March 2017 Employment Change

The March report, by the Bureau of Labor Statistics, known as the Employment Situation (link), produced something of a shock. February’s gains were 235,000. First of all those results were revised downward by 16,000 (to 219,000); January’s results of a 238,000 jobs gain were revised downward as well by 22,000 (to 216,000). And this month’s results, for March 2017, came in at 98,000—thus roughly half of what most people expected. NOT GOOD, as DT might tweet. Herewith the graphic I show for the total period from December 2007 to the current month:

The big drop in employment gain had much to do with chaotic weather all through March—much colder and liberally plagued by floods, storms, and tornadoes. Job gains in Construction, for instance, which had produced a gain of 59,000 jobs in February, came in with a gain of only 6,000 in March. The Retail Sector, which had shown growth of 35,300 jobs in January, showed losses in total employment of 30,900 in February and 29,700 in March. Turbulence and cold weather put a crimp in shopping too. Leisure and Hospitality, as one might expect, went from a job gain of 27,000 in February to a gain of only 9,000 in March.

Let’s next look at the annual projection produced by three months of gains in 2017. The graphic that follows shows it (last bar).

The projection is worse than it was for the 2012-2016 years—thus just a shade better than 2011. But, of course, it’s still early in the year. Having exploded $60 million worth of Tomahawk missiles recently—59 that landed and one that fell into the ocean—we’ve created a new demand for replacing them in the year that is still left. That might make up for some of the jobs taken away by misbehaving weather (or “fringe attacks” by Global Warming).

Hope’s just around the corner.

February 2017 Employment Updates

It’s been a while since I’ve posted these data—the last time for November 2015. Herewith an update. It covers all of 2016 as well as the first two months of 2017. I do this because of all the hoopla from the Trump administration—which tends to label good news as due to Trump, bad news as numbers-games put out by his the opposition. The data shown are from the most recent issuance by the Bureau of Labor Statistics on the Employment Situation (link).

February results show that the economy added 235,000 jobs in February: February thus produced a good number, to be sure. But that number is shy of the January 2017 result by 3,000 jobs. That sort of change, again, is normal; but no big fuss had been made over the January result. And, looking back, 2016 produced, four months in which job growth exceeded the 235,000 jobs-gain number. So we’re in effect just soldiering on. Note, however, that February 2016 produced 237,000 jobs, beating this year’s result under an Obama Administration. That surely can't be true, can it?

Alas. When looking at a long history of employment growth (or decline), as we do when looking at the information in the graphic above, the year so far shows no obvious sign of a coming “revolution” in job gains. To be sure, the next graphic, which projects full-year 2017 results from two months’ data, suggests that 2017 is on track to be second best to 2014  since the Great Recession:

November 2015 Employment Change

The Bureau of Labor Statistics report on the Employment Situation (link) showed a gain of 211,000 jobs over October 2015. Herewith the standard chart:

The number is in the respectable range. But I got to wondering: How does it compare to other transitions from October to November—considering that November is the first month of the biggest retail months of the year? Herewith another graphic:

This one goes back to 2005 and shows changes, October to November, in the 2005-2015 period. Notice how the October-November change signals the coming of the Great Recession—and thereafter the annual increase October to November of the same number—until 2015. Last month the number, while respectable, indicates a divergence from trend. Last year we added 423,000 jobs; this year less than half as much. Does that signal that Christmas sales are moving to December—or is it a sign of continued uncertainty and lack of confidence? We shall see how December behaves.

The next chart, showing projections for 2015 based on 11 months of data, show that 2015 may also break the total annual job-growth trend since the Great Recession by under-performing 2014:

Another “Black Friday” Note

Going back to 2011, I’ve posted notes on Black Friday on LaMarotte, the last such being in 2013. The marketing efforts of an almost hysterical Retail Sector, intended to incentivize us to shop—with a mountain (or a log-pile, as Monique has put it) of paper—nicely drenched by the rain that fell from 2 am onwards early this morning. In my case it incentivizes me to think about the economy—and try to explain to myself the broad patterns I note and note again on the first Friday of every month when the Bureau of Labor Statistics (BLS) brings its employment report. Certainly since the Great Recession (2008-2009) I cannot help but think that something really new is in the works. The Consumer Society appears to be fading. Since that time has also coincided with vast troubles all across the world, the beginnings of what may some day be called the Thirty-Years War of the Muslim culture, the explanation for a continuingly sluggish economic performance here at home cannot be entirely economic. Indeed I don’t think it is. But the spine, the core, of it, is. We may be feeling the effects of a paradox. It is that for profitability business benefits by getting rid of labor in the work place (i.e. the Luddites had it right), but shifting more and more activity to technology has the paradoxical effect to curbing demand by depriving at least a part of the population of income.

