Electronics: So What Exactly Happened Circa 2000?

Herewith a graphic showing what has happened to the major components of our domestic electronics industry—thus semiconductors, computers, computer peripherals, and telephone apparatus. I’ve derived these data from the Economic Census conducted by the Bureau of the Census in years ending in 2 and 7—and for other years the Annual Surveys of Manufacturing also conducted by the Bureau. Thanks to the shift from the old Standard Industrial Classification (SIC) to the North American Industrial Classification System (NAICS), comparable data for some industries cannot be obtained for the pre-1997 period, but where available, I show them. Here is the graphic:

What happened, exactly, is that circa 2000 we reached what might be called Peak Electronics (on the analogy of Peak Oil). We stopped making most of the products we buy at home and began to consume the same products but made elsewhere in the world.

The only trend line still pointing up, but almost flat, is the trend associated with semiconductors, but that trend appears also destined to decline. The major product categories that depend on electronics are all headed for de facto extinction as domestic products—and the employment associated with them is therefore heading for what? Part time work in retail?

What is still climbing is software—and that with barely so much as a hiccup during the Great Recession. It’s the silver lining, you might say. And arguably technological innovation in electronics is also still firmly in our domestic grasp as well, but no sooner perfected on paper and in the lab, it gets shipped overseas for manufacturing. But here, as in other regions of our economic life, the beneficiaries are relatively small domestic elites while the ordinary people are sliding slowly toward the Third World.

I am a holdout. I am against globalism, for a National Economic Policy. We must protect jobs locally. And it won’t happen if we let whole industries just disappear without a single political murmur.

Cyber Madness

I am looking at a Staples ad sent me this morning. It says:

Cyber Monday Event

Starts Sunday!

Black Friday was really Black Thursday. Now Cyber Monday is on Sunday. I’m not, by the way, trying to single out Staples for scorn. It’s the same all over. Every seller has drunk the poisoned water. They’ve all gone mad.

Staples’ promotion is centered on laser toner, more specifically on Hewlett-Packard toner. It happens that I use that product. So let me see how good the deal is. Well, I can get $30 off if I buy $200 worth of HP toner—or $20 off if I spend $150. The toner I use costs, at Staples, $109.99. In either case I’d have to buy two cartridges to get a discount. But a cartridge lasts me several months, so why bother? And the discount is relatively small, 13.6 percent ($30 off $219.98). Toner is supposed to have a limited shelf life, but I don’t know how long that is. In effect I’d be taking a chance storing one for a long time for a relatively small discount.

The whole premise of the modern economy is to sell consumers more than they need. To have a rosy future, we must over-consume. Systematically promoting that is madness.

It’s strange to live in a culture the core premise of which is systematic undermining of rational frugality. 

December Retail Sales

Back in 2009 I posted data on percent change in retail sales, December to December. Back then the last hard data point was for 2008, showing a huge dip. You can still see that post on the old LaMarotte (link). I thought I would update the graphic. The source for it is a tabulation by the Bureau of the Census (link).

The updated graphic, together with a projection (in red) showing what might happen next month is below:

The graphed data show changes in total retail sales, December to December, from 1992 through 2010. The value for 2011 is a projection of the trend shown earlier. We begin in 1992; the change in that year, therefore is zero; but for all other years, I show the change from the previous December. To this I have added a trend line, courtesy of Microsoft Excel. The conclusion is that growth in retail December to December is definitely trending down, but this down-trend is entirely due to the severity of recessions. Just to check on this, I tried making the 2007-2008 recession milder; thus I assumed that the change, 2007 to 2008, would be a mild growth, about 3 percent—rather then the nearly 13 percent dip. In that case the trend of this series is flat for all practical purposes. The illustration of that is inserted as a smaller graphic on the left; 2008 is “corrected,” and I’ve only plotted through 2010, thus only using actual data.

Let’s face it. December is the nation’s big shopping month. This pattern only weakens when the economy is really diving into the sand, as it did in 2008. In this period two recessions took place: March to November in 2001 and December 2007 through June 2009. The public felt both of these coming—and curbed its spending. But the last one was severe, and people really sat on their wallets.

More October-November Retail Stats

Yesterday I showed retail sales for two categories (all retail and general merchandise stores) for three years (1992, 2002, and 2010). Today I am showing data on October and November sales for the same two categories and for every year in the 1992 through 2010 period.

