US economy

Error message

Deprecated function: The each() function is deprecated. This message will be suppressed on further calls in _menu_load_objects() (line 579 of /var/www/drupal-7.x/includes/menu.inc).

US labour market – things are getting worse again as the virus spreads

Published by Anonymous (not verified) on Mon, 18/01/2021 - 1:08pm in

Tags 

US economy

US Department of Labor’s latest unemployment claimant data is worrying with the claimants in the week to January 9, 2021 rising to 1,151,051 a shift of 231,335. This is the highest level since the week ending July 25, 2020 and confirms what we now know – that unless a nation deals with the health crisis and gets the virus infections under control (preferably to the point of zero community transmission), it cannot hope for a sustainable economic recovery. The data is the result of lockdowns leading to layoffs in the hospitality and recreation sectors which has pushed the US economy back into contraction. The rise in new claimants follows the payroll data that revealed that employment had fallen by 140,000 (net) – see this blog post for analysis of that data release – US labour market recovery has ended as health problem intensifies (January 11, 2021). And given the nature of the employment most impacted, you can be sure that socio-economic inequalities will have risen. I will write about that last issue another day.

Here is the latest update (as for the week ending October 17, 2020) from the US Department of Labor’s weekly data releases for the unemployment insurance claimants.

The Department of Labor provides an archive of the weekly unemployment insurance claims data back to January 7, 1967 – HERE.

The weekly data can be found in the – UI Weekly Claims Report.

New claimants rise sharply

The next graph shows the data for New claimants data from January 1, 2020 to January 10, 2021.

I had previously posted the full sample, which showed how insignificant the previous deep recessions of the early 1980s, 1990s and the GFC were by comparison with the current event.

But we get little information from seeing a huge vertical line dwarfing all previous observations. We know the scale.

This series provides the best information on the state of the labour market and reinforces the information we learned from the monthly payroll and labour force survey data – with the virus out of control – the economy will worsen.

The problem that the data on new (first-time) claimants for benefits demonstrates is that the weekly claims have not substantially declined since August, which tells me that employment growth has not been not fast enough to absorb the accumulated pool of jobless workers.

Continuing claims and covered unemployment rate

The other series, which is of interest is the continuing claims, which lags the new claims by a week.

The following graph shows that this series is dropping steadily until November 2020 but then levelled off as the health crisis deepened.

There are now 5,271,000.

On March 7, 2020, the stock of continuing claims was 1,702,000 persons. The figure for the week ending January 2, 2021 remains at 3.1 times that level.

It signals that the new US government will have to prioritise economic relief if they want to make any inroads into this disaster.

The next graph shows the evolution of the insured unemployment rate, which measures the proportion of the labour force that is collecting unemployment benefits.

This time last year, the rate was 1.2 per cent.

In the week to January 2, 2021, the rate rose from 3.5 per cent to 3.7 per cent (seasonally adjusted), which suggests a deteriorating situation.

Bringing together the archived data and the most recent release (January 10, 2021), the following table tells the story for those who like numbers.

Week ending
Initial Claims (SA)
Weekly Change

March 7, 2020
211,000
-6,000

December 12, 2020
941,910
-14,563

December 19, 2020
872,941
-68,969

December 26, 2020
835,972
-36,969

January 2, 2021
919,680
83,708

January 9, 2021
1,151,015
+231,335

Past Recessions Comparison

I wondered what the behaviour of this time series had been in past recessions. The data goes back to January 1967, which means it covers 8 official US recessions.

I started the indexes at 100 for each recession in the week where the lowest claimant count occurred before the recession began and then graphed the index out to 40 weeks, which is the duration of the current COVID recession.

The following graph covers the 7 official recessions up to and including the GFC.

I decided to graph the COVID episode separately because it completely obliterates any of the past dynamics in amplitude.

As you can see, the pattern is very similar for all these events (with some variational spikes).

Here is the graph for the COVID period. Stunning.

The current observation (January 10, 2021) is worse than any of the peaks in previous recessions (even the 1973 episode).

The spatial patterns

The following Table presents the most recent data to January 10, 2020 for the US states.

The columns are:

1. State

2. The Change in New Claimants for week ending January 9, 2021 – which gives you an idea of where the deterioration is occurring – huge shifts in Arizona, California, Florida, Illinois, Kansas, Maryland, New Mexico, New York, Texas, and Virginia.

3. Insured Unemployment as at January 2, 2021

4. Insured Unemployment as at January 2, 2021 as a percent of the each state’s working age population.

Conclusion

I am currently digging further into the regional data to record the socio-economic impact of the deteriorating situation.

I will write more about that tomorrow.

It is clear that the pandemic has also been a socio-economic disaster, which led one medical writer to coin the term ‘global syndemic’ to link the health disaster with the socio-economic considerations in the context of the worst health outcomes impacting on the poorest communities. A perfect neoliberal storm.

But it is also obvious that without further fiscal support, the situation in the US will become untenable from a social standpoint.

That is enough for today!

(c) Copyright 2021 William Mitchell. All Rights Reserved.

US labour market recovery has ended as health problem intensifies

Published by Anonymous (not verified) on Mon, 11/01/2021 - 12:33pm in

Tags 

US economy

It has been clear that with the virus infections in the US increasing rapidly and with the lack of fiscal support from government, that the labour market conditions would probably start to deteriorate after a brief period of recovery following the first blush with the virus. I have been predicting that since December 2020. The latest data reveals that assessment was accurate. On January 8, 2021, the US Bureau of Labor Statistics (BLS) released their latest labour market data – Employment Situation Summary – December 2020 – which reveals a deteriorating or static situation, depending on the weight one gives to the payroll data relative to the household survey. Payroll employment fell by 140 thousand. In terms of the household survey, with employment and the labour force hardly moving, unemployment and the unemployment rate was unchanged. While the signals are a little confused, the data is showing the recovery has ended as the health crisis intensifies. I consider that the US will have to stabilise the health situation before they will be able to sustain any economic recovery. The US appears to be going in the opposite direction to that.

Overview for December 2020:

  • Payroll employment fell by 140,000.
  • Total labour force survey employment rose by 21 thousand net (0.01 per cent).
  • The seasonally adjusted labour force rose by 31 thousand (0.02 per cent).
  • Official unemployment was unchanged at 10,736 thousand
  • The official unemployment rate was unchanged at 6.7 per cent.
  • The participation rate fell by 0.2 points to 61.5 per cent.
  • The broad labour underutilisation measure (U6) fell by 0.3 points to 11.7 per cent, as the part-time for economic reasons cohort (the US indicator of underemployment) fell by 471 thousand (7.1 per cent).

For those who are confused about the difference between the payroll (establishment) data and the household survey data you should read this blog post – US labour market is in a deplorable state – where I explain the differences in detail.

BLS explanation

The BLS provided a special note to help us understand the results this month.

We learn:

1. “The collection rate for the establishment survey was 76 percent in December, about the same as the average for the 12 months ending in February 2020.”

2. “The household survey response rate was 77 percent in December, considerably higher than the low of 65 percent in June but below the average of 83 percent for the 12 months ending in February 2020.”

3. Both results reduce the accuracy of the surveys.

4. In the payroll survey:

… workers who are paid by their employer for all or any part of the pay period including the 12th of the month are counted as employed, even if they were not actually at their jobs. Workers who are temporarily or permanently absent from their jobs and are not being paid are not counted as employed, even if they continue to receive benefits.

5. In the Labour Force survey:

… individuals are classified as employed, unemployed, or not in the labor force based on their answers to a series of questions about their activities during the survey reference week (December 6th through December 12th). Workers who indicate they were not working during the entire survey reference week and expect to be recalled to their jobs should be classified as unemployed on temporary layoff. As in recent months, a large number of persons were classified as unemployed on temporary layoff in November.

The BLS wanted the latter group classified as unemployed for consistency but the survey staff didn’t always comply, which means that the employment estimates are probably overstated.

What impact might this have had?

The BLS say:

… the share of responses that may have been misclassified was highest in the early months of the pandemic and has been considerably lower in recent months.

For March through November, BLS published an estimate of what the unemployment rate would have been had misclassified workers been included among the unemployed. Repeating this same approach, the overall December unemployment rate would have been 0.6 percentage point higher than reported. However, this represents the upper bound of our estimate of misclassification and probably overstates the size of the misclassification error.

So we are still operating in an environment of uncertainty but the data accuracy has increased.

Payroll employment trends

The BLS noted that:

Total nonfarm payroll employment declined by 140,000 in December. Employment declines in leisure and hospitality, private education, and government were partially offset by gains in professional and business services, retail trade, construction, and transportation and warehousing. In December, nonfarm employment was below its February level by 9.8 million, or 6.5 percent.

It is clear that the US is in a dire situation. With the virus spiralling out of control, hospitals becoming overcrowded and the death rate rising to unimaginable levels, policy makers will have to reimpose lockdowns and the labour market will deteriorate as a consequence.

That is evident by where the losses in December have occurred:

In December, employment in leisure and hospitality declined by 498,000, with three-quarters of the decrease in food services and drinking places (-372,000). Employment also fell in the amusements, gambling, and recreation industry (-92,000) and in the accommodation industry (-24,000). Since February, employment in leisure and hospitality is down by 3.9 million, or 23.2 percent.

The other worry is that:

Government employment declined by 45,000 in December. Employment in the component of local government that excludes education declined by 32,000, and state government education lost 20,000 jobs. Federal government employment increased by 6,000. Since February, government employment overall is down by 1.3 million.

That signals a failure of the policy response.

The first graph shows the monthly change in payroll employment (in thousands, expressed as a 3-month moving average to take out the monthly noise). The gray lines are the annual averages.

The data swings are still large and dwarf the past history.

Clearly, the 20.7 million job loss in April has not yet been reversed. Given the loss of payroll jobs in March and April, the US labour market is still 9.8 million jobs short from where it was at the end of February.

The next graph shows the same data in a different way – in this case the graph shows the average net monthly change in payroll employment (actual) for the calendar years from 1940 to 2020 (the 2020 average is for the months to date).

I usually only show this graph from 2005 but because history is being created at present I included the full sample available from 1940.

The final average for 2019 was 178 thousand.

The average so far for 2020 is -781 thousand.

Labour Force Survey – employment growth nearly zero

The data for December reveals:

1. Employment as measured by the household survey rose by 21 thousand net (0.01 per cent).

2. The labour force rose by 31 thousand (0.02 per cent).

3. The participation rate was unchanged.

4. As a result (in accounting terms), total measured unemployment rose by 8 thousand and the unemployment rate was unchanged at 6.7 per cent.

The following graph shows the monthly employment growth since January 2008, which shows the massive disruption this sickness has caused.

The Employment-Population ratio is a good measure of the strength of the labour market because the movements are relatively unambiguous because the denominator population is not particularly sensitive to the cycle (unlike the labour force).

The following graph shows the US Employment-Population from January 1950 to December 2020.

While the ratio fluctuates a little, the April 2020 ratio fell by 8.7 points to 51.3 per cent, which is the largest monthly fall since the sample began in January 1948.

In December 2020, the ratio was unchanged at 57.4 per cent.

It is still well down on the level in January 2020 (61.1 per cent).

As a matter of history, the following graph shows employment indexes for the US (from US Bureau of Labor Statistics data) for the five NBER recessions since the mid-1970s and the current 2020-COVID crisis.

They are indexed at the employment peak in each case and we trace the data out for each episode until one month before the next peak.

So you get an idea of:

1. The amplitude (depth) of each cycle in employment terms.

2. The length of the cycle in months from peak-trough-peak.

The early 1980s recession was in two parts – a short downturn in 1981, which was followed by a second major downturn 12 months later in July 1982 which then endured.

Other facts:

1. Return to peak for the GFC was after 78 months.

2. The previous recessions have returned to the 100 index value after around 30 to 34 months.

3. Even at the end of the GFC cycle (146 months), total employment in the US had still only risen by 8.3 per cent (since December 2007), which is a very moderate growth path as is shown in the graph.

The current collapse is something else and progress has now now stalled.

Unemployment and underutilisation trends

The BLS report that:

In December, both the unemployment rate, at 6.7 percent, and the number of unemployed persons, at 10.7 million, were unchanged. Although both measures are much lower than their April highs, they are nearly twice their pre-pandemic levels in February (3.5 percent and 5.7 million, respectively)

The official unemployment rate was unchanged in December 2020 largely because the labour force and employment barely changed. Participation was constant.

The first graph shows the official unemployment rate since January 1994.

The official unemployment rate is a narrow measure of labour wastage, which means that a strict comparison with the 1960s, for example, in terms of how tight the labour market, has to take into account broader measures of labour underutilisation.

The next graph shows the BLS measure U6, which is defined as:

Total unemployed, plus all marginally attached workers plus total employed part time for economic reasons, as a percent of all civilian labor force plus all marginally attached workers.

It is thus the broadest quantitative measure of labour underutilisation that the BLS publish.

In December 2006, before the effects of the slowdown started to impact upon the labour market, the measure was estimated to be 7.9 per cent.

In December 2020 the U6 measure decreased by 0.3 points to 11.7 per cent.

What drove this decline in U6?

The BLS say that:

The number of persons employed part time for economic reasons, at 6.2 million, decreased by 471,000 over the month. This measure is down from its April high of 10.9 million but is 1.8 million higher than the February level. These individuals, who would have preferred full-time employment, were working part time because their hours had been reduced or they were unable to find full-time jobs …

In December, the number of persons not in the labor force who currently want a job, at 7.3 million, was little changed over the month but is 2.3 million higher than in February. These individuals were not counted as unemployed because they were not actively looking for work during the last 4 weeks or were unavailable to take a job …

Among those not in the labor force who currently want a job, the number of persons marginally attached to the labor force, at 2.2 million, changed little in December but is up by 749,000 since February. These individuals wanted and were available for work and had looked for a job sometime in the prior 12 months but had not looked for work in the 4 weeks preceding the survey. The number of discouraged workers, a subset of the marginally attached who believed that no jobs were available for them, was essentially unchanged at 663,000 in December but is up by 262,000 since February.

Ethnicity and Education

The next graph shows the evolution of unemployment rates for three cohorts based on educational attainment: (a) those with less than high school completion; (b) high school graduates; and (c) university graduates.

As usual, when there is a crisis, the least educated suffer disproportionately.

In the collapse in employment, the unemployment rates rose by:

  • 14.4 points for those with less than high-school diploma.
  • 12.9 points for high school, no college graduates.
  • 5.9 points for those with university degrees.

