A Decade in Housing

One way of looking at the housing bubble is to see how much economic activity it first stimulated and how much of it we then lost. In this industry the U.S. Bureau of the Census avoids words like “shipments”—homes are not exactly shipped. The Bureau talks instead of “Value of Business Done.” Herewith then a graphic that shows this value from 1997 through the year 2000.

The big kid on the block is the single-family home, a category that also includes townhouses of the kind that, while they touch, a full wall separates the two residences from roof to the lowest basement, if any; the little brother is multi-unit residential construction; it includes apartment houses, condos, and the like.

The Bureau only reports on these two sectors in Economic Census years (they end in 2 or 7). I’ve rendered values for those years in black—and then, to get a proper curve, I’ve extrapolated the other points using percentage changes to housing starts—which are reported every year, indeed every month.

Interesting picture, this one. The multi-unit sector shows how the single-family sector would have performed had the bubble never come. The pattern is visible in the upper curve from 1997 through 2001. Then the speculation suddenly set in. Single-family rose like a rocket. Of added interest here is that the construction industry itself—if not yet the whole world, knew that things were badly off. The bubble here peaks three years before it bursts, in the financial sector, in 2008. The dark fairy suddenly swooped down in 2005—and the industry had to give it all back again—and more.

Now we constantly hear the innovators, progressives, and the cool asking, when others are leery of going upstairs, never mind all the way, “Hey, what century is this, doll? Hey, this is the twenty! first!”  The idiots, alas, are always saying that. Before the dot.com bubble people thought that fundamental economic laws had been suspended inside the dizzying heights of cyberspace. Not so.

Whatever the century, we may be dead certain. Somebody will try to get something for nothing. Both those who seductively whisper and those who yield to temptation must eventually—pay up. Here’s how it looked in housing. And the sobriety will last until this bubble sinks from memory and some other crazy “innovation” takes somebody to the cleaners. Next time.

1890 - A Good Year That!

Objects we use every day—and I assure you that we all do use this object, every day, 366 days in a leap year like 2012—just don’t get the respect that they deserve. In fact you’d have to be at least 127 years of age to remember what it was like in the good old days before toilet paper came in rolls. By chance and circumstance I discovered today how it used to be. Scott Paper introduced the toilet paper roll in 1890. Bless them—and bless the year!

Before that time? Well, toilet paper came in boxes. They were square and coarse sheets of rather dark paper. The Chinese were the first to use paper, and records going back to 589 attest to the fact. The less civilized or economically more backward reaches of the globe had recourse to leaves and grass and ferns and such. Am I glad that I got to live in modern times? Oh, yes. I didn’t know this in 1990—or I’d have celebrated the centennial. And if I should live to see 2090, I’d certain observe the bi-centennial of the roll—but while life expectancy is increasing, I don’t think it will carry me to my 154th birthday. And who knows. By that time—energy shortages and so forth—we may be back to reaching into precious and fiercely guarded black garbage bags to get a handful of leaves saved from last fall. 

Presidential Elections: The Money

The gatekeeper for money spent on federal electoral context is the Federal Election Commission. It publishes mountains of data but in forms so opaque that real labor is necessary to tease out totals. That work, however, is undertaken by public service organizations, among the OpenSecrets.org (link). The data I am showing comes from that source but was obtained from the FEC. Herewith contributions to the Presidential campaigns beginning with the one in 1976, Jimmy Carter beating Gerald Ford.

The raw dollar expenditures are growing, whether we measure them in dollars or as percent of Gross Domestic Product. The total contributions to these campaigns don’t amount to much, but of late they have been rising. Two points don’t make a trend. Adding 2012 results (which I will do next year sometime), may signal that the effort to buy the presidency, rather than just compete for it on well-reasoned issues, is continuing apace. We’ll see.

Just Watch that Curve Rise!

Click to enlarge, Esc to return.

