The Unemployment Rate, the Growth in Employment, and Productivity

A.  Introduction

The January jobs report (more properly the “Employment Situation” report) released by the Bureau of Labor Statistics (BLS) on February 3, was extraordinarily – and surprisingly – strong.  The unemployment rate fell to 3.4% – the lowest it has been since May 1969 more than a half-century ago.  And despite the low unemployment rate, the number of “new jobs created” (also a misnomer – it is actually the net increase in non-farm payroll employment) was a surprising 517,000.  But it was not only this.  The regular annual revisions undertaken each January to reflect revised population controls and weights for the employment estimates led this year to significantly higher labor force and employment estimates.  With the new industry weights, the increase in the estimated number of those employed in 2022 (the number of `”new jobs”) rose to 4.8 million.  The earlier estimate had been 4.5 million.

All this is an extraordinarily strong jobs report.  However, one should not go too far.  It is important to understand what lies behind these estimates, as well as some of the implications.  For example, strong growth in the total number employed while GDP growth is more modest implies that productivity (GDP per person employed) went down.  That could be a concern, except that when viewed in the context of the last several years we will see that productivity growth has in fact been rather good.

This post will first examine the new figures on unemployment and then on employment growth.  We will then look at the change in productivity – both in the recent past and from a longer-term perspective.

B.  The Unemployment Rate and Its (Non)-Impact on Inflation

The unemployment rate in January fell to 3.4%.  This is the lowest it has been since May 1969.  And if it falls a notch further to 3.3% in some upcoming month, it will have fallen to the lowest since 1953.

A 3.4% unemployment rate is certainly low.  But what is more significant is that the unemployment rate has been almost as low for most of the past year.  It fell to just 3.6% in March 2022, and until last month varied within the narrow range of 3.5 to 3.7% – hitting the 3.5% rate several times.  It is now at 3.4%, but what is most significant is that it has been at 3.7% or less for almost a year.

One needs to recognize that the unemployment rate is derived from a survey of a sample of households (implemented by the Census Bureau) called the Current Population Survey (CPS).  The CPS sample includes approximately 60,000 households each month, in a rotating panel, and from this they derive estimates on the labor force participation rate, the unemployment rate, and much more.  It complements the Current Employment Statistics (CES) survey, which covers a much larger sample of 122,000 businesses and government agencies representing 666,000 individual worksites (with each employing many workers).  Hence employment figures are generally taken from the CES as there will be less statistical noise.  But the employers surveyed for the CES cannot know how many workers are unemployed (they will only know how many workers are employed by them), so the smaller CPS needs to be used for that.  (A brief explanation of the CPS and CES is provided by the BLS as a “Technical Note” included in each of the monthly Employment Situation reports.)

Due to the size of the sample, the estimated unemployment rate is actually only known within an error limit of +/- 0.2 percentage points, using a 90% confidence interval.  That is, simply due to the statistical noise a change in the unemployment rate of 0.1 percentage point from one month to the next should not be considered statistically significant, and 10% of the time even a 0.2 percentage point change may have just been a consequence of the statistical variation.  However, repeated observations over several months in a row of an unemployment rate at some level will be a measurement one can have much more confidence in.  That can no longer be a consequence of simply statistical noise.  Thus one should not place too much weight on the January change in the unemployment rate to 3.4% from 3.5% the month before.  But the fact that the unemployment rate has consistently been within the relatively narrow – and extremely low – range of 3.4 to 3.7% since March 2022 is highly significant.

An unemployment rate anywhere close to a range of 3.4 to 3.7% is also far below the rate at which economists used to believe would be possible without the rate of inflation accelerating – i.e. without inflation going higher and higher.  This was given the acronym name of “NAIRU” (for Non-Accelerating Inflation Rate of Unemployment).  It was held that at an unemployment rate of less than the NAIRU rate, the rate of inflation would rise from whatever pace it was at to something higher.  This was viewed as unsustainable, and hence the proper goal of economic policy was, in this view, to manage macro conditions so that the unemployment rate would never fall below the NAIRU rate.  That rate was also sometimes called the “full employment rate of unemployment”.

The question then is what the NAIRU rate might be.  While different economists came up with different estimates, estimates generally fell within the range of 5 to 6%.  An unemployment rate of less than this would then (under this theory) lead to a rise in inflation.

But that did not happen.  The unemployment rate fell to below 5% in 2016, and inflation remained low.  It fell to below 4% in 2018 and inflation remained low.  It fell to 3.5% in 2019 and into early 2020 and inflation remained low.

With the once again very strong labor market – with unemployment hitting 3.4% – has this now changed?  The rate of inflation did rise in 2021 and into 2022.  But if one looks at this chart, one sees that the timing is wrong:  Inflation rose earlier – in 2021 – when the unemployment rate was still well over 6% early in the year.  Furthermore, nominal wages only rose later:

Inflation (measured here by the consumer price index – the CPI – for all goods and services) can be volatile, but the upward trend began already in the second half of 2020 (although in part this was initially due to a recovery in prices from depressed levels earlier in 2020 due to the Covid crisis).  The chart shows the rates in terms of 3-month rolling averages (at annual equivalent rates and in arrears, so the figure for a January, say, would be for the months of November through January).  The pace of change in nominal wages (also as 3-month rolling averages and at annual rates) did not start to rise until mid-2021.  The increase in nominal wages appears to be more in response to the prior increase in prices – as firms found it profitable to employ more workers in an economy that grew strongly in 2021 – rather than a cause of those higher prices.  This is consistent with the view that the inflation was primarily due to demand-pull, rather than cost-push, factors.

[Technical Note:  The figures on changes in the nominal wage come from data assembled by the Federal Reserve Bank of Atlanta, drawing on data that can be obtained in the underlying micro-data files of the CPS.  The rotating panel of households in the CPS are interviewed for four months, not interviewed for the next eight months, and then interviewed again for four months.  New households are added each month and then removed after month 16 for them.  This allows the researchers to match individuals with their reported wages to what they had earned 12 months before.  It also allows them to examine the wage changes broken down by individual characteristics – such as age, gender, race, education level, occupation, where they are in the income distribution, and more – as these are all recorded in the CPS.  It is all very interesting, and worth visiting their website where they make it easy to see the impact on the measured changes in wages of many of these different factors.

The matching of wage changes by individuals also provides a much more reliable index than the commonly cited changes in average wages provided in the monthly Employment Situation report.  The latter comes from what employers report in the CES survey on the average wages they are paying.  Those averages will be affected by compositional effects.  For example, the reported average wages will often jump at the start of an economic downturn – such as it did in 2020 – as the less experienced and lower-wage workers are generally laid off first.  This leaves a greater share of more highly paid workers, which will lead the reported average wage to rise even though the economy had entered into a downturn.]

Not only did the rise in inflation precede the more modest increase in the pace at which nominal wages rose, but since mid-2022 the rate of inflation has come down while the job market has, if anything, become tighter.  The unemployment rate, as noted above, has been in the 3.4 to 3.7% range since March 2022, and is now at 3.4%.  Despite this, the three-month average increase in the seasonally adjusted CPI fell from 11.0% (at an annual rate) in the three months ending in June 2022, to just 1.8% in the three months ending in December.  If a tight labor market was driving inflation, one would have expected inflation to have kept going up rather than fall – and certainly not to fall by such a degree.

Furthermore, growth in nominal wages fell slightly from a peak of over 6.7% in the three months ending in June and also July 2022 (at an annual rate), to 6.1% as of December.  One would have expected the pace of change in wages to have continued to go up, rather than start to ease.

It is still early to be definitive on any of this.  Trends could change again.  Importantly, a significant part of the sharp fall in inflation in the second half of 2022 (when measured by the full CPI) was due to a fall in the prices of oil and other energy products.  However, while more recent, there are also early indications that core inflation (where food and energy prices are left out) is also falling.  In terms of the core CPI (again the seasonally adjusted index), the pace of inflation fell from a peak of 7.9% (at an annual rate) in the three months ending in June 2022, to just 3.1% in the three months ending in December.