The Consumer Society was based on confidence—confidence that jobs would be present; that holding one would be rewarding; that jobs would be safe, well paying; that income would grow with seniority. Needless to say, travel would be safe—and sending children to school would not be tantamount to sending them to a potential shooting gallery as innocent targets. The Great Recession, perhaps, was a kind of moment in recent history—like the fall of the Berlin Wall. It was the falling of global confidence in the economy.

One instance of this is the transformation of fulltime, permanent into temporary employment. A graph will illustrate this. It’s just a sliver of evidence, but meaningful. I present, below, data on part time employment since 1995. I have the data from successive reports of the BLS’ Current Population Survey; for a beginning point, see the link here.

Temporary employment began rising around 2000, shot up sharply in the Great Recession, and has stayed up there ever since—indeed is growing still. In 2015 we have nearly 4.5 million more temporary workers than we had in 1995. Full time employment grew 18.2 percent (1995-2015—from 101.7 to 120.2 million), temporary employment 19.8% (same dates, from 23.2 to 27.7 million). The annual rate of growth for fulltime employment is 0.84, that of temporary employment 0.91 percent. These are small numbers, to be sure, but the phenomenon is measurable. And if you know any people in their 50s, say, looking for permanent work and being able only to get temporary assignments—and we certainly do—those facts begin to circulate…and have an ever growing effect on one’s general confidence.

October 2015 Employment Change

The October report on the Employment Situation arrived from the Bureau of Labor Statistics yesterday (link) and was, you might say, well received. BLS reported a gain of 271,000 jobs—well above the 200K level that is generally anticipated. Indeed, this month’s result has been the best for October since the end of the Great Recession as shown in the following graphic:

 To be sure, the data are subject to revision and may therefore eventually turn out to be either even better or be revised downward. The second best performance came in 2010 (a gain of 248K jobs)—when, it seemed, the economy behaved as if a normal, meaning rapid, recovery would be taking place. But 2010 did not quite deliver.

The regular month-by-month report is presented graphically below:

October looks good, but the exuberant sentiment in the media may well be premature. Personal observation while shopping—and scattered reports in the business press—suggests that an almost desperate Retail Sector was pushing everything back in time lest it miss out on what may turn out, again, to be a weak-ish holiday season.

October looks good, but projections for the year as a whole (see the next graphic) still has 2015 under-performing 2014:

A look at the job gains in some detail, thus sector by sector, also reveals signs of chronic weakness. Thus the highest gains were scored by Professional and Business Serives (78K), Health Care and Social Services (56.7K), Retail Trade (43.8K – presumably staffing up for the holidays), and Leisure and Hospitality (41K). Four sectors showed loss of jobs (Mining and Logging, Transportation and Warehousing, Utilities, and Information (Publishing and Media). Manufacturing added zero jobs! Thus the more “serious” sectors were at zero or negative growth. In other words, let’s curb our enthusiasm.

The media make much of the fact that unemployment has now reached 5 percent; but I don’t trust that number. It does not count those who’ve given up looking for work…

September 2015 Employment Change

This most recent report on the Employment Situation, for September 2015, clearly surprised the business media and the financial sector. These data are reported by the Bureau of Labor Statistics (link). Virtually everyone anticipated job creation at a level of roughly 200,000. The actual result—142,000—came as a shock. Furthermore, data for August and July were also revised downward by 59,000. This impelled me to update my own numbers here. My last report was for April. Back then it looked like 2015 would be weak; five months later, that trend is still weak. Herewith an updated monthly graphic followed by a projection of 2015 based on nine months of actual results:

Thus far, projected job creation in 2015 looks lower than either 2013 and 2014. Since the Great Recession, 2014 has thus far been best, producing an average monthly growth of 260,000 jobs; 2015 (thus far) has produced 198,000—versus 199,000 in 2013.

Next I show two trend lines. The first shows the growth trend between 2013 and 2014. The second the declining trend between 2014 and 2015. In both cases 2014 is shown in pink:

The big picture since the Great Recession (visible on the first, the monthly graphic) is one of hesitant growth. What we must have is around 87,000 new jobs per month—to keep up with our population growth. We’ve averaged well above that; therefore we are not in any dire trouble. But neither have we resumed, or are likely to resume, the exuberant celebration of a Consumption Culture. That game requires confidence; and no matter a few points increase in Consumer Confidence; that confidence fades as rapidly as it increases.

