the labor force basically lie on top of each other:



For both men and women, the share not participating in the labor force (and excluding those with full time home responsibilities as well), both rose sharply over this period, basically doubling, with similar shares throughout (within a percentage point or less).

Finally, it is interesting to compare between men and women the stated underlying reasons for not participating in the labor force.  The chart above shows that the totals, once when excludes the big differences between men and women with home responsibilities, are similar, and has been over time (since at least 1991).  The chart below compares the male and female rates for the underlying reasons, for the year 2015:


The totals, excluding home responsibilities, are similar, as already seen.  But it is interesting that the male and female rates for the underlying causes, other than home responsibilities, are also mostly similar.  The shares of prime age men and women who are not in the labor force due to illness or disability are quite close, at 5.6% for men and 5.4% for women.  A conclusion that illness or disability is more of a problem for men than for women is not supported.  Also very similar are the rates in this age group who report being retired:  1.1% of men and 1.2% of women.  This is also the case for those reporting to be full time students, with rates of 1.7% for men and 1.9% for women.  The female rate reporting they could not find work is less than the male rate (0.7% for males and 0.4% for females), as is the rate reported under “other” (0.9% for males and 0.6% for females), but both of these are relatively small in absolute level.

It appears that similar factors for men and women (other than home responsibilities) might be underlying these rates, and their increase over time.  What might those be?

D.  Possible Reasons for These Changes in Shares Not in the Labor Force 

It was noted in the introduction that conservatives have interpreted the decline in the labor force participation rates, particularly of men, as reflecting an increasing unwillingness to work.  Liberals have focussed more on fewer “good jobs” or an inability to get and hold them due to conditions like previous incarceration or deteriorating health.  Can we conclude from the data reviewed above which, if any, of these interpretations might be correct?

To summarize some of the points already noted above:

a)  There appear to be multiple reasons given in the responses for each sex as to why they are not participating in the labor force.  That is, it is not just one factor that explains, at least directly, the increasing share not working.

b)  Furthermore, aside from changes in the shares taking on home responsibilities (which do differ, and differ greatly, between each sex), the multiple reasons appear to be broadly similar in the share of males and share of females not participating in the labor force.

c)  But one stated reason that is low in level and also has not grown over time is the share of the prime working age population who are not in the labor force because they say they could not find work.  The share was just 0.7% of all men of prime working age in 2015, and just 0.4% for all women of prime working age.

d)  The share saying they could not find work varies to a limited degree with the overall state of the labor market (somewhat higher when official unemployment is high, although not by a huge amount).  And while it was relatively high (in comparison to its level at other times) in 2009/2010, when official unemployment reached 10%, it is now back to levels seen previously.

e)  The “other reasons” factor is relatively low and without an obvious upward trend. This is fortunate, since we do not really know what lies behind it.  But being low, it does not appear to be important.

Can the increase be attributed then to an increased unwillingness to work, as the conservatives charge?  That is not so clear.  While this is now more speculative, one can also interpret the data as reflecting more positive developments.  Specifically:

a)  There was a substantial increase in the share of men and women aged 25 to 54 who were enrolled full time in school.  This is almost certainly a good thing.  This probably reflects an increasing share of students in their late 20s and perhaps later enrolled in post-graduate studies.  Medicine requires many years of study, for example, and business schools increasingly require students applying to their MBA programs to have worked for several years before being accepted.  One might similarly see students in post-graduate academic programs, in particular Ph.D. students, who are 25 or older.  Finally, there may now be an increasing number of students who have worked for 5 or 10 years or more who decide to go back to school to learn a new skill or profession.  This is not bad.  Finally, it is worth noting that the increasing shares of students in this 25 to 54 age group are similar for both men and women, suggesting that the underlying cause may well be due to developments in the system of education.

b)  One also sees increases, and similar increases for both men and women, in the share saying they are retired despite being age 54 or less.  Such early retirement is certainly unusual, but the shares are low (1.1% of the men in the full 25 to 54 age group in 2015, and 1.2% of the women).  But given how the retirement system has changed in recent decades, an increase over time should not be surprising. Traditional defined benefit pension systems typically required work to some age (perhaps 62 or 65) before they could be drawn.  With income in retirement now driven by individual accounts (401(k)s, IRAs, and even just normal savings), there is now more of an opportunity to retire earlier.  To the extent early retirement reflects what a person prefers, and is something that he or she can afford, this should be seen as a positive development.

c)  Home responsibilities have been the largest single reason for women not being part of the formal, paid, labor force, and came down sharply until 1999.  Since then it has risen, but with significant volatility.  As noted above, it may well reflect a degree of hidden unemployment, as it appears to rise and fall (although with a lag) with labor market conditions.  But if it is a personal preference, and something the family can afford, it is not necessarily a bad thing.

d)  The share of males reporting home responsibilities as the reason they are not participating in the formal labor force, while still well below the female rates, has trended upwards over this period.  This may reflect both changes in social acceptance of males staying home to take care of children or elderly parents, but also the increase in female participation in the labor force to the ceiling reached in 1999. With more women in the formal labor force, often in jobs that pay well, a married couple might well decide that they prefer that the husband take on home responsibilities rather than the wife.  The fact that such a choice can now be made is a good thing.

There may therefore be benign explanations for several of these developments leading to lower labor force participation rates.  From just the evidence here, we cannot be sure.  But similarly, we should not assume the development are necessarily negative.

Health issues are more complex, and also a much larger factor.  The highest single cause cited for not participating in the labor force was illness or disability, for both prime age men and for prime age women when one excludes home responsibilities.  In 2015, it accounted for 50% of the prime age men and 57% of the prime age women (excluding home responsibilities) not in the labor force.  The shares, while high, did not change that much over time.  They were 60% for men and 55% for these women in 1991.

But a roughly constant share of a total that has doubled implies a rough doubling due to illness or disability.  It is certainly possible that health conditions have deteriorated for a significant sub-set of the population in recent decades.  As earlier posts on this blog have documented, median real wages have been stagnant since around 1980.  And the distribution of income has also become remarkably worse, with all but the top 10% seeing their real incomes falling between 1980 and 2014.  Stagnant incomes do correlate with poor health status.