That measure of inflation – the core CPI, which is often taken to be a better measure of underlying inflationary trends than the overall CPI as food and energy prices are volatile and go down as well as up – is now falling despite unemployment at the lowest rate it has been in more than a half-century.  If a tight labor market was driving inflation, then one would expect the pace of inflation to be rising, not falling.

C.  Employment Growth

The January jobs report was also noteworthy for its figures on employment growth.  Nonfarm payroll employment rose by 517,000 – far higher than most expected.  It is not that an increase in employment of a half million in a month is unprecedented.  It is rather that there was such an increase even though the unemployment rate was already at an extremely low 3.5% in the prior month.  (And while nonfarm payroll employment excludes those working in agriculture, that number is now small at only 1.4% of the labor force – based on estimates from the CPS and including those in agriculture who are self-employed.  It also excludes the self-employed outside of agriculture – a more substantial 5.6% of the labor force according to the CPS – but still not that large.  In terms of changes in the numbers from one period to the next, the impact on the employment estimates will be small.)

In addition, the January report also reflected revisions – undertaken every January – where new weights are used to generalize from what is found in the sample in the CES of firms and other entities (such as government agencies) that employ workers to what is estimated for the economy as a whole.  The re-weighting is based on a comprehensive count of payroll jobs in March of the year, with this then used to revise the estimates for all of the year (2022 in this case).

Due to the new weights, the increase in the number of jobs in the economy rose from the earlier estimate of 4.5 million in 2022 (i.e. from December 2021 to December 2022) to 4.8 million.  Between January 2022 and January 2023 the increase was an estimated 5.0 million additional jobs.  That is, between January 2022 and January 2023, the number employed increased by an average of 414,000 per month.

The 4.8 million growth in the number employed in 2022 was remarkable not only because it is a big number, but also because it came after the even stronger growth in employment in 2021.  Employment grew by 7.3 million in 2021.  In absolute terms, the 4.8 million figure in 2022 is higher than that of any year (other than 2021) in the statistics going back to when they started to be collected in the present form in 1939 (using BLS data).  Such a comparison is more than a bit unfair, of course, as the US economy has been growing and there are far more people employed now than decades ago.  But taking 2021 and 2022 together, the percentage growth over the two years – at 8.5% – was exceeded since 1951 only by greater increases in 1977-78 (10.2%), in 1965-66 (9.7%), and in 1964-65 (8.7% – that is, there was strong growth in the three straight years of 1964, 1965, and 1966).  Joe Biden was right when he said job growth in the first two years of his presidency (of 12.1 million) was greater than that of any other president, but it is not really a fair comparison as the economy is now larger.  But even in percentage terms, his record is excellent.

But such growth in the number employed cannot continue much longer.  To put this in perspective, the total adult population in the US (as reflected in the CPS, and with the new population controls) rose by only 1.8 million between January 2022 and January 2023, or 150,000 per month on average.  And the labor force figure, as estimated in the CPS, grew by only 1.3 million over that period, or 111,000 per month.  One cannot keep adding 414,000 per month to the number employed (as we saw in the year to January 2022) when the labor force is only growing by 111,000 per month, when the unemployment rate is already at a historical low of 3.4%.

[Note that one cannot simply subtract the January 2022 figures reported from the new January 2023 figures, since in the CPS they do not go back and revise the previous year figures to reflect the new population controls.  But they do show what the impact would have been on the December 2022 figures, and I assumed that they would have had the same impact on the January 2023 numbers.  The impacts should be similar.  One can then do the subtractions on a consistent basis.]

An increase in the number employed of an estimated 414,000 per month when the labor force was growing by only an estimated 111,000 per month was possible in 2022 in part because the unemployment rate came down (from 4.0% in January 2022 to 3.4% in January 2023), and in part because the labor force participation rate went up slightly (from 62.2% in January 2022 to 62.4% in January 2023).

But also a factor is that these are surveys from two different sources (households for the CPS and firms and other employers for the CES), and the sample estimates will not always be fully consistent with each other.  As was discussed in an earlier post on this blog, the estimates can differ from each other sometimes for significant periods of time.  However and importantly, over the long term the two estimates will eventually have to approach each other.  The population estimates used for the CPS will yield (for a given labor force participation rate) figures on the labor force, and hence growth in the adult population will yield figures on growth in the labor force.  For a given unemployment rate, the number employed – within the bounds of the statistical estimates – cannot grow faster than this.

With the unemployment rate now at 3.4%, one should not expect much if any further fall.  Indeed, the general expectation (and the more or less openly stated hope of the Fed) is that it will start to rise.  It is possible that the labor force participation rate will rise, but changes in this are generally pretty slow, driven mostly by demographics and social factors (the share of people aging into the normal age of retirement; the share of the young entering into the labor force given their decisions on whether and for how long to enroll in colleges and universities; decisions by households on whether one or both spouses will work; and similarly).

While there will be uncertainty in what will happen to the unemployment rate and the labor force participation rate, for given levels of each of these, employment cannot grow any faster than the labor force does.  (Indeed it is slightly less:  At an unemployment rate of 3.4%, employment will only grow at 96.6% of what the labor force grows by.)  With the labor force growing by 111,000 per month in the year ending in January 2023 (with this already reflecting a small increase in the labor force participation rate from 62.2% to 62.4%), it will not be possible for the monthly increase in employment to grow by much more than this.

Looking forward, one should not, therefore, expect growth in the number employed to be sustained at a level that is anywhere close to the 517,000 we had in January.  There will be month to month fluctuations, but one should not expect an average increase over several months that would be much in excess of the 111,000 figure for the growth in the labor force seen in the year ending in January 2023.

D.  Productivity

Politicians like strong job growth.  It is indeed popular.  But the flip side of this is that while the number employed grew rapidly in 2021 (by 3.2% December to December), GDP growth was less (1.0% from the fourth quarter of 2021 to the fourth quarter of 2022, based on the most recent estimates).  With the number employed growing faster than GDP, the mathematical consequence is that GDP per person employed went down.  That is:  Productivity fell in the year.

Higher productivity is ultimately what allows for higher living standards.  Falling productivity would thus be a problem.  However, in the context of the last several years, productivity growth has in fact been pretty good:

We are once again seeing the consequences of the highly unusual circumstances surrounding the Covid crisis.  With the onset of a downturn, firms will lay off workers.  But they may often lay off more workers than their output falls.  This might be because of uncertainty on how much the demand for whatever they make will fall in the downturn (and they will wish to be careful and if anything to overcompensate, given the difficulty of obtaining finance in a downturn and the very real possibility of bankruptcy); or because special government programs during the downturn reduce the cost to them and their workers of these layoffs (for example through the common response of extending unemployment benefits and making them more generous); or because the first workers being laid off are the least productive ones (possibly because they are relatively new and do not yet have as much experience as others working there) so that they end up with a workforce which is on average more productive.  Or, and very likely, it could be a combination of all three factors.  It looks very much like Schumpeter’s “creative destruction”.

The consequence is that productivity can in fact jump up in a downturn.  One sees such a clear jump in the chart in 2020, at the time of the sharp collapse due to the Covid crisis.  One also sees it in 2008-09, with the financial and economic collapse in the last year of the Bush administration and then the turnaround that began in mid-2009.  In terms of the numbers:  Real GDP fell by 1.3% between the first quarter of 2020 and the third quarter of 2020 (in absolute terms – not annualized).  But employment over this period fell by 7.4%.  As a result, productivity (real GDP per person employed) jumped by 6.6% in this half year.  In 2008/2009, real GDP was basically flat between the last quarter of 2008 and the last quarter of 2009 – rising by just 0.1%  But employment over this period fell by 4.1%, leading to an increase in productivity of 4.4%.

Following these brief periods where businesses are scrambling to survive the downturn by producing more (or perhaps not too much less) with many fewer workers, firms then enter into a more normal period where, as the economy recovers, they are able to sell more of their product.  They hire additional workers who are, by definition, less experienced in the work of that firm than their existing workforce.  The new workers might also be less capable or have a less applicable skill mix.  Productivity may then level off or even go down.  The latter situation is in particular likely when the economy recovers quickly and firms scramble to keep up with the increased demand for their product.