My object, of course, is to throw some light on Black Friday, the day when, based on the retail industry’s experience, retailer begin to turn a profit for the year. My focus is on the general trend, and the graphics today do a better job in illuminating which way things are trending over an eighteen-year period. Here are the two charts:

What these patterns shows is that the October-to-November jump in sales is much more important for general merchandise stores than for retail sales as a whole. The latter have much bigger gains in this month, averaging 16.8 percent over the period versus retail as a whole, averaging 3.4 percent. The trend in month-to-month percentage gains is down in both cases, but the decline is much more pronounced for the general merchandise stores.

By way of contrast, the following graphic shows the same patterns for book stores. The performance of these retailers falls somewhere midway between all retailing and merchandising stores. The average percentage jump in sales, October to November, is better than for retailing as a whole, thus 5.3 versus 3.4 percent—but less than shown for general merchandise stores. And the trend, it turns out, is flat.

So what do we make of these trends—particularly the smaller-and-smaller jump in retail sales, October-to-November, experienced by general merchandise stores. Behind that trend, I propose, lies another and much more pervasive one. It is the gradual blurring of once much more sharply defined retail categories. Consider, for instance, that the largest grocery store in the United States is Wal-Mart. But for purposes of reporting, the Census Bureau categorizes Wal-Mart as a general merchandise store (NAICS 452910) whereas the Bureau places Kroger into the supermarkets and other grocers category (NAICS 445110). Wal-Mart-owned Sam’s Club has been featuring groceries since 1983; regular Wal-Mart stores have sold food at least since 1990, the year Wal-Mart acquired McLane Company (which it later sold), a grocery and food distributor. I am tentative about the date because I cannot discover exactly when Wal-Mart began selling groceries; maybe it always did. At present, according to Wal-Mart, half of its revenues are derived from groceries. Have they always? And under a 2010 program the company is restructuring small stores to be principally grocery stores.

Now, mind you, other major general merchandise stores are also selling groceries. One thinks of Costco and other warehouse clubs. And so are Kmart, Sears (which is owned by Kmart), Meier, and Target. So also are drug stores, for that matter. This is what I mean by a fuzzing of the definitions.

Quite possibly the ever smaller sales jumps of general merchandisers in November have something to do with internal shifts in the share of the product lines that they carry. As these stores come ever more to resemble “all retailing,” so also will Black Friday gradually grey out.

Some “Black” Perspectives

Black Friday, this year, begins in the evening of Turkey Thursday, and the smell of our retailers’ tangible hysteria almost hides the pleasing odors of that roasting bird. I thought I’d look at retail sales by month and see what the pattern looks like for some years going backwards.

Here is the first such chart. It shows all retail sales by month, excluding only motor vehicles and parts.

There is certainly a “lift” in sales between October and November in the three years selected, 1992, 2002, and 2010. But the real lift actually comes in December. What color do we paint the last month of the year?

The increase in sales, while meaningfully present above, is not exactly dramatic, of course, while the sales-leap in December is. I thought I’d look at a narrower segment, General Merchandise Stores. Here is the graphic for these:

General merchandise stores certainly show much sharper increases than retail as a whole. In 1992 all retail increased (October to November) by a mere 1.6 percent; general merchandise store sales increased by 19.3 percent! So that’s where we really get this new way of celebrating Thanksgiving.

An interesting phenomenon now appears. As we advance in time, the monthly growth rates experienced by general merchandise stores decline. In 2002 they advanced 17 and in 2010 only 13.2 percent. Meanwhile all retail (ex automotive) increased from the 1.6 percent base in 1992 to 3.9 percent in 2002 and 4.4 percent in 2010. All retail, of course, includes the general merchandise category. The panic seems to relate more directly to people who sell special goods that, perhaps, are more discretionary.

What will 2011 bring? It will be interesting to see. And we can be sure the results will be very well reported—because the holidays, these days, mean shopping. And little else.

Cheap Shot

Looking at a timeline for computing on Wikipedia (here), I came across this quote for the year 1977:

There is no reason anyone would want a computer in their home.

