Friday, March 6, 2015

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.

Wednesday, February 11, 2015

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.

*     *     *

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?

Tuesday, February 10, 2015

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.

Monday, January 19, 2015

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.

Friday, January 16, 2015

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.

It Took a While

In the earlier version of LaMarotte I’d posted multiple times on my problems with Radio Shack. Unfortunately that earlier version is no longer up. In any case, the slow decline of this once very competent retailer has been taking decades; presumably dissatisfied customers like me have numbered in the multiple hundreds of thousands. What is amazing about current news, stating that Radio Shack is preparing to go into bankruptcy as early as February, is how long it has taken.

Corporate collectives have life times not that much longer than humans. Radio Shack saw its beginnings in 1921, so it is 94 now. It will presumably live on, after bankruptcy, for a while anyway until, probably eaten by another one, it will gradually disappear.

Friday, January 9, 2015

Employment Update: December 2014

Another year has passed and therefore we have complete numbers for 2014 issued today by the Bureau of Labor Statistics (link).

I’ve tracked these data on a monthly basis (with two or three skips only) since February 2010. The series, from March 2011 forward, can be found on this version of LaMarotte. My purpose, when I first began, was to see how long it would take the U.S. economy to recover the total jobs lost in 2008 and 2009, the Great Recession, 8.7 million jobs. Well, it took four full years (2010-2013) and five months to recover the lost jobs. After that, from June through the present, the economy has been recovering the jobs lost due to an absence of actual job growth since 2008, a total of 6.6 million jobs. As of December of 2014, we have recovered 22.1 percent of those jobs as well, suggesting that “normal,” meaning status quo ante, will be reached some time in 2015—unless another recession sets in this year.

Now for the December 2014—and the year 2014—results. In December we gained 252,000 new jobs, a healthy number. November had the largest gain in 2015, 353,000 jobs. For the year as a whole, we gained a total of 2.961 million jobs, the best performance since 2010. Graphics by month and by year follow:





In this report, annual figures all show actual (rather than projected) data. The 2014 total, however, may be (and most likely will be) revised by BLS in February. Given current trends, the revision may very well be upward.

As we wave good-bye to 2014, the U.S. economy is acting robust and the dollar is strong. Gas prices are at their lowest in a very long time. By contrast, a sense of crisis still wafts over Europe. China’s growth has softened. Japan is still in its now decades-long slump—perhaps showing what the future holds for the global economy. We shall see. My own view is that there must surely be a Third Way—something other than frenetic growth on the upside and abysmall slumps on the other. 2015 may show us which way things will be trending.

Saturday, November 15, 2014

Employment Update: October 2014

October jobs report by the Bureau of Labor Statistics (link), called The Employment Situation, issued on November 7, 2014. Last month’s result, a gain of 248,000 jobs, was revised upward to 256,000, a gain of 8,000 jobs. And the October result showed a gain of 214,000 jobs. The updated graphic, which also shows other changes in earlier months, amounting to an additional addition of 31,000 jobs, follows:


The net result is continued growth in jobs. This growth was distributed as follows: Goods Producing sectors: 13.1% of gains, Service Providing: 84.6 %, and Government: 2.3%. Within the Services Providing sectors, temporary employment showed a substantial growth of 7.1% of all new jobs added, which is a sour note here. The only sector showing losses was Information, which includes the media, -4,000 jobs.

Herewith a tabulation of gains by each sector, with numbers representing jobs in thousands:

Total nonfarm
214.0
  Total private
209.0
    Mining and logging
1.0
    Construction
12.0
    Manufacturing
15.0
    Wholesale trade
8.5
    Retail trade
27.1
    Transportation and warehousing
13.3
    Information
-4.0
    Financial activities
3.0
    Professional and business services
37.0
    Education and health services
41.0
    Leisure and hospitality
52.0
    Other services
3.0
  Government
5.0

The projection for the year is shown in the next graphic:


In this chart actual data are shown for all years except 2014; results for that year are projected based on 10 months of actual data. In the post-recession period, 2014 is shaping up as the best year yet.