The period since April 2020 has seen the unemployment rate fall by:

  • 11.1 points for those with less than high-school diploma meaning the unemployment rate is now 3.8 points above the March level.
  • 9.5 points for high school, no college graduates meaning the unemployment rate is now 4.6 points above the March level.
  • 4.2 points for those with university degrees meaning the unemployment rate is now 2.3 points above the March level.

In the last month, the change in the unemployment rate has been:

  • +0.6 points points for those with less than high-school diploma.
  • No change for high school, no college graduates meaning the unemployment rate.
  • -0.4 points for those with university degrees meaning the unemployment rate.

So a deterioration for those with less than high-school education

In the US context, especially in the current time, the trends in trends in unemployment by ethnicity are interesting.

Two questions arise:

1. How have the Black and African American and White unemployment rate fared in the post-GFC period?

2. How has the relationship between the Black and African American unemployment rate and the White unemployment rate changed since the GFC?

Summary:

1. All the series move together as economic activity cycles. The data also moves around a lot on a monthly basis.

2. The Black and African American unemployment rate was 6.7 per cent in March 2020, rose to 16.8 per cent in May and is now down to 9.9 per cent in December 2020.

3. The Hispanic or Latino unemployment rate was 6 per cent in March 2020, rose to 18.9 per cent in April and fell to 9.3 per cent in December 2020.

4. The White unemployment rate was 4 per cent in March 2020, rose to 14.2 per cent in April and fell to 6 per cent in December 2020.

The next graph shows the Black and African American unemployment rate to White unemployment rate (ratio) from January 2018, when the White unemployment rate was at 3.5 per cent and the Black or African American rate was at 7.5 per cent.

This graph allows us to see whether the relative position of the two cohorts has changed since the crisis. If it is rising, then the unemployment rate of the Black and African American cohort is either rising faster than the white unemployment rate or falling more slowly (or a combination of that relativity).

While there is month-to-month variability, the data shows that, in fact, through to mid-2019, the position of Black and African Americans had improved in relative terms (to Whites), although that just reflected the fact that the White unemployment was so low that employers were forced to take on other ‘less preferred’ workers if they wanted to maintain growth.

In April 2019, the ratio was 2.1 (meaning the Black and African American unemployment rate was more than 2 times the White rate).

By April 2020, the ratio had fallen to its lowest level of 1.2, reflecting the improved relative Black and African American position.

As the pandemic hit, the ratio rose and peaked at 1.8 in August 2020, but fell to 1.7 in September, reflecting an improvement in the relative position of the Black and African American workers.

In December 2020, the ratio was 1.65 down from 1.75 in November.

Conclusion

The December 2020 US BLS labour market data release reveals that the recovery seen since the catastrophic labour market collapse in March and April has gone into reverse or at best stalled, depending on the weight one gives to the payroll data relative to the household survey.

Payroll employment fell by 140 thousand. In terms of the household survey, with employment and the labour force hardly moving, unemployment and the unemployment rate was unchanged.

While the signals are a little confused, the data is showing the recovery has ended as the health crisis intensifies.

The attrition in government employment continued which makes no sense at all.

And, I haven’t read anything from the incoming Administration to suggest they will take a dramatically different approach.

I consider that the US will have to stabilise the health situation before they will be able to sustain any economic recovery.

The US appears to be going in the opposite direction to that.

That is enough for today!

(c) Copyright 2021 William Mitchell. All Rights Reserved.

Is the $US900 billion stimulus in the US likely to overheat the economy – Part 2?

Published by Anonymous (not verified) on Thu, 31/12/2020 - 5:36pm in

The answer to the question posed in the title is No! Lawrence Summers’ macroeconomic assessment does not stack up. In – Is the $US900 billion stimulus in the US likely to overheat the economy – Part 1? (December 30, 2020) – I developed the framework for considering whether it was sensible for the US government to provide a $US2,000 once-off, means-tested payment as part of its latest fiscal stimulus. Summers was opposed to it claiming that it would push the economy into an inflationary spiral because it would more than close the current output gap. Today, I do the numbers. The conclusion is that there is more than enough scope for the Government to make the transfers without running out of fiscal space.

Measuring the output gap in the US

The first graph gives you an idea of the real GDP (output) history and the CBO measure of potential GDP. The grey bars are the NBER recessions (peak to trough).

The boxed area is shown in more detail in a later graph.

The thing that stands out in this graph is that the GFC was a very bad recession relative to the previous downturns, of which some were quite serious – such as the 1981-82 recession.

Not only was the length of downturn of the GFC prolonged but the amplitude of the real GDP contraction stands out.

But the other major issue is that CBO estimated that the potential growth path contracted significantly as a result of the prolonged recession.

One of the reasons, potential GDP declines after a recession is if the investment ratio declines significantly.

Investment spending has two impacts:

(a) It adds to current demand for goods and services (capital equipment, etc).

(b) It adds productive capacity to the economy which increases the potential GDP.

So an enduring decline in investment, which commonly drives recessions, not only opens up the output gap, but also reduces potential output.

The impact on potential GDP depends on how deep and how long the recession is.

The GFC was particularly severe.

The decline in the investment ratio as a result of the crisis was substantial and endured for 2 years. It went from 18.2 per cent in the June-quarter 2006 to a low of 12.3 per cent in the December-quarter 2009.

As a result the potential productive capacity of the US contracted somewhat The question is how much?

There are various estimates available but the overall message is that potential GDP fell considerably as a result of the lack of productive investment in the period following the crisis (see below).

It returned slowly (the cyclical response was asymmetric) to 18 per cent by the June-quarter 2018, fell back somewhat and then peaked at 18.4 per cent in the June-quarter 2019.

The current decline due to the pandemic only accentuates the downturn spiral that began in the September-quarter 2019.

The next graph shows the percentage annual change in business investment in the US since 1950.

Now consider the next graph which zooms in on the rectangular area identified in the earlier graph.

To get some idea of what has happened to potential real GDP growth in the US, the next graph shows the actual real GDP for the US (in $US billions) and two estimates of the potential GDP. There are many ways of estimating potential GDP given it is unobservable.

In this blog post – Common elements linking US and UK economic slowdowns (May 1, 2017) – I discussed estimates of potential GDP in the US and the shortcomings of traditional methods used by institutions such as the Congressional Budget Office.

So if you are interested please go back and review that discussion.

The latest CBO estimates, made available through – St Louis Federal Reserve Bank, show why we should be skeptical.

While I could have adopted a much more sophisticated technique to produce the red dotted series (potential GDP) in the graph, I decided to do some simple extrapolation instead to provide one base case.

The question is when to start the projection and at what rate. I chose to extrapolate from the most pre-GFC GDP peak (December-quarter 2007). This is a fairly standard sort of exercise.

The projected rate of growth was the average quarterly growth rate between 2001Q4 and 2007Q4, which was a period (as you can see in the graph) where real GDP grew steadily (at 0.65 per cent per quarter) with no major shocks.

If the global financial crisis had not have occurred it would be reasonable to assume that the economy would have grown along the red dotted line (or thereabouts) for some period.

The gap between actual and potential GDP (red dotted version) in the September-quarter 2020 is around $US3,377.3 billion or around 15.4 per cent.

The green dotted line is the estimate of potential output provided by the US Congressional Budget Office and suggests that the US economy is 3.5 per cent below potential GDP (as calculated by the CBO).

Note that prior to the pandemic, the CBO was estimating that the US economy was operating above its potential limits by 1.2 points (in the December-quarter 2019).

They considered the economy had been operating at over-full capacity since the March-quarter 2018.

It is hard to believe the estimate!

Why?

1. Inflation has shown no signs of accelerating.

2. Inflationary expectations declined over that period.

The following graphs are compiled using the Cleveland Federal Reserve Bank’s – Inflation Expectations data.

The first graph shows the expected price inflation for the next 12 months and for the next 10 years from 1985 to November 2020.

The second graph zooms in on the period one-quarter before the CBO estimated the US economy was ‘overheating’ (that is, producing more than its capacity).

Over that period the inflationary expectations have been trending down and well below 2 per cent, which is a benchmark the Federal Reserve uses to define price stability.

In other words, the market participants have no expectation that inflation is going to rise at all over the next year or over the ten-year period ahead.

Inflationary expectations are benign.

While it might take a few quarters for an over-capacity economy to ‘heat up’, it doesn’t make any sense for the market to systematically believe that inflation will continue to spiral downwards at the same time the economy is operating at more than 1 percentage point above its potential.

3. The US Federal Reserve Open Market Committee (FOMC) probably bought some of the OBS kool-aid and started hiking rates in December 2016. There were 8 subsequent increases before they worked out the economy was not overheating at all and they quickly cut the rate to 0.25 per cent (cutting 2 points).

They had already cut it three times before the pandemic hit.

4. While the unemployment fell to levels not seen since the 1960s, the broader measures of labour underutilisation indicated there was still considerable slack.

Even though the official unemployment rate has been relatively low, the question to ask is this: How much lower would the unemployment rate and the broader underutilisation rate go if the US federal government offered a Job Guarantee on an unconditional basis?

I would bet the answer would be much lower without any inflation acceleration emerging.

The flat wages growth supports that interpretation.

The only group that enjoyed significant wages growth has been at the top-end of the wage distribution (95th percentile and beyond).

The bottom percentiles have barely seen any growth and certainly not sufficient to think of the last few years as being an overheating economy.

Taken together, all the usual indicators suggest that the CBO output gap estimates are inaccurate – probably by several percentage points.

And that inaccuracy is a direct function of the way they define potential GDP and integrate the NAIRU into the estimation process.

We know (and I explain this in more detail in the blog post mentioned above), the CBO base their estimate of Potential GDP on their estimate of the NAIRU – the (unobservable) Non-accelerating Inflation Rate of Unemployment.

This is a conceptual unemployment rate that is consistent with a stable rate of inflation.

The literature demonstrates that the history of NAIRU estimation is far from precise. Studies have provided estimates of this so-called ‘full employment’ unemployment rate as high as 8 per cent or as low as 3 per cent all at the same time, given how imprecise the methodology is.

The former estimate would hardly be considered ”high rate of resource use”. Similarly, underemployment is not factored into these estimates.

The continued slack in the labour market (bias towards low-pay and high underemployment) would lead to the conclusion that the output gap is likely to be somewhat closer to the extrapolated estimate (red dotted line) than the CBO estimate.

However, while the red dotted line may have had some validity as a guide to potential output in the early part of the GFC, it is also clear that with the poor investment response during the GFC that the true potential GDP has fallen off that trend and lies somewhere between the CBO estimate and the crude extrapolation (red dotted line).

Think about the period between 2017 and 2018.

GDP growth steadied after its long recovery and a new trend looked like emerging before the pandemic.

If we extrapolate from that point, based on the average growth from the December-quarter 2015 to the December-quarter 2019 (0.57 per cent per quarter growth, which was below the pre-GFC trend of 0.65 per cent) out to the September-quarter 2020, we get a new line denoted by the red line in the next graph.

You can see that it lies above the CBO potential GDP estimates and closer to but well below the red dotted line (which is not shown here).

The estimated output gaps then – as at September-quarter 2020 – are:

1. Red dotted line – 15.4 per cent.

2. Red line – 5.1 per cent.

3. CBO official – 3.5 per cent.

4. Jobs gap method (see below) – 6.6 per cent.

I would suspect that the truth is somewhere between 1 and 2 but much closer to 4.

The US jobs deficit and the output gap

I updated the participation shifts due to ageing this morning to allow us to decompose the shift in participation into cyclical components and ageing population component.

As the population ages, and older workers have lower participation rates, the aggregate participation rate, which is a weighted average of the individual age cohort participation rates, falls – not because the individual age cohort rates change but that there are more workers in the total with lower rates.

That is, some of the drop in US participation rates over the last 2 decades is due to a compositional effect rather than a cyclical effect (the latter captures workers dropping out of the labour force temporarily when they stop searching as a result of the lack of job opportunities).

My detailed analysis which I will write up in another blog post some time later shows that about 66 per cent of the decline in the participation rate since April 2000 is due to these compositional shifts and 33.8 per cent is due to the economic cycle (output below potential).

The current participation rate of 61.5 per cent is a long way below the most recent peak in January 2007 of 66.4 per cent.

Adjusting for the demographic effect would give an estimate of the participation rate in November 2020 of 65.3 per cent if there had been no cyclical effects.

To compute the job gaps, a ‘full employment’ benchmark of 3.5 per cent is used – which was the low-point rate rate achieved in December 2019 before the pandemic.

I explain in this blog post – US labour market – strengthened in February but still not at full employment (April 13, 2018).

Using the estimated potential labour force (controlling for declining participation), we can compute a ‘necessary’ employment series which is defined as the level of employment that would ensure on 3.5 per cent of the simulated labour force remained unemployed.

This time series tells us by how much employment has to increase in each month (in thousands) to match the underlying growth in the working age population to maintain the 3.5 per cent unemployment rate benchmark.

In the blog post cited above (US labour market – strengthened in February but still not at full employment), I provide more information and analysis on the method.

There are two separate effects:

  • The actual loss of jobs between the employment peak in December 2019 and November 2020 is 9,071 thousand jobs.
  • The shortfall of jobs (the overall jobs gap) is the actual employment relative to the jobs that would have been generated had the demand-side of the labour market kept pace with the underlying population growth and the participation rate adjusted for ageing. This shortfall loss amounts to 5,711 thousand jobs.
  • The total jobs gap is thus 14,782 thousand.

This gives another perspective on what the output gap might be.

We can estimate the extra output that would be forthcoming if these workers were engaged as the current potential by multiplying the jobs gap by the average average productivity per person employed.

The aggregate average productivity is likely to overstate the actual productivity gain from the workers who are currently without work given they typically work disproproportionately in the lower paying jobs I adjust the average productivity to be only 70 per cent of the economy-wide average.

Using that benchmark we get an output gap in the September-quarter of 6.6 per cent.

The $US900 billion package

The stimulus package that the President has signed is included in the – Consolidated Appropriations Act 2021 (all 5,600 pages of it).

Distilling the essential features leads to this summary (which may not be perfect):

1. $US286 billion in direct aid comprising $US600 cheques means-tested (those earning below $US75,000 annually) and weekly unemployment assistance of $US300 per week for 11 weeks (to March 14, 2021).

The $US600 cheque outlays are to be capped at a total of $US166 billion.

2. $US325 billion for small business assistance, including $US284 in foregivable loans .

