First-time readers, the dialogue in this blog is set in the future (sometime after the year 2020).  Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution.  More about Revenge Revolution and author, Entry #1.  List and general description of entries to date.  Annual assessment if Revolution plausible.

Note: most characters appear in a number of entries, with many entries building on previous conversations.  Profile of characters.  You’ll catch on quickly.  Thanks for your time and interest…and comments.

Scene: Gelly, Jordan’s assistant, has been editing and updating a primer Jordan wrote about 2011.  Section starts Entry #235.  (Primer will be available as PDF in more traditional format after Chapter 5 or 6.  Then the primer download will be updated regularly.) 

Gelly: “Jordan, my apologies.  I’ve fallen behind on editing the primer.  I’m working on catching up but it might be another week or so .”

Jordan: “No apologies necessary. We both took a week off from the business.  And, yes, I’m behind on some of my work as well.  What’s the topic of the next chapter?”

Gelly: “Seasonally adjusted annual rates and trends.  I confess, it was not a topic that gave me goosebumps.  However… ”

Jordan: “I take the ‘however’ to mean it wasn’t so boring.”

Gelly:  “Actually, it was interesting.  Now, I think I understand what it’s all about.”

Jordan: “Good, let’s see what you think we should publish.”

———— CHAPTER 5 ————-

If you thought Chapter 4, the write-up on unemployment was confusing, go grab a coffee. The concept of seasonal adjustments is widely used…and also widely misunderstood.

Economic data are frequently reported as being “seasonally adjusted” and equal to an “annual rate.”  Just what does that mean?  A “seasonally adjusted annual rate” (aka, SAAR) is an attempt to predict what sales would be for an entire year, recognizing that sales for many products vary month to month and are not simply 1/12 of the total for the year.

Two examples:

1. Sales of gift items are higher at certain times of the year – Valentine’s Day, Mother’s Day and especially leading up to Christmas. Sales of these-type items might be very strong one month and fall-off sharply the next month, or months because of the “pull-ahead” effect. The term “Black Friday” originated in the retail business because the Friday after Thanksgiving is when retailers usually began making money for the entire year, or as accounts say “going in the black.”  These monthly swings in sales make it very hard to gauge whether sales are headed up or down.  Without some sort of “seasonal adjustment,” a manufacturer or retailer might view lower sales in January vs. December as negative when in fact the sales pattern might be improving.  The seasonal adjustment attempts to “normalize” sales for the month.
2. Sales of cars and trucks in the US are lower in the winter months as people spend money on Christmas gifts and delay buying new cars/trucks during inclement weather. Thus, sales of cars and trucks in the winter – and then the spring – need to be “seasonally adjusted” to help gauge whether sales are trending up, down or staying about the same.

Seasonal adjustments are often based on averages of actual data over a given period – say 5-10 years.  Because of changing economic conditions, sales activity in any given year probably will be somewhat different from the “average” sales pattern.  Adjusting the data for individual months or quarters can help determine sales trends.

Calculating Seasonal Adjustments.  While there are some sophisticated techniques to calculating how each month should be adjusted, the reality is for many users there are no published seasonal adjustments.  To create your own seasonal adjustment, start by making a table with at least five (5) years of sales data by month.  If you have 10 years, great.  More than 10 years, stick with 10 years for now.

Begin by adding up sales for all the January’s, then the February’s and each month of the year.  After you have totaled 5 (or 10) years of sales, then divide total January sales by total sales for all five years.  If you’re in the lawn chair business, the “seasonal adjustment” percentage for sales of chairs in January should be less than 8.33% (1÷12).  Sales of lawn chairs in June should be well above 8.33%.

To calculate the “seasonally adjusted annual rate for this year’s sales in January, simply divide sales by the January percentage (%).  If January sales in Year 6 were 50 lawn chairs and the “seasonal adjustment” percent was 3.0% (well below average), the seasonally adjusted annual rate of sales would be 1,667 lawn chairs.  If sales of lawn chairs in June were 125 (75 units higher than January) and the June adjustment percent was 12.2% (above average), the annual rate would be 1,000 units – a significant decline from the seasonally adjusted annual rate in January and an indicator that sales might be trending downward.