The person quoted is supposedly Ken Olsen, founder, president, and chairman of Digital Equipment Corporation. I stared at that for a moment. The first thing that bothered me was that revealing “their.” This is 1977, I thought. Back then people had not yet succumbed to the disease of gender-neutral PC newspeak. My next thought was that Ken Olsen was no dummy. Apple had been launched the year before—and behind it a rather sizeable cloud of amateurs building little personal computers. And Commodore had already launched its first little computer too, dubbed PET (for personal electronic transactor). So I went on a search. One thing that the Internet age has taught me is that you do not automatically believe what you read on a screen. Sure enough…

What Olsen had said, in an address to the World Future Society in Boston, was “There is no reason for any individual to have a computer in his home.” Notice that “his.” And the context was quite different. I learned from Snopes.com, “Rumor Has It” (link), that Olsen’s context was a computer installed to control every function of the residence, “turning lights on and off, regulating temperature, choosing entertainments, monitoring food supplies and preparing meals, etc.” Snopes quotes Olsen himself saying later was that this interpretation

…is, of course, ridiculous because the business we were in was making PCs, and almost from the start I had them at home and my wife played Scrabble with time-sharing machines, and my sixth grade son was networking the MIT computers and the DEC computers together, hopefully without doing mischief, using the computers I had at home.

Now, amusingly, Snopes itself gives no attribution for this quote beyond saying: “As Olsen later noted…” Sloppy, I would say. The truth of the matter is, the information is out there, but it’s best to trust—but verify.

Michigan as a Country

Michigan has a population of 9.88 million. Got to wondering where we might fit into the list of the world’s genuinely sovereign countries? Well, Michigan would be sandwiched between Hungary and Somalia. Herewith a little table:

	Population	GDP (in $ billions)	Per capita income ($)	Land Area (square miles)	Water as % of land area	Density (people per sq.m)
Hungary	9,985,722	128.960	12,879	35,919	0.74	279
Michigan	9,883,640	326.123	25,172	96,716	41.5	102
Somalia	9,557,000	5.896	600	245,200		6

I was born in Hungary. Looks like the move to the United States gained me income, land, and water. The dice-roll of fate…

I might do this for other states in the future as well. Candidates are Missouri, California, Texas, Minnesota, and New York...

SME: Profile of a Globalizing Industry

Working on another project, I chanced across some data on the Semiconductor Manufacturing Equipment (SME) industry. In 2009, the last year for which we have hard Census data, it was 5.6 percent of the $98.3 billion domestic electronics industry, at least as measured in shipments. Herewith a profile of it from 1992 through 2011:

This industry makes the tooling for other sectors of the electronics industry. Thus in a sense it stands in relation to electronics as a whole like the machine tool industry stands in relation to all manufacturing. Electronics got its start in 1958 with the invention of the integrated circuit; a decade later Intel was launched. This fundamentally American technology has been globalizing, globalizing, globalizing—and what that means for the domestic industry is plainly visible in the graphic above.

Now, of course, we’re looking at what is undoubtedly a natural phenomenon, if our faith in the Hidden Hand is unflagging. Indeed, with the very best of efforts, technologies can never be held close and protected from spreading around the globe. But the downward trend visible here also represents employment decline from 81,900 people in 1992 to 19,362 people in 2009. This illustrates the inherent conflict that arises when we let nature take its course on the one hand and protect the domestic employment on the other. At best, of course, we can only slow things down.

Japanese Method for Pulling Square Roots by Hand

Take two, you might say. An earlier post introduced this method (link), but while it is perfectly correct as far as it goes, it actually provides a German version of how to solve the problem of squaring. I learned of the Japanese method from Murai Takayuki. A second set of message from Murai finally enabled me to see how the Japanese actually do it. It is presented here. The example I shall use is to calculate the square root of 99—which presents problems when using the German mehod I described earlier.

The Japanese method involves a two-column approach. Calculations on the left side provide inputs for the division-like calculation on the right side. We also obtain successive digits of the actual answer on the left side. The following illustration sums up the method. Click to enlarge, press Esc to return:

As explained in the earlier post, the number is arrayed in digital pairs. The decimal point, if any, must fall on one of the spatial divisions. Therefore, the number 3.099, for example, must be divided 03 . 09 90 not 3.0 99.