3. $US82 billion for assistance to help schools.

4. $US54 billion for public-health measures associated with contact tracing and vaccination.

5. $US45 billion for transportation – assisting airline payroll support and public transport.

6. $US25 billion in rental assistance.

7. $US13 billion for food-assistance (SNAP).

8. $US10 billion to help pre-school assistance, child-care.

9. $US15 billion to aid the arts sector (theatres, cinemas, music venues, etc).

10. $US10 billion to US Postal service.

11. $US7 billion to expand high-speed internet access to low-income families.

12. $US35 billion for development of wind, solar and other clean energy projects.

So the stimulus package is a mixture of individual transfers, government consumption expenditure, loans to businesses and transfers to state and local governments.

The composition is important because it has implications for the multiplier effects (see below).

With more than a third being in the form of loans to business, which may or may not be re-cycled into the spending stream, the direct injection from the package will be considerably lower than $US900 billion.

Further, as I pointed out in this blog post – Tax cuts are unlikely to work at present and are less effective than government spending increases (October 1, 2020) – the evidence from the cash handouts under the CARES Act (the first stimulus package) indicated that:

1. “Only 15 percent of recipients of this transfer say that they spent (or planned to spend) most of their transfer payment, with the large majority of respondents saying instead that they either mostly saved it (33 percent) or used it to pay down debt (52 percent).”

2. “U.S. households report having spent approximately 40 percent of their checks on average, with about 30 percent of the average check being saved and the remaining 30 percent being used to pay down debt.”

3. “Little of the spending went to hard-hit industries selling large durable goods (cars, appliances, etc.). Instead, most of the spending went to food, beauty, and other non-durable consumer products that had already seen large spikes in spending even before the stimulus package was passed because of hoarding.”

I provided more analysis in the blog post cited.

So it is questionable how much of the direct assistance via individual transfers will actually be spent, given the fact that American households are carrying excessive debt levels.

The fiscal multiplier

The next step is to think about the spending multiplier, which measures the impact on final output and income of a unit change in an injection of spending.

So, if the multiplier is 1.5, then a $1 injected into the spending stream, say, by government fiscal stimulus, will lead to a final increase in GDP of $1.50.

The value depends on the proportion of each extra income received that is spent on consumption, the tax rate structure and the extra dollars that leak out to import spending.

An extra dollar in the hands of a low-income worker is likely to be most spent whereas the same is not true for an extra dollar given to a high-income earner.

Further, during crises, when borrowing capacities fall and assets cannot be easily sold, the proportion increases.

Please read my blog post – Spending multipliers (December 28, 2009) – for more discussion on this point.

This recent ‘FRBSF Economic Letter’ published by the Federal Reserve Bank of San Francisco – The COVID-19 Fiscal Multiplier: Lessons from the Great Recession (May 26, 2020) – provides some interesting discussion of the likely multiplier effects of the COVID stimulus packages.

They note that the composition of the stimulus package influences the value of the multiplier:

1. Individual transfers – trigger high on-spending.

2. Government consumption – “the multiplier may be as high as 1.5 to 2.0”.

3. Transfers to state and local governments – “unlikely that states would use any of their federal transfer funds to finance tax cuts or pay down preexisting debt.”

Overall, they conclude that the multiplier is likely to be “near or above 1” which means that a fiscal stimulus will be expansionary.

They conclude that:

Overall, the evidence suggests that the output boost from the current fiscal response is likely to be large.

So is the $US900 billion too expansionary?

We now have some concept of how far the US economy is from its potential.

I might also project that the output gap will widen in the next quarter or so given the horrific state of the pandemic in the US.

A $US900 billion spending increasing would represent about 1.2 per cent of annual GDP.

There are two other uncertainties:

1. We do not know the time profile of when the spending will enter the spending stream.

2. We do not know how much of the $900 billion will enter the spending stream given the fact that a significant proportion of the CARES stimulus was saved or used to pay down debt and that more than a third of this stimulus package is in the form of loans.

What does an percentage output gap translate into billions?

1. 5.1 per cent is $US3,950 billion over a year.

2. 6.6 per cent is $US5,267 billion over a year.

3. CBO 3.5 per cent is $US2,684 billion over a year.

So even if all the $US900 billion entered the spending stream over 2021 and the CBO’s estimates of the output gap were accurate, there would be no likelihood that the stimulus (multiplied up) would drive the economy into a state of overheating (that is, exhausting its productive potential).

Clearly, given that the full $US900 billion is not going to enter the spending stream over 2021 and the output gap is likely to be closer to 6.6 per cent than the CBO’s estimate, then the fiscal space is clearly able to accommodate the $US600 payment and would also be able to accommodate the revised proposal for $US2,000 per eligible person.

Distributional matters

Which means there would also be scope to address the distributional anomalies that concern progressives within the current fiscal space (see my discussion in Part 1) without any offset fiscal measures to reduce the net spending injection.

That is the topic of another blog post though.

Conclusion

Larry Summers was not correct in his macroeconomic analysis and that is where the attacks should have begun.

I hope I have given a feel for how analysis of this type is an art form rather than an exact science.

There are assumptions, uncertainties, and complete unknowns that enter into the exercise, which ultimately has to be distilled down to a numbers game.

Some heterodox economists argue that because of the endemic uncertainty this sort of analysis is meaningless.

They overlook the fact that governments have to outlay dollars to motivate changes in the aggregates and so it is better to provide some numerical scope for what those outlays will deliver.

A good analysis also has an eye to sensitivity of settings, which I have demonstrated by considering the reasonable range of output gaps, for example.

Then you have to consider the consequences of error.

In this case, the consequences of not providing enough fiscal stimulus are much more significant than providing too much.

In the former case, a shortfall of spending will leave unemployment higher than otherwise necessary and sacrifice billions in foregone income.

The consequences of pushing spending a little more than is necessary is some price pressures, which are less destructive than unemployment and can be easily dealt with.

Happy New Year – as Victoria again closes its border to NSW after the latter has failed to deal with the latest virus numbers and spread the infection to Melbourne from Sydney.

More flights I had planned for tomorrow have just been cancelled.

2021 looking like 2020.

That is enough for today!

(c) Copyright 2020 William Mitchell. All Rights Reserved.

Is the $US900 billion stimulus in the US likely to overheat the economy – Part 1?

Published by Anonymous (not verified) on Wed, 30/12/2020 - 1:35pm in

Comments made last week by the former Clinton, Obama and now Biden economist Lawrence Summers contesting whether it was sensible for the US government to provide a $US2,000 once-off, means-tested payments was met with widespread derision and ridicule from progressive commentators. There were Tweets about eviction rates, bankruptcy rates, poverty rates, and more asserting that the widespread social problems in the US clearly meant that Summers was wrong and a monster parading as a progressive voice in the US debate. I didn’t see one response that really addressed the points Summers was making. They were mostly addressing a different point. In fact, the Summers statement makes for an excellent educational case study in how to conduct macroeconomic reasoning and how we need to carefully distinguish macro considerations from distributional considerations, even though the two are inextricably linked, a link that mainstream macroeconomics has long ignored. So while Summers might have been correct on the macro issues (we will see) he certainly wasn’t voicing progressive concern about the distributional issues and should not be part of the in-coming Administration. This is Part 1 of a two-part analysis. In Part 2 we will do some sums. In this part, we will build the conceptual base.

Two levels of analysis involved

Laurence Summers was interviewed by Bloomberg (December 24, 2020) – $2,000 Stimulus Checks Don’t Make Sense, Says Larry Summers.

I wrote about Summers in this blog post – Being shamed and disgraced is not enough (December 18, 2009).

My assessment of him has only deteriorated since.

He will occupy a senior economics position in the incoming US administration.

Pity America.

Here is the – (edited) transcript of the interview from Bloomberg:

… I don’t think the two thousand dollar checks make much sense. The real issue is going to be sustaining this expansion. Think about it. The nine hundred and eight stimulus bill probably would pay out two hundred two hundred and fifty billion dollars a month for the next three months.

The level of compensation is running about 30 billion dollars a month below what we would have expected it would. GDP is running about 70 billion dollars a month below what we would have expected it would. So in a way that’s quite unprecedented. We have stimulus already much more than filling out a hole.

And given that lots of a hole is from the fact not that people don’t want to spend but that they can’t spend because they can’t take a flight and they can’t go to a restaurant.

I don’t necessarily think that the priority should be on promoting consumer spending beyond where we are now. So I’m not even sure that I’m so enthusiastic about the six hundred dollar checks. And I think taking them to two thousand dollars would actually be a pretty serious mistake that would risk a temporary overheat.

I would like to see more assistance to state and local governments. I would like to see more money put into testing more money put into accelerating of vaccines.

But gosh David I think it would be a real mistake to be going to two thousand dollars. And I have to say that when you see the two extremes agreeing you can almost be certain that something crazy is in the air. And so when I see a correlation of Josh and Bernie Sanders and Donald Trump getting in behind that idea I think that’s time to run for cover.

And I know that many of my fellow Keynesians who believe in fiscal stimulus will likely be in favor of this. But sometimes there can be too much too poorly designed of even a basically good idea. And that’s my reaction to two thousand dollar stimulus …

Almost as soon as the interview was made public, progressives went wild.

They pointed out the harm done by COVID to workers and their families, the impending rent eviction maelstrom, the rising mortgage defaults, and all sorts of other social pathologies that are threatening social stability in the US and have been increasing over the last several decades.

The problem is that these responses didn’t really address the issue that Summers was making.

The critics were largely constructing their claims in terms of Summers being a heartless so-and-so who didn’t have a progressive bone in his body and was just reverting to form (of the type I discussed in the blog post linked to above).

I have sympathy with that assessment of the man.

But in doing, the critics failed to contest the actual point he was making – a macroeconomic point.

There were thus two levels of analysis at work:

1. A macro analysis of output gaps (Summers).

2. A distributional assessment of how existing resources and income is distributed in the US (the critics)

Summers might be correct on (1) but sadly lacking on (2).

We need to carefully separate the arguments.

Lawrence Summers was making a macroeconomic point that simply is this.

1. We define potential output where all productive resources are fully employed and no further output can be produced

2. An output gap forms when the current level of spending in the economy drives output below the potential level. This is an indication of how much extra spending is required, taking into account the multiplier effets that follow spending injections, to move the economy back to potential.

3. Driving spending growth beyond that full employment capacity will probably introduce demand-pull inflationary pressures as firms exhaust their capacity to produce and respond to the increasing spending demand by pushing up prices.

So Summers believed that the $US900 stimulus alone would threaten that limit.

Adding another $US1,400 to the cash handout would, in his view, push the economy past the limit.

That assertion is empirically testable (see below) although the frameworks we use to conduct that sort of analysis is ridden with conceptual and measurement problems which means that we are doing art rather than science.

But within the notion of ‘ball park’ estimates, we can make some statements that bear on whether Summers was correct in his analysis.

However, and this is the important point – there is no guarantee that at full capacity, the well-being of the people, the fortunes of the least privileged, the scope and quality of government services, etc – will be at any levels considered desirable.

At the extreme, a nation could be producing all sort of military equipment and all the workers and productive capital fully employed, but with the majority living in abject poverty.

The output gap might be zero – but the society is devastated by poverty and disease.

So within that spending room, there is a debate that to be had about what initiatives are best – so Summers favoured health care and assistance to sub-federal governments rather than a $US2,000 cash handout.

I found that part of his assessment disclosed his own preferences, which progressives might find rather offensive, but doesn’t make him wrong.

So here are some deeper considerations.

The NAIRU redux

The following blog posts cover past writing on the NAIRU:

1. The NAIRU/Output gap scam reprise (February 27, 2019).

2. The NAIRU/Output gap scam (February 26, 2019).

3. No coherent evidence of a rising US NAIRU (December 10, 2013).

4. Why we have to learn about the NAIRU (and reject it) (November 19, 2013).

5. Why did unemployment and inflation fall in the 1990s? (October 3, 2013).

6. NAIRU mantra prevents good macroeconomic policy (November 19, 2010).

7. The dreaded NAIRU is still about! (April 6, 2009).

I also have written books, PhD theses and many Op Eds about this topic.

Here is a summary of the Non-NAIRU facts which taken together provide strong evidence against the dynamics implied by the NAIRU approach:

  • Unemployment rates exhibit high degrees of persistence to shocks.
  • The dynamics of the unemployment rate exhibit sharp asymmetries over the economic cycle. The unemployment rate rises quickly and sharply when overall spending (demand) contracts but persists and falls slowly when expansion occurs.
  • Inflation dynamics do not seem to accord with those specified in the NAIRU hypothesis.
  • The constant NAIRU concept (the earliest form of the assertion) was abandoned and replaced by so-called Time-varying-NAIRUs, which became just another ad hoc fudge to try to get the concept to fit the data.
  • All NAIRU estimates have large standard errors, which make them all but meaningless for policy analysis. The majority of econometric models developed to estimate the NAIRU are misspecified and deliver very inaccurate estimates of the NAIRU. Most of the research output confidently asserted that the NAIRU had changed over time but very few authors dared to publish the confidence intervals around their point estimates.
  • Estimates of steady-state unemployment rates are cyclically-sensitive (hysteretic) and thus the previously eschewed use of fiscal and monetary policy to attenuate the rise in unemployment has no conceptual foundation.
  • There is no clear correlation between changes in the inflation rate and the level of unemployment, such that inflation rises and falls at many different unemployment rates without any systematic relationship evident.
  • The use of univariate filters (Hodrick-Prescott filters) with no economic content and Kalman Filters with little or no economic content has rendered the NAIRU concept relatively arbitrary. Kalman Filter estimates are extremely sensitive to underlying assumptions about the variance components in the measurement and state equations. Small signal to noise ratio changes can have major impacts on the measurement of the NAIRU. Spline estimation is similarly arbitrary in the choice of knots and the order of the polynomials.
  • In the end, the NAIRU estimates are just some smoothed trend of the actual unemployment rate and provide no additional informational content.

Consider the following graph, which uses data from the March-quarter 1950 to the December-quarter 2020 (the last observation is the average for October and November 2020).

The blue line is the is the gap between the actual unemployment rate (UR) and the CBO estimate of the NAIRU (long-term) while the grey bars are the change in the inflation rate.

We would expect, if the NAIRU framework provided any predictive capacity, that when the gap was positive, that is, the actual unemployment rate is above the NAIRU, that the inflation rate would be falling and vice versa.

There might be some lags in this relationship but we should be able to detect a fairly systematic relationship over time.