April 2015 Employment Change

The Bureau of Labor Statistics publishes employment changes on the first Friday of each month (link)—for the previous month. Employment in April increased by 223,000. A lower number had been anticipated, hence sighs of relief came yesterday. 2015, however, is not looking all that energetic. If the economy’s performance January through April is projected for the entire year, the results indicate that employment growth in 2015 will be lower than in 2013 and 2014. Such an outcome is not very likely, but it does show that something significant has changed since the Great Recession. When economies begin to produce patterns similar to the annual seasons—now better, now worse—the safe presumption is that something is missing; in this case it is public belief that things are destined, always, to get better: unlimited growth, in other words. Public confidence.

Herewith the two graphics that show monthly data from December 2007 forward and annual results for 2007 through 2014 (actual) and for 2015 (projection):

If we examine how April’s employment gains were distributed, we note the following: The numerically largest increase in employment came in the two largest sectors, Professional and Business Services and Education and Health Services (62,000 and 61,000 jobs respectively). Construction, a relatively small sector, gained significant number of new jobs—45,000. Two sectors (Mining and Logging and Wholesale Trade) lost employment (-15,000 and -4,500 respectively). The other sectors all had small gains. The continuing and persistent trend is an increase in private sector services, including private education.  In terms of total size, Government, which represents 15.5 percent of total employment (all those public sector teachers) only gained 10,000 jobs; in effect it lost share of total employment again in April. The tax cutters ought to be rejoicing; those who long for Big Picture improvements ought to mourn.

Speaking of share of total employment, nine sectors lost share, including Mining and Logging, Manufacturing, the Trades, Information, Financial Services, Leisure and Hospitality, and Other Services; the biggest loser was Government. Utilities were unchanged. The share shifts are tiny, but the cumulative picture is not that of an economy in uniform growth but one growing because an aging population is exerting a new demand (Health Care and Social Assistance) and because industry is more and more into management (Professional and Business Services) rather than actually making or delivering goods.

Employment Update: February 2015

The first Friday of the month brings us the Employment Situation courtesy of the Bureau of Labor Statistics (link). In summary, the economy added 295,000 new jobs. The BLS, however, revised January results downward (-18,000 jobs); hence the net increase since the last report here has been 277,000 jobs. In the 2010-2015 period, this has been the second best result for February yet; the best came in 2013 when we had a gain of 314,000 jobs.

The graphic above shows the monthly progress from the “grand canyon” of the Great Recession to the present. We’ve yet to match the huge monthly gain in May of 2010, but the overall pattern shows steady growth in economic health.

Taking results for January and February and projecting the entire year 2015 based on these preliminary results, it appears that 2015 will outperform the earlier years of the recovery—as shown in the second graphic.

We had recovered all jobs lost in the Great Recession in December of 2013*. Since then I have been tracking how we are doing recovering what I’ve been calling the “Labor Force Growth Deficit”—thus jobs required just to keep up with the growth of the labor force. As of the end of 2013, we needed to recover 4.19 million jobs. Of these we have now recovered 87 percent, leaving just 13 percent still to recover. Growth in the labor force alone requires us to gain 87,300 jobs every month minimally. Any gains above that number are net gains for the economy as a whole. The graphic above shows us how we are progressing.

Now for a brief look at where the growth has been most prominent. February job gains divide as follows: The Goods Producing Sectors’ share has been 9.8 percent, Private Service Producing Sectors accounted for 87.8 percent, and Government for 2.4 percent. Retail Trade alone, part of Services, accounted for more jobs than Mining, Logging, Construction, and Manufacturing put together. That does not please me much. And biggest gainer within Services was Leisure and Hospitality. Doesn’t please me much because, for me, a really robust economy is based on Goods Production; but seeing that sector come to dominance again is a bit of an idle dream.
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*This date, thanks to later data revisions, is wrong. It should be April 2014. 

The Gini Coefficient — But Don’t Run!

This post originally appeared, in 2008, on an earlier version of LaMarotte. It is reprinted here without changes.

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The Gini Coefficient measures income inequality in a country—or any region—using a single number. It was created by Corrado Gini, an Italian statistician, in 1912. I’ve know of it for a long time—and it has irritated me at right regular intervals. Why? I was taught by one of my wise elders, then a junior in business analysis, that any number that people produce in such analysis should present all of the data necessary to replicate it with a simple calculator. My guru, who then labored as the chief of statistics for Anheuser Busch, carried his calculator strapped to his suit-belt. He practiced what he preached. But when we look for an explanation, we’re bowled over by references to the Lorenz curve and presented with stuff that looks like this:

G = 1 – 2 ∫_o¹ L(X)dX

The last time this happened to me (yesterday) my irritation  produced a determined search for a simple explanation. Therefore I am now prepared to explain the Gini Coefficient in plain language, namely how it is actually calculated and how the data, to be used, must be arrayed for the calculation.  I’ll use the following chart using U.S. household data for 2008 for this explanation.