More directly, a study published last year by Professors Anne Case and Sir Angus Deaton (Nobel laureate) of Princeton found that mortality rates of middle-aged non-Hispanic white Americans have actually risen in the last decade and a half.  There are clearly issues with health, at least among a significant segment of the population.  This coincided with reports of increased incidence of severe pain and increased daily use of prescription strength pain killers, a factor highlighted by Professor Krueger in his paper on labor force participation rates.

It is difficult to say with certainty, however, whether such health conditions necessarily account for the rising share of prime working age Americans who report illness or disability as the reason for not participating in the labor force.  It may also be the case that the safety net that provides support for those who are ill or disabled (such as through disability insurance that is provided as part of the Social Security system in the US) has improved over time.  Workers who previously could not get such support may have remained in the official labor force, but in low wage or unproductive jobs and in great pain.  If support is now provided to such workers, which was not done before, this can be a good thing.

But it must be recognized that the level of support provided to disabled workers is extremely stingy in the US.  The average monthly benefit paid under Social Security Disability Insurance in the US is currently only $1,166 per disabled worker (as of August 2016), or $13,992 a year.  You do not take this if you can work.  The share of prime working age men not in the labor force is also higher in the US than in such countries as Canada, France, Germany, and Japan, all of which have far more generous safety nets for disabled workers than the US has.

Further work is needed to separate out these possible causes for the increase in the share reporting illness or disability.  And it is important, given the dominance of this stated reason for those not participating in the labor force.

E.  The Impact of Low and Stagnant Real Wages

Multiple factors appear, then, to underlie the rise in the share of prime working age males (for decades) and females (since 1999) who are not participating in the formal labor force. While certain analysts may emphasize one factor or another, often consistent with their particular political leanings, the truth is that the differing interpretations may well apply to different sets of individuals.  For example, those reporting that they have retired may have retired because, as noted above, they wanted to and they could afford to.  But it might well also reflect that at least some in this group could not find a good job, and hence decided (unhappily) to start to draw on their retirement savings.

More fundamentally, it is not an issue of a strict either/or.  What is missing from the various rationales given is the recognition that there are trade-offs, and a decision is made as to whether to participate or not in the formal labor force depending on a balancing of these considerations.  And this is really just basic economics.  Econ 101 teaches that decisions are made by a weighing of different factors, and that one needs to recognize that there are trade-offs.

Critical to this is the need to recognize that median real wages have been stagnant for decades, as discussed in the earlier post on this blog cited above.  The issue is not whether or not “good” jobs exist, but rather how much is being paid in wages for those jobs.  Real wages have been flat, and the minimum wage is now more than one-third less in real terms than what it was in 1968.

At such rates of pay, prime working age men or women may well find it better, for example, to go to school for a few more years in the hope of getting a better paying job later, rather than work now at relatively low wages on a job.  As standard economics teaches, an important cost of schooling (and typically far more important than the cost of tuition) is the cost of not working while one is in school.  But if wages are low, what is lost from not working is not so high, and at the margin it makes more sense to go to school. And this factor has become increasingly important over the past several decades, as real wages have stagnated.

Similarly, at the margin one might well decide to retire early, if one can afford it, than to work longer in a low paying job.  As wages have stagnated in recent decades, standard economics teaches that more workers, at the margin, will choose to switch over to early retirement.  This will also hold for those who are ill or disabled.  What matters is not just what might be available to the worker in disability payments (which are low), but how much this is relative to the wages they might earn.  As the real minimum wage has fallen over recent decades, taking disability payments (if one is eligible) becomes relatively more attractive than taking a minimum wage job.

And this of course very much holds for those taking on home responsibilities, in particular for those taking care of children or elderly parents.  If the wage of the job one can get is stagnant and low, while the cost of child care and elder care has been going up, the rational choice will increasingly be to stay at home to provide such care rather than work in a formal paid job.

The stagnation in real wages since around 1980 might then help explain, at least in part, the increase in the share in recent decades of those prime working age men and women choosing not to participate in the formal labor market.  And it is interesting to note that the pace at which prime age men have chosen to stay out of the formal labor force accelerated in the period after 1980 compared to the period before.  Over the 27 years between 1953, when the prime working age male labor force participation rate peaked at an average over the year of 97 1/2%, and 1980, when the average over the year was 94 1/2%, the average pace of change in the rate was 0.111% points a year.  Over the 36 years from 1980 to 2016, the pace picked up to an average of 0.167% points a year.  This is 50% faster.  It accelerated in the period that real wages have stagnated.

F.  Conclusion

The labor force participation rate for the prime working age population has been declining for men since the mid-1950s and for women since 1999.  This is significant.  Growth depends on the working population, and if fewer work, there will be less growth.  And not being able to find a job when one wants one, whether you are counted among the openly unemployed or the hidden unemployed, can be devastating to an individual.  It is not just the income that is lost, although this is of course hugely important, but also the impact on the psyche and sense of self-worth.

One has to be careful, however, in any attribution of the cause of this increasing share of the population not in the formal labor force.  Many factors are involved, and one should not jump to a conclusion such as that people are lazier now than they were before, or that jobs are simply not available now and were before.  Once should rather recognize that choices are being made and that there are tradeoffs.  People may rationally and happily be choosing to enroll as a full time student, or to stay at home to take care of children or elderly parents, or to retire early.

But one should similarly not jump to the conclusion that these are necessarily happy choices.  This is especially clear for those who are not working due to illness or disability, who may obtain minimal or even no support from various disability insurance programs. Indeed, I would suspect that most of those who are not working due to illness or disability are depending on a working spouse for support.

Recognizing that these are choices that are being made is simple, basic, Economics 101. The choices may be happy ones or not, but they are all choices.  Basic to such choices is what one would obtain by working at a job, which is the opportunity cost of what one is giving up by deciding not to participate in the formal, paying, job market.  Central to this is the fact that wages have been stagnant for decades in the US, since around 1980.  At the margin, it might make more sense now than it had before not to seek a job but rather to enroll as a student, take care of home responsibilities, or retire early.  This stagnation in real wages may in part explain the acceleration of the pace of working age men dropping out of the formal labor force since around 1980.