There is no such relationship.

Another way of seeing this more clearly is to consult the next graph which uses the same data but with the horizontal axis depicting the gap between the actual unemployment rate (UR) and the CBO estimate of the NAIRU (long-term) and the vertical axis taking the value of 1 if the inflation rate is falling and zero if it is rising.

We should expect the zeros to be mostly to the right of the zero line on the horizontal axis and the ones to be to the left of the zero line.

The distribution of the observations is nothing like that.

The output gap redux

I started with the NAIRU because it has been widely used to define full capacity utilisation. If the economy is running an unemployment equal to the estimated NAIRU then mainstream economists conclude that the economy is at full capacity.

Of-course, they kept changing their estimates of the NAIRU which were in turn accompanied by huge standard errors. These error bands in the estimates meant their calculated NAIRUs might vary between 3 and 13 per cent in some studies which made the concept useless for policy purposes.

But they still persist in using it because it carries the ideological weight – the neo-liberal attack on government intervention.

But the point here is that the NAIRU estimates are tied in with estimates of the Output Gap, which is the difference between potential and actual GDP at any point in time.

As I note in this blog – Structural deficits and automatic stabilisers (November 29, 2009) – the problem is that the estimates of output gaps are extremely sensitive to the methodology employed.

It is clear that the typical methods used to estimate the unobservable Potential GDP reflect ideological conceptions of the macroeconomy, which are problematic when confronted with the empirical reality.

For example, on Page 3 of the US Congressional Budget Office document – Measuring the Effects of the Business Cycle on the Federal Budget – we read:

… different estimates of potential GDP will produce different estimates of the size of the cyclically adjusted deficit or surplus …

The CBO is representative in the way they seek to estimate Potential GDP.

They explain their methodology in this document.

Effectively, the estimated NAIRU is front and centre, so Potential GDP becomes the level of GDP where the unemployment rate equals some estimated NAIRU.

It becomes a self-serving circularity.

Potential GDP is not to be taken as being the output achieved when there is full employment.

Rather, it is the output that would be forthcoming at the unobservable NAIRU. If the estimates of the NAIRU are flawed, then so will the result output gap measures.

The problem is that policy makers make assessments of their current fiscal position based on these artificial, (assumed) cyclically invariant benchmarks.

And, because the estimates of the NAIRU are typically ‘inflated’ (well above what the true full employment unemployment rates are), the conclusion is always that the current discretionary fiscal policy stance is too expansionary (because their methods understate the cyclical component).

Which then means that in recessions, the output gap estimates will be too small, and the extra net government spending that is advocated will subsequently also be too small.

As we saw during the GFC, the more extreme misuse of these under-estimated output gaps provokes the austerity bias – cutting discretionary spending or increasing taxes (mostly the former) when, the reality of the situation is usually indicating the opposite is required.

New Keynesians talk of ‘deficit biases’, when in fact their framework leads to ‘austerity biases’ and elevated levels of mass unemployment and resulting income (production) losses persisting for long periods.

Conclusion

The first problem then is assessing what the output gap actually is.

In Part 2, some arithmetic will be forthcoming.

That is enough for today!

(c) Copyright 2020 William Mitchell. All Rights Reserved.

US labour market deteriorating – health and economic policy failures

Published by Anonymous (not verified) on Mon, 07/12/2020 - 10:55am in

Tags 

US economy

Last month, I noted that with the virus infections in the US increasing rapidly and renewed lockdowns almost inevitable combined with the lack of fiscal support from government, labour market conditions would probably deteriorate in November. I thought the US faced an uncertain and pessimistic future. The latest data reveals that assessment was accurate. On December 4, 2020, the US Bureau of Labor Statistics (BLS) released their latest labour market data – Employment Situation Summary – November 2020 – which reveals a deteriorating situation. Employment growth has slowed dramatically and participation fell by 0.2 points, which is the only reason that the unemployment rate fell by 0.2 points. Once we take into account the decline in the labour force, we realise that the fall in unemployment is illusory – it just means that workers who would normally be considered unemployed are now being classified as outside the labour force (that is, as hidden unemployed). The impasse at Congress on the the size and design of the next tranche of fiscal support is not helping. And then the data shows the lax health policy is allowing the virus to run out of control and how that plays out is anyone’s guess. I suspect a nation has to get the health problem sorted before they can really sort out the economic problem. The US appears to be going in the opposite direction to that. I doubt it will turn out well.

Overview for November 2020:

  • Payroll employment rose by 245,000 (slowing dramatically).
  • Total labour force survey employment rose by 2,243 thousand net (0.05 per cent).
  • The seasonally adjusted labour force fell by 400 thousand (0.25 per cent).
  • Official unemployment fell by 326 thousand to 10,735 thousand
  • The official unemployment rate fell by 0.2 points to 6.7 per cent.
  • The participation rate fell by 0.2 points to 61.5 per cent.
  • The broad labour underutilisation measure (U6) fell by 0.1 points to 12 per cent, as the part-time for economic reasons cohort (the US indicator of underemployment) fell by 23 thousand (0.3 per cent).

For those who are confused about the difference between the payroll (establishment) data and the household survey data you should read this blog post – US labour market is in a deplorable state – where I explain the differences in detail.

BLS explanation

The BLS provided a special note to help us understand the results this month.

We learn:

1. “The collection rate for the establishment survey was 74 percent in November, about the same as the average for the 12 months ending in February 2020.”

2. “The household survey response rate was 79 percent in November, considerably higher than the low of 65 percent in June but below the average of 83 percent for the 12 months ending in February 2020”

3. Both results reduce the accuracy of the surveys.

4. In the payroll survey:

… workers who are paid by their employer for all or any part of the pay period including the 12th of the month are counted as employed, even if they were not actually at their jobs. Workers who are temporarily or permanently absent from their jobs and are not being paid are not counted as employed, even if they continue to receive benefits.

5. In the Labour Force survey:

… individuals are classified as employed, unemployed, or not in the labor force based on their answers to a series of questions about their activities during the survey reference week (November 8th through November 14th). Workers who indicate they were not working during the entire survey reference week and expect to be recalled to their jobs should be classified as unemployed on temporary layoff. As in recent months, a large number of persons were classified as unemployed on temporary layoff in November.

The BLS wanted the latter group classified as unemployed for consistency but the survey staff didn’t always comply, which means that the employment estimates are probably overstated.

What impact might this have had?

The BLS say:

… the share of responses that may have been misclassified was highest in the early months of the pandemic and has been considerably lower in recent months.

For March through October, BLS published an estimate of what the unemployment rate would have been had misclassified workers been included among the unemployed. Repeating this same approach, the overall November unemployment rate would have been 0.4 percentage point higher than reported. However, this represents the upper bound of our estimate of misclassification and probably overstates the size of the misclassification error.

So we are still operating in an environment of uncertainty but the data accuracy has increased.

Once these classification issues are resolved, the participation response becomes more normal (workers coming back into the labour force), and the number of jobs lost forever becomes apparent, the true residual impact of the pandemic on the US labour market will become clearer.

Payroll employment trends

The BLS noted that:

Total nonfarm payroll employment rose by 245,000, following gains of larger magnitude in the prior 6 months. In November, nonfarm employment was below its February level by 9.8 million, or 6.5 percent. Notable job gains occurred over the month in transportation and warehousing, professional and business services, and health care. Employment declined in government and retail trade.

It is clear that the US cannot continue with a no lockdown approach with the virus spiralling out of control, hospitals becoming overcrowded and the death rate rising to unimaginable levels.

Several states are now starting to reimpose lockdowns and the labour market will deteriorate as a consequence.

That is evident by the loss of 35 thousand jobs in the retail trade sector as the previous seasonal hiring dries up.

The other worry is that:

Government employment declined for the third consecutive month, decreasing by 99,000 in November. A decline of 86,000 in federal government employment reflected the loss of 93,000 temporary workers who had been hired for the 2020 Census. Employment in local government education continued to trend down (-21,000).

That signals a failure of the policy response.

The first graph shows the monthly change in payroll employment (in thousands, expressed as a 3-month moving average to take out the monthly noise). The gray lines are the annual averages.

The data swings are still large and dwarf the past history.

Clearly, the 20.7 million job loss in April has not yet been reversed. Given the loss of payroll jobs in March and April, the US labour market is still 10.1 million jobs short from where it was at the end of February.

The next graph shows the same data in a different way – in this case the graph shows the average net monthly change in payroll employment (actual) for the calendar years from 1940 to 2020 (the 2020 average is for the months to date).

I usually only show this graph from 2005 but because history is being created at present I included the full sample available from 1940.

The final average for 2019 was 178 thousand.

The average so far for 2020 is -852 thousand.

Labour Force Survey – employment growth negative

The data for September reveals that the labour market is now going backwards in the US.

1. Employment as measured by the household survey fell by 74 thousand net (0.05 per cent).

2. The labour force fell by 400 thousand (0.25 per cent).

3. The participation rate fell by 0.2 points.

4. As a result (in accounting terms), total measured unemployment fell by 326 thousand and the unemployment rate fell by 0.2 points to 6.7 per cent.

Taken together this is a poor outcome, even though unemployment fell.

It fell because more people dropped out of the active labour force as employment opportunities declined.

The following graph shows the monthly employment growth since January 2008, which shows the massive disruption this sickness has caused.

The Employment-Population ratio is a good measure of the strength of the labour market because the movements are relatively unambiguous because the denominator population is not particularly sensitive to the cycle (unlike the labour force).

The following graph shows the US Employment-Population from January 1950 to November 2020.

While the ratio fluctuates a little, the April 2020 ratio fell by 8.7 points to 51.3 per cent, which is the largest monthly fall since the sample began in January 1948.

In November 2020, it fell by 0.1 points to 57.3 per cent.

It is still well down on the level in January 2020 (61.2 per cent).

As a matter of history, the following graph shows employment indexes for the US (from US Bureau of Labor Statistics data) for the five NBER recessions since the mid-1970s and the current 2020-COVID crisis.

They are indexed at the employment peak in each case and we trace the data out for each episode until one month before the next peak.

So you get an idea of:

1. The amplitude (depth) of each cycle in employment terms.

2. The length of the cycle in months from peak-trough-peak.

The early 1980s recession was in two parts – a short downturn in 1981, which was followed by a second major downturn 12 months later in July 1982 which then endured.

Other facts:

1. Return to peak for the GFC was after 78 months.

2. The previous recessions have returned to the 100 index value after around 30 to 34 months.

3. Even at the end of the GFC cycle (146 months), total employment in the US had still only risen by 8.3 per cent (since December 2007), which is a very moderate growth path as is shown in the graph.

The current collapse is something else and progress has now gone into reverse.

Unemployment and underutilisation trends

The BLS report that:

In November, the unemployment rate edged down to 6.7 percent. The rate is down by 8.0 percentage points from its recent high in April but is 3.2 percentage points higher than it was in February. The number of unemployed persons, at 10.7 million, continued to trend down in November but is 4.9 million higher than in February.

The official unemployment rate declined in November 2020 largely because the labour force shrunk by a greater amount than the contraction in employment – a bad coincidence.

The first graph shows the official unemployment rate since January 1994.

The official unemployment rate is a narrow measure of labour wastage, which means that a strict comparison with the 1960s, for example, in terms of how tight the labour market, has to take into account broader measures of labour underutilisation.

The next graph shows the BLS measure U6, which is defined as:

Total unemployed, plus all marginally attached workers plus total employed part time for economic reasons, as a percent of all civilian labor force plus all marginally attached workers.

It is thus the broadest quantitative measure of labour underutilisation that the BLS publish.

In December 2006, before the effects of the slowdown started to impact upon the labour market, the measure was estimated to be 7.9 per cent.

In November 2020 the U6 measure decreased by 0.1 points to 12 per cent.

What drove this decline in U6?

The BLS say that:

The number of persons employed part time for economic reasons was about unchanged over the month at 6.7 million but remains 2.3 million higher than the February level …

In November, the number of persons not in the labor force who currently want a job increased by 448,000 to 7.1 million; this measure is 2.2 million higher than in February. These individuals were not counted as unemployed because they were not actively looking for work during the last 4 weeks or were unavailable to take a job …

Among those not in the labor force who currently want a job, the number of persons marginally attached to the labor force, at 2.1 million, changed little in November. These individuals wanted and were available for work and had looked for a job sometime in the prior 12 months but had not looked for work in the 4 weeks preceding the survey. The number of discouraged workers, a subset of the marginally attached who believed that no jobs were available for them, was 657,000 in November, little changed from the previous month.

Ethnicity and Education

The next graph shows the evolution of unemployment rates for three cohorts based on educational attainment: (a) those with less than high school completion; (b) high school graduates; and (c) university graduates.

As usual, when there is a crisis, the least educated suffer disproportionately.

In the collapse in employment, the unemployment rates rose by:

  • 14.4 points for those with less than high-school diploma.
  • 12.9 points for high school, no college graduates.
  • 5.9 points for those with university degrees.

The bounce back since April 2020 has seen the unemployment rate fall by:

  • 12.2 points for those with less than high-school diploma meaning the unemployment rate is now 3.8 points above the March level.
  • 9.6 points for high school, no college graduates meaning the unemployment rate is now 4.6 points above the March level.
  • 4.2 points for those with university degrees meaning the unemployment rate is now 2.3 points above the March level.

In the last month, the change in the unemployment rate has been:

  • -0.8 points points for those with less than high-school diploma.
  • -0.4 points for high school, no college graduates meaning the unemployment rate.
  • 0 points for those with university degrees meaning the unemployment rate.

In the US context, especially in the current time, the trends in trends in unemployment by ethnicity are interesting.

Two questions arise:

1. How have the Black and African American and White unemployment rate fared in the post-GFC period?

2. How has the relationship between the Black and African American unemployment rate and the White unemployment rate changed since the GFC?

Summary:

1. All the series move together as economic activity cycles. The data also moves around a lot on a monthly basis.

2. The Black and African American unemployment rate was 6.7 per cent in March 2020, rose to 16.8 per cent in May and is now down to 10.3 per cent in November 2020.

3. The Hispanic or Latino unemployment rate was 6 per cent in March 2020, rose to 18.9 per cent in April and fell to 8.4 per cent in November 2020.

4. The White unemployment rate was 4 per cent in March 2020, rose to 14.2 per cent in April and fell to 5.9 per cent in November 2020.

The next graph shows the Black and African American unemployment rate to White unemployment rate (ratio) from January 2018, when the White unemployment rate was at 3.5 per cent and the Black or African American rate was at 7.5 per cent.

