This Morning’s Report: Another Big Jobs Gain, But Other Results Aren’t Following, and Latent Demand Grew 1.2 Million to 17,152,000 Per the AJSN

Some will say today’s Bureau of Labor Statistics Employment Situation Summary was first-class, and according to the most publicized number, total net nonfarm payroll employment jumped 353,000, almost matching both published estimates I saw combined, it was.  But how about the rest?

Seasonally adjusted unemployment held at 3.7%, with the unadjusted variety, reflecting how many people work in December but not in January, up from 3.5% to 4.1%.  The adjusted count of unemployed was off 200,000 to 6.1 million, again consistent with the unadjusted gain of just under 900,000 to 6,778,000.  The number claiming no interest in working dropped 716,000, losing most of December’s gain, to 95.149 million.  Unadjusted employment fell a seasonal 1.1 million.  The count of long-term joblessness, people out of work for 12 months or longer, fell 100,000 to 1.1 million, and the tally of people working part-time for economic reasons, or keeping part-time positions while so far not finding full-time ones they want, matched last month’s change with a 200,000 gain, and is now at a dispiriting 4.4 million.  The two measures of how common it is for Americans to be working or nearly so, the labor force participation rate and the employment-population ratio, stayed the same and gained 0.1% respectively to reach 62.5% and 60.2%. 

The American Job Shortage Number or AJSN, the metric showing how many additional positions could be quickly filled if everyone knew they could be obtained easily and routinely, increased almost 1.2 million to the following:

Almost 800,000 of the change was from higher unemployment, with nearly all the remainder from those not looking for a year or more and those discouraged.  The share of the AJSN from the officially jobless rose 2.3% to 35.6%.  As the AJSN is not seasonally adjusted, this result is not particularly discouraging, however, when compared with the measure a year before it has gained over 400,000, mostly from higher unemployment.

How should we assess this data?  It is generally good, but what is noteworthy to me is how much the number of people with positions increases month after month, but the unemployment rates and the measures of partial attachment above don’t improve.  Since for the past year or two we have known about “overemployment,” or people secretly having more than one full-time job, is it possible that many of these 353,000 additional people working were doing that already?  Those taking on extra jobs may be no more honest with pollsters than they are with employers.  It would not be a shock to discover that the 159-plus million people reported as working are really something like 155 million, with over 4,000,000 undiscovered multi-job workers.  I don’t know if that is technically possible, but if it is, it is worthy of investigation.  In the meantime, the turtle took another small step – but no more than that – forward. 

Artificial Intelligence – Three Weeks of Bad News

Last week I went through positive things for this technology coming out since December.  Here are the others.

The first was “The Times Sues OpenAI and Microsoft over A.I. Use of Copyrighted Work” (Michael M. Grynbaum and Ryan Mac, The New York Times, December 27^th).  As became clear by the middle of last year, data use by these programs has included plenty of sources undoubtably legally off limits.  Although “the suit does not include an exact monetary demand,” it may end up being a lot, though to prevent easy assessment of the values of what could be great masses of similar attempts by others, it will almost certainly be settled out of court for an undisclosed sum.  Further development was published in “Boom in A.I. Prompts a Test of Copyright Law” (J. Edward Moreno, The New York Times, December 30^th).  Not much fun for future venture capitalists to consider.

A disappointment came to light in “ChatGPT Helps, and Worries, Business Consultants, Study Finds” (David Berreby, The New York Times, December 28^th).  While “the A.I. tool helped most with creative tasks,” including providing good structure and preliminary ideas when it “was to brainstorm about a new type of shoe, sketch a persuasive business plan for making it and write about it persuasively,” “on a task that required reasoning based on evidence… ChatGPT was not helpful at all,” with the danger that “”people told us they neglected to check it because it’s so polished, it looks so right.””  That means, as other results have shown, that generative AI programs are now better for starting business output than finishing it.

Speaking of venture capitalists, we also got “What happened to the artificial intelligence investment boom?” (The Economist, January 7^th).  Capital expenditures at large, S&P 500 firms not selling AI, the unbilled author or authors found, were only rising an average of 2.5% this year, with similar increases in Europe.  Per the piece, although this statistic may indicate that “adoption of new general-purpose tech tends to take time,” it may be instead that “generative AI is a busted flush,” that “big tech firms… are going to struggle to find customers for the products and services that they have spent tens of billions of dollars developing.” 