What you see here is retail sales, indexed from 1992 to 2010. The sales of each industry were set to 100 for 1992, and then expressed, going forward, as change from that base. The winner of this race was Non-Store Retailers, a category dominated by electronic commerce. It is a relatively small category of the total sectors shown here, 12.9 percent in 2010. But it was 6.3 percent in 1992; its sales had quadrupled in volume. Is that finger pointing to the future? Are brick and mortar doomed? Not quite, to be sure. But if I were in the brick-and-mortar sector of retailing, I would be worried—and no doubt I would already have my website up, just to hedge my bets.

Some notes:

• General merchandise includes department stores, big discounters like Wal-Mar, small discounters like dollar stores, and warehouse clubs. Warehouse clubs turned in the biggest growth in the 1992-2010 period within this category.
• Miscellaneous stores include florists, office supplies, stationary, gifts, novelties, souvenirs, used goods stores, and others not specifically called out.
• Health and personal care stores are dominated by drug stores (Walgreens, CVS, etc.)
• Non-store retailers also include vending machines, direct sellers like Avon, and companies that sell fuel oil or gas (propane and butane) directly to home-owners. E-commerce was the second largest portion of this industry in 1992 (44.9%). In 2010 it was the largest (76.4%).

Volume ranks in 1992 and in 2010 were these:

1992	2010
Food and beverage stores	General merchandise stores
General merchandise stores	Food and beverage stores
Building materials and garden equipment	Non-store retailers
Clothing and clothing access. stores	Building materials and garden equipment
Health and personal care stores	Health and personal care stores
Non-store retailers	Clothing and clothing access. stores
Miscellaneous store retailers	Miscellaneous store retailers
Furniture and home furnishings stores	Furniture and home furnishings stores
Sporting  goods, hobby, book, and music	Sporting  goods, hobby, book, and music
Electronics and appliance stores	Electronics and appliance stores

I have the data from the U.S. Bureau of the Census. Use this link and then select Latest Annual Retail Trade Report, using Sales (1992-2010) under that heading. 

I’m Quantitatively Eased

No. Sorry. I’m not about to lambaste Ben Bernanke. A quite informative article in the April 2012 Atlantic, titled “The Villain,” persuades me that Bernanke is all right. But he is merely another mortal in a world of subprime collective intelligence. Collective intelligence, of course, is always subprime. The Fed Chair has been trying his damndest to try to help the economy with what little in the way of tooling is available to the monetary ruler of the land.

Quantitative easing? Apparently it’s an innovation we have from Japan. They coined the phrase in 2001 using the words “quantitative monetary easing.” Functionally it consists of central bank purchases of financial assets—such as bonds. The money for this purpose is in fact “printed,” thus created (in our case) by the Federal Reserve Bank. It is intended to bring down long term interest rates.

To understand why the traded value of bonds changes the value of the bond’s yield, we must understand that bonds have a face or par value (e.g. $1,000) but, when traded in the market, they may be bought for less or for more: their market value. Bonds, however, have a coupon rate, set on the face value, say 4 percent of par, thus $40 a year. But when a bond’s traded value rises, say to $1,500, the yield remains $40/year, but the interest rate has now dropped to 2.7 percent.

The motivation behind quantitative easing is to stimulate the market by lowering the cost of money—the presumption evidently being that people aren’t borrowing because interest rates are too high. If only interest rates were lower! But what if people aren’t borrowing for some other set of reasons? Suppose that they do not borrow because they have no confidence? Suppose they do not borrow to build new factories because they don’t believe they can sell the goods they would be making? What if interest rate is, uh, irrelevant for the moment.

That being the case, let’s just suppose, the Federal Reserve is, in fact, facing a hopeless situation. Its tools are inadequate to influence collective behavior. Interest rates have been creeping at rock bottom levels for a long time. Our bank now offers an interest rate on savings of—are you ready?—0.1 percent. Why? They don’t need money. Nobody is borrowing. But the Fed wishes to do good. The other part of government, meanwhile, which could stimulate the economy by actually buying things and services, is entirely mesmerized by trillion dollar deficits.

I look at that headline of mine up there. Am I really quantitatively eased? Maybe not.