Thursday, October 23, 2014

Employment Update: September 2014

The Bureau of Labor Statistics (link) issued new employment number on October 3. According to the report, the economy added 248,000 jobs in September. BLS also corrected its August figures, upward, by 69,000 jobs. Therefore the net gain, since the last report, has been 317,000.

As a percent of total employment, the Goods-Producing sector represented 13.7 percent of jobs and 11.7 percent of gains since August. The Private Service Producing sector accounted for 70.5 percent of total jobs and 83.5 percent of all gains. Government was 15.1 percent of total jobs and 4.8 percent of gains. So the “action” was all in the Service Producing segment. Within that major category, the top three gainers were Professional and Business Services, Retail Trade, and Leisure and Hospitality; they accounted for 60.2 percent of all gains in September.

The month-by-month chart follows. The orange bar reflects changes made to August numbers in the September report.


Data showing annual results and an annualized projection for 2014 are next:



Last month the 2014 projection was 2.598 million for the year. This month the projection has improve and now stands at 2.732 million.

In May of this year, the economy recovered the loss of 8.663 million jobs lost in the Great Recession. Since then I’ve been tracking recovery of new jobs not created while we were making up losses. To keep up with the growth in the workforce, a number driven by demographics, we need to created 87,300 jobs every month. Once that number is met, anything in excess may be counted against what I’ve labeled the Growth Deficit. That number stood at 6.635 million in April, just before we caught erased the losses created by the Great Recession.

As of July, we had already recovered 7.1 percent of that deficit. The numbers were good enough in September to change that recovery rate to 12.3 percent, as shown in the last graphic:


Employment is headed in the right direction now, but its “quality” is only so-so. The economy is adding service employment, not least temporary positions; those accounted in September for nearly 8 percent of all new jobs created.

Saturday, September 6, 2014

Employment Update: August 2014

Numbers for August, released by the Bureau of Labor Statistics yesterday (link), produced an interesting mix of reaction. Some observers deplored the results, some suggested that BLS hadn’t gotten them right, yet others pointed out that uneven performance of this indicator is a normal phenomenon.

The BLS reported that 142,000 jobs were created in August. Those who expected at least 200,000 were disappointed. At the same time, BLS also revised July results downward from 209,000 to 181,000, a loss of 28,000 jobs. Therefore the net gain in August was just 114,000 jobs.

The Retail sector lost 8,400 jobs—once more underlining that consumer confidence may not be as robust as assumed. The Information sector (read communications media) lost 3,000. Manufacturing employment remained unchanged from July. Mining and Construction both produced fewer jobs than in July. The pattern is familiar by now. The basic industries are still sluggish. All the gains are coming from the Service categories.

Herewith the monthly chart, with July colored tan to indicate that results for the month were revised downward:

Data showing annual results and an annualized projection for 2014 are next:


Last month the 2014 projection was 2.774 million for the year. This month the projection has dropped to 2.598 million because of the July changes and the lackluster August results. The projection for 2014, however, still remains the best since 2007.

In May of this year, the economy recovered the loss of 8.663 million jobs lost in the Great Recession. Since then I’ve been tracking recovery of new jobs not created while we were making up losses. To keep up with the growth in the workforce, a number driven by demographics, we need to create 87,300 jobs every month. Once that number is met, anything in excess may be counted against what I’ve labeled the Growth Deficit. That number stood at 6.635 million in April, just before we erased the losses created by the Great Recession.

As of July, we had already recovered 7.1 percent of that deficit. The numbers were good enough in August to change that recovery rate to 8.9 percent, as shown in the last graphic:


The trend is still positive, but some kind of “new normal” seems to try to deny the eager observers of the economy the triumphant feeling that we’re heading for what we really like: “irrational exuberance.”