The core of this process is the method by which the digits are determined. In the earlier post, showing the European formula instead of the Japanese (e.g. 18 *  ≤ 1800 explained above), two equations are used to calculate first the next digit of the Answer and the sum to be deducted from the last Remainder. Let us take the case, above where the first 4 is obtained. Using the Japanese method, we set up 198 *  ≤ 9900. We can start with the highest digit, 9. Therefore we get 1989 * 9 = 17901. That’s too big. Next we might try 5, therefore 1985 * 5 = 9925. Still too big. The next attempt, with 4, will succeed: 1984 * 4 = 7936. That’s quite simple. We get, at once, both the next digit of our answer, 4, and the sum to deduct, 7936.

The European method begins with a division. The last Remainder (9900) is divided by a number constructed by multiplying 2 * 10 * the already calculated Answer. In this case that number is 99, and 99 rather than 9.9 because the decimal is ignored. 2 * 10 * 99 = 1980. Then 9900 / 1980 = 5. Next we test that number. We take (1980 + 5) * 5 = 9925. But that number is too high. Therefore we reduce 5 by 1 to get 4. Next we apply the new number, thus (1980+4) * 4 = 7936.

As is evident, this process is much more complicated than the method Murai suggests. We have to engage in double-column bookkeeping, to be sure, but everything is clearer, and the procedure is much simpler.

Nice, handy method, readily used with a sheet of paper divided in two and a hand calculator.

For those able to read Japanese an excellent tutorial with live demos is available here from suguru.jp. Google will translate the Japanese into English. The result is so-so but one can make out the sense and follow the numbers.

Thanks Murai. This has been a lot of fun.

Square Root Extraction the Japanese Way

A comment came today from Murai Takayuki (村井　剛志) in comment on my piece on calculating logarithms by hand. In that post I suggested that a certain weariness also accompanies pulling square roots by hand. Murai wrote: “In Japanese schools we learn a method resembling long division for finding square roots by hand. If you haven't ever heard about this method I would love to tell you about it!!” Now it turns out that I’ve also published here a relatively easy method (link), but I’m always game for new ways—hence I asked for enlightenment and immediately got it by a returning e-mail. The missive took the form of two images. You can see one of them here on the left. Clicking through it will make it big; Esc will bring you back. Murai’s accompanying instructions, alas, were pretty brief: “I think you can figure out how it works with these two images.” I was flattered but baffled. Now it so happens that at least 65 years have passed since I was in school and learning such things; therefore I utterly failed to grasp the progression of numbers. English language web sites all flunked too—as indeed I had expected them to do. Then a brilliant notion came. I tried a web search in German and rapidly found multiple sites able to give me what I needed. As in Japan, so in Germany. Herewith, therefore, the results. (Mind, I could have asked Murai to help as well, but I thought he’d already done enough.) So let us take the problem presented in that image. The other JPEG Murai sent is much the same. In that one the square root of 5 is pulled using the method I describe below.

We want the square root of 628.5049. The first step is to divide the number into pairs from the back as follows:

06 28 | 50 49

The first step is by eyeballing, the other steps are by using two formulae.

Step 1: Determine the closest square to the first group. In our case that is 4, 2*2. The root we used is also the first digit of our answer.

Step 2: Deduct the actual number from the first pair, thus 06 - 4. Next pull down the next pair of numbers awaiting action and place them alongside. Here is how it looks:

Note that the root of that 4 is now the first digit of our answer, already in place. The \/ symbolism ahead of the first digit is meant to represent the square root symbol (√).

Step 3: This step and all successive iterations have the same requirement. We want to do two things in this and every succeeding step, if necessary. First, we want to calculate the next digit of our answer. That is done by Formula 1:

[1] Next digit = Int(R / (20*A))

R here is our Remainder (2 28 above) and A is our current Answer, thus the 2 following the equals sign above. The Int means that whatever answer we get will be only the integer part. In this particular instance the formula fleshes out as 228 / (20*2) or 228/40 = 5.7. The Int prefix renders the answer as 5. That is the next digit of our answer.

Next we want to calculate the number to deduct from our Remainder. The formula for that is the following:

[2] New Deducter = ((20*A)+L)* L

Here L is the Last digit to be added to Answer, 5 in this case. The formula fills in as follows: ((20*2)+5)*5 = 45*5 = 225. This is our New Deducter. We put it in place and add the Last digit to the answer. Here is what it looks like now:

Step 4: Notice that after deducting the New Deducter from the last Remainder, we also crossed the decimal point. For this reason we now also add a decimal point to our Answer.

