Political Calculations
Unexpectedly Intriguing!
August 1, 2014

Earlier this week, we wrote what was perhaps one of the most timely posts ever in the history of Political Calculations, as we discussed how we may have finally succeeded in compensating for the echo effect in our forecasting method for anticipating the future of the S&P 500:

Here's the result of our rebaselining the calculation to incorporate the historic stock data in our projections of today:

Rebaselined Alternative Future Trajectories for the S&P 500, 30 June 2014 through 30 September 2014, Snapshot on 25 July 2014

Suddenly, we find that stock prices would appear to be once again predictable, currently following the trajectories that are consistent with investors continuing to be focused on either 2014-Q3 or 2015-Q2 in setting current day stock prices - just as they were before we ran into the echo effect using our regular one-year ago base reference period!

But now, we appear to have reached a fork for that trajectory, where we'll soon determine which future investors are really focused upon.

That's become relevant again today because from all appearances, the S&P 500 followed Yogi Berra's advice about what to do when facing a fork in the road: it took it!

Or more accurately, after a few days of seeming to split their forward-looking focus between the futures defined by the expectations associated with 2014-Q3 and 2015-Q2, investors really focused upon 2015-Q2 in setting today's stock prices.

Rebaselined Alternative Future Trajectories for the S&P 500, 30 June 2014 through 30 September 2014, Snapshot on 31 July 2014

Meanwhile, the news reports of the day's trading activity would suggest that nobody else had any sort of handle on what was driving stock prices, so they were more or less randomly pointing in all directions:

Investors said an upbeat reading from the labor market sowed concerns about the Federal Reserve possibly raising rates quicker than many investors anticipate. Some pointed to disappointing earnings reports from U.S. companies Thursday, which disrupted what has been a strong season for corporate profits. Others pointed to Argentina's default on some bonds and fresh worries that the euro zone's central bank will need to provide more stimulus.

The Dow Jones Industrial Average fell 317.06 points, or 1.9%, to 16563.30. The S&P 500 shed 39.40 points, or 2%, to 1930.67 and the Nasdaq Composite Index dropped 93.13 points, or 2.1%, to 4369.77.

"There are so many things that are coming to a head simultaneously," said Joe Spinelli, head of Americas single stock trading at Deutsche Bank. "Clients are wanting to get into a position to ride out any storm that might pop up."

In reality, investors were adapting their investment portfolio holdings to match the fundamental expectations that coincide with the specific point of time in the future that they've focused upon in making their investment decisions today. And on 31 July 2014, that meant a sudden decline in stock prices, as the S&P 500 suddenly caught up to the future investors had focused upon.

The only real randomness in how stock prices behaved was in the timing for when that shift in focus occurred. How much they would change was not so random considering how stock prices really work as a quantum phenomenon.


Labels: ,

July 31, 2014

On 28 December 2013, approximately 74,000 Illinoisans who had been unemployed for more than 26 weeks but less than 73 weeks lost their unemployment insurance benefits when the federal government's emergency extended unemployment benefits program expired. Paying an average benefit of $320 per week, up to a maximum of $413 per week, Democratic Party politicians and interest groups vowed to do whatever it took to get their unemployment benefits back.

By spring, Illinois' elected representatives in the U.S. Congress used their influence to get the Illinois Department of Economic Security (IDES) to exploit a unique set of data it collects, which gave it the ability to track how these individuals fared in the state's labor market in the months following when they lost their eligibility to continue receiving the state's politically-coveted and federally-funded extended unemployment insurance benefits. In April 2014, the IDES reported that in January 2014, 10,000 of the 74,000 Illinoisans who had lost their unemployment benefits had gotten jobs.

One month later, the IDES reported that 12,700 of the 74,000 Illinoisans who had stopped receiving their extended unemployment checks when the federal government's program expired were working as of February 2014.

That was the last time the Illinois Department of Economic Security made that data public. Earlier this month, we contacted IDES to inquire if they would be publishing any additional data regarding the work status of these 74,000 individuals. Illinois DES spokesman Greg Rivara indicated that they had provided the data in response to requests from elected officials to support the legislative effort in Washington D.C. to reestablish federal funding for the program. Since that effort had stalled out, IDES' analysts had moved on to other work. Rivara also indicated that there were no plans to resume reporting Illinois' unique data on how well this segment of the state's jobless population was faring in the job market beyond what it had already provided.

But we have a really good idea of what happened next. We've already determined that the net number of marginal jobs created in Illinois surged after February 2014.