Instapost

I own neither an iPod nor an Android—but I have a couple of little handheld cameras and the Picasa software on my PC. Impossession (to coin a word) of these newest devices made it impossible for me to test the great innovation that has catapulted Instagram in two years from a raw startup without money to a $1 billion corporation which will be soon be the property of Facebook. The hoopla made me curious. What innovation has caused this astonishing growth? Was it the company’s ability to hold down total employment to 13? Thirteen is a good number!

The simple answer is that social media represents our only evidently growing industry, and the founders of Instagram, Kevin Systrom and Mike Krieger (based on photos they’re in their twenties) wrote software for the little hand-held devices capable of editing photos, on the phones themselves, and publishing them on social networks, not least Instagram’s own. The technology consists of sixteen filters that manipulate a snapshot. The filters have fetching names like Amaro, Hudson, Xpro-II, Inkwell (for black-and-white), Hefe, Nashville, and 1977 along with others. That last one, presumably, to make pictures look antique. The innovation here lies in automating the editing function. You can have any look, dear users, so long as it’s one of those sixteen.

Making their storage systems work rapidly—and creating a system that will scale massively and rapidly—shows me that Systrom and Krieger know their stuff.  They’re using very sophisticated database management techniques that probably took much longer to learn than pixel manipulation. It isn’t innovative because the techniques they deploy were pioneered by Google quite some time ago.

Reasonable photo editors perform  the functions of those filters well—albeit it takes more time and thought. Picasa’s software is among them—also free. To give some sense of what I’m talking about, here is a before-and-after of an old winter outdoor shot of mine.

Now the original is nice enough—but if you want to make it look more edgy, contradictory—thus as if night were just around the corner, the modified image is a “filtered” version.

The miracle of economic growth that Instagram represents appears, therefore, to rest entirely on the miniaturization of computers and the irresistible attraction advertisers feel when viewing large numbers of people at play. 

Japanese and U.S. Agriculture

In writing yesterday’s post, I discovered, to my surprise, that Japan employs more people in its agricultural sector (2.3 million) than we do (2.2 million)! This then made me look up data on agricultural land in each country. Japan farms 11.5 million acres; we farm 922 million. Thus every Japanese farmer (on average, of course), tends 4.8 acres; every American farmer tends 418. Velly interesting! Further thought about this began to yield some reasons for this startling difference. The first thing that comes to mind is crop. Japanese agriculture is focused on rice—a kind of farming that does not lend itself to automation; our own enormous productivity is due to machines and chemicals applied to grains that grow on dry land. The second is that Japan is second to no one in the fierce protection it gives its agricultural sector.  So I thought I’d look into automation of rice production—and came up with a video (link). It shows the prototype of a robotic rice planting machine—the one that won Japan’s “The Robot Award 2008” Grand Prize. 2008? That’s just yesterday. And we learn that it still has problems. Commercial models are promised us within a decade. Why is automation beginning so late? Well, evidently the farming population in Japan is old, as in years, and the young are disinclined to follow their grandmas and grandpas into the paddy. So Japan is rolling up its sleeves…

The Vanishing Farmer

A fascinating report from the Bureau of Labor Statistics, issued about a year ago, shows data on agricultural (and other sectoral) employment for a 40 year period by leading industrial countries (link). I came across the report in trying to get at reasonably current and accurate estimates of employment in Agriculture.  Here is a graphic that provides a look at this sector:

What we see here is the gradual disappearance of the farmer across a selection of countries from the industrialized world. I’ve charted data from 1973 (rather than 1970), because values were missing for some of the countries in the first year of this series. Food is basic to humanity, yet in the technologically advanced societies represented in this sample, only 2.6 percent of total employment was required for its growth for the group in 2010, a significant decline from 1973 when the average was 8.7 percent.

In 2010 the United States employed 2.2 million people in farming, down from 3.6 million in 1973. It surprised me to discover that Japan employed more people in farming in 2010 (2.4 million) than we did; it also employed more in that sector in 1973 (6.8 million).  The lowest percentages belong to the United Kingdom—the first of the industrialized countries.