The latter fits well with what we saw in 2021.  GDP in 2021 rose by 5.9%, the highest of any year since 1984.  And the Personal Consumption component of GDP rose by 8.3% in 2021, the highest of any year since 1946.  This was spurred by the series of Covid relief packages passed in 2020 (under Trump) and in 2021 (under Biden), which totaled $5.7 trillion in the two years, or 12.8% of GDP of 2020 and 2021 together.  Personal savings rose to an unprecedented level as a share of GDP (other than during World War II, with data that go back to 1929), which then supported the strong growth in personal consumption in 2021.  This is consistent with a demand-led inflation that got underway in late 2020 or early 2021 (discussed above) – a risk of inflation that Larry Summers had warned of in early February 2021 when Biden’s $1.9 trillion Covid package was first proposed (and eventually passed, largely as proposed).

But what matters to long-term living standards is not so much the changes in average productivity in the periods surrounding economic downturns, but rather the trends in productivity growth over time.  A ten-year moving average is a useful metric:

The chart shows rolling ten-year averages starting from 1947/57 through to 2012/22 of the growth in GDP, in employment, and in productivity (GDP per person employed).  Productivity growth was relatively high at about 2% per annum in the 1950s and through most of the 1960s.  But it then started to fall in the 1970s to less than 1% a year before recovering and returning to about 2% a year in the ten-year period ending in 2004.  It then fell to roughly 0.8% a year since about 2017 (in terms of the ten-year averages), with some sharp fluctuations around that rate associated with the 2020 Covid crisis.  As of the end of 2022, the most recent ten-year average growth rate for productivity was 0.80%.

This has important implications for GDP growth might be going forward.  The labor force grew by 0.8% in 2022 (the adult population grew by 0.7%).  With unemployment close to a record low, employment will not be able to grow faster than the labor force – as discussed above.  And the labor force cannot grow faster than the adult population unless labor force participation rates increase.  But while there major disruptions in labor force participation in 2020 and 2021 surrounding the Covid crisis – with its lockdowns, economic collapse and then recovery, as well as health concerns affecting many – labor force participation largely returned to previous patterns in 2022.  Labor force participation rates have been slowly trending downwards since the late 1990s, and while it is possible this pattern might be reversed, it is difficult to see why it would.  There might well be short-term fluctuations for a period of a few years, but longer-term patterns are driven mostly by demographics (the age structure of the population) and social customs (e.g. whether women decide to enter into the paid labor force).

What follows from this is that if the labor force continues to grow at 0.8% a year (as it did in 2022 – and it grew only at a lower rate of 0.6% a year in the ten-year period ending in 2022), and productivity grows at 0.8% a year (as it did in the ten-year period ending in 2022), then GDP can at most grow at 1.6% a year on average.  This would be disappointing to many.  While there certainly can be and will be significant year to year variation around such a trend, faster growth would require either higher productivity growth or more entering into the labor force.

E.  Summary and Conclusion

The January jobs report was strong.  The unemployment rate is now at the lowest it has been in more than a half-century, and the number employed grew by more than a half million – a very high figure when the unemployment rate is so low.  While these are still preliminary figures and are subject to change as additional data become available, they present a picture of an extremely strong labor market.

The fall in the unemployment rate by one notch to 3.4% from the previous 3.5% should not, in itself, be taken too seriously.  That is well within the normal statistical error for this figure.  But what is indeed significant is that the unemployment rate has been within the narrow range of just 3.4 to 3.7% since March 2022.  That is low.  And it was in this low range during a period (in the second half of 2022) when inflation was coming down.  While changes in the price of oil have been a major factor in driving the inflation rate in 2022, the core rate of inflation (which excludes energy prices as well as those for food) has also started to come down.  The rate of change in nominal wages did start to grow in mid-2021, but this appears more to be a consequence of the rising prices rather than a cause of them.  And there has been a slight reduction in the pace of change in wages in recent months.

One does not see in this any evidence that a tight labor market with extremely low unemployment (the lowest in more than a half-century), has led to higher inflation.  The opposite has happened.  Inflation has come down at precisely the time the labor market has been the tightest.

GDP grew rapidly in 2021, but then slowed to a more modest 1.0% rate in 2022 (from fourth quarter to fourth quarter).  Coupled with rapid employment growth in the year, productivity (as measured by GDP per employed person) fell.  However, this appears more to be a continued reaction to changes surrounding the disruptions resulting from the 2020 Covid crisis.  During that crisis, GDP fell but employment fell by much more, leading to a jump in productivity despite the downturn.  As the economy recovered and the situation normalized, workers were hired to bring workforces back to desired levels.  Viewed in a longer timeframe, productivity growth has been similar to what it has now been since the mid-2010s.

That productivity growth is not especially high.  It was 0.8% at an annual rate in the most recent ten-year average.  Coupled with a labor force that grew at 0.8% in 2022, and going forward might grow by even less (it grew at 0.6% a year in the ten-year period ending in 2022), the ceiling on GDP growth would be 1.6% a year, or less.  That is not high, but expectations need to adjust.

That is also a ceiling on what GDP growth might be.  Many expect that there very well could be a recession either later in 2023 or in 2024.  Much will depend on whether the government will be able to respond appropriately if the economy appears to be heading into a downturn.  But with Republicans now in control of the House of Representatives, and threatening to force the US Treasury into default on the nation’s public debt if their demands for drastic spending cuts are not met, one cannot be optimistic that the government will be allowed to respond appropriately.

Personal Savings in the US Following the COVID Relief Programs, and the Possible Impact in 2023 and 2024

A.  Introduction

The US economy has just gone through an extraordinary period.  The impacts are still being felt – and probably will be for several more years, including into the presidential election year of 2024.  A key issue will be whether personal consumption expenditures will continue to grow – at least at some modest pace – as such expenditures are important not only in themselves, but also as they account for more than two-thirds of the demand side of GDP.  And this consumption will depend, in turn, on what happens to household incomes and on the decisions households make on their savings.

Very briefly, we will find:

a)  Personal Income before taxes and transfers (at the national level as measured in the GDP accounts, and where taxes and transfers are for all levels of government including state and local in addition to federal) fell during the Covid crisis but then recovered to where it was before by mid-2021.  Since then, however, it has been relatively flat in real terms.

b)  Personal Income after taxes and transfers (called Disposable Personal Income in the GDP accounts) rose during the Covid crisis due to the massive Covid relief packages, but returned to its previous trend path by mid-2021.  But as the Covid relief programs wound down, Disposable Personal Income (in real terms) fell, and by October 2022 was almost 7% below its previous trend path.

This stagnation in Personal Income, and fall in Disposable Personal Income, may well explain the common view of many that the economy is not well, despite unemployment rates that have matched the lowest levels of more than the last half-century.

c)  But while Disposable Personal Income fell below its trend path, Personal Consumption Expenditure (which had fallen during the Covid crisis) returned fully to its previous trend path by the Spring of 2021.  It has since followed that trend path almost exactly.

d)  This return of Personal Consumption to its previous trend path, while Disposable Personal Income fell well below its previous trend path, was only possible as households could draw on large savings balances that they had built up during the Covid crisis period.

e)  Those savings balances are finite, however, and are being drawn down.  While only a crude estimate is possible, calculations based on the savings rates that prevailed before the Covid crisis and then extrapolation based on the pace of the drawdown in 2022, suggest that the excess savings balances will be depleted sometime in 2024.

This may have significant implications, both economically and politically.  The Fed is currently raising interest rates aggressively in order to reduce investment spending and hence aggregate demand, with the objective of reducing inflation.  Federal fiscal spending has also been falling, with a reduction expected in FY2023 of a further about 1% of GDP.  Many analysts (including myself) have felt that a reduction in consumer expenditures in 2023 (as the excess savings balances built up during the Covid crisis run out) should be expected on top of this.  But based on the calculations discussed below, those balances might last into 2024.  That makes 2024 a complicated year economically, and 2024 is a presidential election year.