This graph allows us to see whether the relative position of the two cohorts has changed since the crisis. If it is rising, then the unemployment rate of the Black and African American cohort is either rising faster than the white unemployment rate or falling more slowly (or a combination of that relativity).

While there is month-to-month variability, the data shows that, in fact, through to mid-2019, the position of Black and African Americans had improved in relative terms (to Whites), although that just reflected the fact that the White unemployment was so low that employers were forced to take on other ‘less preferred’ workers if they wanted to maintain growth.

In April 2019, the ratio was 2.1 (meaning the Black and African American unemployment rate was more than 2 times the White rate).

By April 2020, the ratio had fallen to its lowest level of 1.2, reflecting the improved relative Black and African American position.

As the pandemic hit, the ratio rose and peaked at 1.8 in August 2020, but fell to 1.7 in September, reflecting an improvement in the relative position of the Black and African American workers.

In November, the ratio was 1.7.

Aggregate participation rate – fell by 0.2 points to 61.5 per cent

What is the impact of that decline for the actual unemployment situation?

We can make two comparisons:

1. Compare the November 2020 with the March 2020 state.

2. Compare the changes in the last month.

The labour force is a subset of the working-age population (those above 15 years old). The proportion of the working-age population that constitutes the labour force is called the labour force participation rate. Thus changes in the labour force can impact on the official unemployment rate, and, as a result, movements in the latter need to be interpreted carefully. A rising unemployment rate may not indicate a recessing economy.

The labour force can expand as a result of general population growth and/or increases in the labour force participation rates.

The following Table decomposes these effects and summarises the relevant aggregates:

1. The labour force in November 2020 was 160,467 thousand.

2. The labour force has shrunk by 400 thousand in the last month as a result of the 0.2 points fall in the labour force participation over that period.

3. If we assume those workers are hidden unemployed – they want to work, are willing to work, but did not actively seek work – and add them back into the official unemployment, the adjusted unemployment rate in November 2020 would be 6.99 per cent rather than the official estimate of 6.7 per cent.

4. Since March 2020, the labour force has contracted by 2,446 thousand as a result of the 1.2 points fall in the labour force participation over that period.

5. If we assume those workers are hidden unemployed – they want to work, are willing to work, but did not actively seek work – and add them back into the official unemployment, the adjusted unemployment rate in November 2020 would be 8.5 per cent rather than the official estimate of 6.7 per cent.

That gives a very different picture of how well the US labour market is recovering from the crisis and with the virus numbers still very high and with winter approaching, the immediate future does not look good.

Conclusion

The November 2020 US BLS labour market data release reveals that the improvement that the US has seen since the catastrophic labour market collapse in March and April has gone into reverse.

The payroll data suggests the pace of recovery is slowing, whereas the labour force data has recorded a reversal.

It is clear that the US cannot continue with a no lockdown approach with the virus spiralling out of control, hospitals becoming overcrowded and the death rate rising to unimaginable levels.

Several states are now starting to reimpose lockdowns and the labour market will deteriorate as a consequence.

That is evident by the loss of 35 thousand jobs in the retail trade sector as the previous seasonal hiring dries up.

Total (net) jobs lost in the government sector was 99 thousand in November.

It doesn’t make sense in a massive crisis for government employment to be falling.

The delays in extra US government assistance are not helpful and perhaps with the political situation less uncertain (for most) the Congress will resolve the impasse.

That is enough for today!

(c) Copyright 2020 William Mitchell. All Rights Reserved.

Why improve policy when a government can pillory a low-paid, precarious worker instead

Published by Anonymous (not verified) on Mon, 23/11/2020 - 1:47pm in

Tags 

US economy

Last week we saw further evidence of the way in which class divisions create havoc for society although the way these events have been constructed in the media and popular perception are the antithesis of what was really going on. After having no coronavirus cases since April 16, 2020, suddenly we were informed on Sunday, November 15, 2020, that a dangerous virus cluster had emerged in South Australia (in particular the capital Adelaide) as a result of a breach in quarantine. The memories of Victoria’s second wave, which had started as a result of a similar breach came flooding back and the South Australian state government almost immediately imposed a very harsh 6-day lockdown (the most restrictive imaginable). The following day, amidst all the furore about the severity of the restrictions, the Government announced they were rescinding the orders (mostly). Why? Because some foreign worker had contracted the virus had lied to investigators about his status and was, in fact, working at both the quarantine hotel where the breach occurred and a pizza shop were additional cases had been detected. Apparently this ‘lie’ led to the severe lockdown because it created some uncertainty in transmission links. I doubt that was the case and I think the Government just overreacted and lacked confidence in their own systems. But now it is the ‘lie’ that everyone is focusing on and the Premier is threatening to ‘throw the book’ at the individual. Not many questions are being asked in the media about the poor systems that led to the breach in the first place nor the overreaction of the government. All attention is being focused on a casualised, precarious worker who was forced to work (at least) two jobs to survive. There lies the issue.

I have been reading the research output that is starting to come out linking the incidence of Covid-19 and the resulting deaths to socio-economic status.

There are numerous studies which support the conclusion that individuals from the more disadvantaged socioeconomic groups endure worse health (mental and physical), higher rates of illness and disability, and, die earlier than those from better-off backgrounds.

This phenomenon is referred to as the ‘social gradient of health’, which the World Health Organization defined as (Source):

The poorest of the poor, around the world, have the worst health. Within countries, the evidence shows that in general the lower an individual’s socioeconomic position the worse their health. There is a social gradient in health that runs from top to bottom of the socioeconomic spectrum. This is a global phenomenon, seen in low, middle and high income countries. The social gradient in health means that health inequities affect everyone.

So during a pandemic such as we are living through at present, this phenomenon has intensified.

An interesting US-study published on June 15, 2020 – Poverty and Covid-19: Rates of Incidence and Deaths in the United States During the First 10 Weeks of the Pandemic – by W. and M. Finch, sought to examine how poverty incidence intersected with Covid-19 incidence and death.

They found an interesting evolution of the virus incidence:

… that during the early weeks of the pandemic more disadvantaged counties in the United States had a larger number of confirmed Covid-19 cases, but that over time this trend changed so that by the beginning of April, 2020 more affluent counties had more confirmed cases of the virus.

This indicates that ultimately communities are interlinked in various ways, and, while the better-off citizens can insulate themselves from the rest in many ways, ultimately, they too become vulnerable in a disaster of this scale.

However, as the pandemic ensued “the number of deaths was greater in areas of relatively greater poverty”:

Furthermore, a larger number of deaths was associated with a larger percent of county residents living in poverty, living in deep poverty, a higher incidence of low weight births, and with the county being designated as urban.

So while, eventually, the better-off neighbourhoods experienced sickness, they were able to access superior health care which reduced the death rate.

However, the authors are clear that the data deficiencies (particularly poor testing rates in poorer communities) may be hiding the incidence in the more disadvantaged communities.

The Lerner Center for Public Health Promotion – at Syracuse University provides some interesting US-based data that is relevant.

One study (April 1, 2020) – Data Slice Issue Number 15 – found that:

… testing rates to date have been lower in states with higher percent black populations and higher poverty rates … For example, whereas the average COVID-19 testing rate in states with the lowest percent black populations (bottom 25th percentile of percent black) is 403.5 per 100,000 population, the average rate among states with the highest percent black populations (top 25th percentile) is only 206.4 per 100,000 population.

The reliance on public transport is also a factor.

This US study published in the Journal of Epidemiology and Community Health (Vol 69, Issue 12) – Associations between individual socioeconomic position, neighbourhood disadvantage and transport mode: baseline results from the HABITAT multilevel study – found that:

… the odds of using public transport were higher for white collar employees … members of lower income households … and residents of more disadvantaged neighbourhoods …

But attenuating that tendency for white collar workers was the increased capacity to ‘work from home’ during the pandemic, thus severing their reliance or propensity to be exposed to disease on public transport.

In the US context, the latest Bureau of Labor Statistics – America Time Use Survey – reveals that:

1. “24 percent of employed persons did some or all of their work at home”.

2. “Workers employed in management, business, and financial operations occupations (37 percent) and workers employed in professional and related occupations (33 percent) were more likely than those employed in other occupations to do some or all of their work from home on days they worked.”

3. “Among workers age 25 and over, those with an advanced degree were more likely to work at home than were persons with lower levels of educational attainment”.

The following graphic compiled by the BLS is telling.

These trends are mirrored elsewhere.

Research published by Roy Morgan Surveys for Australia on June 29, 2020 – Nearly a third of Australian workers have been ‘#WFH’ – shows that:

1. “There are also significant differences between people working in different industries. Over half of people working in Finance & Insurance (58%) and Public Administration & Defence (51%) have been working from home and just under half of those in Communications (47%).”

2. “Far less likely to be working from home are Australians working in more ‘hands-on’ industries. Fewer than one-in-six Australians working in Manufacturing (16%), Transport & Storage (15%), Agriculture (13%) or Retail (12%) have been working from home during the last few months.”

Then we have to also consider the lockdown bias across socioeconomic groups.

Amnesty International released an interesting report (June 24, 2020) – Europe: Policing the pandemic: Human rights violations in the enforcement of COVID-19 measures in Europe – provides another dimension to this issue.

They found that:

1. “The police enforcement of lockdowns disproportionately impacted poorer areas, which often have a higher proportion of residents from minority ethnic groups.”

2. “In Nice, nine predominantly working class and minority ethnic neighbourhoods were subjected to longer overnight curfews than the rest of the city.”

3. “police in London registered a 22 percent rise in stop and searches between March and April 2020. During that time the proportion of Black people who were searched rose by nearly a third.”

4. “During mandatory quarantines in Bulgaria over 50,000 Roma were cut off from the rest of the country and suffered severe food shortages.”

The gig economy and the ‘lying’ worker

I have wrote about this theme in several past blog posts including:

1. The coronavirus crisis is just exposing the failure of neoliberalism (May 12, 2020).

3. The coronavirus crisis – a particular type of shock – Part 2 (March 11, 2020).

4. We are all entrepreneurs now marching towards a precarious and impoverished future (June 4, 2019).

5. Why Uber is not a progressive development (August 16, 2016).

6. The New Economy cannot flourish with fiscal austerity (May 31, 2012).

An increasing numbers of workers now rely on precarious employment situations for their incomes.

They rely employment through apps without the normal protections, without proper pay, and so on.

Neoliberalism clearly subjugates human development and opportunity to the interests of profit.

It has created a ‘Just-in-Time’ culture in manufacturing, in work (the gig economy), in our personal finances (debt vulnerability) as part of the deliberate strategy to gain a greater share of national income for profits at the expense of workers.

Only 60 per cent of Australia’s workforce is engaged in full-time or permanent part-time employment.

The most recent ABS – Characteristics of Employment, Australia – data as at August 2019 (next release for 2020 is due in December) shows that there are around 25 per cent of workers without paid-leave entitlements, which in the Australian context is often an indicator of ‘casual’ status.

This ABC Fact Check (March 30, 2020) – COVID-19 has put jobs in danger. How many workers don’t have leave entitlements? – explores the data in some detail.

These workers are concentrated in industry sectors that have been severely impacted by the Covid-19 policy responses – hospitality, retail trade, tourism, cleaning, food services etc.

The sectors that enjoy much lower rates of casualisation also tend to have higher capacity for workers to work from home.

So the least-paid, most precarious workers are those that are less able to work from home.

Which brings us to the way the individual pizza worker in Adelaide has been pilloried by the politicians and the smug, well-paid health authories for apparently lying about his work status.

The South Australian premier claimed at his press conference last Friday where he announced the backdown on the severe lockdown, that:

To say I am fuming about the actions of this individual is an absolute understatement. The selfish actions of this individual have put our whole state in a very difficult situation. His actions have affected businesses, individuals, family groups and is completely and utterly unacceptable.

The reality is that while they can claim that the “selfish actions of an indvidual” may have led to the Government’s decision to invoke a rather harsh lockdown, the fact that a low-paid precarious worker found the need to ‘lie’ is an indication of a much larger issue in Australian society.

Policy makers have allowed a situation to develop where desperation rather than hope drives action.

First, they have deregulated the labour market to allow employers much more power.

Second, they allowed the wage setting bodies to reduce penalty rates for non-standard work in already low-paid occuptions.

Third, governments have been reluctant to offer income insurance (that is, pay wages) for workers who are forced into isolation and/or quarantine because they test positive or are a close contact to someone else who tests positive.

The incentives have not been provided to precarious workers to do the right thing by all of us to stay away from work and public transport.

It would have been so easy for the Federal government to implement as scheme offering 100 per cent income protection, which would have eliminated the incentive to evade the lockdown rules, resist testing and not disclose to contact teams the full details.

Once again this failure by government is an example of the myopia of neoliberalism.

See this blog post (among others) – The myopia of fiscal austerity (June 10, 2015).

Interestingly, the Victorian government did introduce a partial scheme in this regard, which helped. But it should have been implemented more generously and by the currency-issuing federal government.

Further, today (November 23, 2020), the Victorian Premier said that “the idea of providing paid sick or carer’s leave to workers had benefits beyond the lifespan of the pandemic” (Source).

He said:

The Commonwealth government are well aware of our views around insecure work and the fact that it’s neither fair nor safe. It’s neither profitable nor in any way sustainable. We can’t continue to ignore this as a nation. I don’t have those levers though.

QED.

Fourth, when the pandemic hit, the federal government refused to support financially more than a million casual workers, despite providing a wage subsidy to other workers. The workers excluded from the JobKeeper program were those who could not show a continuous work association with their employment over the last 12 months.

That, of course, was a deliberate policy choice to reduce government spending given they know that a characteristic of that segment of the labour market is a definite lack of on-going work.

Casual workers cycle between stints of precarious work and joblessness continually. At least a million workers were thus excluded.

Fifth, the South Australian government chose to put private, untrained security firms in charge of the quarantine hotels they have set up to provide a barrier between infected, returning travellers and the rest of us.

They clearly didn’t learn from Victoria, which made the same mistake that led to the second wage.

It turns out that a casual, untrained security guard at one of the hotels became ill with Covid-19. He also worker at a pizza bar as a second job.

The gig economy is characterised by workers having to work multiple jobs to make enough income to survive.

The data shows that more than 2.1 million workers in Australia (around 15.6 per cent) work in multiple jobs to make ends meet and that proportion is steadily rising (Source).

And these workers are concentrated in health care, social assistance, education and training, administration, accommodation and food services, and retail trade.