What Are Trends?  Would you believe someone who claimed the weather last June 12 was an indicator of what the weather would likely be for the next 12 months? In fact, most people would laugh at such an assertion. Yet, many of the same people believe a politician or talking head when single economic data-point is used to justify a claim that a particular program is working or not working.

The period for determining trends can vary.  Depending on the subject matter, reports of activity are issued weekly, monthly, quarterly and some annually. When viewing data, it is important to consider the type of data and how frequently a change becomes meaningful.

Data for weather may be the most extreme example.  Weather conditions and temperatures change daily, even hourly.  However, what constitutes a change in weather “trend”?  An early frost or a late snowfall might simply be an aberration.  But a pattern of increasing temperatures year after year after year indicates a change in the trend.

But what about trends in economic data or a company’s sales data?  How does one calculate a trend?  Are sales of lawn chairs headed up or down…or staying about the same?

Calculating a trend line can be as simple as plotting data on a chart and then taking a ruler and adjusting it so ½ the data points are above the ruler and ½ are below the ruler.  This “eyeball” method is not a bad place to start.

In this chart of lawn chair sales, the “linear” trend line — i.e., ½ the data points are above the trend line and ½ below the trend line — suggests that:

• Monthly sales bounce around…a lot
• Overall, sales are improving…maybe
• Using data for any single month is not an accurate predictor of other months

A more sophisticated method to fit the data is called “exponential fitting” (think of compound interest rates on your savings). For many sets of data, using an “exponential” trend line provides a more accurate picture of the results. Using an exponential fit, the trend line indicates sales of lawn chairs are flat to falling compared to rising sales using a simpler liner trend line.

While the differences between the linear and exponential lines may not seem significant, if you were in charge of manufacturing for the lawn-chair company, the difference could change your decision. If you looked only at the data using a linear trend, you might add to the production schedule, assuming that sales were likely to increase. However, if you looked the data fitted exponentially, you would not add to the production schedule and might even consider reducing the schedule.

There are several credible methods to calculate trend lines. If you use Excel or a similar program, most have formulae built into the program. Sometime you will also hear these methods referred to as “regressions.” If you decide to use more sophisticated regression techniques to calculate trend lines or “fit the data,” and have not completed college-level statistics – or do not remember – I suggest you read at least two articles on the plusses and minuses of the best approach for a particular task.

Trend lines, aka regressions, can be extremely useful when looking for patterns. When I was a grad student at MIT, there was an oft repeated saying among the professors, “When in doubt run a regression.”

The “when-in-doubt” advice was sound and has served me well over many years in many different jobs and in addressing many different problems. Regressions and trend lines help you create some order out of chaos.

The seasonally adjusted annual rates and the trend lines described in this section can help reduce the risk of making a terribly wrong decision. Try both approaches individually, and then in combination.  I think you will find the approaches very useful.  Just do not make the analysis too complicated.

 

First-time readers, the blog is usually constructed as a dialogue between characters.  The dialogue is set in the future (sometime after the year 2020) and assumes there has been a 5th revolution in the US — the Revenge Revolution.  More about Revenge Revolution and author, Entry #1.  List and general description of entries to date.  Annual assessment whether Revolution plausible.

Note: most characters appear in a number of entries, with many entries building on previous conversations.  Profile of characters.  You’ll catch on quickly.  Thanks for your time and interest…and comments.

Special 2016 Year-End Review.  Is the premise of this blog realistic?  Is the US headed for a 5^th revolution sometime after 2020 – the Revenge Revolution? Or is the premise more like “fake news,” which became so prevalent leading up to the election and continues today?  The blog about a 5^th US revolution, the Revenge Revolution, was first published in late 2013 – before the campaign for the 2016 presidential election heated up and certainly before anyone took a Trump presidential bid seriously, including Donald Trump. 

One can legitimately argue that the Revenge Revolution has already begun — with the election of Donald Trump.  Who would have thunk  Donald Trump would replace an older, more famous Donald, let alone become president?

Yet, a large percentage of the population voted for a candidate with no prior political experience, no experience running a large organization (the Trump organization despite claims to the contrary is quite small with only about 150 staff members, including family), no demonstrated understanding of macro and micro-economics, no demonstrated understanding of international relations, no demonstrated desire to learn…and a very long record of behavior that many people characterize as unethical and even immoral.