For even worse, look at “Robotics Expert Says AI Hype is Due for a Brutal Reality Check” (Futurism.com, January 8^th).  “Rodney Brooks, who co-founded the company iRobot – which invented the Roomba,” said that “the AI industry is merely “following a well worn hype cycle that we have seen again, and again, during the 60+ year history of AI.”” He said that “more than likely… advancements in the field will stagnate for many dark years before reaching the next huge breakthrough,” which would be “quite a calamitous comedown.”  Reminiscent of what has happened, or more properly didn’t happen, with driverless vehicles, “he’s skeptical that we’ll even be able to create “a robot that seems as intelligent, as attentive, and as faithful as a dog” before 2048.”  So, ““get your thick coats now.  There may be yet another AI winter, and perhaps even a full scale tech winter, just around the corner.  And it is going to be cold.””

Similarly, Daron Acemoglu told us to “Get Ready for the Great AI Disappointment” (Wired.com, January 10^th).  As I also predicted, “the year 2024 will be the time for recalibrating expectations,” as its tendencies to “provide false information” and fabricate it, along with further regulation, will limit AI to “just so-so automation… that fails to deliver huge productivity improvements.”  The author expected that its largest use “will be in social media and online search” – hardly justifying “talk of the “existential risks.””

A concerning set of applications now in use is the subject of “Dark Corners of the Web Offer a Glimpse of A.I.’s Nefarious Future” (Stuart A. Thompson, The New York Times, January 8^th).  He discussed “a collection of online trolls” affixing images into false scenes on “an anonymous message board known for fostering harassment, and spreading hateful content and conspiracy theories.”  Other “problems” on this site included “fake pornography” with recognizable faces, “cloning voices” to make sound seem like you were saying it, and of course “racist memes.”  Since “there is no federal law banning the creation of fake images of people,” we can expect many more.

All of these may have been influential, as “Elon Musk puts the brakes on AI development at Tesla until he gets more control” (Beatrice Nolan, Business Insider, January 16^th). That 13% owner, who wants to be “controlling 25% of the votes,” may see a rough path ahead, and so is willing to stop activity.  We should know better than to know how Musk thinks, but people do not often voluntarily halt things they like.  As well, it is time to doubt whether artificial intelligence will take over anything except some electronic documents.

There will be no post next week - I will return on February 2nd with a look at the new jobs report and the latest AJSN.

Artificial Intelligence: The Good News

Since June I have been expressing generally contrarian views on AI, that it will not fulfill the concerns and expectations it has gathered since its February news explosion.  As always, there are many facets of its progress.  What are some of the favorable ones from the past month?

In Fox News on December 20^th, Melissa Rudy published “Artificial intelligence experts share 6 of the biggest AI innovations of 2023: ‘A landmark year.’”  The advances, all medical-related, were “ChatGPT and other generative AI,” the subject of the blitz above which “has revolutionized health care communication by providing tools for personalized treatment plans and remote patient engagement,” though “its responses have sometimes been found lacking in accuracy and thoroughness”; “disease detection through retinal images,” which as of September “excels in diagnosing and predicting both eye diseases and systemic disorders such as heart failure and myocardial infarction”; “improvements to medical productivity,” also in assessing problems using retinal photography; “medical imaging and education” by “faster scanning times, enhanced image resolution and reduced radiation exposure”; “accelerated cancer research” through “using it to find hidden patterns in data, personalize treatment decision-making and help predict treatment benefit”; and “AI medical devices,” at least one-third of 692 AI-incorporating now FDA-approved added since 2022. 

Another new product was the subject of “The next generation of Tesla’s humanoid robot makes its debut” (Kurt Knutsson, Fox News, December 24^th).  This automaton “designed to be a general-purpose machine that can assist humans in various domains, such as manufacturing, construction, healthcare and entertainment,” is made up to have an almost-human frame, with hands having “11 degrees of freedom… equipped with tactile sensors and faster actuators, which allow it to manipulate objects with more precision and dexterity” among other refinements.  Overall, per Knutsson, this item “is a stunning example of how far humanoid robotics has come and how far it can go.”

In the December 27^th New York Times, Andrew Ross Sorkin took a stab at “What’s next in A.I.?”  He got information from “some of the world’s foremost experts in artificial intelligence,” and used it “to gauge what could be in store for the buzzy technology in the year ahead.”  Yet a section by Vivienne Walt claimed that “if 2023 was the year the world woke up to A.I., 2024 might be the year in which its legal and technical limits will be tested, and perhaps breached.”  Also, “judges and lawmakers will increasingly weigh in,” “some fear overloading A.I. businesses with regulations,” a prediction that “A.I capabilities will soar,” and “billions in investment will be needed.” 