The possible macro consequences will be discussed in the concluding section of this post.  They are necessarily more speculative.  But first we will look at what happened to the savings rate during and following the Covid crisis (the chart at the top of this post), and then what happened to Personal Incomes, Disposable Personal Incomes, and Personal Consumption Expenditures – both in terms of their levels and relative to their previous trend paths.  The penultimate section will then provide an estimate of how much excess savings was built up during the Covid crisis period, the pace at which it is now being drawn down, and how long such balances might last before being used up.

A note on usage:  When terms such as personal incomes or personal consumption expenditures are capitalized, they are referring to the specific concepts as measured in the published GDP accounts (or more properly, the National Income and Product Accounts, or NIPA).  Terms that are not capitalized refer to the concepts more generally.  And I made one modification: “Personal Current Transfer Receipts” is defined in the NIPA accounts as net of social insurance (Social Security and Medicare) taxes paid.  I instead include such taxes in the category of Personal Current Taxes (i.e. together with individual income taxes), and Personal Transfers are then just the gross transfers (from Social Security, etc.).

B.  The Personal Savings Rate

The personal savings rate jumped sharply with the onset of the Covid crisis in March 2020.  From a rate of between 6 and 8% of disposable incomes for most of the period between 2013 and 2019, and reaching 9% in 2019 and early 2020, the rate jumped to 14% in March and then 34% in April 2020.  Such a jump is unprecedented in peacetime.  The only time there has been anything similar was during World War II.

The data for this chart (and those below) were calculated from data published by the Bureau of Economic Analysis (BEA) as part of the National Income and Product Accounts.  And while the GDP estimates themselves are only presented on a quarterly basis, the BEA provides monthly estimates for Personal Income, its sources (wages, etc.), Personal Taxes paid and Transfers received, and how the income thus derived is then used for consumption expenditures and other outlays, and residually for Personal Savings.  See in particular Table 2.6 in the NIPA accounts.  All the figures used here are seasonally adjusted and (where relevant) at annual rates.

The Personal Savings rate is defined as Personal Savings as a share of Disposable Personal Income, where Disposable Personal Income is Personal Income as received in the market (from wages; interest, dividends, and rents received; and income from unincorporated businesses) less Personal Taxes paid plus Personal Transfers received.  These Personal Transfers include that received from Social Security, Medicare, Medicaid, Veterans’ benefits, unemployment compensation, and other such programs, but during the Covid crisis there were also major transfers from the various Covid relief bills (the direct stimulus checks, the paycheck protection program, grants to small as well as large businesses, and much more) as well as from a large jump in unemployment compensation.

The series of Covid relief measures were huge.  The total appropriated under the six packages passed for Covid relief (five while Trump was president and one early in the Biden administration) sums to $5.7 trillion.  To put this in perspective, the total paid in federal individual income taxes each year is only about $2.6 trillion.  Spread over two years, the $5.7 trillion came to 12.8% of the GDP of 2020 and 2021 together.  A bit more than two-thirds of that money was appropriated under the bills signed into law by Trump, and a bit less than one-third by Biden.  And while the appropriations were passed by Congress with bipartisan (indeed often unanimous) support while Trump was president, the American Rescue Plan signed by Biden on March 11, 2021, received zero votes from Republicans in Congress.

The Covid relief bills provided massive transfers to households (in addition to massive transfers to the corporate sector as well).  But especially with the lockdowns, and then continuing to a lesser extent once the lockdowns were lifted due to Covid concerns (thus leading to less travel, less eating out at restaurants, etc.), consumption expenditures by households fell.  Much of the transfers received under the Covid relief bills hence ended up accumulating in savings balances (including regular bank accounts).  One can see in the chart at the top of this post the peaks in April 2020, January 2021, and March 2021.  These coincided with when what is commonly referred to as the “stimulus checks” – of $1,200, $600, and $1,400 respectively – were sent out.

As conditions normalized, the savings rate came down as the Covid relief measures wound down and as consumption recovered.  But then the savings rate continued to fall to levels well below those of 2019 and before.  The next section will review what was behind this.

C.  Personal Incomes, Personal Disposable Income, and Consumption

The paths followed for Personal Income and its components, from 2013 through to October 2022, are shown in the following chart:

The top three curves show the levels (in constant 2012 dollars) of Personal Income before Taxes and Transfers (in black), Disposable Personal Income (in purple), and Personal Outlays (in orange).  Personal Outlays are in essence almost the same as Personal Consumption Expenditures, but not quite.  Personal Consumption Expenditures accounted for almost all of Personal Outlays consistently throughout this period (never less than 96.0% nor more than 97.1%), but Personal Outlays also include non-mortgage interest payments (mortgage interest is included in housing expenditures) and small amounts of transfers of households to the rest of the world (i.e. overseas, probably mostly to family) and to government.  But since Personal Outlays are almost entirely Personal Consumption Expenditures, and their paths almost identical (just shifted slightly due to the steady 96 to 97% share), we will use the two concepts interchangeably for the purposes here.

The light blue lines on top of each are the simple linear regression lines of the paths from January 2013 to February 2020 – a period where each of the paths were extraordinarily stable – and with each then extrapolated at that same trend pace through to October 2022.  Not only was there little fluctuation in the paths between January 2013 and February 2020, but it was the same path through both the second term of Obama and the first three years of Trump (followed by the crash in Trump’s fourth year).  Indeed, the paths were so stable that the light blue lines of the linear regressions almost obscure the black, purple, and orange paths of the underlying data – up to February 2020.

This then changed abruptly in March 2020 with the onset of the Covid crisis.  But before getting to that, we should discuss the three additional curves in the lower part of the chart.  Shown are the amounts paid in Personal Current Taxes (in red), Personal Current Transfers (in green), and Personal Savings (in brown).  Personal Savings will equal Disposable Personal Income less Personal Outlays (which, as noted above, are basically Personal Consumption Expenditures).

Starting in March 2020, Personal Savings shot upward.  This was due to a combination of the far higher transfers (in green – under the first of the major Covid relief packages), the lower Personal Outlays (in orange – due to the lockdowns and general caution in going out to spend money due to the spread of the virus that causes Covid), and, to a lesser extent, lower taxes paid (in red – as the Covid relief measures included allowing tax payments to be deferred).  With a good deal of volatility (as a consequence of the timing of the major Covid relief packages), this continued through 2020 and to roughly the spring of 2021.

The resulting impacts on Personal Incomes (before and after taxes and transfers) and on Personal Outlays are shown in the upper right of the chart.  A blow-up of this section of the chart may make this easier to follow:

Personal Incomes (before taxes and transfers) recovered quickly, albeit only partially, as the lockdowns were lifted in 2020.  They then continued to rise, although at a slower pace, to the latter part of 2021 as the general economy recovered.  Since then, they have been largely flat.  By October 2022, they were 4.6% below where they would have been had they continued to follow their light-blue regression line for their path prior to March 2020.

Disposable Personal Incomes (i.e. after taxes and transfers) rose during the Covid crisis due to the Covid relief packages – as these more than offset the reduction in Personal Incomes during the crisis (when GDP fell and unemployment rose).  But by mid-2021, Disposable Personal Incomes had come down to the level of Personal Incomes before taxes and transfers, and then continued to fall as the Covid packages wound down.  By October 2022, Disposable Personal Incomes were almost 7% below where they would have been had they continued to follow their light-blue regression line for their path prior to March 2020.

In sharp contrast to Personal Incomes (before or after taxes and transfers), Personal Outlays (or Consumption Expenditures) returned to their previous path by March 2021, and since then have followed that previous path almost exactly.  They could do this only because households could draw down on the high savings balances they had built up during the Covid crisis period.  But there is only so much in those savings balances.  How long might they last?

D.  Excess Savings Balances

Savings rates shot up with the onset of the Covid crisis – due to the transfers received and the difficulties in spending – but the savings balances are now being drawn down.  While the resulting growth in private consumption expenditures has accounted for much of the growth in the demand for GDP in 2021 and continuing into 2022, those excess savings balances cannot last forever.