Illinois: Net Change in Total Employed and Non-Farm Payroll Since December 2013, December 2013 through June 2014

Let's next apply the bits of information that IDES has already provided about how well the state's population of 74,000 long-term unemployed have fared since their eligibility to continue receiving the state's unemployment benefits expired.

Since these individuals were outside of the employed portion of Illinois' civilian labor force, it is very unlikely that these individuals displaced people who were already employed. That would mean then that the members of this large population of individuals, who were suddenly seeking to replace the income they had previously been collecting in the form of weekly extended unemployment benefits, would most likely be filling the newly created marginal jobs in the state. The next chart shows how that played out for this population using the data we know for January and February 2014, then projects the range of most likely outcomes for this group with respect to those newly generated marginal jobs over the next four months.

Illinois: Net Change in Total Employed and Non-Farm Payroll Since December 2013, December 2013 through June 2014

In both January and February 2014, we find that approximately 25.1% of the new increase in jobs that were generated in the state were claimed by Illinoisans who had previously been receiving extended unemployment benefits. We then apply that percentage of total new marginal jobs created as being representative of what the minimum number of hires would be each month from March through June 2014 for this unique segment of Illinois' civilian labor force.

But here, we should note that most individuals who start a job search from scratch will typically find work some three to six months after they get serious about it and start seeking employment in earnest. And with an average weekly income of $320, any full time job paying at least Illinois' minimum wage of $8.25 per hour would be capable of replacing the unemployment benefits they had been receiving for as long as the previous 17 months. And of course, jobs that pay higher wages could do the same for them with fewer hours worked.

We've therefore also indicated on the chart a potential likely trajectory that would represent the pace of re-employment for the 74,000 Illinoisans who became ineligible to receive any additional unemployment insurance benefits after 28 December 2013. What we clearly observe is that the net increase in the number of jobs in the margin of Illinois' economy is more than sufficient to provide for the employment of these 74,000 individuals.

So in addition to a general decline in the state of Illinois' economy in 2014, which we observe in the decline of non-farm payroll jobs after December 2013, in which we also observe an increase in the total employment figure as these displaced workers start working in marginal jobs, we see that the loss of extended unemployment benefits for 74,000 Illinoisans could have also contributed to the large boost of employment in hiring to fill newly created marginal jobs in the state during the first six months of 2014.

Ultimately, this outcome is why Illinois' elected representatives in the U.S. Congress will likely no longer be using their influence to get the Illinois Department of Economic Security to resume its accounting of the fate of those 74,000 Illinoisans whose extended unemployment benefits ran out after 28 December 2013 anytime soon. And you can bet that the political activists who mindlessly cite the IDES' data in their calls to crank up the federal government's extended unemployment benefits program will be happy to never see that data updated beyond February 2014 as well.

For such activists, that's just part of the modus operandi that is part and parcel with their kind of rent seeking.

And that's a shame for serious analysts, because the kind of economic data that can provide really useful insights in how people respond to incentives in their environment is far more rare than it should be.

Update: The Wall Street Journal reports on a study that confirms what we found!

Also, Kevin Erdmann wonders if the federal government's Extended Unemployment Insurance (EUI) program for the long-term unemployed hurt these displaced, marginal workers far more than it actually helped them:

I've been fairly clear that I don't think such long term EUI was a wise policy. I'm not sure we did these workers any favors by having such generous EUI policy. If the main point of this policy was to lessen the incentive for them to accept sub-optimal work opportunities in the months following their loss of work, it seems that what we have done is to create about a million and a half workers, who, at the end of the labor contraction, still are in a position where they will need to accept sub-optimal work opportunities, but now have to try to acquire those opportunities with a big red flag on their resumes. So, they are likely, after having missed two years or more of potential productive work time, to be facing even worse opportunities than they had initially. In trying to save workers from uncomfortable, but manageable, outcomes, we may have subtly pushed them into desperate outcomes with no obvious, systematic solution.

Data Sources

U.S. Bureau of Labor Statistics. States and selected areas: Employment status of the civilian noninstitutional population, January 1976 to date, seasonally adjusted. [Text Document]. Accessed 25 July 2014.

U.S. Bureau of Labor Statistics. Economy at a Glance: Illinois. [HTML Document]. Accessed 25 July 2014.

References

Abraham, Katharine, G., Haltiwanger, John C., Sandusky, Kristin and Spletzer, James. Exploring Differences in Employment Between Household and establishment Data. Journal of Labor Economics, Vol. 31, No. 2, Pt 2, pp. S129-S172. [PDF Document]. http://www.jstor.org/stable/10.1086/669062. 11 June 2013.

