A Dash of Insight

Parabola Hyperbole

As we close the books on May, the S&P 500 has a two-month gain of nearly eight percent.  We have offered reasons for investors to expect this advance to continue, although we certainly cannot vouch for the pace.

With increasing frequency we are seeing comments that the U.S. market gains are "parabolic" or sometimes "straight up."  We will not cite specific references to those using these terms, but if you watch for them, you will see what we mean.

Terminology often has  a strong symbolic content.  It may be designed to express emotion or to convince readers of something that may not stand on facts alone.  At "A Dash" we have noted the pervasive use of negative symbols in discussing the stock market, and sometimes offered alternatives.

Parabolas

We strongly suspect three things about parabolas and those following the stock market:

1. Even the really smart people who are following the market carefully do not remember enough geometry to define a parabola, or to write the mathematical equation.  You can check your own definition here.
2. These same folks cannot draw a parabola.
3. Everyone knows that parabolic growth is some unsustainable pace.  Parabolas precede bubbles and crashes.  That is the source of the symbolism.

The figure below shows a parabola of the simplest form, where Y=aX^2. 
The increase in values on the right side of the chart has that unsustainable exponential quality.  You can see more images of parabolas at Wikipedia.

Parabolic Growth and Stocks

When the Shanghai Composite declined over 6% before Thursday's U.S. trading, there was plenty of discussion about whether this had a significant bearing on the prospects for U.S. stocks.  Some suggested that both markets were "parabolic."  Now that we understand what this means in factual --not emotional -- terms, a simple chart is worth many words.

 
The wise investor or trader is not swayed by emotional language and symbols.

Oil Prices and Gasoline Prices: An Interesting Divergence

Those trading energy stocks must always follow crude oil prices.  This is especially important for investors in Transocean, Inc. (RIG) and Global SantaFe (GSF), both stocks that we hold in trading and individual portfolios.

Even though the front-month spot price has a lot of variation, the energy ETF's seem to follow the front month.  This makes no sense for stocks that are "upstream" like RIG and GSF,  but it fits the pattern.

We have observed that futures trading sometimes seems irrational.  The common scenario is that there is some problem with refinery capacity.  When these stories have hit in the past, often due to weather, crude oil futures have spiked.

Economic analysis suggests that the opposite should occur.  If refineries have reduced capacity, the demand for crude is reduced.  That demand curve should shift, leading to lower crude prices.

The countervailing force is trade in the "crack spread."  Traders study and trade the relationship between the price of a barrel of oil and the price of refined products, using ratios that vary according to the season.  When the crack spread reaches an extreme, there is a mean-reverting trade.  This causes buys in crude.

Today we saw an interesting divergence, noted in the Wall Street Journal.  Crude prices fell in the face of reduced refinery capacity.  This is new!

At "A Dash" we continue to believe that investors in energy stocks can use these moves to adjust  positions.  If the investor is focused on the long-term demand for future drilling, any dip provides an opportunity.

Summary

Equity investors do not study the futures markets and the forces behind that trading.  Those that do can gain a significant advantage in their stock trading.

Market Higher in 2007: The Underlying Bid from Stock Buybacks

Since investing is about risk and reward, one must always ask a key question?

Is there an underlying bid for stocks?

The current answer is a resounding "Yes".  The bid comes from corporate stock buybacks and private equity.  It does not yet include individual or foreign investors.  This article focuses on buybacks.

Background

Pretend for a moment that you are an executive at a major corporation that is enjoying fantastic profit growth.  You are faced with four choices for your cash:

1. Reinvest in growth -- research, development, or new equipment.
2. Retain cash, building up the balance sheet.
3. Increase the dividend.
4. Buy back stock.

Corporations choose among these alternatives based upon their own assessment of opportunities and rewarding investors.  Whatever they do may be second-guessed by Street analysts, most of whom have never met a payroll, who claim to know the best decision.

Retaining cash may preserve the opportunity for future investment or acquisition, or it might be a cushion for weaker prospects.

Increasing dividends is a long-term commitment to a higher return of earnings.  Companies do not take this action lightly, since they hate to reduce dividends if circumstances change.

Buying back stock provides an alternative payoff for investors.  As a result, each investor owns a larger share of future earnings.

Investor Preferences

Some investors want dividends, buying stocks with big yields.  Some funds will only buy stocks that pay dividends.  Other investors seek capital gains.  For these investors, buying in stock is quite attractive.