Last, we had a look at “How the Federal Government Can Rein In A.I. in Law Enforcement” (Joy Buolamwini and Barry Friedman, The New York Times, January 2^nd).  The problems appear when “law enforcement deploys emerging technologies without transparency or community agreement that they should be used at all, with little or no consideration of the consequences, insufficient training and inadequate guardrails.”  A proposal from the federal Office of Management and Budget states that “agencies must be transparent and provide a public inventory of cases in which A.I. was used,” in which “the risks to individuals… must be identified and reduced.”  However, “there is also a vague exception for “national security,”” which, per the authors, “requires a sharper definition.” 

Artificial intelligence has contributed more than the generally incremental and future-bound achievements here.  Yet it is difficult to tease out what has happened over the past ten months from what was there before and what hasn’t actually happened yet. 

What are less favorable things that have occurred around AI?  That will be the subject of next week’s post.

This Morning’s Employment Report Featured Another Fine Jobs Gain, But Latent Demand by AJSN Grew 300,000, With Overall Weakness Elsewhere

The new Bureau of Labor Statistics Employment Situation Summary started out, again, by exceeding expectations.  The number of net new nonfarm payroll positions, formally estimated at 160,000 and 170,000, handily beat both with 216,000.  Seasonally adjusted and unadjusted unemployment did not drop but held their November 0.2% and 0.1% improvements to stay at 3.7% and 3.5%.  The count of jobless remained at 6.3 million, and those out for 27 weeks or longer held at 1.2 million.  Given that inflation keeps dropping, we can cheer the average private nonfarm payroll earnings rising more than that, 17 cents per hour to $34.27. 

From there, the numbers disappointed.  Those employed fell about 1.4 million to 160,754,000.  Those not interested rose just over a million to 95,865,000.  The count of those working part-time for economic reasons, or staying in part-time positions while looking for full-time ones, gave up most of its November improvement to reach 4.2 million.  The two measures of how common it is for Americans to be working or close to that, the labor force participation rate and the employment-population ratio, did even worse, dropping 0.3% and 0.4% to get to 62.5% and 60.1%. 

The American Job Shortage Number or AJSN, the measure showing how many new positions could be quickly filled if all knew that getting one would be about as hard as running a household errand, increased 324,000 to this:

Most of the change from November was from almost 300,000 more people not looking for work for the previous year, offset partially by fewer claiming discouragement.  Compared with a year before, the AJSN is almost 400,000 higher, with the unemployed contributing almost half a million to the metric and the effect of more people wanting work but not looking for it for a year or more adding a surprising 184,000.  The share of the AJSN from official unemployment was 33.3%, meaning that two-thirds of people who would fill new jobs would not have that status.

So where are we now?  Some of the downturns look like possible mid-December biases, as it is then easy for people to hold off on job-seeking activities and positive attitudes about it until after the holidays.  When people are not working then, it’s easier than usual for them to accept that.  Yet the previous December was better.  The number of net new positions keeps marching on, but there’s little improvement elsewhere, and more unemployed Americans in conjunction suggests that those choosing to be overemployed or working more than one full-time position, or keeping more than one part-time job, are getting more common.  But it’s too early to claim any trends there.  Next month’s report, based on a historically strong back-to-work month in January, will tell us whether underlying factors in American unemployment and employment are changing.  In the meantime, the turtle took but a tiny step forward.

Activity vs. Production – What’s Happening, and Why It Would Be Beneficial to Do Better

It’s an ancient problem.  Some workers look busy, but don’t accomplish much.  Some are low-profile, efficient, and quietly, often with lower hours or even apparent effort, get a lot more done.  Some focus on quality, others on quantity. 

How can supervisors and higher-ups best manage these different situations? 

One way is electronic monitoring.  That is nothing new.  When I worked at a data-entry position 36 years ago, supervisors got reports giving workers’ production, though at a coarse level, and other statistics such as how many things they deleted.  That was a start, though not all items produced were the same difficulty.  For most cubicle jobs, though, direct production is harder to assess, and some measures can be simply misleading. 