U.S. Bureau of Labor Statistics. Employment Situation Technical Note. [HTML Document]. Last Modified 3 July 2014. Accessed 12 July 2014.

Labels:

July 30, 2014

What does it mean when the trends for non-farm payroll jobs and total employment in the U.S. are on two separate and diverging tracks?

We're asking that question today because of something we've observed in the data for the state of Illinois while working on a different project. The chart below shows what we found when we looked at that state's total employment numbers and nonfarm payroll jobs since December 2012.

Illinois: Total Employment and Non-Farm Payroll Employment, Seasonally-Adjusted, December 2012 through June 2014

Here, we observe that the trends for the state's total employment and for the state's non-farm payroll jobs would appear to be on diverging trajectories over time. As we've previously discussed in considering the differences between the Household and Establishment surveys that document employment trends in the U.S., that pattern is largely due to cyclical factors related to turning points in the economy:

One other factor that can contribute to differences between the two surveys' reported data is driven by cyclical factors, which are often present during economic turning points, such as the beginning of recessions or periods of economic expansion. Here, during recessions, the Establishment survey will show job losses as recessionary conditions take hold and workers are laid off, while the Household survey will show gains as those displaced workers move into the kind of marginal employment that is captured by that survey.

That script gets flipped when an economic recovery takes hold, as establishments boost their hiring, pulling workers out of marginal employment, with the results showing up in the data as job gains in the Establishment survey but as a falling level of employment in the Household survey.

The chart above shows those patterns. Here, in 2013, the total employment level declined as the number of people who had been marginally employed declined as the number of people in non-farm payroll "establishment" jobs increased, which suggests that labor market conditions in Illinois improved throughout the year.

But those improving conditions for Illinois' labor market would appear to have reversed since the end of 2013. Here, the number of people employed in non-farm payroll jobs have declined while the total employment figure for the state has increased rather dramatically, which suggests a massive increase in the number of people who are marginally employed in Illinois beginning in January 2014. The chart below takes a closer look at the recent trend in Illinois' employment situation.

Illinois: Total Employment and Non-Farm Payroll Employment, Seasonally-Adjusted, December 2013 through June 2014

Although the data for non-farm payroll jobs and total employment are based on different surveys and cover different portions of the civilian U.S. labor force, we're going to treat them as if they do fit neatly together like jigsaw puzzle pieces in the following analysis to get a sense of how the number of newly created jobs in Illinois would have had to change in order to produce these figures. The chart below shows the change in the number of people counted as being employed for each data series since December 2013.

Illinois: Change in Total and Non-Farm Payroll Employment Since December 2013, December 2013 through June 2014

What's important to consider here is the spread between the disappearing number of jobs counted in Illinois' non-farm establishments and the increasing number of jobs that were counted in surveying Illinois' households. That spread would represent the number of newly generated marginal jobs in the state.

Illinois: Net Change in Total Employed and Non-Farm Payroll Since December 2013, December 2013 through June 2014

The curious thing here is that the magnitude of the net increase in the number of marginal jobs in Illinois through June 2014 is over eight times greater than the actual loss of non-farm jobs at Illinois' establishments during the same period of time. That difference suggests that what we're seeing isn't the migration of workers from establishment to marginal employment after being laid off, but rather a large scale increase in the number of people in Illinois from outside of the state's employed population into marginal jobs that have been created since the beginning of the year.

Where that extra population of job-finding Illinoisans came from will be our next stop in this series.

Data Sources

U.S. Bureau of Labor Statistics. States and selected areas: Employment status of the civilian noninstitutional population, January 1976 to date, seasonally adjusted. [Text Document]. Accessed 25 July 2014.

U.S. Bureau of Labor Statistics. Economy at a Glance: Illinois. [HTML Document]. Accessed 25 July 2014.

References

Abraham, Katharine, G., Haltiwanger, John C., Sandusky, Kristin and Spletzer, James. Exploring Differences in Employment Between Household and establishment Data. Journal of Labor Economics, Vol. 31, No. 2, Pt 2, pp. S129-S172. [PDF Document]. http://www.jstor.org/stable/10.1086/669062. 11 June 2013.

U.S. Bureau of Labor Statistics. Employment Situation Technical Note. [HTML Document]. Last Modified 3 July 2014. Accessed 12 July 2014.

Labels:

July 29, 2014

Every month, when the U.S. Bureau of Labor Statistics (BLS) puts out its Employment Situation report, it provides the results of two different surveys that it conducts each month: the Household survey and the Establishment survey. We thought we'd take this opportunity to note the differences between the two.