A crude calculation can be made of how much might be in those savings balances and how long they might last.  It can only be crude as one cannot know with any certainty how much would have been saved in the absence of the Covid crisis and all the impacts it had, nor can one know what returns might have been earned on those savings balances (returns that would depend on how they might have been invested – or not).

Savings rates were relatively stable between 2013 and early 2020 (as seen in the chart at the top of this post), and it is reasonable to assume savings rates would have been similar in the absence of the Covid crisis.  For the purposes here, I looked at scenarios where the savings rate would have remained at its average over 2013 to 2019 (which was 7.3%), or at its somewhat higher average over 2017 to 2019 (of 7.9%).  I also assumed, in part for simplicity, that there was no return earned on these excess savings balances.  This is not unreasonable, as much of what was received under the Covid relief packages were left to accumulate in bank accounts where there was no return.  Interest rates on CDs and such have also been very low for most of this period (and negative when adjusted for inflation).  And to the extent the funds were invested in the stock market (or in bitcoins!), the returns will depend very much on precisely when the investments were made.  The markets were going up for much of the period but now have come down – and sharply.

When the actual savings rates were higher than those assumed in the scenarios (of 7.3% or 7.9%), an excess savings balance was built up, and when the actual savings rates were below these benchmarks, these savings balances were brought down.  Expressed as a share of GDP, the resulting excess balances were:

The balances grew, often rapidly, to March 2021 and then peaked in August 2021 at about 10 to 11% of GDP (depending on what base savings rate is assumed).  Since then, those balances have come down.  Based on the pace of their fall in the most recent six months, they could last for another 18 or 23 months – i.e. for another one and a half to two years – depending on the base savings rate assumed.  That is, they would carry over into 2024, and possibly be all used up just prior to election day in 2024.

There is a good deal of uncertainty in any such forecast – in part due to the factors discussed above that make any such estimate of excess savings balances only approximate.  But there are also issues in what might transpire going forward.  The estimate that the balances might last for another year and a half to two years is based on a simple extrapolation of the extent to which such balances (as imperfectly estimated) have come down over the past half year.  That pace might accelerate.  For example, if Disposable Personal Income widens further from its trend path (this might have stopped in the last few months, but it is still early and hard to say), while Personal Consumption continues to rise according to its trend path, then Personal Savings will fall further and the pace at which the savings balances will be brought down will accelerate.  On the other hand, if the economy weakens and unemployment rises, consumers may become more cautious and decide to conserve their savings balances.

So one should draw only broad conclusions.  But the data does suggest that the excess savings balances built up during the Covid crisis remain significant, and could provide support to continued growth in Personal Consumption Expenditures for some time – perhaps a year or more.  Many had assumed – including me before I looked at the data in this way – that the strong Personal Consumption Expenditures of the last two years would be diminishing soon, as excess savings balances were being used up.  But this data suggests that strong consumption growth might persist for another year or more.  What does this imply for the macro economy?

E.  Macro Implications

Inflation has been high – at 6 to over 8% year-on-year by various measures.  This is far in excess of the goal of the Fed of an inflation rate of around 2%.  In response, the Fed has been aggressively raising the short-term interest rates it controls, as well as reducing its holdings of bonds on its balance sheet (with the aim of raising longer-term interest rates).  Higher interest rates can be expected to reduce demand for investment (in particular in long-lived assets such as housing and other structures), and this lower demand will reduce pressures on prices.

Inflation had averaged around 2% – or even less – since the mid-1990s, but then rose as the economy recovered from the Covid crisis.  As discussed above, Personal Consumption Expenditures recovered quickly and strongly, with this made possible by the high savings balances that had been built up following the series of Covid relief packages while consumption was limited.  But the strong consumption expenditure demands that followed in 2021 and 2022 then faced often limited supplies due to supply chain difficulties as well as the cutbacks in production generally during the peak of the Covid crisis in 2020.  And some items of production cannot be placed into an inventory to be sold later.  For example, a restaurant produces meals for diners, but a meal that was not produced and sold during the Covid crisis cannot simply be kept somewhere and then sold later.  The meal not produced is gone forever.

The result has been a classic “demand-pull” inflation.  While the labor market is now tight, with unemployment the lowest it has been for more than a half-century, increases in nominal wages have fallen short of inflation.  That is, real wages have been falling, and one cannot attribute the inflation observed as primarily stemming from cost-push factors.

The Fed is thus raising interest rates to limit investment demand, and hence aggregate demand.  Whether it will be able to do this without sparking a general recession is the challenge it is facing.  While not impossible, it will certainly be tricky.  In addition, federal fiscal policy will also likely be acting in the direction of reducing demand.  Federal fiscal expenditures fell sharply in FY2022, as the Covid relief packages wound down.  As I write this, Congress has yet to approve a budget for FY2023, but the most recent forecast of the Congressional Budget Office (from July) was that federal fiscal expenditures would fall a further 1.2% of GDP in FY2023.  And with Republicans controlling the House starting in January, it is not likely that fiscal spending will be allowed to respond should the need arise next year due to a downturn developing.

In this sensitive balance of policies – with the Fed seeking to constrain demand but not by too much, and fiscal expenditures unresponsive should conditions change – what will happen to personal consumption expenditures will be critical.  A concern of many has been that such consumption expenditures might also be abruptly reduced once the excess in savings balances built up during the Covid crisis had become used up.  Inflation might well then come down quickly, but possibly with the economy falling into a recession as well.

The analysis above suggests that personal consumption expenditures – growing as it has over the last year and a half – could still be sustained through 2023.  If so, the likelihood of a recession in 2023 will be reduced (although still possible – depending on what the Fed does).  But conditions in 2024 might well then become more difficult to manage.  With the House controlled by the Republicans, who have said they will seek to force through cuts in the federal budget (as they did following their election win in 2010), a fiscal response to the changing conditions might not be forthcoming.  The Fed may be forced to switch rapidly from raising interest rates to cutting them, in an effort to stem a downturn.

It will likely not be easy to manage.  And with 2024 a presidential election year, there may well also be political factors complicating any response.

Measures of GDP; How Recessions Are Determined and Dated; the Economy in the First Half of 2022; and the Prospects for 2023

A.  Introduction

The Bureau of Economic Analysis (BEA) of the US Department of Commerce released on August 25 its second estimate of the GDP accounts for the second quarter of 2022.  The figures indicate that GDP fell by 0.6% in the quarter, a bit less than the fall of 0.9% in its initial estimate released in late July (what it calls its “advance estimate”).  But it was still a fall, and following the reduction in GDP in the first quarter of 2022 (by 1.6% in the most recent estimate), there have now been two consecutive quarters where estimated GDP has gone down.

Many mistakenly believe that an economic recession is defined as two consecutive quarters of falling real GDP.  This is not correct – there is no such definition for a recession.  But it is easy to see that such confusion can arise, as a commonly used “rule of thumb” is that if real GDP fell for two consecutive quarters, then this is a sign that the economy is in a recession.

The reality is more complex.  Much more enters into a designation that the US economy was in a recession in some period.  Indeed, while the quarterly GDP figures are certainly important, they actually play a secondary role as the designation of a recession is based more on a number of indicators that are available on a monthly basis (such as the monthly employment figures, wholesale and retail sales, and more).  Indeed, the dates assigned to a recession (when it began and when it ended) are of specific months, not calendar quarters.

Usually this does not matter much.  Such economic indicators normally move together.  But not always, and they certainly have not in 2022 thus far.  While real GDP as currently estimated fell in the first half of this year, the employment market has been extremely strong.  Employment has grown by an average of over 440,000 per month in the first half of 2022, and the unemployment rate fell from an already low 4.0% in January to just 3.6% in June and an even lower 3.5% in July.  This is the lowest the unemployment rate has been since 1969 – matching the 3.5% rate hit in early 2020 just before the pandemic crisis.  While a formal determination has not been made on whether the economy is in a recession or not – and as discussed below will not be made until more of the data are in and the trends are clear – it is highly doubtful that the first half of 2022 will be so designated.

This blog post will cover how that designation process works.  But it is of interest first to look at the current estimates of what has happened to real GDP in the first half of 2022.  The period illustrates well the pitfalls of exclusively focussing on whether real GDP fell for two consecutive quarters as an indicator of whether the economy is in a recession.