Now what we’re really seeing here is actually the massive deployment of fuels, chemicals, machinery, and automation to the basic industry of humanity. I put fuels first because all else depends on them. Everything today is stamped by the great mark of the Age of Fossil Fuels. And as these disappear  by this century’s end, a reversal of these trends is certain.

Yes. The same trends are visible also in the other categories covered by this report. Employment as a percent of total has also declined in Industry and Manufacturing as a part of that. All the gains in these countries have been in Services. And unemployment has increased in each.

The paradox is that “the end” is still too far away, hence the loud voices are shouting Growth, Growth, Growth. No one minds the barely heard voices crying in the wilderness: Prepare, Prepare, Prepare. The Great Transition is too far away. Our timid leaders find it far easier to hold up tin gods for us worship—human ingenuity that will (deus ex machina, literally) save us before it is too late.

Job Gain/Loss by Sector, March 2012

Herewith the employment change from February to March in a somewhat different format. I am showing actual employment in the two months, the gain or loss, and then the percent gain or loss in each of the sectors. The sectors are sorted by percent gain.

Employment Change by Sector	(Values in 000 or %)
Sector	February	March	Gain/Loss
	2012	2012	Value	%
Total non-farm	132,701	132,821	120	0.09
Total Private	110,703	110,824	121	0.11
Manufacturing	11,891	11,928	37	0.31
Leisure and Hospitality	13,548	13,587	39	0.29
Utilities	561	562	1.2	0.21
Financial Activities	7,706	7,721	15	0.19
Education and Health Services	20,176	20,213	37	0.18
Professional and Business Services	17,758	17,789	31	0.17
Mining	834	835	1	0.12
Wholesale Trade	5,590	5,594	4.1	0.07
Transportation and Warehousing	4,353	4,356	2.8	0.06
Other Services	5,359	5,362	3	0.06
Government	21,998	21,997	-1	0.00
Construction	5,558	5,551	-7	-0.13
Retail Trade	14,728	14,694	-33.8	-0.23
Information	2,641	2,632	-9	-0.34

This view of things shows that Retail, which sustained the largest losses, did a little better than the Information sector (that’s the media and publishing). Manufacturing did better than the Education/Health, although both gained the same number of jobs.

That overall growth rate of 0.09 percent in one month suggests that, if it remains in place, it will take 29 months (August 2014), before we shall have once more achieved the employment level we had at the end of 2007. Meanwhile, of course, the workforce has grown. Those two years remind me of the Pharaoh’s dream that Joseph interpreted as meaning seven lean years in Genesis 41.

The tabulation is also interesting in that it shows the relative importance of the sectors.  Government is our largest employer—and it is that because virtually our entire educational sector falls into that category. The Education and Health Services sector, which includes non-government education, is dominated by the health sector. Combined into layers, these data produce my favorite pyramid or children’s “top”:

Here I’ve added an agriculture sector, not present in the table, using a 5 million employment figure; it somewhat overstates the total. I call this a top because it’s top-heavy and stays in balance only by the vigorous application of a whip. We live in an amazingly rich country considering that most of our consumption is not, strictly speaking, of the basic and necessary kind. And hence we can lose 8.7 million jobs and keep on trucking.

Employment Update: March 2012

Something of a wave of high expectations came ahead of the actual release of data this Friday by the Bureau of Labor Statistics (link). The Wall Street Journal reported that expectation this morning, hoping for an employment increase of 200,000, the consensus of economy watchers. And, I think, the economy watchers thought that they were being cautious. The actual reported number last month was 227,000. The Journal even lamented the fact that no markets would be open today (Good Friday) and hence the exuberance would not be immediately felt by the markets.

Well, the data are in. And they fall well below expectations. Job gains in March were 120,000—thus continuing what I called “business as usual” last month. Two steps forward, one step back. Nor did the revisions of last month’s result bring much cheer. Last month’s results were adjusted upward, to be sure, but only by a mere 4,000 jobs, to 231,000. This month the Retail sector showed a sizeable loss in employment (33,800 jobs); but even if that sector had been neutral, we’d still not have achieved the anticipated 200,000.