The Household portion of the Employment Situation report is conducted by the U.S. Census Bureau, which surveys some 60,000 American households during the week of the 12th of each month as part of its Current Population Survey (CPS). In addition to determining the employment status of the individuals in each surveyed household, which it classifies as employed, unemployed or not in the civilian labor force, the Census collects data on their demographic profiles, including race, Hispanic origin, age, sex, et cetera.

Meanwhile, data for the Establishment is collected by the U.S. Bureau of Labor Statistics as part of its Current Employment Statistics (CES) survey, which incorporates the payroll records of some 144,000 non-farm establishments and government agencies, covering workers at some 554,000 individual worksites. In addition to determining the number of people employed at the surveyed locations as of the payroll period including the 12th of each month, the BLS collects data on the number of hours worked, earnings and the industries in which individuals are employed at the surveyed organizations.

The BLS notes the following differences between the surveys:

  • The household survey includes agricultural workers, self-employed workers whose businesses are unincorporated, unpaid family workers, and private household workers among the employed. These groups are excluded from the establishment survey.
  • The household survey includes people on unpaid leave among the employed. The establishment survey does not.
  • The household survey is limited to workers 16 years of age and older. The establishment survey is not limited by age.
  • The household survey has no duplication of individuals, because individuals are counted only once, even if they hold more than one job. In the establishment survey, employees working at more than one job and thus appearing on more than one payroll are counted separately for each appearance.

These differences mean that the results from each survey do not necessarily fit together neatly like the pieces of a jigsaw puzzle. Census Bureau statisticians have suggested that in addition to the differences noted above, many of the discrepancies between the surveys may be attributed to the characteristics of marginally-employed workers, such as those who work as independent, self-employed contractors or in "off-the-books" or other types of non-standard occupations, which are often captured by the Household survey but not by the Establishment survey.

One other factor that can contribute to differences between the two surveys' reported data is driven by cyclical factors, which are often present during economic turning points, such as the beginning of recessions or periods of economic expansion. Here, during recessions, the Establishment survey will show job losses as recessionary conditions take hold and workers are laid off, while the Household survey will show gains as those displaced workers move into the kind of marginal employment that is captured by that survey.

That script gets flipped when an economic recovery takes hold, as establishments boost their hiring, pulling workers out of marginal employment, with the results showing up in the data as job gains in the Establishment survey but as a falling level of employment in the Household survey.

But economic turning points like recessions are not the only driving factor that can produce these results, which is an idea that we'll be exploring in upcoming posts.

References

Abraham, Katharine, G., Haltiwanger, John C., Sandusky, Kristin and Spletzer, James. Exploring Differences in Employment Between Household and establishment Data. Journal of Labor Economics, Vol. 31, No. 2, Pt 2, pp. S129-S172. [PDF Document]. http://www.jstor.org/stable/10.1086/669062. 11 June 2013.

U.S. Bureau of Labor Statistics. Employment Situation Technical Note. [HTML Document]. Last Modified 3 July 2014. Accessed 12 July 2014.

Labels:

July 28, 2014

We think we may finally have a decent handle on how to compensate for the echo effect in our forecasting of the S&P 500's future.

To briefly recap the story to date, our index value forecasting method incorporates historic stock prices from a year earlier as part of the base reference points from which we project the future value of stock prices. The "echo effect" is something that results from our use of that historic data, particularly when stock prices had experienced a "noise event". A noise event is when stock prices deviate from the level that their fundamental underlying driver, the change in the growth rate of their trailing year dividends per share expected at a discrete point of time in the future, would otherwise suggest they should be set according to our model of how stock prices work.

Those deviations from various noise events are clear when you compare what our model had forecast against the actual trajectory that stock prices took in 2013.

We had previously come up with a filtering technique that initially showed promise, but which turned out to not be able to handle the situation where the stock market had undergone a volatile series of disruptive noise events, which was the case from mid-June through mid-October 2013. So we pulled the plug on it last month.

So we seemed to be up a creek without a paddle for compensating for the echo effect in our forecasting. That much is certainly evident when you compare our forecast with the current trajectory of stock prices, where it would appear that the stock market began experiencing a significant negative noise event on 17 July 2014, but which turns out to really be an artifact of the echo effect in our projections - the echo of the noise events of a year ago.

Alternative Future Trajectories for the S&P 500, 30 June 2014 through 30 September 2014, Snapshot on 25 July 2014

We started thinking about how we recognize the presence of noise in the market in the first place, where we observe it as the deviation from our forecast trajectory of where stock prices would go when investors are focused on a particular point of time in the future. We know what that trajectory looks like and we know what the actual trajectory of stock prices was.