This then suggests a further reason for why we need to be concerned with real wages that have remained stagnant, despite the significant productivity growth of recent decades. Real GDP per worker (i.e. productivity) is now 60% higher than what it was in 1980, but wages have been flat.  Prior to 1980, real wages and GDP per worker both rose at a similar rate. This then broke down after around 1980.

Returning to a more equitable growth process is not, however, a trivial task nor one which can be accomplished by fiat.  But this analysis suggests that should progress be made towards this, one would then expect to see higher labor force participation rates.  And there are indeed actions the government can take.  A number were discussed in this earlier blog post.  Ensuring workers are in a position to bargain for good wages by keeping the economy at close to full employment is probably the most basic.  And raising the minimum wage, which is now more than one-third below where it was in real terms in 1968, and indeed lower in real terms than what it was when Harry Truman was president, would be important for all low wage workers.

Low and stagnant real wages have had a number of adverse effects on the economy, including on productivity.  A lower rate of labor force participation is likely also one of them. If you want more people in paying jobs, pay them better.

Health Insurance Coverage is Improving, Especially in States that Have Not Tried to Block It



A.    Introduction

The US Census Bureau released on September 13 this year’s editions of three reports which normally come out at about this time:  Its report on Income and Poverty in the United States, its report on Health Insurance Coverage, and its Supplemental Poverty Measure report, which provides figures on poverty when government transfer programs are taken into account.  They all cover the period through 2015.

The reports show exceptionally strong improvements in a range of measures of income and well-being.  To start, real median household incomes rose by an estimated 5.2% in 2015. There has never before been such a large jump in real incomes since this series first started being reported in 1967.  Perhaps more importantly than the overall gains, the Census Bureau data also show that the gains were widespread across income groups (with the poorest 10% decile in fact seeing the largest gains) as well as across race and ethnic groups.  It was not only the rich who saw an improvement.

I should hasten to add that these results are from just one year, and that they follow far less satisfactory results over the last several years.  Real household incomes plummeted in the 2008 downturn in the last year of the Bush administration, and were flat or fell further in most years since.  It should also be recognized that the Census Bureau figures are based on household surveys, and thus that there will be statistical noise (as the Census Bureau emphasizes).  It remains to be seen whether the positive news will continue.  But with labor markets now at or close to levels generally considered to be full employment, and with real wages now rising, it is likely there has been an improvement also in 2016. But we will only know a year from now what the survey results will be.

The Health Insurance Coverage report found that health insurance coverage also improved significantly in 2015, as it had also in 2014 but importantly not in the years before.  The big change in 2014 was of course the coming into effect of the Affordable Care Act (ACA, or ObamaCare) reforms, with the introduction of the market exchanges on which the previously uninsured could purchase insurance at a reasonable price, as well as the expansion of Medicaid coverage in a number of states (but not all).  There are now over 20 million more Americans who have health insurance coverage than had it in 2013, before ObamaCare went into effect.

Not surprisingly, the reports received a good deal of news coverage.  It was the lead front page article of the Washington Post the next day, for example.  Not surprisingly also, the White House released a summary of some of the key, highly positive, findings.  But while the news reports focussed on the strong income gains, and many also noted the health insurance gains, I have not seen a chart such as that above which shows the gains in historical context, and with the Medicaid expansion states and non-expansion states shown separately.  This post will discuss that chart and what is going on behind it.

B.  The Gains in Health Insurance Coverage Under ObamaCare

The chart above shows the percentage share of the population without health insurance coverage in each year from 2008 to 2015, with this shown separately for those states where Medicaid was permitted to expand (27 states plus Washington, DC, with the status taken as of January 1, 2015) and for those states that did not allow Medicaid to expand (23 states). The figures were calculated from the underlying data tables (the “HIC” series) used in the Census Bureau Health Insurance Coverage report.  The data series used here comes from the American Community Survey (ACS), which has an extremely large sample size which permits a meaningful state by state breakdown.  It asks whether the individual was uninsured at the time of the interview.

The Health Insurance Coverage report also presents figures at the national level obtained from a different survey called the Current Population Survey – Annual Social and Economic Supplement (CPS ASEC), which is undertaken each Spring. This survey has a smaller sample size than the ACS, which is fine for national level estimates but which does not suffice for state by state breakdowns (as one needs when looking at Medicaid coverage by state).  It also asks the somewhat different question of whether the individual had health insurance cover for the entire previous year, rather than on the date of the interview.

The share of the US population without health insurance coverage fell sharply in 2014 and again in 2015.  Using figures from the ACS, it had fluctuated modestly in the period from 2008 through 2013, rising from 14.6% of the population in 2008 to 15.5% as unemployment hit its peak in 2010, and then recovering slowly to 14.5% by 2013.  It then dropped sharply to 11.7% in 2014 and to 9.4% in 2015.  Critics of ObamaCare asserted at the start that the reforms did not and would not lead to more Americans being covered by health insurance.  That was certainly not the case.  By 2015, there were 20.7 million more Americans with health insurance cover than had it in 2013.  This is far from minor, and can make an immense difference in a family’s life.

The CPS ASEC figures also show a sharp drop in the share of the population without health insurance, with these figures quoted in many of the news reports one might see. With its differing definition of who is not covered (for the entire year, rather than on the date of the interview as in the ACS), the shares are somewhat lower, at 9.1% in 2015.  It fell from a 13.3% share in 2013 and a 10.4% share in 2014 in these estimates of the share of the population who did not have health insurance over the entire year.

By whichever measure, health insurance cover expanded sharply once the ObamaCare reforms entered into effect.  By the ACS measure, the share of the population without health insurance fell from 14.5% of the population in 2013 to 9.4% two years later, or by 5.1% points.  It can be expected to fall further, although not to zero.  Certain groups in the population (including certain immigrant groups) are not eligible for purchasing insurance through the ObamaCare market exchanges, and thus the non-insured rate will never go to zero.  While the floor is not certain, many analysts set the figure at perhaps 4 or 5% of the population.  If so, then the improvement seen so far is approximately half of what might ultimately be achievable, provided politically imposed roadblocks are all removed.