There is indeed a question of whether GDP in fact fell in the first two quarters of 2022 – even setting aside the issue that there will be further revisions in the current estimates.  Specifically, the BEA issues figures for GDP based on two different ways of estimating it:  One is based on expenditures (for consumption, investment, etc.) which it labels the expenditure-based GDP (or just GDP for short), and another is based on incomes earned (which it labels Gross Domestic Income, or GDI for short).  They should in principle be identical, as whatever is spent is someone’s income.  But the two estimates will differ in practice, as they are based on different approaches and different sources of data.

As seen in the chart at the top of this post, these two measures of GDP, while generally moving together over time, have diverged significantly from each other since late 2020.  And in the first half of 2022, GDI continued to grow while GDP fell.  The reasons for this divergence are not clear, but I am sure economists at the BEA are ardently trying to figure this out now.

At this point we do not know what the answer is.  It might well simply be a consequence of the estimates still being recent, and might go away as further data become available to yield better estimates.  But that difference between the two estimates illustrates well why one should not simplistically assert that two quarters of real GDP decline signals a recession underway.

This post will thus first look at the recent data, focusing on what the GDP and GDI concepts mean, why they should be identical (and indeed, for this reason serve as a useful check on each other in the estimates), and what might have caused the recent divergence.  The post will then look at the process followed in the US for designating periods of economic recession and expansion, where for historical reasons the process is overseen not by the government, but rather by a nonpartisan organization called the National Bureau of Economic Research (NBER).  It will conclude with a brief discussion of the prospects for 2023.  While it is doubtful that the economy in the first half of 2022 will ever be designated as being in a recession, the prospects of a recession in 2023, or even later in 2022, are substantial.

B.  Gross Domestic Product and Gross Domestic Income

Gross Domestic Product (GDP) is a measure of production – how much the economy is producing.  But while it is a measure of production, the primary way estimates are made of how much was produced, as well as the way most people think of GDP, is not by how much is produced but by how much is used.  That is, everyone who has taken an Econ 101 macro course will know that GDP will equal the sum of Private Consumption, Private Investment, Government Consumption and Investment Spending (often combined as simply Government Spending – but excluding spending on transfers to households such as for Social Security), and Net Foreign Trade (Exports less Imports).

Why should that sum of expenditures equal production?  The trick (as discussed in this earlier post on this blog) is that investment includes investment in any net buildup of inventories.  That is, changes in net inventories in a period will balance out any difference between what was produced and what was sold.

This is then a convenient way to estimate GDP.  But one should keep in mind that GDP is a measure of production, and that there are other ways to measure that which should yield the same result.  One is to approach it via incomes, as whatever is produced and sold is then someone’s income (when one includes the value of any net inventory accumulation).  Those incomes accrue as someone’s wages (including all forms of labor compensation) or as profits (net operating surplus more formally).  The BEA can assemble available data on wages and profits in the economy, and the sum should in principle be the same as GDP (with adjustments for indirect taxes such as sales taxes and including whatever was set aside in depreciation allowances).  (For those interested in the detailed breakdown, see Table 1.10 in the BEA NIPA Interactive Tables.)  For clarity, the BEA labels this income-based estimate of what should sum also to GDP as Gross Domestic Income, or GDI.

A third approach to estimating GDP is to estimate directly what production was in each sector of the economy.  The BEA does this as well, but one needs to take into account that the net contribution to production in the economy as a whole is not the gross output of any given sector, but that gross output less the value of whatever inputs it purchased from other sectors of the economy.  This is so that one does not double-count what is being produced.  That is, in each sector one estimates what economists call “value-added” – the value of what was produced less the value of the material inputs purchased to make that product.  The sum of this value-added across all sectors should once again be GDP.  The BEA refers to these estimates of value-added by sector as “GDP by Industry”.

The three measures should in principle yield the same figures for overall GDP.  But while in practice generally close, they don’t exactly match as they are all estimates based on data, and the data come from different sources.  Furthermore, that data is subject to revision as more complete information becomes available, so even though initial estimates may differ by some amount, the degree of those differences generally falls over time as better estimates become possible.

Why then does the public discussion generally focus on the expenditure-based estimate of GDP?  One simple reason is that it is always the first one that is published.  The BEA issues this initial estimate of GDP (its “advance estimate”) just one month after the end of the calendar quarter.  This estimate is eagerly awaited both by policymakers and the general public, and receives a good deal of attention in the news media.

The BEA only releases its first estimate of the income-based estimate of GDP (i.e. GDI) a month later, along with its second estimate of the expenditure-based approach to estimating GDP.  Since it comes later, and possibly also because it is less well known, less attention is given by the public (and consequently in the news media) to this income-based estimate of GDP.  But the quarter-to-quarter changes in GDI can differ significantly from the quarter-to-quarter changes in the expenditure-based estimate of GDP.  For example, in the estimates released on August 25, the revised (“second estimate”) for expenditure-based GDP was of a fall of 0.6% in real terms (at an annual rate and seasonally adjusted).  However, the initial estimate of the income-based estimate of GDP (i.e. of GDI) was that GDP grew by 1.4%.  This will be discussed further below.

The initial estimates using the third approach to estimating GDP (i.e. value-added by sector) are then only made available a month after that, i.e. along with the third estimate of the expenditure-based estimate of GDP and the second estimate of the income-based estimate of GDP (i.e. GDI).  These estimates receive even less attention.  The BEA has also been publishing them along with the monthly GDP reports only recently – starting in September 2020 for the second quarter of 2020 GDP figures.  They released them separately before with some further lag, and the underlying data series themselves are only available (in a consistent series based on the current methodology used) from 2005 on a quarterly basis and from 1997 on an annual basis.

Furthermore, while this third approach to estimating GDP could yield an additional check on the GDP estimates, in practice the BEA does not do this.  I am not sure precisely why, but in its methodology for estimating these GDP by Industry figures, it scales the estimates so that the sum matches the expenditure-based estimate of GDP for the period.  The BEA may feel that the underlying data for the GDP by Industry estimates are not sufficiently good to provide an independent estimate of GDP, or it might be concerned that a third but different estimate for GDP might cause confusion in the public.

It is thus not surprising that most attention is paid to the expenditure-based estimates of GDP.  They are available first, and thus they provide the figures that first indicate whether GDP is rising or falling.  But there is also a more fundamental reason why they deserve such attention.  As we have known since Keynes, the primary driver of GDP in the near term is what is happening to the various components of demand for GDP, i.e. the expenditure-based components of GDP.  Production (within the bounds of productive capacity) will respond to those demands, and in particular production will fall when the sum of those demands (what economists call “aggregate demand”) falls.  This might be in response to some financial crisis (with chaos in the financial markets leading to less investment), or to the Fed raising interest rates with the deliberate intention of reducing demand (with the higher interest rates leading to less investment), or due to cuts in government spending (possibly due to politics, such as when the Republican-controlled Congress elected in 2010 forced through government expenditure cuts in the subsequent years, thus slowing the recovery from the 2008/09 financial and economic crash while blaming this on Obama).  Similarly, spurs to growth will be found in what is happening to the various expenditure components of GDP.

The interest in this estimate of expenditure-based GDP is thus well-founded.  But one needs to keep in mind that the figures are still estimates, and are imperfect as the data are imperfect.  An independent check on this, such as from the independent estimate of GDP based on estimated incomes (i.e. GDI), is thus of interest.  Henceforward, for simplicity I will generally refer to the expenditure-based estimate of GDP as simply “GDP”, and the income-based estimate as simply “GDI” (the same terms the BEA uses).

The two estimates (GDP and GDI) generally move quite closely together.  This can be seen in the chart at the top of this post.  Note that while the figures here are shown in real terms, the price deflator used for both GDP and GDI is the same.  The reason is that while price indices can be calculated for the goods and services that make up the expenditure-based estimate of GDP, one cannot define such price indices for the wages and profits that make up the income-based GDI. Thus to deflate the GDI estimate to real terms, the BEA uses the same price deflator as it has estimated for GDP.  This is convenient for the interpretation of the figures as well, as any deviation of one from the other cannot then be attributed in some way to two different price deflators being used.  There is only one.