So what if we used our older forecast as the baseline reference for projecting future stock prices?

Well, that wouldn't make much sense, would it? After all, it's a projection, one that was significantly different from the trajectory that stock prices actually took. We shouldn't be in the business of making forecasts based on the hypothetical path that stock prices could have taken a year ago.

But then we thought about it some more. That forecast incorporated the historic stock prices of a year earlier, which are a very real thing that we could use as our baseline point of reference. Instead of using the stock prices of a year ago as the base reference point of our projections, we would instead be using the stock prices of two years ago.

Better still, we wouldn't even need to complicate our basic math like we did with our initial echo filtering technique - we would just need to adjust all the older data points to use the same, but older data that applied at the older point in time. The same math could work!

So that's what we did. Here's the result of our rebaselining the calculation to incorporate the historic stock data in our projections of today:

Rebaselined Alternative Future Trajectories for the S&P 500, 30 June 2014 through 30 September 2014, Snapshot on 25 July 2014

Suddenly, we find that stock prices would appear to be once again predictable, currently following the trajectories that are consistent with investors continuing to be focused on either 2014-Q3 or 2015-Q2 in setting current day stock prices - just as they were before we ran into the echo effect using our regular one-year ago base reference period!

But now, we appear to have reached a fork for that trajectory, where we'll soon determine which future investors are really focused upon.

Now, there are some obvious downsides with this approach, as in addition to trading the base reference points for our projections, we've also traded one year's noise events for the preceding year's. But since the period of 2012-Q3 was relatively quiet in terms of those events, we should expect stock prices to fall within the expected error range for whichever alternative trajectory that coincide with the actual point of time in the future where investors are currently focused, with any major deviations we observe now being attributable to current day noise events rather than the echoes of noise events past.

Previously on Political Calculations

We've been working on how to crack the echo effect in our S&P 500 forecasting method since November 2013. The posts below, presented in reverse chronological order, describe our experience in that endeavor to date as we've worked out how to compensate for the echo effect in real time.*

Reading through all these, we can see why we stuck with our echo-filtering technique for so long, even though we never really liked it very much because of how much it complicated the basic math behind our S&P 500 forecasting method. In the end, it turned out to be capable of compensating for relatively stable short-term echoes, such as from the Great Dividend Raid Rally and the subsequent Fiscal Cliff Deal Rally spanning 15 November 2012 through 17 April 2013, but not the echoes from the much more volatile series of noise events that defined the QE-Uncertainty and Debt Ceiling Crisis noise events that disrupted the U.S. stock market in the period from 19 June 2013 through 17 October 2013.

* Note: To the best of our knowledge, we're the only stock market analysts who have made our work product fully transparent by developing it in public and sharing our observations and results in near-real time on the Internet. And we've been doing it since we announced our original discovery of what really drives stock prices on 6 December 2007.

Welcome back to the cutting edge!

Labels: ,

About Political Calculations



blog advertising
is good for you

Welcome to the blogosphere's toolchest! Here, unlike other blogs dedicated to analyzing current events, we create easy-to-use, simple tools to do the math related to them so you can get in on the action too! If you would like to learn more about these tools, or if you would like to contribute ideas to develop for this blog, please e-mail us at:

ironman at politicalcalculations.com

Thanks in advance!

Recent Posts

Applications

This year, we'll be experimenting with a number of apps to bring more of a current events focus to Political Calculations - we're test driving the app(s) below!

Most Popular Posts
Quick Index

Site Data

This site is primarily powered by:

This page is powered by Blogger. Isn't yours?

Visitors since December 6, 2004:

CSS Validation

Valid CSS!

RSS Site Feed

AddThis Feed Button

JavaScript

The tools on this site are built using JavaScript. If you would like to learn more, one of the best free resources on the web is available at W3Schools.com.

Other Cool Resources

Blog Roll

Market Links
Charities We Support
Recommended Reading
Recommended Viewing
Recently Shopped

Seeking Alpha Certified

Archives
Legal Disclaimer

Materials on this website are published by Political Calculations to provide visitors with free information and insights regarding the incentives created by the laws and policies described. However, this website is not designed for the purpose of providing legal, medical or financial advice to individuals. Visitors should not rely upon information on this website as a substitute for personal legal, medical or financial advice. While we make every effort to provide accurate website information, laws can change and inaccuracies happen despite our best efforts. If you have an individual problem, you should seek advice from a licensed professional in your state, i.e., by a competent authority with specialized knowledge who can apply it to the particular circumstances of your case.