C.  Medicaid Expansion

The chart also shows the shares of the population without health insurance separately for the states that expanded Medicaid coverage (supported by the ACA and an integral part of it) and those that did not. The system as designed under the ACA has that the working poor and lower income classes would obtain health insurance under Medicaid, with eligibility expanded from those with income up to generally 100% of the federal poverty line previously, to 133% from 2014 onwards.  Those with incomes higher than this would purchase insurance from the market exchanges, with a subsidy that phases out as incomes grow and is phased out entirely at 400% of the federal poverty line.  Thus the entire population, no matter how poor, would be able to obtain health insurance.

However, the Supreme Court decided that Medicaid expansion could not be made obligatory on the states even if the federal government is paying for it (as it is here). Rather, the states could choose whether or not to allow Medicaid to expand cover to include those making up to 133% of the federal poverty line.  It would be financially foolish for the states not to, as the federal government would cover 100% of the cost of the expanded coverage in the first several years, with this then phasing down to 90% of the additional cost from 2020 onwards.  But even with the states covering 10% of the cost from 2020, a net gain can be expected for the state budget due to the increased incomes of hospitals, doctors, nurses, and other health car suppliers who would now be providing care to the poor when they need it (and be compensated for it), and the state tax revenues that would be generated by such higher incomes. The states would also save by being able to reduce state payments made to cover a portion of the costs incurred by hospitals to provide health services to patients who were not able to pay for their treatments, due to a lack of health insurance.

Despite this, 23 states (as of January 2015) decided that the low income earners in their states would not be allowed to receive health insurance cover from Medicaid.  Note that these families must indeed be working to be able to have an income of 100% of the federal poverty line (of $24,300 in 2016 for a household of four).  Assuming one wage earner, working 40 hours a week for 52 weeks a year (no vacations), they would need to earn a wage of $11.68 per hour to earn this much, or well above the minimum wage of $7.25 per hour.  More likely there would be two income earners in such a household, each earning a wage rate of closer to the minimum wage, but likely not able to obtain full time employment of 40 hours a week for 52 weeks a year.  These households are not slackers, but rather are working hard to get by.

Yet these states are refusing to allow such households to obtain health insurance cover from Medicaid, despite a net financial benefit to their state budgets.  And since the Affordable Care Act was structured that such families would obtain health insurance coverage from Medicaid, and not purchased (with a partial subsidy assistance) through the health insurance market exchanges, they are now left with nothing.  These states have deliberately created a gap where their low income workers are effectively denied access to health insurance.

The reason these states have done this is of course political.  The 23 states (as of January 1, 2015) that had not permitted Medicaid to expand were states with Republican governors or Republican legislatures (or mostly both) that refused to allow Medicaid in their states to serve such families.  And as noted above, this was done even at financial cost to themselves.  Nebulous arguments were given that while the federal government would be paying for most or all of the costs in the near term, the federal government might reverse this later, due perhaps to budget pressures.  But there is no reason why such a reversal should be expected, nor why, if there were indeed such budget pressures, it would apply to Medicaid but not to other federally funded programs that those states are taking advantage of.  Furthermore, if this did indeed happen at some uncertain point in the future, the Medicaid programs in the state could be cut then, rather than now in anticipation that this might somehow happen at some unknown point in the unknown future.

As shown in the chart at the top of this post, the share of the population without health insurance cover fell to just 7.2% in 2015 in the 27 states (plus Washington, DC) that allowed Medicaid to expand, far below the 12.3% in those states that blocked that expansion.  Compared to 2013, before the ObamaCare reforms went into effect, this was a reduction of 5.6% points in the states that allowed Medicaid to expand, versus a reduction of 4.5% points in the states where the expansion was blocked.  Put another way, the share of the population without health insurance fell by 43% in the states that allowed Medicaid to expand, versus a fall of just 27% in the states that blocked it.

Furthermore, the far better improvement in the Medicaid expansion states was from a lower starting point in 2013 (of 12.8% of their population without health insurance, versus 16.7% in the states blocking Medicaid expansion).  One should expect that improvement becomes more difficult as one comes closer to the achievable ceiling in coverage.

But the chart also serves to show that the states blocking Medicaid expansion historically had a high share of their populations without health insurance.  These were conservative states, often relatively poor, with political establishments that did not exhibit great concern over the fact that a high share of their population could not get health insurance.  But not all were poor.  Indeed, the state with the absolute worst share of any state was oil-rich Texas, with 22.1% of its population without health insurance in 2013, and still 17.1% without it in 2015 (where both figures were the highest in the US in the respective years). Out of 50 states (plus Washington, DC), Texas was the worst.  This was a political choice, not an economic one.

It should also be noted that the reduction in the shares of uninsured in those states that allowed Medicaid to expand was not due solely to the increased number of Medicaid enrollees.  Between 2013 and 2015, those states saw 12.2 million of their citizens obtain health insurance cover.  Of these, 7.6 million came from increased enrollment under Medicaid, while 4.5 million came from other health insurance cover (including through the ObamaCare market exchanges).  And as noted above, they were starting from a point where a relatively high share of their citizens (compared to the states where Medicaid expansion was blocked) enjoyed some form of health insurance cover previously.

D.  The States That Allowed Medicaid to Expand Also Had Lower Premiums on ObamaCare Health Insurance Plans than on Company-Based Plans

There is also an interesting finding that the states that allowed Medicaid to expand not only saw greater improvements in the shares of their citizens who enjoyed health insurance cover, but also saw insurance premiums on their ObamaCare exchanges (as of 2016) which were lower than comparable company-sponsored plans in those states.

recent study by the Urban Institute (a non-profit think tank) found that for similar health insurance cover, the full prices (before subsidies) of health insurance purchased through the ObamaCare exchanges were 10% lower on average (at the national level), than the full prices of similar health insurance plans provided through employers. The calculations were made state by state, as costs varied by state, and varied widely.  But on average, the ObamaCare plans cost 10% less.