That issue came to the fore with “Microsoft executives say it’s ‘wrong’ for managers to spy on remote employees’ mouse clicks and keystrokes: ‘That’s measuring heat rather than outcome’” (Grace Kay, Business Insider, September 22^nd, 2022).  That is old also – an AT&T second-level manager in a group I was in over 30 years ago had software set up to tell him when a certain worker opened the databases he used; it wasn’t effective for long, as the employee set up something to automatically do that every morning he was scheduled.  The modern version may, per a quote from Microsoft’s CEO, be a result of “productivity paranoia,” especially concerning remote and hybrid workers. 

Another more general involvement area is about working extra hours.  A noticeable indication of that is communicating at unusual times.  However, “After-hours work emails are facing more legal restrictions” (Megan Cerullo, Yahoo Finance, February 3^rd).  One example is that “employers in Ontario, Canada are required to have written policies on disconnecting from work that outline when work-related communications, including emails, phone call and video conferences, are prohibited.”  Clearly, “the onus is on both the employer and employee to set boundaries around communicating outside of normal working hours,” and – for that matter, working in general – but often that does not happen.

Going further, Adam Waytz, in the March-April Harvard Business Review, wrote an article printing out to over 12 pages, titled “Beware a Culture of Busyness.”  The idea is also well-established, and the first part, with office people when asked how they were doing saying they were “busy,” matched AT&T culture when I was there.  Per Waytz, “Busyness has become a status symbol,” research has showed that those seeming busy are perceived as ““important and impressive”” and “”morally admirable,” regardless of their output.”  The author described how “a culture of busyness” can perpetuate itself, and named five ways to roll that back: “reward output, not just activity”; “assess whether your organization is generating deep work and eliminating low-value work”; “force people off the clock”; “model the right behavior”; and “build slack into the system.”

A development newer than quiet quitting, or refusing to work additional time or put in unusual effort, is the subject of “Gen Z’s ‘lazy girl jobs’ trend hits back at hustle culture, but critics warn outcome could be problematic” (Taylor Penley, Fox Business, July 29^th).  Such arrangements, per the article, are “well-paying often fully or partially remote jobs that require minimal effort to cut back on the stress and anxiety they say is harmful to mental health.”  Per one respondent, they include exercising and doing household tasks during work hours.  Unsurprisingly, “not everyone is on board with the concept,” and it “isn’t gender-exclusive.”  I suspect this trend comes mostly from lax remote-work supervision and standards, with Generation Z workers, with shorter work-experience sets containing little time during low-hiring eras, especially willing to articulate and practice what they want, even if it sounds bad.  If employers can harvest the advantages of clear policies and performance-centered employee evaluations, they can integrate those things with a conscious, focused retreat from busyness culture, and get a net benefit from it, especially considering how those policies can minimize expensive worker turnover. 

Encouraging and rewarding activity over results is not only constructive but good business.  I was a top producer at AT&T, even though I worked little extra time.  When I saw those inflating their hours but not their production, it discouraged me and my kin.  Management did not want people doing the most work moving to competitors, but that was sometimes a needless consequence.  When companies realize why it is poor practice to encourage “heat, rather than outcome,” they can in theory improve this problem.  But can they in reality?  Many managers cannot tell the difference between quality and quantity.  If they can get past that, many will be surprised at how much their businesses will improve.

Artificial Intelligence: More Concerns, Proposals, and Organizational Progress

While there have been various areas of AI progress over the past few months – incremental and automobile-related, anyway – more things have popped up since late November.

In “A.I. Belongs to the Capitalists Now” (The New York Times, November 22^nd), Kevin Roose said there had been “a fight between two dueling visions of artificial intelligence,” which with the Sam Altman OpenAI firing-and-rehiring had been won by “Team Capitalism,” which held that “A.I. is a transformative new tool, the latest in a line of world-changing innovations that includes the steam engine, electricity and the personal computer, and that, if put to the right uses, could usher in a new era of prosperity and make gobs of money for the businesses that harness its potential,” instead of something “that must be restrained and deployed with extreme caution in order to prevent it from taking over and killing us all.”  We’ll see.

A solution to one of AI’s huge problems?  Possibly, in “Big Companies Find a Way to Identify A.I. Data They Can Trust” (Steve Lohr, The New York Times, November 30^th).  That day, “a consortium of companies (released) standards for describing the origin, history, and legal rights to data,” along with “intended use and restrictions.”  The limitations seem a way of stifling unwanted findings, but the first part appears mandatory – but what about data already incorporated?