Further, the claims by Trump during the campaign were so outlandish and contrary to facts, that by historical standards, he should have not progressed past one or two primaries.  Despite these flaws, Trump gained sufficient votes to win a majority of the Electoral College and become the president elect.  I note the Electoral College because Hillary Clinton received about three million more popular votes than Donald Trump.

From my perspective and what I find ironic, is many of the people who voted for Trump seem the most likely to initiate the Revenge Revolution.  Why?  Because the promise to those voters about returning America to the days of widespread manufacturing and mining jobs for those with limited technical skills is impossible to keep.

As discussed in this blog, I agree some of the manufacturing jobs lost in the US have been shipped to countries with lower labor costs.  But the jobs shipped elsewhere are going to suffer the same fate as many manufacturing jobs in the US – being replaced by technology. 

For Trumpsters, the reason you have a cell phone, flat-screen TV, iPad, fast internet speed and a car with a bunch of electronic do-dads, is the same reason there are robots doing many of the jobs in the  manufacturing and mining sectors (and other sectors as well) formerly done by semi-skilled and even some skilled labor.  As unpleasant as this might be for Trumpsters, your vote does not count whether your job is replaced by a robot.  You have about as much influence on the fate of your job as 100 years ago when horses couldn’t vote whether families bought a horseless carriage.

In addition, while waiting for the non-existent manufacturing jobs to return, the Trump Administration will likely attempt to dismantle or restructure the basic financial foundation for many retirees – Social Security and Medicare. Although efforts to radically change Social Security and Medicare seem unlikely to succeed, the mere attempt will create widespread anger among today’s Trumpsters.

A few more reasons of a long list why the Trumpsters…and others…will become increasingly incensed.

·         Cabinet appointees.  Many appointees have no experience running a large organization, public or private.  Further, many appointees were selected because of intense opposition to the purpose of the agency – Education, HUD, HHS, EPA, Budget, Interior, etc. 

·         Financial conflicts of interest.  Several cabinet appointees as well as Donald Trump/Trump family are likely to be charged with significant financial conflicts of interest.  Many of the people who voted for Trump because of alleged financial conflicts of interest by Hillary Clinton and the Clinton Foundation, will eventually tire of the claims that (i) the president cannot have conflicts of interest and (ii) charges of conflicts by cabinet members are being fabricated by Democrats and the media.   The conflicts in the Trump Administration are likely to be so blatant that even the most ardent supporters will be angered.

·         Irrational behavior by the president on a number of fronts – nuclear weapons, trade agreements, economic policy are part of a long list.  The challenge to other countries of trying to outmatch the US with nuclear arms will be the turning point for many older Trumpsters.  These Trumpsters remember as children there was widespread fear in the US of a nuclear holocaust. 

·         Unbecoming boorish behavior by the president, his direct staff and some cabinet members.  The public and even the Republican members of Congress will tire of tirades by the president and staff over even the most minor criticism.   The American people want the president and staff to be role models and act like adults, rather than petulant 4-year olds…or even worse, neighborhood bullies.

One final thought…and I’m unsure if the event will have any effect on the likelihood of a Revenge Revolution.  To me it is unlikely Trump will finish a 4-year term, whether the term ends because he is forced from office or incapacitated, physically or mentally.  If Trump leaves and Mike Pence assumes office, there will be little calming of the unrest among the populous since many voters consider Pence more radical than Trump.  Even if Pence is more moderate than Trump in the attempt to restructure agencies and programs — Social Security, Medicare, etc. — his policies will be unable to fulfill many of the campaign promises made to Trumpsters, especially bringing back manufacturing jobs.

Throughout history revolutions have been caused by extreme frustration among the populous.  Repeatedly over-promising and under-delivering, especially to ardent supporters, is a sure recipe for creating extreme frustration…and the Revenge Revolution.          

Note: after this segment was written, I decided to write another segment about a possible Revenge Revolution.  The segments are not continuous but complementary.             

First-time readers, this blog is set in the future (sometime after the year 2020).  Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution.  More about Revenge Revolution and author, Entry #1.  List and general description of entries to date.

Note: most characters appear in a number of entries, with many entries building on previous conversations.  Profile of characters.  You’ll catch on quickly.  Thanks for your time and interest…and comments. 