Wednesday, September 3, 2014

PCE: The Real Measure of Confidence

We hear it said quite frequently that Personal Consumption Expenditures represent 70 percent of Gross Domestic Product. Such a rough approximation is false, by and large. The last time the PCE was at or above 70 percent was in the 1929-1939 period, thus roughly coinciding with the Great Depression. Thereafter it dropped into the 50s and has been gradually rising in percentage since, as illustrated in the following table:

PCE as % of GDP
Year
79.9
1932
54.9
1942
59.7
1952
61.6
1962
60.0
1972
61.0
1982
64.5
1992
67.5
2002
68.0
2012
68.1
2013

What this tabulation teaches is that PCE is, these days, closer to “two thirds of GDP”—and that when consumer confidence really tanks, the numbers start going up and come close to touching 70 percent. Notice also that the lowest number in that table comes in 1942—when GDP had swollen with expenditures on war. But whether we are nearer 60 or closer to 70 percent, the obvious is staring us in the face. It is what ordinary people spend that makes an economy. And these expenditures are driven by personal necessity and—if PCE is growing at rates above population increase—spending is also driven by personal choice. Such is still the case for this period: the U.S. population grew at a rate of 0.9 percent annually (1999-2013) over against PCE growth at 2.2 percent. (All of the numbers shown here, by the way, are based on real, meaning inflation-adjusted, dollars.)

When people spend money, corporations begin to hire and invest. When demand is sluggish, the economy—unless artificially stimulated by government expenditures—will reflect the public’s lack of confidence.

This, of course, suggests that incentivizing corporations—as by keeping interest rates artificially low—only incentivizes speculation, not investment or hiring. Therefore the Fed, and thus monetary policy, is never enough to produce confidence in the real public, which controls two-thirds of the economy, and only stirs up those at the 1 percent level who are into investing and such.

The following chart shows the relationships between PCE and GDP for the recent 2000-2013 period:


In this period, the GDP generally lags PCE, growing at a lower rate (2.0% 1999-2013 versus PCE which grew at 2.2% in the period). The GDP appears to be waiting; and even when growth of the PCE signals rising confidence, the GDP is following it sluggishly at best. In the most recent survey of consumer confidence, conducted by The Conference Board, Consumer Confidence was up 2.1 points but CEO confidence was down by a point. That illustrates my point. The CEOs are still waiting for a more robust sign of growing public confidence. Meanwhile the markets are reaching new highs—which reflects the confidence of the rootless 1 percent that lives in the clouds.

Saturday, August 30, 2014

Growth Tremors in Europe

Once more, in the news this morning, gloom and doom (as if we didn’t have enough of that already). The reason for this is that, in Europe, German (-0.6%), French (-0.1), and Italian (-0.8) Gross Domestic Product numbers came in negative for the second quarter compared with the first. The change in Europe’s total GDP was a positive 0.2 percent, but in our day and age positive growth at such low levels is viewed with alarm.

In our times nobody asks how much growth is necessary in our economies. In other words: What is the underlying measure? The underlying measure, it seems to me, is population growth. Whenever GDP growth exceeds population growth—and the more it does so the more true this is—we are engaged in unnecessary overconsumption.

Just to check this out, I looked to see where European population growth now stands. “Now” in this context is 2012, the last year for which UN statistics are available. That year the growth stood at roughly 0.18 or 0.19 (I’m taking data from a graph). Therefore the Q2 GDP growth in Europe is just a shade higher than actual population growth. The two, in other words, are in equilibrium. I am showing the population graphic below; I found it here; the data for it come from this UN report (link).



Sooner or later, and all over the world, we will have to adjust to GDP growth rates that match population growth rates pretty closely rather than diverging sharply—as in the graphic that I’m reproducing from a previous post:


Why? Because the Age of Oil is drawing to a close and we shall be obliged to adjust to the “new normal” eventually. This reasonable projection is simply never seriously pondered by our media which are still convinced that nothing is changing at the basic levels of the world economy. But things are changing. Europe may be ahead of its time and Angela Merkel wise rather than foolhardy in insisting on austerity.