The raw data for this chart, which I’ve taken from this Census Bureau site, shows the cumulative share of household income as we proceed from the poorest toward all households, thus from the lowest fifth of all households up the line until all households are included.  That is the blue line. Here is the way we must read the chart. The lowest 20 percent of households (lowest quintile), accounts for 3.5 percent of total income. The lowest 40 percent of households (the lowest and second quintile cumulated) account for 12.1 percent of total income… And so on to the last column where—surprise—all households account for all of the income. Clear so far?

The blue line represents actual results for 2008. The red line, by comparison, shows what the results would be if every group earned exactly the same amount. Not surprisingly, 60 percent of all households, then, would be earning 60 percent of the total income. This is not rocket science either.

Notice now the area surrounded by these two curves. It represents the inequality in income, thus the difference between an ideal and an actual state of affairs. What the Gini coefficient (also called an Index or a Ratio) actually calculates and reduces to a single number is the magnitude of this difference.  I’ll present the formula and how its elements are obtained. I have not penetrated deeply enough to explain the formula itself.

To begin with, we make note of the last number—100 percent in our case. We’ll call that T for Total. Next, we calculate a value called Sigma. It consists of the sum of all of the numbers added together—up to but excluding the last. In our case that is 3.5 + 12.1 + 26.7 + 50.9 = 93.2. That is Sigma. Finally we note the number of groups we used in the analysis. We used quintiles, therefore we used five groups. We generalize that number by calling it n. Now we insert these values into the formula used to obtain the Gini Ratio. That formula is:

Gini = 1 – (2 divided by T times Sigma + 1) divided by n.

Translated into numbers, this means Gini = 1 – (2/100 * 93.2 +1) / 5.  The result of this calculation is 0.4272. That’s the Gini Ratio. You may encounter it multiplied by 100 for easier readability (here 42.7).

If we apply the same approach to the top line, we have a T=100, Sigma = 200 and the formula becomes Gini = 1 – (2/100) * 200 + 1) / 5. This results in 0. In the ideal case, in other words, there is zero inequality.

Having followed this procedure, we have now generated a single number for each curve and we can therefore compare them. The rule here is:  The lower the Gini the more equal is the income distribution. It can’t get any lower than zero–and can never exceed 1. A result of 1 would mean that a single group has all the income and nobody else has any.

Let me follow this up by looking at the Gini Ratio over some period of time. The following graph (its source is here) does that for us for the period 1967 to 2007.

Income inequality, although it rises and falls year to year, has been increasing steadily over the recent forty year history presented above. The Gini is useful especially at this level of macro analysis. It holds a vast amount of detail in a single number. And now that I know how it is obtained, I find it much more acceptable. [For an updated Gini Ratio to 2013, see the previous post here, same date.]

An additional note. Country to country comparisons using Gini calculation are interesting but not much more than that. Several organizations (the CIA and UN are two) calculate this number for many countries. The U.S. falls generally into the upper ranges of inequality–but not at the very top. To find the peaks, we can single out Brazil and Mexico. China? China’s inequality is just about the same as ours. And Japan’s falls below ours. Bulgaria is hugging the bottom range–at least in the list of countries shown in this Wikipedia chart.

Income and Inequality: Update to 2013

Back in 2011 I presented here graphics on Household Income (Average and Median) and on Income Inequality (as measured by the Gini Index). Herewith an update of those graphics.

The data in this chart are in 2013 constant dollars and obtained from this BLS facility (Table H-6, All Races). Median here means that half of all households earn less, half earn more—therefore it is the income at the precise middle of the total earnings range. Note how close average and median are to one another in 1975 ($7,800) and how that difference has grown by 2013 ($20,702)—and this in constant dollars, thus in actual purchasing power. The difference is accounted for by growing income inequality, which brings us to the next chart.

In this graphic I reproduce the Gini Coefficient which measures inequality. A Gini Index of 0.0 means absolute equality of all incomes. Therefore the higher the value the greater the inequality. The data for this graphic are from this BLS facility; select Income Inequality and then Table H-4. Posts on how the Gini is calculated will be put up here in due time; they were on the old LaMarotte which is no longer accessible.

Worth noting here is that the Great Recession affected Inequality only briefly, by causing it to drop somewhat between 2007 and 2008—significant numbers of the very rich lost income in the housing crash. The Gini has grown since although, in the 2011 to 2013 period, it has shown signs of lessening. I’ll revisit this picture a year or so later when new data are published. For the time being, the rich are getting richer…. So what else is new?