Scene: JC, Greenie, and Jordan sitting outside at a restaurant near Jordan’s office.  Conversation starts #169.

Greenie: “The story of Big Cat Clydesdale is fascinating. I would have loved to meet him. But I have a question.”

Jordan: “About Big Cat?”

Greenie: “More ethereal. Before you got those calls we were talking about the galaxies and the possibility of life on other planets…and other stuff. So, my question is when the physical body dies, where does the soul go?”

Jordan: “Not a new question but still a great question. Where does the soul go?”

JC: “Are you implying the soul might be connected to a 4^th or even 5^th dimension?”

Greenie: “You know there’s a 5^th Dimension – ‘Age of Aquarius‘, ‘Wedding Bell Blues‘ and a bunch of other really good songs”

JC: “Seriously, you think there is a 4^th or 5^th dimension?”

Jordan: “Yes, too many unexplained phenomena. What about your father visiting you that one night? And he’d been dead what, more than 20 years?”

JC: “He also visited my brother the same night, except my brother was about 1,000 miles away from where I was. I’m telling you guys that visit was real…and a bit scary in retrospect, although interestingly I was not scared at the time. It was really nice to see my father again.  The other strange part of the visit was he was dressed as if he were in his early 30’s.”

Jordan: “I’ve never doubted your story. Most people, I think, have some experiences that just cannot be explained logically.”

Greenie: “Far be it from me to claim any scientific credentials but I understand some physicists are beginning to offer credible theories about how a 4^th and 5^th dimension could exist. Don’t ask me to explain the theories they seem plausible.”

JC: “Where is this conversation headed? Does it really matter where the soul goes? And, besides, who knows?”

Greenie: “JC, what’s happened to your intellectual curiosity? You been hanging around with some right-wing Republicans?”

JC: “You know that’s not the case. Maybe my curiosity is having a bad-hair day. But I admit the visit from my father was intriguing then and remains so today.”

Jordan: “What I find even more fascinating is your father visited you and your brother the same night.”

Greenie: “Me, too. I’ve forgotten how you found out that he visited your brother…because he never told you, right?”

JC: “He never told me. My sister-in-law told me, but only after I asked her an indirect question.”

Greenie: “Which was?”

JC: “I merely asked if anything unusual happened during the night of I think it was April 8^th.”

Greenie: “Her response?”

JC: “Big, wide eyes and flushed face. Then she told me the story my brother told her. The stories paralleled. It was only after she finished did I gave her any details of my experience.”

Greenie: “An amazing story. If I didn’t know you so well, I might not believe you. The visit obviously had a lasting impact…and the visit was about 10 years ago?”

JC: “OK, guys, I’ve changed my mind. Asking where the soul goes is a great question. But what if we had the answer? What would we do with it?”

Greenie: “You know, we probably have the answer right in front of us. But just haven’t opened our eyes to see it.”

JC: “That sounds like some story out of the Torah. Just open your eyes and look. C’mon guys, you seem to be off in the weeds…or maybe smoking weed…or both. How will we ever know where the soul goes?”

Jordan: “JC, just step back for a second. Greenie’s point is well taken. I’ll bet the answer is staring us in the face. And, aside from some Ultra-Orthodox fanatic, most people consider Torah as leading one on a spiritual journey. If you view Torah as a spiritual journey, then there’s probably more truth than fiction to ‘opening your eyes.'”

JC: “I’m still not sure what this conversation means but I am reminded of a cartoon I saw years ago.”

Jordan: “Must have been from the New Yorker. Only guys remember cartoons from Playboy.”

JC: “Probably the New Yorker. Anyway, this guy has died and now in line to get admitted to heaven. And Saint Peter…is Saint Peter the maître d’?”

Greenie: “I think so but it doesn’t matter. Keep going.”

JC: “Saint Peter points to a cute little dog and says, ‘…Rex here has been going on and on about you for the last 50 years.'”

Jordan: “See, JC, now it is important to know where your soul goes. I could see my dog from when I was growing up. She was one of the smartest dogs I’ve ever met.”

JC: “Greenie, that might be one of the few times he’s admitted women are smart. Let’s take a break.”

Jordan: “What did I do to deserve this treatment? OK, let’s break.”