This may be come as a surprise to many.  The issue is that most employees do not know what the full cost of their company-sponsored health insurance plans in fact is.  The full cost includes not only what they pay directly, but also what they pay indirectly through the employer (which they typically never see) as part of their overall labor compensation package.  But it is part of their wages and a cost that must be covered.

The 10% lower cost is an average at the national level.  But the Urban Institute figures are calculated at the state level, and one can calculate from this how they vary between those states that expanded their Medicaid coverage and those states that blocked it. The results are interesting.  The simple unweighted averages (I did not have the underlying data necessary to calculate a weighted average properly) were:

Health Insurance Plan Costs:  ObamaCare Exchanges vs. Company Based

Unweighted averages

All States      


Medicaid Expanded


Medicaid Not Expanded


The unweight average lower cost of the ObamaCare plans was 8% nationally.  This is different from the 10% figure the Urban Institute cited because the lower costs were especially large in some of the larger states, such as New York, Illinois, Pennsylvania, Michigan, and Ohio (all of which had lower costs of 18% or more).  In the unweighted averages, these larger states are weighted the same as smaller states.

But what is especially interesting is that the (unweighted) average lower cost of the ObamaCare plans compared to company based plans was 15% in the states that approved Medicaid expansion but was no different on average in the states that blocked Medicaid expansion.

Why would this be?  It was probably not due to the Medicaid expansion itself.  One would expect Medicaid expansion would lead to lower health insurance costs for those obtaining health insurance.  The reason is that hospitals and other health service providers will have lower costs due to less uncompensated care of patients without health insurance coverage (as more would have Medicaid coverage), and one can expect that these lower costs would then be reflected in lower health insurance costs for those who do pay. However, this should affect health insurance costs of policies purchased through the ObamaCare exchanges and company-based policies similarly, and hence would not likely affect the ratio in cost between the two.

However, the Medicaid expansion states were also the ones that encouraged competitive ObamaCare market exchanges to be established.  They did not seek to block these markets or keep them from functioning well.  They encouraged competition rather than did whatever they could to hinder it.

It was likely due to this greater degree of competition in those states that supported, rather than hindered, the ObamaCare exchanges that explains the lower costs in those states. This is also consistent with the fact noted above that many of the larger states saw especially low costs (relative to company-based plans) than were observed among the relatively smaller states.  The larger states will in general see greater competition, and competition drives down prices.

E.  ObamaCare Issues Remain

One can no longer dispute that ObamaCare has succeeded in its primary goal of making it possible for a higher share of the population to obtain the security of health insurance coverage.  But this certainly does not mean there are no issues with ObamaCare.

Republicans openly acknowledge that they continue to do whatever they can to block the expansion of access to health insurance under ObamaCare.  And these efforts to hinder ObamaCare have achieved some success.  As noted above, states that blocked Medicaid expansion have seen less of a reduction in their uninsured populations than was achieved in the states that allowed that expansion.  But the efforts to block access to ObamaCare went beyond blocking Medicaid.  Most of these states also decided not to implement directly the ObamaCare market exchanges in their states.  The Affordable Care Act envisioned that to best allow local control and adaptation to a state’s particular circumstances, state level authorities would be allowed and indeed encouraged to establish such exchanges.  Fortunately, the law also included a back-up provision that should a state choose not to establish such an exchange, the federal government could do it to allow the citizens of that state access to an affordable health insurance plan.  This was not without difficulties; recall the initial failure of the federal level computer systems when enrollment opened in October 2013 and the system was overwhelmed.

More recently, several of the larger health insurers have decided to withdraw from some of the markets in which they had previously offered health insurance plans on the ObamaCare market exchanges.  Most recently, Aetna announced in August that it would withdraw in 2017 from 11 of the 15 states where it had been offering such plans.  This followed earlier announcements by UnitedHealth and Humana that they also would be scaling back offerings significantly.  This will reduce competition among the insurers in a number of markets around the country, limiting the options enrollees in those markets will have.  Indeed, in some counties around the country there will be only one insurer offering coverage through the exchanges, and (unless something is now done) one county in Arizona where there will be no such insurer offering coverage through the exchanges.

The issues could certainly be addressed, if there is the will.  All major new social programs, including Medicare and Social Security were fine-tuned through new legislation following their launch to address issues that developed.  And this was done on a bipartisan basis. The problem now is that the Republican Party, for political reasons, is doing what it can to block any such adjustments, with the openly stated aim of trying to destroy ObamaCare.

It is still to be seen whether these efforts will succeed.  If they do, the US will revert to its previous system, with millions of Americans denied access to health insurance and with sharply rising health care costs that outpaced general inflation for decades.

Bringing Democracy to America: The Popular Vote Should Determine Who Wins the Presidency

Map of Battleground States in 2012

A.  Introduction

The US is once again in the middle of a presidential election, with possible consequences this time that are more worrying than ever.  And once again it is an election where the candidates focus their attention on a limited sub-set of US states – those states where the result is expected to be relatively close and winnable by a candidate if given sufficient attention. This is a consequence of the unique US system where presidents are selected not by who receives the most votes in the nation, but rather by who wins a plurality of votes in individual states whose electoral college votes sum to 270 or more (i.e. more than half of the total 538 electoral votes allocated across the nation).  It does not matter if the candidate wins the state by a little or a lot; they receive the same number of electoral votes from the state regardless.

Hence if a candidate is almost certain to win a state, as well as if they are almost certain to lose a state, it makes no sense to campaign there.  They gain nothing by winning by somewhat more, or by losing by somewhat less.  Total votes in the nation by the population do not count; only electoral votes count, and these are won at the state level.

This is not a democratic system, and no other democratic country in the world with a president with substantial real powers selects their president this way.  There are systems in some countries with a parliamentary form of government (where the party with a majority of seats in the parliament selects the prime minister) that might be seen as somewhat similar to an electoral college.  But in such situations, the president is largely or totally a figurehead.  In no other democratic country where the president is the head of the executive branch, other than the US, does one select that president other than through a popular vote of the entire nation.