Employment Update: January 2015

At this time of the year, labor force numbers are presented, by the Bureau of Labor Statistics, in fully revised form—with the revisions reaching years back in time. This year’s revision do not change the overall pattern of developments except in one regard. Numbers for 2014 have been revised upward significantly. In my last report I showed job gains for 2014 at 2.96 million; the revised numbers lift the year to 3.12 million. Since 2014 was better than initially reported, total job losses of 8.7 million (not changed) were recovered earlier (by December 2013) than earlier reported (by May 2014). It took us four years to recover all of the jobs lost in 2008 and 2009.

Job gains in January 2015 were 257,000, below the (revised) 329,000 (versus last month’s report of 252,000). Therefore the projected annual results for 2015 are presently lower than the actual 2014 results, but it’s early days yet. The January figure this year is better than in all earlier years, except 2012, since the Great Recession.

Herewith the two charts I usually show—month by month and then annualized. In the second chart, the 2015 figure is a projection.

Since the economy has, since the end of 2013, almost entirely caught up with job gains needed to support population growth as well (about 80 percent), the motivation for this series is beginning to fade. We are recovering. But it took a long time.

Let’s Hear it for the Dollar Store

The other day I bought some picture frames as part of an on-going picture-hanging exercise caused by a move that, while it seems to have taken place just yesterday, actually already goes back almost seven months. The cost of frames astonished me. I began looking at arts and crafts stores like Michaels and Jo-Ann Fabrics; then, needing smaller frames, I thought I’d find them at CVS. Find them I did, but the cost of these frames was not noticeably lower at the drug store than at the art stores. Then an inspiration came. One of my routes to one of the Krogers we now frequent takes me by a Dollar Store—or, more formally, a Dollar Tree. There I went.

There I went but—that having been a rather grey sort of day—I was quite convinced that Dollar wouldn’t have any frames. Imagine my surprise when I found a whole rack of them. Moreover, there was actually a yellow sign above them with the word Frames on it. I walked out of there a short while later with ten frames of various sizes. These frames, by the way, were of the same quality, decorative variety, and technical features as those in other stores where, typically, they were priced at multiples of six to twelve of the price I paid here.

I noticed while in there that the clientele had a large admixture of foreigners, immigrants, and other newcomers to the Land of Plenty. One of them was a big man in middle years who had no English at all. I saw him questioning another man about the whereabouts of—well, he was making shaving motions with his hands. The man he was consulting didn’t know how to deal with the problem and told him to go up front to ask, which that man did not exactly understand. The foreigner, incidentally, had been at the entrance to the store when I went in, hesitating there. Was he building up the courage to enter and encounter American Consumerism for the first time ever? Anyway, I resolved to help the gentleman as soon as I’d picked my last frame. As I headed out, one of the store clerks was coming down the aisle. I asked here where shaving gear was stowed. “You too?” she asked. Evidently she had been told about the problem by someone else and was coming to help my foreign gentleman. All was well. He’d have his razor and his razor blades in just a minute for a mere $1.

Family Analogy

Herewith something I'd published on Ghulf Genes yesterday. It fits this blog too...

The sophisticated sector of our society, e.g., the media, don’t much like simplistic analogies. Like, for instance, the notion that our smallest collective, the family, may be like our greatest, the nation. Yet this morning such an analogy arose in my mind. The occasion was a headline in the Wall Street Journal: “Gas Savings Not Spent Yet.” The essence here is that despite good numbers on December retail spending from private associations, national numbers from the Commerce Department indicate 0.9 percent decline in retail and food services spending as compared to November spending. And this despite a huge drop in gasoline costs?

The key word in the headline is that word Yet. The sophisticated understanding of people is based on an artificial notion of pure economic rationality. When people have extra money, they will spend it. If they don’t now, soon they will. Nothing else matters except having money or not having it. There is no future or social dimension present at all.

But if we use a “simplistic analogy,” our economic life today is comparable to the life of a family where mom and dad are at each others’ throats and hellzapoppin. A sign of that is a story on the next page: “House Votes to Block Immigration Policy,” just a day after a frosty meeting between the President and the Congressional leadership to discuss cooperation.

In a family in uproar, the children won’t be jolly. Consumer confidence is based on many things, not least the bigger atmosphere of the social whole. And there we have Mom determined to undermine Dad and vice versa. It’s barely safe to play, with half a mind, behind the couch, while in the kitchen things are heard to break on the tiled floor.