“AI microdosing” (Drake Bennett, Bloomberg, December 1^st) presented a comparison with recent experiments in doing that with hallucinogenic drugs, suggesting that the software be allowed tiny but real hallucinating capability, as “imagination – at the margins – is hard to distinguish from” that.  Reasonable, but first we need to get better control over the current state of that problem.

Back to organization, we saw “How Nations Are Losing a Global Race to Tackle A.I.’s Harms” Adam Satariano and Cecilia King, The New York Times, December 6^th).  Mainly that’s slow execution on regulation, as “A.I. systems are advancing so rapidly and unpredictably that lawmakers and regulators can’t keep pace.”  So why can’t they focus on, say, ChatGPT, as it’s obtainable and in use now?  They may need to react to other products as they come out, but until they do emerge, we need to concentrate on what we actually have.  Similarly, from the same date and the same publication, “Experts on A.I. agree That It Needs Regulation.  That’s the Easy Part” (Alina Tugend).

The sort of thing we would do well to see more of was the focus of “Microsoft and labor unions form alliance on AI” (Jackie Davalos and Josh Eidelson, Benefit News, December 11^th).  The software company “will provide labor leaders and workers with formal training on how artificial intelligence works,” but not until a year from now, and both sides will be “incorporating worker perspectives and expertise in the development of AI technology,” along with “helping shape public policy that supports the technology skills and needs of frontline workers.”  The idea’s implementation success, of course, is unknown.

Finally, “Should A.I. Accelerate?  Decelerate?  The Answer Is Both” (By De Kai, The New York Times, December 10^th).  This is partisan political complaining about the technology being used “to amplify polarization, bias and misinformation,” that “A.I.’s are manipulating humanity,” and so “we need to decelerate deployment of A.I.’s that are exacerbating sociopolitical instability.”  Unfortunately for the author, companies have their own agendas.  Develop your own product and you can direct it as you want.  Until then, we need to be personally responsible for what we believe.  And artificial intelligence will wander into 2024 with its massive achievements, and disasters, still in the future.

From 2023 Into 2024: Nine Areas of Jobs and the Economy

How did this year turn out with economic and employment Issues?  What is likely in the next?

I can only go so far with the latter, as a lot can happen, especially in a year with an unusually critical presidential election.  But we are now heading in some direction with each of these nine areas, and so can say something.  I also feel confident about making annual predictions, as I was in a small minority of economists expecting no 2023 recession.  Will I do as well in 2024?

The first area is employment statistics and the American Job Shortage Number, or AJSN.  From November 2022’s Bureau of Labor Statistics Employment Situation Summary data to a year later, we added 2.79 million net new nonfarm payroll positions.  Since our population, including children and those not wanting to work, rose by 2.43 million, that’s tremendous.  Seasonally adjusted and unadjusted official joblessness went from 3.7% and 3.4% to 3.7% and 3.5%.  The adjusted total number of unemployed increased from 6.0 million to 6.3 million, with the count of long-term jobless, or those out for 27 weeks or longer, holding at 1.2 million.  Those working part-time for economic reasons, or keeping less-hours positions while thus far unsuccessfully seeking full-time ones, gained 300,000 to 4.0 million.  The labor force participation rate jumped 0.7% to 62.8%, and the employment-population ratio grew 0.9% to reach 60.8%.  Average hourly private nonfarm payroll earnings grew $1.28 or 4.2%, more than inflation, to $34.10.  The AJSN showed that latent demand for work fell 155,000 to get to 15.646 million.  Overall, though there were some unfavorable gains, these numbers remain strong.  Expect more of same next year, with continued unemployment below 4% but fewer new jobs.  That would again be excellent – and still recession-free.

Second, we have four-day workweeks.  Per my December 1^st post, I see no progress on pertinent questions that must be answered, such as salary amount change, idle time during workdays, no Friday equivalent, and, most importantly, what a switch to 32 nominally scheduled hours would mean for workers now putting in way over 40.  I see interest fading in this option in 2024, with other alternatives, such as flexible hours and hybrid work, to get its adherents.

Third is autonomous vehicles.  This has been a terrible year for them, with gains approximately offset by San Francisco rollbacks caused by traffic and emergency interference.  It has seemed clear since at least 2021 that there will be no imminent large-scale move to them, but even slow growth was lacking in 2023.  The next will be a critical year for the technology – look for some retrenching and some new locations and applications, but strictly incremental progress.  How 2024 turns out will define where fully driverless cars, buses and trucks will go, which could be back to widespread hopes, steady and slow proliferation, or near-extinction.