The usual suspects.

Women and migrants, who face discrimination in the labour market.

Survey evidence shows the motivation is “income stability”.

Another worker, who also was a casual guard at another quarantine hotel also contracted Covid-19 told the contract tracers that he had bought a pizza at a the shop the other infected worker worked.

The Government thus concluded (why? they don’t say) that the virus outbreak was very serious and they went into overdrive (read: overeaction), even banning people from exercising outdoors, which Victoria (with very bad second wave) resisted invoking for obvious physical and mental health reasons.

Then a day later, the Premier’s press conference. Egg on face. They had to blame someone.

So this second casual worker – low paid and precarious – had lied to them. He actually worked at the same pizza bar as the other guy rather than being a casual customer.

Lockdown revoked.

Police turn on the worker promising to throw the book at him.

Not only that, social media vigilantes announced a boycott of the pizza bar (the gutless heroes on Twitter and Facebook), which just happens to be located in one of Adelaide’s disadvantaged suburbs where deindustrialisation has impacted on employment and household income and many migrant workers live.

The Premier might feel happy about turning the savages on a low-paid, precarious worker but has refused to explain why they used casualised, untrained labour to oversee the security systems for the quarantine hotels, where the outbreak actually started.

The fact that the worker didn’t admit that he was working two jobs is one thing that might have thrown the investigation a little.

But using him in a high risk situation such as the quarantine arrangements, where he had to work two jobs to make ends meet is more the issue.

And why didn’t the government have a regular testing regime in place for such quarantine workers?

Silence from the authorities.

Conclusion

The pandemic is exposing many things about contemporary society.

But above all, it is showing us that the trend to the gig economy and increasing precarity of work is a danger to us all.

The problem is that there is scant regard among the policy makers to make changes that provide less vulnerability.

The South Australian government’s response is classic – blame the victim of a systemic crisis, created by – government.

That is enough for today!

(c) Copyright 2020 William Mitchell. All Rights Reserved.

US labour market data – an uncertain and pessimistic future

Published by Anonymous (not verified) on Mon, 09/11/2020 - 11:42am in

Tags 

US economy

On November 6, 2020, the US Bureau of Labor Statistics (BLS) released their latest labour market data – Employment Situation Summary – October 2020 – which shows that employment continues to grow, but will take a long time at this rate to make up the job losses incurred in March and April. Further, the unemployment rate fell by 1 point to 6.9 per cent and the participation rate rose by 0.3 points. So, on the face of it, this is a positive outcome – jobs growth, participation increasing and unemployment falling. There is some doubt about the strength of the labour force employment estimates but the payroll data also shows steady employment increases. Worrying trends were in the loss of government employment, particularly at the state and local government level. Those losses will worsen if there is no extra fiscal support applied at that level by the federal government. The impasse at Congress on the the size and design of the next tranche of fiscal support is not helping. And then the data shows the lax health policy is allowing the virus to run out of control and how that plays out is anyone’s guess. I suspect a nation has to get the health problem sorted before they can really sort out the economic problem. The US appears to be going in the opposite direction to that. I doubt it will turn out well.

Overview for October 2020:

  • Payroll employment rose by 638,000 (slowing).
  • Total labour force survey employment rose by 2,243 thousand net (1.52 per cent).
  • The seasonally adjusted labour force rose by 724 thousand (0.45 per cent).
  • Official unemployment fell by 1,519 thousand to 11,061 thousand
  • The official unemployment rate fell by 1 point to 6.9 per cent.
  • The participation rate rose by 0.3 points to 61.7 per cent.
  • The broad labour underutilisation measure (U6) fell by 0.7 points to 12.1 per cent, even though the number in the part-time for economic reasons cohort (the US indicator of underemployment) rose by 383 thousand (6.1 per cent).

For those who are confused about the difference between the payroll (establishment) data and the household survey data you should read this blog post – US labour market is in a deplorable state – where I explain the differences in detail.

Election comments

I don’t have much to write at present. But progressives who are out there celebrating that a monster has gone should reflect on the new president’s past record, which is anything but encouraging.

The early rumours about the team he is assembling doesn’t augur well from an economics perspective.

And the lack of empathy with the blue-collar workers who have lost out in this globalised world, which goes back to the Clinton days and has become entrenched in the Democratic machine doesn’t suggest a great progressive future.

The 70 million voters who went for the monster are real people who have seen the Democrats cosy up to Wall Street and endorse deregulation and a refuse to endorse major increases in the wages.

They see a party that refuses to endorse scrapping the massive student loans that give their children any hope of upward mobility.

They saw Clinton’ welfare reforms that were racist and an attack on poverty. A criminalisation of poverty. Meanwhile they have seen the banksters mostly walk free with their government-bailout salaries and bonuses in place.

They have seen Obama care refuse to provide universal health care.

They have seen their children go to illegal wars and die.

And so it goes.

Unless the new president disavows all that including his own past record then nothing much will change.

I don’t think Biden won, rather Trump lost because his preposterous manner was just a little too muchor an already preposterous nation.

BLS explanation

The BLS provided a special note to help us understand the results this month.

We learn:

1. “The collection rate for the establishment survey was 79 percent in October, higher than the average for the 12 months ending in February 2020.”

2. “The household survey response rate was 80 percent in October, considerably higher than the low of 65 percent in June but below the average of 83 percent for the 12 months ending in February 2020.”

3. Both results reduce the accuracy of the surveys.

4. In the payroll survey:

… workers who are paid by their employer for all or any part of the pay period including the 12th of the month are counted as employed, even if they were not actually at their jobs. Workers who are temporarily or permanently absent from their jobs and are not being paid are not counted as employed, even if they are continuing to receive benefits.

5. In the Labour Force survey:

… In the household survey, individuals are classified as employed, unemployed, or not in the labor force based on their answers to a series of questions about their activities during the survey reference week (September 6th through September 12th). Workers who indicate they were no working during the entire survey reference week and expect to be recalled to their jobs should be classified as unemployed on temporary layoff. As in recent months, a large number of persons were classified as unemployed on temporary layoff in September.

The BLS wanted the latter group classified as unemployed for consistency but the survey staff didn’t always comply, which means that the employment estimates are probably overstated.

What impact might this have had?

The BLS say:

… the share of responses that may have been misclassified was highest in the early months of the pandemic and has been considerably lower in recent months.

For March through September, BLS published an estimate of what the unemployment rate would have been had misclassified workers been included among the unemployed. Repeating this same approach, the overall October unemployment rate would have been 0.3 percentage point higher than reported. However, this represents the upper bound of our estimate of misclassification and probably overstates the size of the misclassification error.

So we are still operating in an environment of uncertainty but the data accuracy has increased.

Once these classification issues are resolved, the participation response becomes more normal (workers coming back into the labour force), and the number of jobs lost forever becomes apparent, the true residual impact of the pandemic on the US labour market will become clearer.

Payroll employment trends

The BLS noted that:

Total nonfarm payroll employment rose by 638,000 in October and has increased for 6 consecutive months. In October, nonfarm employment was below its February level by 10.1 million, or 6.6 percent. Notable job gains occurred over the month in leisure and hospitality, professional and business services, retail trade, and construction. Employment in government declined.

The first graph shows the monthly change in payroll employment (in thousands, expressed as a 3-month moving average to take out the monthly noise). The gray lines are the annual averages.

The data swings are still large and dwarf the past history.

Clearly, the 20.7 million job loss in April has not yet been reversed. Given the loss of payroll jobs in March and April, the US labour market is still 10.1 million jobs short from where it was at the end of February.

The next graph shows the same data in a different way – in this case the graph shows the average net monthly change in payroll employment (actual) for the calendar years from 1940 to 2020 (the 2020 average is for the months to date).

I usually only show this graph from 2005 but because history is being created at present I included the full sample available from 1940.

The final average for 2019 was 178 thousand.

The average so far for 2020 is -963 thousand.

In a way, graphs like this lose definition and only present a binary world.

Labour Force Survey – employment growth continues

The data for September continues the improvement for the time being

1. Employment as measured by the household survey rose by 2,243 thousand net 1.52 per cent). This is a massive increase and I suspect it is a sampling issue. At the same time the working age population estimate fell, which is a sure sign some sampling issues are going on

2. The labour force rose by 724 thousand (0.45 per cent).

3. The participation rate rose by 0.3 points.

4. As a result (in accounting terms), total measured unemployment fell by 1,519 thousand and the unemployment rate fell by 1 point to 6.9 per cent.

So, on the face of it, this is a virtuous situation – a rise in jobs, a rise in those seeking jobs and a fall in official unemployment (and hidden unemployment).

But standby for revisions.

The following graph shows the monthly employment growth since January 2008, which shows the massive disruption this sickness has caused.

The Employment-Population ratio is a good measure of the strength of the labour market because the movements are relatively unambiguous because the denominator population is not particularly sensitive to the cycle (unlike the labour force).

The following graph shows the US Employment-Population from January 1950 to October 2020.

While the ratio fluctuates a little, the April 2020 ratio fell by 8.7 points to 51.3 per cent, which is the largest monthly fall since the sample began in January 1948.

In October 2020, it rose by 0.8 points to 57.4 per cent.

It is still well down on the level in January 2020 (61.2 per cent).

As a matter of history, the following graph shows employment indexes for the US (from US Bureau of Labor Statistics data) for the five NBER recessions since the mid-1970s and the current 2020-COVID crisis.

They are indexed at the employment peak in each case and we trace the data out for each episode until one month before the next peak.

So you get an idea of:

1. The amplitude (depth) of each cycle in employment terms.

2. The length of the cycle in months from peak-trough-peak.

The early 1980s recession was in two parts – a short downturn in 1981, which was followed by a second major downturn 12 months later in July 1982 which then endured.

Other facts:

1. Return to peak for the GFC was after 78 months.

2. The previous recessions have returned to the 100 index value after around 30 to 34 months.

3. Even at the end of the GFC cycle (146 months), total employment in the US had still only risen by 8.3 per cent (since December 2007), which is a very moderate growth path as is shown in the graph.

The current collapse is something else.

Unemployment and underutilisation trends

The BLS report that:

In October, the unemployment rate declined by 1.0 percentage point to 6.9 percent, and the number of unemployed persons fell by 1.5 million to 11.1 million. Both measures have declined for 6 consecutive months but are nearly twice their February levels (3.5 percent and 5.8 million, respectively).

The official unemployment rate declined in October 2020 largely because employment growth outstripped the labour force growth (driven by rising participation). This is usually seen as a good sign but be warned the employment estimates were suspect.

The first graph shows the official unemployment rate since January 1994.

The official unemployment rate is a narrow measure of labour wastage, which means that a strict comparison with the 1960s, for example, in terms of how tight the labour market, has to take into account broader measures of labour underutilisation.

The next graph shows the BLS measure U6, which is defined as:

Total unemployed, plus all marginally attached workers plus total employed part time for economic reasons, as a percent of all civilian labor force plus all marginally attached workers.

It is thus the broadest quantitative measure of labour underutilisation that the BLS publish.

In December 2006, before the effects of the slowdown started to impact upon the labour market, the measure was estimated to be 7.9 per cent.

In October 2020 the U6 measure decreased by 0.7 points to 12.1 per cent.

What drove this improvement?

This was driven mostly by the decline in unemployment. Offsetting that was the rise in underemployment – up by 383 thousand.

The BLS say that:

The number of persons employed part time for economic reasons increased by 383,000 to 6.7 million in October, after declines totaling 4.6 million over the prior 5 months. These individuals, who would have preferred full-time employment, were working part time because their hours had been reduced or they were unable to find full-time jobs. This group includes persons who usually work full time and persons who usually work part time …

The number of persons not in the labor force who currently want a job decreased by 539,000 to 6.7 million in October; this measure is 1.7 million higher than in February. These individuals were not counted as unemployed because they were not actively looking for work during the last 4 weeks or were unavailable to take a job …

Among those not in the labor force who currently want a job, the number of persons marginally attached to the labor force, at 2.0 million, was about unchanged in October. These individuals were not in the labor force, wanted and were available for work, and had looked for a job sometime in the prior 12 months but had not looked for work in the 4 weeks preceding the survey. The number of discouraged workers, a subset of the marginally attached who believed that no jobs were available for them, was 588,000 in October, essentially unchanged from the previous month …

Ethnicity and Education

The next graph shows the evolution of unemployment rates for three cohorts based on educational attainment: (a) those with less than high school completion; (b) high school graduates; and (c) university graduates.

As usual, when there is a crisis, the least educated suffer disproportionately.

In the collapse in employment, the unemployment rates rose by:

  • 14.4 points for those with less than high-school diploma.
  • 12.9 points for high school, no college graduates.
  • 5.9 points for those with university degrees.

The bounce back since April 2020 has seen the unemployment rate fall by:

  • 11.4 points for those with less than high-school diploma meaning the unemployment rate is now 3.8 points above the March level.
  • 9.2 points for high school, no college graduates meaning the unemployment rate is now 4.6 points above the March level.
  • 4.2 points for those with university degrees meaning the unemployment rate is now 2.3 points above the March level.

In the US context, especially in the current time, the trends in trends in unemployment by ethnicity are interesting.

Two questions arise:

1. How have the Black and African American and White unemployment rate fared in the post-GFC period?

2. How has the relationship between the Black and African American unemployment rate and the White unemployment rate changed since the GFC?

Summary:

1. All the series move together as economic activity cycles. The data also moves around a lot on a monthly basis.

2. The Black and African American unemployment rate was 6.7 per cent in March 2020, rose to 16.8 per cent in May and is now down to 10.8 per cent in October 2020.

3. The Hispanic or Latino unemployment rate was 6 per cent in March 2020, rose to 18.9 per cent in April and fell to 8.8 per cent in October 2020.

4. The White unemployment rate was 4 per cent in March 2020, rose to 14.2 per cent in April and fell to 6 per cent in October 2020.

The next graph shows the Black and African American unemployment rate to White unemployment rate (ratio) from January 2018, when the White unemployment rate was at 3.5 per cent and the Black or African American rate was at 7.5 per cent.

This graph allows us to see whether the relative position of the two cohorts has changed since the crisis. If it is rising, then the unemployment rate of the Black and African American cohort is either rising faster than the white unemployment rate or falling more slowly (or a combination of that relativity).

While there is month-to-month variability, the data shows that, in fact, through to mid-2019, the position of Black and African Americans had improved in relative terms (to Whites), although that just reflected the fact that the White unemployment was so low that employers were forced to take on other ‘less preferred’ workers if they wanted to maintain growth.