Until recently, I had thought there was nothing one could do about this in the US other than through a constitutional amendment.  And a constitutional amendment on such an issue with divided interests, especially in the current political environment, is a non-starter. But there is in fact an initiative, already well underway, that would resolve this problem through a compact being reached across states that have at least 270 electoral votes between them.  It is actually pretty ingenious, and might well pass.  It is certainly in the interest of the three-quarters of the states that are not swing states to see it approved.

This blog post will first review some of the problems that come out of the current electoral college system.  It will then describe the National Popular Vote Interstate Compact, where an agreement would be reached to ensure electoral votes are cast for the candidate receiving the most votes nationally, and not necessarily the most votes in the individual state.  The benefits of such a system will then be examined, as well as the politics of whether or not it will ultimately be approved.

B.  The Problems With the Current Electoral College System

a)  It is Not Democracy

To start, the current system is not democratic.  Electoral votes are allocated by state to be equal to the number of congressmen from that state plus two (equal to the number of senators from each state).  There are 538 electoral votes, the sum of 435 Congressmen, 100 Senators, and 3 electoral votes granted to Washington, DC, by the 23rd amendment to the Constitution (ratified in 1961).

The result is that voters in a state like Wyoming, a small state with fewer voters even than Washington, DC, have a disproportionate share of influence in the electoral college and hence in the selection of the president.  In 2012, the voting-eligible population (VEP, equal to the voting age population of the state, less non-citizens and felons ineligible to vote) of Wyoming was 425,142.  With 3 electoral votes, Wyoming had 141,714 voters per electoral vote.

In contrast, the voting-eligible population of California in 2012 was 23,681,837 for 55 electoral votes.  Thus there were 430,579 voters in California for each of its electoral votes. That is, there were almost exactly 3 times as many voters in California per electoral vote as there were in Wyoming.  Each vote in California counted only one-third as much.  This is not democracy.  In a democracy, each vote counts the same.

It should be noted that the framers of the Constitution in 1787 never presented the selection of the US President via the electoral college as being democratic.  Congressmen were selected democratically, by popular vote.  But senators were appointed by state legislatures not by popular vote (until the 17th amendment to the Constitution was ratified in 1913) and presidents were chosen through the electoral college process.  There was an open and explicit decision to by-pass a popular vote for the president as a requirement (although that remained as an option within each state), where it was left up to each state to decide how the electors representing that state would be chosen.  Article II, Section 1, Paragraph 2, of the Constitution reads:

“Each State shall appoint, in such Manner as the Legislature thereof may direct, a Number of Electors, equal to the whole Number of Senators and Representatives to which the State may be entitled in the Congress: but no Senator or Representative, or Person holding an Office of Trust or Profit under the United States, shall be appointed an Elector.”

That is, it leaves the method to be used in a state up to the legislature of that state, with the only constraint being that the electors may not be a US Senator, a US Congressman, or a federal government official.

Not surprisingly, the states used a variety of ways initially to choose their electors.  In 1789 (when George Washington was ultimately chosen as president), there were direct popular at-large votes within a state to choose the electors in only two of the states (Maryland and Pennsylvania), and popular votes but by specially drawn districts within the states in two more (Delaware and Virginia).  The electors were simply chosen directly by the state legislatures in four of the states, and two states had hybrid systems where the voters chose a list of possible electors and the state legislatures then chose the specific electors from those lists.  Finally, one state (New York) could not decide in time what to do, and hence did nothing.  Two more (North Carolina and Rhode Island), did not accede to the Constitution until after the process was over.

In the early years of the republic, states frequently changed their system of choosing electors.  But over time, states shifted to systems where their state population would vote for their electors, as is now the case in all states (with Maine and Nebraska choosing them by votes in individual congressional districts, plus two for the winner of the state-wide vote).  The election of 1824 is generally taken as the first election where the popular vote totals were meaningful (even though in that year, 6 of the then 24 states still had their electors chosen by their legislatures).  Indeed, it appears that there is not even any record of what the vote totals were (in the states where votes were used) in the elections before 1824.

As noted, the framers of the Constitution never viewed this system as democratic.  It was only later that the myth grew that the US is a great democracy, including in how it elects the most important official in the land.  We don’t, and this should be recognized.

b)  A Candidate Can Be Elected President Even Though He or She Received Fewer Votes

Directly following from the fact the current system is not democratic, is the possible consequence that whomever receives the most votes might not win the presidency.  It is worth flagging this separately only because many believe that while this is theoretically possible, in practice it has been and would be so rare that we should not worry about it.

The results of the 2000 election between George Bush and Al Gore did serve to wake people up that this result is indeed possible in modern times.  Al Gore won the nation-wide popular vote over Bush by a not so small 0.5% points (544,000 votes), but lost due to a loss in Florida.

Furthermore, the loss in Florida was by just 537 votes, or 0.01% of the votes cast in that state.  But this loss was due to the use of the terribly designed and now infamous “butterfly ballot” in Palm Beach County (and only that county), where to vote for Al Gore, whose name appeared second on the ballot, one had to punch the third hole in the column to the right of his name.  Punching the second hole would be a vote for Pat Buchanan, a minor third party candidate who received only 0.4% of the votes in the country.  A careful statistical analysis of the Palm Beach County results indicate that at least 2,000 votes intended for Al Gore mistakenly went to Buchanan.  This was far more than the 537 vote state-wide margin.  Without this confusing ballot in just one county, Al Gore would have won Florida and the presidency.

The impact of the Florida result on the 2000 election is well known.  And if it were not for the electoral college system, where electoral votes are allocated by state and with winner-take-all in each individual state or district, there would not have been such an impact from one poorly designed ballot in one county of one state.  Al Gore won the popular vote in the country by over a half million votes, and a badly designed ballot in one jurisdiction would not have mattered.

And it is in fact not so rare that there might be an election where the winner of the electoral vote lost the popular vote.  Aside from the 2000 election, there were three other such cases in American history (although all were in the 1800s).  Thus in the 48 presidential elections since 1824 (the first election where, as discussed above, the popular vote at the state level was meaningful), there have been four cases where the person elected president received fewer votes than his opponent.  That is, in one of 12 cases (4 in 48) the loser of the popular vote still became president.  One in 12 cases means, on average, that one might expect there to be such a case every 48 years or so, given the four-year presidential terms.  That is, each voter should expect this to happen about once in their voting lifetimes.  That is not uncommon.

c)  Focus Only on the Swing States

Beyond any statement of principle, there are also other, and highly important, problems stemming from the current system.  As a direct consequence of the current system, presidential candidates and their campaigns will focus their efforts and policy commitments not on the nation as a whole, but only on the limited number of swing states (also referred to as battleground states) where the race is so tight that the victor is not clear.