The fourth area is electric vehicles.  Strangely, 2023 was both very good and very bad for them.  It was a success since one million were sold in the United States alone, and they made up 7.5% of November-to-November sales, a massive increase.  The bad news is in the title of the source article for these facts, “The electric vehicle math isn’t adding up, with average transaction price around $50,000 and gas price nationwide falling to $3 a gallon” (Alexa St. John et al., Fortune, December 7^th).  With charging stations becoming available in almost all areas with high demand, a high share of those who wanted them have accepted their shortcomings and bought, whereas those less interested are, if anything, becoming even more unlikely to buy.  Being forced to cheer for higher oil prices is a hard position to maintain, and fundamental sale price drops may require more to be sold than the market can support.  I predict that by November 2024 the share of electrics as American vehicles will be higher than it is now, but only about 10%, with a growing consensus that under current conditions they will not be completely or even largely taking over.

Fifth, I give you artificial intelligence.  In February, I wrote that “we’ve been sort of stunned by ChatGPT’s recent exploits, which not only suddenly forced people to adjust their methods but solidly moved AI from the future to the present.”  To what extent has this continued?  AI was in use well before then, and there have been some currently running achievements and improvements, particularly in the automotive field, but for various reasons over these past ten months we have seen only small, incremental effects on most American’s lives.  When I posted a promotional message about my latest AI post, “Artificial Intelligence is an Awfully Wobbly Juggernaut,” documenting lack of broad-based progress, a former Silicon Valley worker sent me 18 points to be intended to be to the contrary.  I counted only four actual applications new since February, along with three already in place before then, eight on business deals and technical achievements focusing on the future, and three claiming general large-organization use.  While it is beneficial for those developing technology to focus on the future, it is necessary also to see what has actually been completed and how it measures up to projections.  The problems I named in the August 25^th post as causing AI to be “boxed in” – dishonest employee use distorting results, feeding on its own errors by reading in AI-generated erroneous information, the looming new-data shortage, copyright violations awaiting legal judgments, chip shortages, the uncertainty of coming regulation, and the gigantic cost of future releases, along with reasonable and unreasonable fears about it and a consistent lack of will in enduring temporary problems to implement major technical and logistical improvements – are all still valid, and will probably truncate AI’s effects.  I expect that while in 2024 there will be many more AI-enhanced niches, its overall effect will be more modest than that of mobile phones, with the world-conquering fears and sweeping expectations becoming far rarer.

Sixth is remote work.  This year it met with great resistance, as the pendulum on which its enthusiasm has swung for 30 years moved away from it.  As I have written, businesses often learn little from experiences, and when they again discover the advantages of either working from home or working from the office, they do not remember what went wrong or right before.  There are two sides to the issue, meaning that putting in time remotely is not a panacea, and will not take over.  I project non-office workdays to slightly decrease in 2024, with de facto industry standards calling for few employees in most fields to be granted more than one per week.

Seventh I move to interest rates.  It was an event when on Wednesday the Federal Reserve not only held them the same as expected but announced that they projected cutting interest rates three times next year, and the Dow Jones Industrial Average jumped over 500 points and hit an all-time high.  But how can they attach any conviction to that?  Did they anticipate in December 2021 that a year later the federal funds rate would be almost 5% higher?  They carefully consider recent inputs, weigh a range of factors, and only then decide – and we should all be glad that their 2022 choices turned out that way.  Whether they reduce rates three times, eight times, or not at all in 2024 will depend on data we don’t yet have and can’t really estimate.  I predict that we will indeed pay less for money in a year, but only about 1% or 1.5%, and I certainly am not confident enough about it to even pencil that in.

Eighth, how about investments?  I don’t have much to say here.  Predicting a massively profitable 2024 is unjustified.  There are a lot of problems in the world, and we may add one of our own in November.  A historically justified 5% gain in general seems as good a projection as any.

Last, public beliefs on the economy.  There has been a string of articles discussing that as if it were a problem of its own, and to some extent it is.  Many people are less happy about our economic times, most of whom are influenced by not knowing firsthand what a real recession is like or following the stated views, designed to affect voting, of their political party.  It is easy to take bad individual experiences, such as being fired or not hired, as reflecting everyone’s condition.  I predict that, by year’s end, people’s opinions will be more in line with reality.  That’s optimistic, but irrationality often corrects itself.

For more information on these areas, see other posts in this blog.  With that, here’s to a prosperous 2024, especially for you and your family.