[Technical Note:  The figures are of GDP and GDI each quarter, but they are shown at annual rates from seasonally adjusted figures.  The price indices used are what are called “chain-weighted dollars”, with 2012 as the base year.  One may recall from an Econ 101 class that a Laspeyres price index calculates the index based on the weights of the underlying items in overall expenditures in the base year, and a Paasche price index calculates the index based on the weights of the underlying items in overall expenditures in the final year.  A chain-weighted index calculates the index based on weights that change period by period based on expenditures on the items in each of the periods.]

The estimates of GDI have generally been above the estimate of GDP in recent years – and especially so since late 2020.  That has not always been the case.  One can see in the chart at the top of this post that estimated GDI was below estimated GDP between mid-2007 and the start of 2011.  But broadly they move together, as one should expect and as can be seen in a chart of the data going back to 1947 (when quarterly estimates of GDP and GDI began):

There is, of course, a scale effect over such a long period, as real GDP has grown by a factor of ten between 1947 and 2022.  The difference between GDP and GDI will not then be so apparent in the earlier years, and it is more meaningful to look at the difference between the two estimates as a share of GDP in that year:

The BEA assigns a label to the difference between GDP and GDI:  they call it simply the “Statistical Discrepancy”.  That difference as a share of GDP was quite small and generally within a range of +/- 1% of GDP between 1947 and the late 1970s, and more often positive than negative (i.e. estimated GDP above estimated GDI).  It then moved between greater extremes, but remained generally positive, from the early 1980s to around 1997.  The volatility then continued, but since 1997 the Statistical Discrepancy was more often negative than positive (estimated GDP less than estimated GDI).

Since the fourth quarter of 2020 it has, however, turned more sharply negative than it has ever been before.  Why?  No one really knows, although there is some speculation (and I am sure work underway at the BEA to try to figure this out).  A higher GDI than GDP implies that estimated incomes are higher than what the expenditure-based estimates would imply.  It is possible that some of these incomes are becoming more difficult to estimate.  For example, there are conceptual issues in how properly to account for compensation being paid by transfers of assets – such as happens with stock options – and the BEA data sources may not be good at estimating these.  Individuals may treat these as part of their compensation (as they should), but in the company accounts they may be treated as a transfer of assets (the stock options) that may not then be properly reflected in recorded profits (at least from the viewpoint of the National Income Accounts).

It is also possible that the sharp increase in the Statistical Discrepancy in the last couple of years may in part go away as more complete data becomes available and new and better estimates for GDP and GDI are worked out.  But at this point we just do not know.

Due to these differences in the estimates, many of the more careful economists working with the GDP figures use not solely the GDP estimate nor solely the GDI estimate, but rather the simple average of the two.  By weighting them equally in this simple average, the implication is that the uncertainty on each is similar.  The BEA itself provides this simple average in its monthly releases of the GDP estimates (although with the item blank in the first release of each quarter when only the expenditure-based GDP estimate is available).  But these figures on the average of GDP and GDI do not receive much attention from many.

Focusing in on the last few years:

The chart is as before, but now shows also the simple average of the GDP and GDI estimates.  The path of GDP as estimated by the GDI figures has been substantially above the path as estimated by the expenditure-based GDP figures since the fourth quarter of 2020.  And in the first half of 2022, GDI has continued to grow (although at a slower pace than before) while GDP as measured by expenditures fell.  Neither of the changes are large.  And the simple average of the two comes out as almost flat, but positive (with growth of 0.1% in the first quarter of 2022 and 0.4% in the second quarter – in the estimates as currently published).

Thus by this measure of GDP, the economy has continued to grow in these most recent estimates in the first half of 2022, although at only a slow rate.  This could well change with the revisions to come as more complete data become available, but for now they show positive growth in each of the quarters.

C.  Designating and Dating Recessions

The commonly accepted designation of whether the US economy is in a recession or not is not made by a government agency, nor is it based on some set of specific criteria (such as that GDP fell for two consecutive calendar quarters).  Rather, for historical reasons the designation is made through a private, nonprofit and nonpartisan, organization that supports economic research in the US called the National Bureau of Economic Research (NBER).

The NBER was founded in 1920, on the initiative largely of two individuals – one an executive at AT&T and the other a socialist labor organizer who had a Ph.D. in Economics from Columbia.  While very different in their views on what to do about unemployment, both recognized that the data available at the time were insufficient for an adequate understanding of the conditions.  They founded the NBER with the intention for it to support teams that could produce such data – more than what could be done by individual academics.  They deliberately kept it nonpartisan, where the NBER itself would not produce specific policy recommendations, and were able to obtain funding from a range of sources, including from some of the larger corporations of the time, from certain foundations, and from other private donations.

The NBER’s first director of research was Wesley Clair Mitchell, then a professor at Columbia and an expert on business cycle research.  He assembled a team that produced what was then the best data of the time on business-cycle fluctuations in the US.  This research was published and proved influential.  As part of it, as well as in continued such work later sponsored by the NBER, the researchers would determine, to the best the data they could assemble would allow, the periods when the US economy was expanding and when it was contracting.  Periods of contraction were labeled recessions.

The US Department of Commerce started to produce more systematic data on the state of the economy in the 1930s, due in part to the Great Depression then underway.  They worked out the basic GDP concepts we now use and how to measure them in practice given the data they could assemble, with this early work done often with the help of researchers from the NBER.  A particularly prominent such then-young researcher was Simon Kuznets, a student of Wesley Clair Mitchell who then moved to the NBER, and who is often credited with developing the original concepts for GDP (and who subsequently was granted a Nobel Prize in Economics for this work).

The Department of Commerce (now through its Bureau of Economic Analysis) has since produced the official GDP accounts for the US.  In 1961, a decision was made that rather than have this government agency make a determination on whether the economy was in a “recession” (defined in some way) or not, they would instead simply reference the determinations made at the NBER.

These determinations of the NBER were originally made as a by-product of the research it sponsored on business cycles in the US.  In 1978, the NBER decided to formalize the process and make it independent of specific research projects by appointing a committee of academic economists to make such designations.  The committee members represented a range of views but all members had a focus on macro and business cycle issues.  Formally, it was named the NBER Business Cycle Dating Committee.  There are currently eight members of this Committee, and there has been only limited turnover over time.  There have been only seven other individuals who have served on the Committee in the 44 years since its origin, and the chair (Robert Hall), as well one of the current Committee members (Robert Gordon), have served on it since its start.  Robert Hall is a well-respected economist, a professor at Stanford since 1978, and is politically and economically conservative.  He was a supporter of the Reagan tax cuts and has advocated for a flat tax to replace progressive income taxes in the US.

This NBER committee was set up by Martin Feldstein (a professor at Harvard) soon after he became the president of the NBER.  Feldstein was also a well-respected economist as well as open-minded.  He was the Chair of the Council of Economic Advisers in the Reagan White House between 1982 and 1984.  During that time he brought to the Council two bright and capable young economists with recent Ph.Ds. – one to look at domestic policy issues (Larry Summers) and one to focus on foreign trade issues (Paul Krugman).

The NBER Business Cycle Dating Committee meets when members believe they have sufficient data and other information to determine whether the economy had reached a business cycle peak (following which it would be contracting, with this then a recession), or a trough (after which the economy would be expanding, and the recession would be over).  Such determinations have been made by the Committee anywhere between 4 and 21 months after the dates of those business cycle peaks or troughs (as later determined).  They have no deadline for this, but meet when they believe they may have sufficient data to draw a conclusion.  Indeed, sometimes they have met and then deferred a decision, as they felt that upon review they did not yet have sufficient information to make a decision at that point in time (see this news release for one example).