While most are aware of this focus, the extent of the focus may be surprising.  While the definition of precisely which states might be considered swing states will differ a bit between analysts, and especially for those states near the margin between being considered a swing state or not, there is actually a surprising degree of consensus.  For the 2012 presidential election, 11 states were considered by most as swing states.  They are shown in brown in the map at the top of this post.  The only real debate is whether Michigan should be included, thus leading to 10 swing states.  And some might have substituted Minnesota for Michigan.

These 11 states made up 22% of the voting jurisdictions (50 states plus DC) in the nation, 27% of the voting eligible population, and also 27% of the electoral votes:

11 Swing States

Shares in Nation in 2012:

% Share

Number of States (and DC)


Voting Eligible Population


Electoral Votes


Campaign Events


TV Ad Spending


But these 11 states accounted for 99.6% of the campaign events held in the presidential campaigns in 2012, and 99.8% of the TV ad spending!  The rest of the country simply did not matter, and was ignored.

This also had consequences for voter turnout.  For the largely same set of 10 swing states considered to be battlegrounds in 2012 (the list of 11 above less Michigan), voter turnout has increased steadily over time relative to turnout in the non-swing 40 states plus DC:

10 Swing States of 2012 vs. Rest:

Difference in Turnout in % Points











In 1996, when a number of the states considered to be battlegrounds in 2012 were not so before (as the list evolves, but slowly, over time), voter turnout was essentially the same as in the rest of the country (51.5% in this set of 10 states vs. 51.4%).  But as these states became increasingly seen as competitive, with increased attention then afforded to them and with voters increasingly recognizing that their votes there could indeed matter, the turnout differential grew steadily, reaching a difference of 7.4% points in 2012.  This is a big difference.

A different study made use of the fact that the states considered to be swing or battleground states do evolve over time, and looked at how much voter turnout then shifted based on whether the states gained or lost battleground status:

Difference in % Points

Shifts in Voter Turnout:

2004 to 2008

2008 to 2012

Gained Battleground Status


no cases

Lost Battleground Status



Stayed Battleground



Stayed Spectator



Nation as a Whole



States that gained battleground status in the 2008 election saw their turnout jump by 5.2% points, when national turnout rose by only 1.5% points.  There were no such cases in 2012.  States that lost battleground status saw their turnout drop by 2% points in 2008 and by 4.9% points in 2012.  Other states had smaller changes.

It should not be surprising that fewer people vote if they believe their vote does not count. And for a presidential election, if you do not live in a battleground state, it most certainly does not matter:  One candidate or the other is certain to win that state.  But while this is a problem in itself, there are important implications for the other offices up for election in that year.  Fewer people will vote in the non-battleground states in the congressional and senate races, and for the various state and local offices and referenda that might also be on the ballot.

d)  People Want the President to be Selected by Popular Vote

Finally, doing away with the electoral college and selecting the president by popular vote is overwhelmingly favored by the population.  For example, a Gallup Poll from January 2013 found that 63% are in favor of such a reform:

Gallup Poll, January 2013

Do Away With Electoral College

In Favor


No Opinion

















What is perhaps surprising is that such support is basically identical between Republicans, Independents, and Democrats.  This is not a partisan issue.

Other polls have found similar results (see for example this poll, specifically question # 22).

C.  The National Popular Vote Interstate Compact

While the problems with the electoral college system have long been recognized, most (including myself) thought until recently that a constitutional amendment would be required to change it.  But in fact that is not so.  Following the 2000 election debacle, Professor Roger Bennett of Northwestern University Law School pointed out that the US Constitution (in its Article II, Section 1, Paragraph 2, quoted above) gives state legislatures the power to decide how electors will be chosen in their state.  States could use this power to choose a slate of electors pledged not to the presidential candidate who received the most votes within their own state, but rather pledged to the presidential candidate who received the most votes in the nation.

This is simple and clear, and provided states with electoral votes that sum to 270 or more agree, we could have the democratic election of the president where the candidate who gets most votes nationally, will win.  The mechanism is the approval in each state of legislation that would commit that state, provided other states holding 270 or more electoral votes also agree, to select electors from the slate committed to the candidate that wins the most votes nationally.  So far ten states plus Washington, DC, have approved and signed such legislation.  They hold 165 electoral votes between them, and approvals include from such large states as California and New York.

Not only does this approach by-pass the need for a new constitutional amendment, but it also does not give a veto right to the small number of states who benefit from the current system.  For a swing state, and particularly for a small swing state, the current system has its advantages.  Presidential candidates are forced to pay special attention to you, and to grant you special favors that others may not enjoy and which could indeed cost others. But the system effectively ignores the voters in more than three-quarters of the states, and the National Popular Vote initiative is a mechanism to restore their democratic rights.  One should not want to grant a veto right to this to a small number of swing states who benefit from the current system.

D.  The Benefits of a Selecting the President by National Popular Vote

The benefits of selecting the president by a national popular vote are clear, and include:

  1. It is democratic.
  2. Votes would count the same across the nation.  Currently, a vote in California counts only one-third as much as a vote in Wyoming in terms of electoral votes.
  3. It would end the possibility that a candidate receiving more votes than another would nonetheless lose the election, as happened in Bush vs. Gore in 2000 and three other times in US history.
  4. There would be less incentive than now for states like North Carolina, Florida, and Pennsylvania to try to introduce measures to selectively disenfranchise targeted voters (such as the poor or from minority groups) through voter ID and similar restrictions.  Such voter disenfranchisement measures can be effective at the margin, where by shifting voting shares by a few percentage points in the state the favored candidate might win that state.  But if what now matters is the total votes cast in the nation, a swing of a few percentage points in a few states such as Florida are less likely to decide the outcome.  I should add, however, that while there would be less of an incentive to introduce such voting measures for elections for the president, the incentive would remain for state and local offices.