The two formulae we used in the last step are employed again. Formula 1 produces zero. Here the actual numbers: 350 / (20*25) = 350 / 500 = 0.7 = 0 when chopped to an integer. That 0 is our new digit, the Last digit to be added. Formula 2 also produces a 0 as our New Deducter: ((20*25)+0)*0 = 500 * 0 = 0. Our calculation now looks as follows:

Step 5: In this case Step 5 happens to be the last. Note, again, that we have deducted the 0 and were left with the same number. But we’ve also pulled down the last pair to be considered in our calculation. And we’ve added the 0 to our Answer. Here the two formulae used for the last time:

Formula 1: 35049 / (20*250) = 35049 / 5000 = 7.0098 = 7.
Formula 2: ((20*250)+7)*7) = 5007* 7 = 35049.

Notice that in using these formulae, we ignored the decimal point in the Answer. Our New Deducter now has the same value as our last Remainder, hence we are done. In other cases we can stop as soon as we are happy with the number of digits we have produced. The final picture:

With this explanation, Murai’s presentation will become quite clear—and the derivation of those initially mysterious numbers like the 45, 500, and the 5007 will be evident. Come to think of it, the real virtue of this method is that it is very easily rendered into a quite brief algorithm in Visual Basic. Those who know that language will need no help from me in writing the subroutine.

Added later: In playing with these algorithms, I discovered an interesting problem when applying it to the square root of 99. The layout then is the following:

\/99 | 00 00 00 00 00 = 9
     81
  18   00


The nearest square to 99 is 81. That leaves 18, and the first digit of our answer is 9. Adding two zeroes to the Remainder, we get 1800. Then, applying Formula 1, we get 1800 / (20 * 9) = 1800 / 180 = 10. But the square root of 99 is actually 9.94987… per Texas Instruments calculator. Therefore Formula 1 seems to misfire. The rule here appears to be that if the answer to Formula 1 is 10, it must be reduced by one. If we make that adjustment and proceed to the next step using 9 instead of 10, the answer comes out correctly. But my sources do not mention this rule. Perhaps Murai can come to our rescue…

Added Even Later: I received appropriate instructions from Murai Takayuki. The method finally makes sense. To make it plain I provide a new post (link) titled “Japanese Method for Pulling Square Roots by Hand.”

Employment Change by Sector, September-October 2011

Herewith the details of employment change by sector. The familiar pattern once again repeats with some mildly positive changes:

Last month Construction was negative and Manufacturing positive. Now the results have been reversed. Last month Wholesale, Transportation, Finance, and Leisure were in the red, this month they are positive. But Information, which had been positive has now gone red. And Government, which showed a loss of 33,000 jobs, this months shows a lesser loss of 24,000 jobs.

Herewith some additional notes on the Government sector. The Great Recession officially ended in June 2009. Since then Total Private employment increased by 1.5 percent and All Government lost 2.6 percent of its employment (Federal, -0.1, State, -2.2, and Local -3.2 percent; the Federal loss has been due entirely to losses by the U.S. Postal Service; other employment actually grew). The State and Local sectors together may be broken into educational employment (53.5%) and all other (46.5%). In this recent month, Federal employment dropped by 2,000, State government by 20,000, and Local government by 2,000 employees. The states thus bore the brunt of the October decline. State education declined by 4,300 jobs, all other by 15,600. Local education increased by 1,200. The two numbers for local changes don’t quite add due, no doubt, to rounding errors.

Employment: Update October 2011

The U.S. economy added 80,000 jobs in October—but that number is deceptive. The Bureau of Labor Statistics also revised its numbers for August and for September. In both cases jobs were added to the earlier reported totals. If we add the results of those changes, the total change between the last report and this one is a net addition of 182,000 jobs, 102,000 due to revisions and 80,000 due to changes in October. October data, to be sure, will also be revised before the next report is published, but the good news is that revisions, these days, are in the positive direction. The changes made are shown in the small insert graphic to the left. The results for October are presented below. Details may be obtained from the BLS press release (link). I will follow this up tomorrow with details by sectoral changes.

It pleases me that the trends are up. We’ve clocked 13 months of solid gains. Of 8.7 million jobs lost in 2008-2009, we have recovered 2.2 million, amounting to a 25.3 percent recovery in 22 months. The economy is not roaring back exactly, but it is better to employ than not to.