Keep in mind that an economy in recession is one where economic activity is contracting.  It is not defined as a period where economic activity might be considered “low” in some sense, such as below some previous peak.  Thus unemployment will in general still be relatively high at the point where the economy has started to expand again and has thus emerged from the recession.  This may be confusing to some, as economic conditions “feel” (and in fact are) very similar to how they were the month before a trough was reached.  Indeed, it is common that the unemployment rate will still be growing for a period after that trough even though the economic recession (as defined here) is over.  For example, the NBER Committee determined that the 2007/2009 contraction (and thus recession) ended in June 2009.  At that point, the unemployment rate had hit 9.5% – higher than at any point since Reagan (when unemployment peaked at 10.8%).  But the unemployment rate continued to rise after June 2009, peaking at 10.0% in October 2009.

How then is a “recession” defined?  The NBER Committee defines it as:

“a significant decline in economic activity that is spread across the economy and that lasts more than a few months. The committee’s view is that while each of the three criteria—depth, diffusion, and duration—needs to be met individually to some degree, extreme conditions revealed by one criterion may partially offset weaker indications from another.”

Note that it must be what the Committee determines to be a “significant” decline, spread across much of the economy and not simply concentrated in a few sectors, as well as a decline that lasts for a substantial period (normally more than just a few months).  But no specific minimum values are specified for any of these factors.

The Committee also dates the recession (i.e. the dates of the peak and the trough in economic activity) to a specific month.  For this reason alone, the GDP data will not suffice.  It is only available quarterly.  Rather, the Committee has explained that it pays particular attention to the following data series (from the BEA, the Bureau of Labor Statistics, and other sources), which are made available and published monthly:

Real personal income less transfers;

Real personal consumption expenditures;

Employment (both nonfarm payrolls from the Survey of Establishments and employment as reported in the Current Population Survey of households);

Real manufacturing and wholesale/retail trade sales;

Index of industrial production.

But while the Committee has explicitly noted it pays attention in particular to these data series, they can and will look at whatever they feel may be relevant to their decision.

Once they determine the month in which the economy reached a peak or a trough, they will also report on which calendar quarter they believe the economy reached its peak or trough.  This is normally, but not always, the calendar quarter of the respective peak or trough of the months marking a recession, but not always.  Sometimes it might be the quarter before, or the quarter after.  For example, in the short but extremely sharp downturn in the spring of 2020 due to the lockdowns required to deal with Covid, the date marking the start of the recession (when the economy had reached its peak) was February 2020 and the trough was set as April 2020.  But the peak quarter was determined to be the fourth quarter of 2019, not the first quarter of 2020.

It also should be noted that for these determinations of the quarters where the economy had reached its peak or trough, the Committee does not focus on the expenditure-based estimate of GDP, but rather on the simple average of this GDP and GDI.  And as noted above, by this measure GDP rose in the first half of 2022 (according to the current estimates).

Could the Committee get this dating wrong?  Certainly – they are only human, and judgment is required in making these decisions.  Others can and sometimes do disagree, as one would expect in any science.  But the Committee has been careful, makes its decisions only when they believe sufficient time has passed to allow them to make a decision, and the members of the Committee represent a range of perspectives.  And while they do not say so explicitly on the NBER website where they explain their work, I strongly suspect that the Committee operates by consensus, and that if there is not a consensus when some such meeting has been called, they defer their decision until more complete data allows a consensus to be reached.

For this reason, the dates set by the NBER Committee for the beginning and the end of a recession are generally accepted as soundly based.

D.  Conclusion and the Prospects for 2023

Was the economy in a recession in the first half of 2022, as a number of  commentators have asserted?  (See, for example, this report on Fox Business, that asserted the US was in what they called a “technical recession” in the first half of 2022, or these unsurprising statements from Republican Senators Rick Scott of Florida and Rob Portman of Ohio.)

Formally, the NBER Committee has not met on this, so no such determination has yet been made.  But more fundamentally, based on the criteria the Committee uses it is highly doubtful that it will at some point decide the economy was in a recession in the first half of 2022.  The job market as well as other measures have been extremely strong.  Furthermore, even the GDP measure has been misinterpreted in the media as the Committee pays more attention to the average of the estimates for the expenditure-based GDP and the income-based GDI rather than just the former.  By this measure, the economy in fact grew in the first half of 2022 – although not by much and where future revisions in the data might change this.  But even if future data should indicate there was in fact a decline, it would certainly not be by much.

I should hasten to add that this does not mean the economy might not soon be in a recession.  Personally, I believe there is a significant possibility that the economy will be in a recession in 2023, possibly starting later in 2022.  Government spending is coming down sharply from the giant packages passed under Trump in 2020 and then continued under Biden in 2021 to provide relief from the Covid crisis; households are now spending savings that some had accumulated during the pandemic period; and the Fed is raising interest rates with the deliberate intent to slow the economy in order to reduce inflation.  I will expand on each of these in turn.

Using data from the Congressional Budget Office, total federal government spending rose by $2.1 trillion dollars in FY2020 under Trump, an increase of close to 50% from the $4.4 trillion spent in FY2019.  It rose from 21.0% of GDP in FY2019 to 31.3% of GDP in FY2020.  That was gigantic and unprecedented in the US other than during World War II.  It then stayed at roughly that level in FY2021, the first year under Biden (or rather two-thirds of a year as Biden was inaugurated on January 20 and the fiscal year starts on October 1).  In FY2021 federal government spending in fact fell as a share of GDP to 30.5% while rising in dollar value by $269 billion.  But in FY2022 it has now been reduced under Biden by $1.0 trillion – falling as a share of GDP by 7 percentage points to 23.5% of GDP.  There has not been such a fall in government spending since 1947 (as a share of GDP).

In terms of the federal government fiscal deficit, the deficit was at 4.7% of GDP in FY2019 (already substantially higher under Trump than the 2.4% of GDP it was in FY2015, as Trump increased spending while cutting taxes – mostly on the rich and on corporations).  The deficit then jumped to an unprecedented level (other than during World War II) of 15.0% of GDP in FY2020, before falling to 12.4% of GDP in FY2021 under Biden and an expected 3.9% of GDP in FY2022.  Note that this deficit in FY2022 is well less than the 4.7% of GDP in FY2019 under Trump before the Covid crisis.

This sharp cutback in federal government spending under Biden (not the story normally told by Republican politicians) would in itself be deflationary.  It has not been, however, as households as well as businesses are now spending balances many had saved and built up in 2020 and continuing into 2021.  These saving balances were built up from what they received under the various government support programs as well as due to other Covid-related programs (such as the option to suspend payments on certain debts), while spending was kept down (one did not go out to eat at restaurants as often, if at all, for example).  Note this was not the case for everyone.  Many households could only continue to barely get by – spending what they received.  But for other households, the programs led them to increase their savings balances.

The constraints on spending lifted during the course of 2021, and as accumulated savings were spent there was greater demand for goods than supply.  Prices were bid up despite the sharp cutback in government spending in FY2022.  Amplified also as a consequence of the Russian invasion of Ukraine in February 2022 that led to jumps in the prices of foods and fuels, the year-on-year increase in the CPI hit 9.1% in June 2022, before falling some to a still high 8.5% in July 2022.

The jump in the CPI – which started in mid-2021 – has led the Fed to raise interest rates.  Their aim is that the higher interest cost will lead to lower investment, which will reduce aggregate demand.  It hopes to do this without tipping the economy into a recession, but coupled with the sharp cuts in federal government spending and depletion of the excess savings that had built up during the pandemic, there is a significant danger that the Fed will not succeed in this.

It is always tricky, as interest rates are a blunt instrument for moving the economy.  Also, interest rates affect demand only with some lag that is hard to predict.  Finally, if a sharper than desired downturn does appear imminent and some boost in federal government spending becomes warranted to offset this, a Congress controlled by Republicans following the November elections would almost certainly block this.  As discussed above, one saw such dynamics during the Obama presidency following the election of a Republican-controlled Congress in November 2010.  They forced through government spending cuts in the subsequent years, despite the still weak economy following the 2008/09 collapse – the first time there were such cuts in government spending (since at least the 1970s) when unemployment was still high following a recession.  This slowed the pace of the recovery.

There could very well be a repeat of that mistake in 2023.  A recession cannot be ruled out.