In April 2019, the ratio was 2.1 (meaning the Black and African American unemployment rate was more than 2 times the White rate).

By April 2020, the ratio had fallen to its lowest level of 1.2, reflecting the improved relative Black and African American position.

As the pandemic hit, the ratio rose and peaked at 1.8 in August 2020, but fell to 1.7 in September, reflecting an improvement in the relative position of the Black and African American workers.

In October, the ratio rose to 1.8 reflecting a small deterioration in the relative Black and African American situation against Whites.

The Occupational Impacts to date – low wage workers bearing the brunt

As regular readers will know I have been tracking the sectoral and occupational employment changes in the US in relation to earnings for some time now.

I am exploring now is how is the US labour market collapse impacting on workers across the wage distribution.

The burning question is whether low-paid workers bear the brunt of downturns and how well the respective earnings groups fare in the recovery?

In the past, I have demonstrated that the proportion of jobs in the total employment in sectors that pay below-average pay has increased.

But at that level of aggregation, we are unable to say whether these jobs in question were high-pay or low-pay.

The next calculations help to expand on that understanding.

They show the net job losses (in the downturn) and net job gains (in the recovery to date) for the major occupations in the BLS classification.

I have sorted the occupations relative to median weekly earnings as at the September-quarter 2020 (most recent data).

Low-pay is 75 per cent of the median and in terms of the most recent earnings data includes the Service occupations, Farming, Fishing and Forestry occupations, and the Transportation and material moving occupations.

GFC downturn

1. In the downturn, 90.6 per cent of the jobs lost were in occupations that paid below median weekly earnings (12.3 per cent of those were in low-paid occupations). Very few jobs (relatively) were lost in the higher paying occupations.

2. Given 86.1 per cent of the total jobs lost in the downturn were in sectors paying above average pay. The inference is that the jobs lost were predominantly the lower paying jobs in those sectors (although we cannot strictly compare mean and median in a wage distribution given the skewness).

GFC recovery to February 2020

1. In the upturn to February 2020, the net jobs added had not yet replaced those lost in the occupations with below median weekly earnings. 67 per cent of the net jobs added were in occupations with above median weekly earnings. That proportion rose in the last three months to February 2020.

2. In the recovery, a much larger number of low-paid jobs were added. Of the 33 per cent share of below median earning jobs added in the recovery, almost all of them were in low-pay occupations (31.3 per cent of the total jobs added).

3. This tells us that there is a polarisation going on in the occupational employment structure with a bias towards low-pay jobs in the below median weekly earnings occupations and towards jobs in the above median weekly earnings with a hollowing out in the middle of the distribution.

4. That is, over the recovery period a hollowing out around the overall median pay levels was going on.

The Covid downturn – February 2020 to April 2020

The current crisis is very different to the GFC recession, given that a host of activities were forced to stop altogether ad authorities (slowly) enforced shutdowns and isolation.

The areas that are most affected include hospitality, sports, entertainment, restaurants and cafes, travel, and similar, which are major employers of low-paid, precarious workers.

So I expect the patterns of job loss to be somewhat different as a result.

The summary results are that:

1. Low-paid work slumped by 29.9 per cent between February and April 2020.

2. In just two months, the low-paid service sector occupations shed 160 per cent of the total jobs that were added in the period between January 2010 and February 2020. Think about that!

2. Below-median pay jobs slumped by 21.9 per cent.

3. Above-median pay jobs fell by 7.9 per cent.

4. In terms of total numbers of jobs lost:

(a) 22.9 per cent (5,646 thousand) were in above-median pay occupations.

(b) 77.1 per cent (19,045 thousand) in below-median pay occupations.

(c) 43.2 per cent of the total (10,671 thousand) have been in low-pay occupations.

The Covid recovery – from April 2020

The summary results are that:

1. Low-paid work has grown by 29.7 per cent and gained 70.9 per cent of the jobs lost between February and April 2020.

2. Below-median pay jobs have grown by 21.6 per cent and gained 76.9 per cent of the jobs lost between February and April 2020.

3. Above-median pay jobs have grown by 3.8 per cent and gained 43.5 per cent of the jobs lost between February and April 2020.

4. In terms of total numbers of jobs gained:

(a) 14.4 per cent (2,457 thousand) were in above-median pay occupations.

(b) 85.6 per cent (14,650 thousand) in below-median pay occupations.

(c) 44.3 per cent of the total (7,574 thousand) have been in low-pay occupations.

Occupational Group
Jobs change – Feb-Apr 2020 (000s)
Proportion change (%)
Jobs change – Apr-Oct 2020 (000s)
Proportion change (%)

Above-median pay
-5,646
22.9
2,457
14.4

Management, business, and financial operations occupations
1,471
6.0
549
3.2

Professional and related
-3,452
14.0
1,508
8.8

Installation, maintenance, and repair
-723
2.9
400
2.3

Below-median pay but not low pay
-19,045
77.1
14,650
85.6

Sales and related
-2,846
11.5
2,308
13.5

Office and administrative support
-1,937
7.8
1,682
9.8

Construction and extraction
-1,605
6.5
1,691
9.9

Production
-1,986
8.0
1,395
8.2

Low pay
-10,671
43.2
7,574
44.3

Service
-8,189
33.2
6,103
35.7

Farming, fishing, and forestry
-64
0.3
37
0.2

Transportation and material moving
-2,418
9.8
1,434
8.4

Total
24,691
100.0
17,107
100.0

Conclusion

The October 2020 US BLS labour market data release reveals an on-going rebound from the catastrophic labour market collapse in March and April but the pace of recovery is still not sufficient to wipe out the losses accumulated in March and April.

The payroll data suggests the pace of recovery is slowing, whereas the labour force data gives the opposite view. Next month will resolve those conflicts one suspects as revisions will come.

The question that I have is how far can the US go with its open policy with the virus spiralling out of control, hospitals becoming overcrowded and the death rate rising to unimaginable levels.

Will the states lockdown again or not?

How many firms have failed in the past few months.

One of the questions that we do not know the answer to yet is how many firms have disappeared altogether as a result of the lockdowns in March and April.

One of the issues that will impact on future results is the loss of jobs in the government sector.

Total (net) jobs lost in the government sector was 268 thousand in October.

Of those, 130 thousand (net) jobs fell in the state and local government sector and if the Congress does not approve further support for the states then this figure will escalate.

It doesn’t make sense in a massive crisis for government employment to be falling.

The bankruptcy data also indicates a slight fall in filings in the June-quarter 2020 relative to the March-quarter. So it is unclear at present how many firms have disappeared.

The delays in extra US government assistance are not helpful and perhaps with the political situation less uncertain (for most) the Congress will resolve the impasse.

That is enough for today!

(c) Copyright 2020 William Mitchell. All Rights Reserved

Long-term unemployment in America falls when employment growth increases

Published by Anonymous (not verified) on Mon, 02/11/2020 - 1:37pm in

Tags 

US economy

A few weeks ago, I updated my research on the way employment growth accesses the different unemployment duration pools using Australian data. In that blog post (October 19, 2020) – The long-term unemployed are not an inflation constraint in a recovery – I showed that the claim that the long-term unemployed constitute an inflation constraint because employers will not choose to offer them jobs due to perceived scarring is a popular neoliberal assertion but has no basis in the actual data. The orthodox economists use that assertion to justify microeconomic (supply-side) policies (training, activation, etc) rather than direct job creation. The reality is that when employment growth is strong enough, both short-run and long-run pools of the unemployed are accessed by employers. In the latter case, employers alter hiring standards and offer on-the-job training to ensure they do not lose market share. I have received several E-mails stating that the US is different and the long-term unemployed are shunned by employers, which means that trying to stimulate the economy will hit the inflation constraint sooner than if there was a Job Guarantee in place. Logically, there is no reason the US labour market operates differently in any fundamental way to the Australian labour market so I decided to examine the validity of the ‘irreversibility hypothesis’ using US data. Guess what? The hypothesis doesn’t hold up in the US either.

You should read the earlier analysis cited above for background and additional detail. This blog post is more focused on the data rather than the concepts lying behind the data.

Definitions

While most nations use an unemployment duration of 52 weeks to define the threshold beyond which a person is classified as being long-term unemployed, the US used a threshold of more than 26 weeks.

Patterns of unemployment duration

First, what is the pattern of unemployment duration?

The next graph shows the pattern of unemployment duration in the US since the first-quarter 1950 up to the March-quarter 2020. The grey bars show the official (GDP) recessions after 1967. There were recessions before that date but I haven’t shown them here.

The pattern is typical. During a recession, the average duration rises and the longer the recession the higher the average becomes as the duration categories move from short-term (less than 5 weeks in the US classification) through to the longer-duration categories.

You can clearly see how bad the GFC was. It took a long time for recovery to commence which meant that more unemployed workers remained in that state for longer.

The next graph is taken from the BLS and shows the unemployment numbers (000s) for the four duration categories that they provide data.

The grey bars are recessions.

The graph provides interesting information about how the pool of unemployment builds as the cycle turns down. After a long period of growth, long-term unemployment (currently defined as more than 26 weeks of continuous joblessness) falls to low levels and workers enter and exit the unemployment pool regularly as jobs are created and destroyed.

As I noted in the previous graph, the GFC recession was so deep and drawn out that the long-term unemployment pool rose substantially and took time to fall again, once growth ensued.

The longer the recovery was delayed the more workers flowed into the LTU category.

Once the downturn started (late 2007), the short-duration categories obviously take the initial unemployment and rise sharply.

As the recession persists, you start to see the longer-duration categories rising sharply.

The irreversibility agenda

As unemployment started rising across the globe in the 1970s, orthodox economists concentrated on the supply side of the labour market, hypothesising that full employment should be redefined to occur at much higher unemployment rates than in the past.

The orthodox approach, however, has been to consider long-term unemployment to be a (linear) constraint on a person’s chances of getting a job.

The so-called negative duration effects (scarring etc) are meant to play out through loss of search effectiveness or demand side stigmatisation of the long-term unemployed.

That is, they become lazy and stop trying to find work and employers know that and decline to hire them. Over this period, skill atrophy is also claimed to occur.

It is also claimed that employers will bypass the long-term unemployed and if they come up against labour supply constraints as a consequence they will increase wage offers to those already in employment rather than take on these ‘damaged’ and ‘dirty’ workers.

The wage chase then causes inflation.

So the long-term unemployed represent an inflation constraint until they are subjected to attitudinal training so they work with others, training etc.

In other words, stimulating the economy will only induce inflationary pressures if there is a significant pool of long-term unemployed.

Mainstream economists and policy makers thus postulate that there is a formal link between unemployment persistence, on one hand and so-called ‘negative dependence duration’ and long-term unemployment, on the other hand.

However, no formal link that is credible has ever been established.

Despite the lack of evidence, the entire logic of the 1994 OECD Jobs Study which marked the beginning of the so-called supply-side agenda defined by active labour market programs was based on this idea.

This was the period when governments abandoned their Post World War 2 commitment to full employment, and, instead, adopted the diminished, supply-side goal of full employability.

The import of that shift was that governments stopped dealing with downturns in non-government spending, especially when the downturn was severe, with direct job creation programs, and, instead, introduced supply-side programs – training, attitudinal coaching, CV preparation and all the rest of it.

Labour market recoveries from downturns in the full employment era were much more rapid because governments used their fiscal capacity to address the spending gaps.

In the neoliberal era, a major downturn which drives unemployment up sharply, results in a slow, drawn out recovery where unemployment takes many years to recover.

So the irreversibility hypothesis is core neoliberal mythology that militates against government’s using their fiscal capacity to reduce unemployment after a collapse of non-government spending.

Does long-term unemployment have strong irreversibility properties in the US labour market?

There is little credence in the irreversibility hypothesis when we examine the US data.

Once you examine the dynamics of the data you quickly realise that short-term unemployment rates do not behave much differently to long-term unemployment rates.

The irreversibility hypothesis is unfounded.

Clearly, if the government allows a downturn in non-government spending to descend into recession and refuses to stimulate the economy in any significant manner then long-term unemployment rises just because of the movements of the short-term unemployed through the duration categories.

But the data shows that the relationship between long-term unemployment and the unemployment rate is very close as can be seen in the following graph.

The following graph shows the proportion of long-term unemployment (greater than 26 weeks) in total unemployment from 1950 to the March-quarter 2020. It clearly looks very similar to the average duration graph.

It rises and falls during and after recessions. The deeper the recession, the larger the increase and the longer it takes to resolve.

The next graph adds the dynamics of the overall unemployment rate to the LTU proportion over the same period. If the behaviour of the long-term unemployment pool was markedly different from short-term unemployment, then we should see dissonance between these two time series.

The evidence is clear.

As unemployment rises (falls), the proportion of long-term unemployment in total unemployment rises (falls) with a lag.

Several studies have formally examined this relationship for different countries.

My earlier work has found that a rising proportion of long-term unemployed is not a separate problem from that of the general rise in unemployment.

This casts doubt on the supply-side policy emphasis that OECD governments have adopted over the last two decades.

So while the mainstream economics profession may claim search effectiveness declines and this contributes to rising unemployment rates, the overwhelming evidence is that both are caused by insufficient demand.

The policy response then is entirely different.

To argue that long-term unemployment is a constraint on growth and therefore needs supply-side programs rather than direct job creation, you would have to find that even during growth periods, long-term unemployment was resistant to decline.

I also did some more sophisticated regression modelling this morning which takes us beyond what I would report here (too complex).

The estimates of a number of different econometric models revealed no significant difference in the cyclical behaviour of the short- and long-run unemployment pools.

The results tell me that employers recruit from all the duration pools more or less simultaneously.

And you can get a feel for that from this graph, which shows quarterly GDP growth on the horizontal axis from 1948 to March 2020 and the PLTU on the vertical axis (blue markers) and the overall unemployment rate (green markers). The dotted lines are simple regression lines and the equations are shown. My own econometric equations were more complex than this but the results are not that much different.

So as real GDP growth strengthens the proportion of long-term unemployed in total unemployment (PLTU) falls consistently as does the overall unemployment rate.

The former falls faster than the latter.

Conclusion

The evidence very strongly supports the view that long-term unemployment rises and falls with net job creation. The stronger is employment growth the more quickly long-term unemployment falls.

When recoveries are stalled and slow, the long-term unemployed get trapped in that state.

And in the periods examined, there is no evidence that as the pool of long-term unemployed was declining (simultaneously with the short-run pool) that inflation was accelerating.