But perhaps the biggest concrete impact would be the impact of such a reform on how candidates run for office.  Instead of focusing almost all of their attention on a limited number of swing states, they would now have a reason to campaign across the entire nation.  Their aim would be to pick up votes wherever they can.  Thus a Republican would want to campaign in states like California, New York, and Massachusetts.  While he might not expect to win a majority in such a state, there are a large number of potential Republican voters in such states whom he would want to encourage to go out and vote. Similarly, a Democrat would have an incentive to campaign in states like Texas and Alabama.  Their aim would be to campaign wherever they might gain a significant number of votes, including in states where they might well still expect not to receive a majority overall.

This would change the dynamics of US presidential campaigns, and in a good way. Three-quarters of the nation would not be neglected.

E.  The Politics of the Proposal

As noted above the National Popular Vote Interstate Compact has now seen legislation passed and signed in ten states plus Washington, DC, who between them have 165 electoral votes. Maryland was the first (in 2007) and New York the most recent (in 2014).   Unfortunately for the politics of this, all the states (including DC) who have passed this are strong “blue” (Democratic leaning) states.  No red states have as yet passed it, although such legislation has been passed in one but not both of the legislative chambers in red states such as Arizona, Arkansas, and Oklahoma.

Many Republicans appear to believe that selection of the president by popular vote would not be of benefit to them.  But this is not at all clear.  First, it is quite possible that more Republican votes would be gained on a net basis in states like California, New York, Illinois, and others, than would be gained on a net basis by Democrats in states like Texas. It is very difficult to predict what the net impact on votes will be because, as noted above, the focus of attention of the election campaigns would then be totally different than what it is now.  While one could safely predict that voter turnout will rise (it is abysmally poor in the US), whether the fact that all votes would count (and count equally) would favor one party or the other is not at all clear.

But what is clear is that under the current electoral college system, many observers have concluded that the Democrats have a clear electoral vote advantage over the Republicans. While there are various ways that they have come to this conclusion, one example is based on an examination of which states have voted for the Democrat in every one of the six presidential elections since 1992, in comparison to the states that have every time voted for the Republican.  The Democrats have a huge electoral college advantage by this measure, with 19 states plus Washington, DC, having always voted for the Democratic candidate since 1992, with 242 electoral votes between them.  This has been called the “Blue Wall”.  Starting from this as a base, a win just in also Florida (with its 29 electoral votes) will hand the election to the Democrat (with a minimum of 271 electoral votes, even if no other state is won).  The Republicans, in contrast, have consistently won only 13 states since 1992, with just 102 electoral votes.  It is a far bigger reach for them to get to 271 electoral  votes from this base.

While there are also critics of this specific measure of the Blue Wall, most commentators agree the Democrats do have a major electoral college advantage.  It is then not at all clear that Republicans should oppose a reform where the president would be chosen by a nation-wide popular vote instead.  Presidential elections have generally been won or lost by only a few percentage points when measured in terms of the popular vote (in years other than when there was a major third party candidate, such as Ross Perot in 1992).

Tellingly, even Newt Gingrich, the former Speaker of the House, former presidential candidate, and close advisor to Donald Trump, has endorsed the National Popular Vote initiative.  Newt Gingrich is highly political.  One would not expect him to do this if he saw it to be other than an advantage for the Republicans.

F.  Conclusion

The electoral college system might well have made sense in 1788, when the US Constitution was ratified.  But that does not mean it makes sense now.  While a formal constitutional amendment might well be a preferable solution, the current politics in Washington means that any amendment process would not go far.

But the US Constitution does specifically provide the state legislatures the flexibility to decide how their electors are to be chosen.  States can use that flexibility to direct that the slate of electors for that state will be the slate committed to the candidate who receives the most votes in the nation, rather than in the individual state.  And the states can agree that they will begin to abide by this process when, and only when, states with a minimum of 270 electoral college votes have agreed.

This is thus eminently doable.  However, while states with 165 electoral votes have already approved this initiative, there is a need for states with a further 105 electoral votes also to agree.  This will not happen until Republican controlled states recognize that this reform is as much in their interest as it is for others.

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.

Bernie Sanders and His $27 Average Campaign Donation

Sanders $27 Money

Bernie Sanders is certainly to be commended for leading a modern US political campaign funded almost in its entirety by campaign contributions from individuals.  According to the Center for Responsive Politics, the Sanders campaign (through June 30) raised $226 million in individual contributions, with this accounting for 99% of the total money raised by or for the campaign (including outside groups).  This is impressive, and hopefully will serve as a model for future political campaigns.

Famously, the Sanders campaign touted that the average contribution came out to just $27, thus highlighting the grass roots nature of his support.  And this has been widely quoted.  Even President Obama got in on this.  In his remarks at this year’s White House Correspondents’ Dinner, he noted:

“What an election season.  For example, we’ve got the bright new face of the Democratic Party here tonight  –-  Mr. Bernie Sanders!   There he is  —  Bernie! Bernie, you look like a million bucks.  Or to put it in terms you’ll understand, you look like 37,000 donations of 27 dollars each!”

But listening to Sanders’ speech to the Democratic Convention on Monday, a point bothered me.  And being a numbers person, I had to look it up.  Sanders noted right at the beginning of his remarks that he wanted to:

“thank the 2 1/2 million Americans who helped fund our campaign with an unprecedented 8 million individual campaign contributions – averaging $27 a piece.”

This was the first time I realized that the $27 individual contribution may not be referring to what an average person contributed, but rather to what the average donation was, where they are counting separately each donation from an individual contributor making multiple donations.

And it does appear that this is the case.  The $226 million figure noted above for total contributions divided by 8 million individual campaign contributions comes to a bit over $28 per contribution – close enough to the $27 number; it is within round-off.  But per individual, it comes to over $90 per person over the 2 1/2 million individuals who contributed to the Sanders campaign.  On average, each donor contributed 3.2 times.

This is a quibble, to be sure.  But an average contribution of $90 (per donor) does not sound as democratic as $27 (per donation).