What we are seeing in formation here is a kind of Appalachia of jobs growth—not the steep rising of the Rockies. Overall, looking at the 8.7 million jobs lost in 2008 and 2009, we have recovered 5.2 million jobs in two years and still counting, thus 40.4 percent—a 1.4 percent increase this month. Better gains than losses, I say. But it really does make me wonder whether maybe something’s wrong with the foundations—at least of our expectations.

Emphasis on “Less”

Another medical day (fortunately only tests), brought us into a sunny, plush lobby of St. John Providence hospital where a grand piano was playing all by itself. Those player-pianos are proud representatives of the first automata, although ambiguously named. Player piano? No. Playerless piano.

Reminded me of something I’d stumbled across the other day, Google’s driverless car. They’re multiplying, these babies. The personless voice that answers phones and uses the Royal We (“Your call is important to us!”) is so common now we do not even flinch or curse or even sigh. The pilotless drone is yet something else. While waiting for Brigitte, who underwent the test today, a vision arose in me, a kind of sci-fi panorama. Space ships are landing on a life-supporting planet. The ships’ passengers are jubilant. Their orbital probes have discovered cities, houses,  radio traffic, farms, vehicles in motion. They land with Great Expectations. And they discover a crowded planet filled with machines. They’re engaged in doing everything imaginable: cars and trucks are driving down the highways, airplanes take off, fly, and land. The homes clean, heat, and maintain themselves; they cook food, serve it, clear the dishes, dispose of waste. Voices sing on video and radio; keyboards click as lenses read words on printed sheets, farm machinery plows and reaps, silos fill and empty. But there is no sign of anything, like, living. Where have all the people gone? It’s a peopleless planet.

YouTube has quite a few videos on Google’s driverless car. Put in those words for searching and they line up. It is now the most talked-about instance of a project that began as far back as the 1939 World’s Fair where General Motors’ exhibit, Futurama, showed cars travelling on an automated highway.  There have been multiple implementations of the driverless car since, but no commercialization.

By the way. People have now also developed programs that produce writerless news stories (here is a link). This post, however, still used a human being. So yesterday.

“Got Milk?”

The advertising campaign known by that name is viewed as one of the most famous commodity brand campaigns in the United States. It was created in 1993 by Goodby Silverstein & Partners for the California Milk Processors Board; the campaign was later licensed to others in the industry. Now here is the interesting outcome of this campaign, still running today. It increased milk consumption—but only in California.

Below I present per capita consumption data on all dairy products published by the Economic Research Service of the U.S. Department of Agriculture (link to the data is here).

To bring out the movement in the commodities made from milk, I show the largest portion of the dairy industry, fluid milk, indexed to the right axis; if I didn’t do that, the growth or decline of the other categories would become invisible. But all data are shown in consumption per pound. Milk is by far the most dominant product category in dairy—and consumption has been in steady decline; milk, incidentally, also includes (as reported here), yoghurt and sour cream.

The “exciting” new product in dairy is cheese! It has shown dramatic growth in this 1975 to 2010 period. Interestingly enough, one component of that category, cottage cheese, has declined almost as much as milk; the growth of American cheese has been mild; the big advances are associated with the “other cheese” category, the cheddars and the like. Butter has held its own, as it were, growing just a little. All other categories have shown decline.

A big surprise here (for me) is the decline in per capita consumption of ice cream. That category has four subdivisions: regular, low-fat, sherbet, and frozen specialties. The biggest decline has been in regular ice cream. The low-fat variety showed flat growth; the frozen specialties, however, actually increased their hold on the consumer.

The “all other” category includes evaporated and condensed milk and dried milk products, including, surprisingly, dried buttermilk. They too point downward.

Milk provides an interesting comment on the effectiveness of advertising. All those celebrity-lips whitened attractively by milk have not actually delivered growth for the fundamental product of this industry. The public does its thing. Advertising appears to influence behavior only on the margins.