It is far better for the government to ensure there is strong spending support when non-government spending declines to prevent the build up of long-term unemployed in the first place.

This should not be taken to mean that the introduction of a Job Guarantee would not improve the situation considerably.

Clearly, if there is a Job Guarantee in place, then in the early days of a recovery, when the Job Guarantee pool might be bigger than usual, the wage offers required to bid the workers back into the private labour market may be modest and there are plenty of workers available, so it is unlikely that there would be any inflationary pressures.

It is also true that Job Guarantee workers are more attached to the labour market than the unemployed.

But the hysteretic mechanisms that see firms relax and tighten hiring standards and combine training slots with jobs slots at different points of the economic cycle also mean that the long-term unemployed are absorbed along with the short-term unemployment when economic growth is strong enough coming out of a recession.

In a deep and long recession, the number of long-term duration Job Guarantee workers will be higher than if the recession is short and sharp.

If the recovery is strong enough, then they will get absorbed back into the employed workforce just as they would be if they were long-term unemployed.

But once the economy gets close to capacity and the Job Guarantee pool is minimised, then any extra bidding from that pool will be stronger than before and the margin over the Job Guarantee wage that would arise will be larger than before. The point is that the price anchor provided by the Job Guarantee becomes moot when the pool of jobs becomes very small, just as in the case when the unemployment pool is small.

The difference between the two buffer stock mechanisms, however, is that if there are inflationary pressures in the non-government sector, and the government tightens policy settings to suppress them, then under the unemployment buffer stock approach, workers lose their jobs, whereas under a Job Guarantee workers are redistributed from the inflating sector to the fixed price job sector.

While neither system is ideal, the employment buffer approach is vastly superior to using the unemployed as a front line fighting force to discipline distributional struggles between labour and capital.

That is enough for today!

(c) Copyright 2020 William Mitchell. All Rights Reserved.

US claimants recovery stalls

Published by Anonymous (not verified) on Mon, 26/10/2020 - 2:11pm in

Tags 

US economy

Today, I celebrate – my home town of Melbourne has recorded zero new infections for the first time since June 9, 2020 and zero deaths. But things are not so hot elsewhere in the world. As the US labour market started to rebound over the summer, I stopped updating my analysis of the claimants data horror story that had earlier demonstrated how sharp the decline in March and April had been. But I have still been monitoring it on a weekly basis and the information we are now getting from the US Department of Labor’s weekly data releases are indicating that as the virus escalates, seemingly out of control, the labour market recovery has all but stalled and a reasonable prediction would be that it will deteriorate somewhat if the infection rate leads to tighter restrictions (which it should). A relatively short blog post today (tied up with things today) – just some notes as I updated the data to see what was going on. The conclusions are obvious. Much more fiscal support is needed in the US, especially targetted at the bottom end of the labour market. Devastation will follow with the sorts of numbers that appear to be entrenched at present.

Here is the latest update (as for the week ending October 17, 2020) from the US Department of Labor’s weekly data releases for the unemployment insurance claimants.

The Department of Labor provides an archive of the weekly unemployment insurance claims data back to January 7, 1967 – HERE.

The weekly data can be found in the – UI Weekly Claims Report.

New claimants recovery stalled

The next graph shows the data for New claimants data from January 1, 2020 to October 17, 2020.

I had previously posted the full sample, which showed how insignificant the previous deep recessions of the early 1980s, 1990s and the GFC were by comparison with the current event.

But we get little information from seeing a huge vertical line dwarfing all previous observations. We know the scale.

This series provides the best information on the state of the labour market and reinforces the information we learned from the monthly payroll and labour force survey data, which showed that while employment was still growing in September, the rate of improvement has moderated significantly.

I analysed that data in this blog post – US labour market – floundering now despite modest gains (October 5, 2020).

The problem that the data on new (first-time) claimants for benefits demonstrates is that the weekly claims have not substantially declined since August, which tells me that employment growth is not fast enough to absorb the accumulated pool of jobless workers.

Continuing claims and covered unemployment rate

The other series, which is of interest is the continuing claims, which lags the new claims by a week.

The following graph shows that this series is dropping steadily and is now at 8.3 million. On March 7, 2020, the stock of continuing claims was 1,702,000 persons. So the figure has grown nearly 5 times.

The next graph shows the evolution of the insured unemployment rate, which measures the proportion of the labour force that is collecting unemployment benefits.

It fell from 6.4 per cent to 5.7 per cent which might on the surface suggest an improving situation.

However, the monthly labour force data (see link to my analysis above) showed that the decline in the unemployment rate was mostly driven by a fall in the participation rate, which effectively means that the official unemployed are becoming hidden unemployed outside the labour force measure.

Bringing together the archived data and the most recent release (October 17, 2020), the following table tells the story for those who like numbers.

Week ending
Initial Claims (SA)
Weekly Change
Cumulative sum since March 7, 2020

March 7, 2020
211,000
-6,000
n/a

March 14, 2020
282,000
+71,000
282,000

March 21, 2020
3,307,000
+3,025,000
3,589,000

March 28, 2020
6,687,700
+3,560,000
10,456,000

April 4, 2020
6,615,000
-252,000
17,071,000

April 11, 2020
5,237,000
-1,378,000
22,308,00

April 18, 2020
4,442,000
-795,000
26,750,000

April 25, 2020
3,867,000
-575,000
30,617,000

May 2, 2020
3,176,000
-691,000
33,793,000

May 9, 2020
2,687,000
-489,000
36,480,000

May 16, 2020
2,446,000
-241,000
38,926,000

May 23, 2020
2,123,000
-323,000
41,049,000

May 30, 2020
1,897,000
-226,000
42,946,000

June 6, 2020
1,566,000
-331,000
44,512,000

June 13, 2020
1,540,000
-26,000
46,052,000

June 20, 2020
1,482,000
-58,000
47,534,000

June 27, 2020
1,408,000
-74,000
48,942,000

July 4, 2020
1,310,000
-98,000
50,252,000

July 11, 2020
1,308,000
-2,000
51,560,000

July 18, 2020
1,422,000
114,000
52,982,000

July 25, 2020
1,435,000
13,000
54,417,000

August 1, 2020
1,191,000
-244,000
55,608,000

August 8, 2020
971,000
-220,000
56,579,000

August 15, 2020
1,104,000
133,000
57,683,000

August 22, 2020
1,011,000
-93,000
58,694,000

August 29, 2020
884,000
-127,000
59,578,000

September 5, 2020
893,000
9,000
560,471,000

September 12, 2020
866,000
-27,000
61,337,000

September 19, 2020
873,000
7,000
62,210,000

September 26, 2020
849,000
-243,000
63,059,000

October 3, 2020
767,000
-82,000
63,826,000

October 10, 2020
842,000
75,000
64,668,000

October 17, 2020
787,000
-55,000
65,455,000

Past Recessions Comparison

I wondered what the behaviour of this time series had been in past recessions. The data goes back to January 1967, which means it covers 8 official US recessions.

I started the indexes at 100 for each recession in the week where the lowest claimant count occurred before the recession began and then graphed the index out to 40 weeks, which is the duration of the current COVID recession.

The following graph covers the 7 official recessions up to and including the GFC.

I decided to graph the COVID episode separately because it completely obliterates any of the past dynamics in amplitude.

As you can see, the pattern is very similar for all these events (with some variational spikes).

Here is the graph for the COVID period. Stunning.

The spatial patterns

The following Table presents the most recent data to October 10, 2020 for the US states.

It shows the cumulative claims since February 26, 2020 to October 10, 2020 in total and as a percentage of the State’s working age population, as well as the insured unemployment rate.

Upcoming event – Public Access

October 29, 2020 – Economic Policy after Brexit and COVID-19: Taking Control

The team at the Full Brexit is sponsoring this event.

Date: October, 29, 2020.

Time: 20:00-21:30 (online event) – This is London time.

Britain is in its worst economic crisis since the Great Depression. The costs of the coronavirus pandemic continue to dwarf even the most exaggerated Remainer predictions of the costs of leaving the European Union.

But neoliberal shibboleths have also been shattered, with the government intervening to save jobs and businesses, while even the EU has set aside its treasured state aid rules (despite continuing to try to force the UK to abide by them).

At the same time, governments around the world seem short on imaginative ideas to reboot the economy. The priority seems to be trying to restore a pre-crisis system that was already failing millions long before COVID-19.

So how do we really “build back better”? How do we avoid a slow, jobless recovery – a degraded “new normal”? What policies and programmes are required to allow working people to take control of their lives, and enjoy a more prosperous and fulfilling future?

Join two world-leading experts to debate these crucial issues:

  • Professor Costas Lapavitsas, renowned economist, former member of the Greek parliament, and author of The Left Case Against the EU (Polity, 2019).
  • Professor Bill Mitchell, one of the leading lights of Modern Monetary Theory, and co-author, with Thomas Fazi, of Reclaiming the State: A Progressive Vision of Sovereignty for a Post-Neoliberal World (Pluto, 2017).

Professor Costas Lapavitsas, renowned economist, former member of the Greek parliament, and author of The Left Case Against the EU (Polity, 2019), and

Registration Available Here.

The event is free but you have to register to get Zoom access. Registered attendees will be emailed with the link on the day of the event.

Conclusion

Without further fiscal support, I suspect the situation will become very grim in the US as the pace of the recovery has slowed and this locks in those who lost jobs at the beginning of the crisis to a long period of joblessness.

That is enough for today!

(c) Copyright 2020 William Mitchell. All Rights Reserved.

Podcast – Biden and Trump, climate crisis, US healthcare, UBI

Published by Anonymous (not verified) on Wed, 14/10/2020 - 11:32am in

Its Wednesday and as usual I am not writing much here. Further, I have many commitments today (see one of them below). So we just have some information for you plus a podcast I did recently. And, finally, some Bob and Johnny for our music segment.

Cheese and Macro – Juxtapositions with Bill Mitchell Podcast

I recently recorded an interview with Steve Grumbine who leads the fabulous team at Real Progressives in the US, who tirelessly work to promote Modern Monetary Theory (MMT), effort that I am eternally grateful for.

We talked about a lot of things and the edited version captures the scope of the conversation.

You can access the discussion – HERE.

Thanks to Steve who stayed up late to fit into our global dispersion.

It is the first time I have been in the same picture as Biden and Trump and I have never worn a yellow tie!

Upcoming events

I have been doing a lot of presentations in the recent period to a variety of audiences, mostly restricted.

Two public events that are coming up include, one tonight and another later in the month.

PHAA event – An economy that guarantees health and wellbeing for all: the right to work and income security

Date: October, 14, 2020.

Time: 18:00 Melbourne, Australia summer time.

Tonight, the Public Health Association, Australia is sponsoring an event – An economy that guarantees health and wellbeing for all: the right to work and income security.

In the neoliberal era, poverty, income inequality and unemployment have been on the rise and have come to be seen as inevitable and immutable features of market-based economies. During this time governments, increasingly obsessed with austerity economics, have come to be cast as powerless to tackle these issues with the burden of responsibility being placed on the individual. The individual and societal health consequences of the failure to address these issues are profound and wide-ranging. Far from being inevitable and immutable problems, solutions are certainly at hand, at the centre of which is the fiscal capacity of our governments to provide for the wellbeing of all.

Our distinguished guests, Professor John Quiggin, Noel Pearson and Professor Bill Mitchell will participate in a panel discussion on the health, social and economic impacts of the ongoing failure to address the problems of poverty, income inequality and unemployment. The meaning and benefits of work; welfare systems and income security; the ever-growing gap between the rich and the poor; the case for a Job Guarantee and/or a Basic Income Guarantee; Modern Monetary Theory and the fiscal capacity of monetary sovereigns are just some of the topics likely to be discussed as we explore the health implications of achieving a full employment economy and welfare system reform that guarantees the health and well-being of all.

It will be a Zoom event (yes, another one) and you can – Register Here.

The participation is free up to an audience limit. Get in early if you want a guaranteed spot.

The event begins at 18:00 Melbourne, Australia summer time.

October 29, 2020 – Economic Policy after Brexit and COVID-19: Taking Control

The team at the Full Brexit is sponsoring this event.

Date: October, 29, 2020.

Time: 20:00-21:30 (online event) – This is London time.

Britain is in its worst economic crisis since the Great Depression. The costs of the coronavirus pandemic continue to dwarf even the most exaggerated Remainer predictions of the costs of leaving the European Union.

But neoliberal shibboleths have also been shattered, with the government intervening to save jobs and businesses, while even the EU has set aside its treasured state aid rules (despite continuing to try to force the UK to abide by them).

At the same time, governments around the world seem short on imaginative ideas to reboot the economy. The priority seems to be trying to restore a pre-crisis system that was already failing millions long before COVID-19.

So how do we really “build back better”? How do we avoid a slow, jobless recovery – a degraded “new normal”? What policies and programmes are required to allow working people to take control of their lives, and enjoy a more prosperous and fulfilling future?

Join two world-leading experts to debate these crucial issues:

  • Professor Costas Lapavitsas, renowned economist, former member of the Greek parliament, and author of The Left Case Against the EU (Polity, 2019).
  • Professor Bill Mitchell, one of the leading lights of Modern Monetary Theory, and co-author, with Thomas Fazi, of Reclaiming the State: A Progressive Vision of Sovereignty for a Post-Neoliberal World (Pluto, 2017).

Professor Costas Lapavitsas, renowned economist, former member of the Greek parliament, and author of The Left Case Against the EU (Polity, 2019), and

Registration Available Here.

The event is free but you have to register to get Zoom access. Registered attendees will be emailed with the link on the day of the event.

Music – This is the favourite song of a 7-year old I know

And I like it a lot too.

Its from Bob Dylan with Johnny Cash.

The song – Girl from the North Country – was originally on Bob Dylan’s 1963 second album – The Freewheelin’ Bob Dylan – which I used to play to its ultimate death. The album has so many classic songs on it that it is hard to think of a better album.

He took the melody for this song from the traditional English folk ballad – Scarborough Fair.

This version, however, is on Bob Dylan 1969 album – Nashville Skyline – which was released on Columbia Records and features the song in duet form.

I think this is a special case of a song cover (even though Bob is still involved) that is better than the original. The original is a bit quicker and I think i like the slower tempo. I also like the baritone register that Johnny Cash brings.

My question: How can a 7-year old have such sophisticated tastes?

That is enough for today!

(c) Copyright 2020 William Mitchell. All Rights Reserved.

Pages