Investor preferences are often driven by tax consequences.  Buying back stock generates capital gains while dividends create income.  The (temporary?) tax reductions on dividends equalize this picture, but some individual preferences still favor capital gains.

In the mid 90's many valuation models that were based upon dividend yield completely broke down.  We experimented with these models, but abandoned them in the face of an obvious trend.  Corporations realized that many investors preferred capital gains taxation to dividend taxation.  Investors were "voting with their feet."

The Significance

The stock buyback trend has become so important that it now exceeds dividends in the payoff for the investor.  Standard & Poors shows that the tipping point for this trend was in 2004, with the buyback impact now about twice as important as dividends.

For those interested in the prospects for equities -- asset allocation, the most important decision and most common mistake -- the support of stock buybacks is crucial.  Please note that the existence and significance is a fact, and an important element of the current market rally.  There is no sign that it is stopping.  Strong corporate balance sheets, built through several years of double-digit profit gains, suggest that the trend can endure.

Writing for RealMoney last November, James Altucher put is as follows:

I really disagree with the notion that share buybacks are bad for a company. I think, in this day and age when private equity firms and S&P 500 companies have more cash than ever, we'll be seeing the supply of shares slowly being taken out of the market over the next few years. You can argue it's because they have no better use for the cash. But the real reason is that profits and margins are at all-time highs because of increases in productivity and the companies just plain and simply don't need the cash. So why not give it back to us?

A prescient comment from Altucher.

The Naysayers

There is a lot of commentary on buybacks from pundits who have been wrong about the stock market for a time period now measured in years.  The complaints include the following points:

• If companies were really confident, they would pay higher dividends (a micro decision);
• Some buybacks merely cover option grants (sometimes true, worth watching at a micro level);
• Many investors would prefer higher dividends (investors have a choice here);
• Companies are buying stock merely to inflate the stock price (this is what we want, so do we know the true value of the company better than the insiders?);
• This cannot go on forever (but it can go on for a long time).

Conclusion

The Naysayers sound like debaters who are losing on the macro facts.  They then make company-level assertions that the decisions are unwise or unsound.  In my reading of these comments it is never accompanied by a quantitative analysis.  It is second-guessing of corporate management by people who have no experience running a company.

On a company- specific level, the investor should do homework and decide about the company.  On the question of market valuation, these arguments are hollow.

The "poster-company" for buybacks is IBM.  Some bearish analysts choose to talk about what IBM earnings would be if they had not engaged in buybacks.  Who cares?  That was their choice, and investors should look at the capital structure of the company as it now stands.  Where does that leave the current IBM shareholder?

Take a look at the recent upgrade of IBM by Goldman Sachs to see the real market effect.  Take this case and start multiplying.....

 

Market Higher in 2007 Series: Handling Adversity

How should one react when expecting a big move, but the market moves against you?

Having laid out our basic thesis, the potential for major gains in U.S. equities, we are immediately faced by selling that is described as "ugly" by most traders.  What this really means depends upon one's time frame.

A Good Example

CNBC today featured an interview with a technical analyst who does good work.  Let us recap his comments, with the S&P 500 daily chart in front of us.

 

The analyst was asked whether it was a good time to "buy the dip."  The market was down about 1% at the time.  His response was as follows:

• It was good to take money off of the table from the run-up.  (It was not clear whether that was to be done at the moment of the statement, a week earlier, gradually, or on yesterday's close.
• There would be continued selling.
• The basic trend was upward, so one should be getting long in the 1450-1475 range.

Let us suppose that an active fund manager or trader had followed this advice.  Since there was no specific guidance and days or amounts, we shall assume that he sold 20% of his position at about 1500 give or take a few points.  (This was a popular technical point, 1503 in the SPU's and a bit less in the cash.)

Let us further suppose that the fund manager sold another 20% with the market down 1% today.

What is the plan?  Is he to buy some at 1475 and the rest at 1450, assuming that point is reached?
Even if everything is executed to perfection, the trader makes about 0.4% on one leg (20% times 2%) and 0.8% on the other leg (20% times 4%).

Most traders are neither so agile nor so accurate.  Meanwhile, what if the full dip does not occur?  Most traders have trouble "chasing" when the predicted dip does not happen.  The risk is that they are under-invested during a major run.

It is tricky to time the market for a small gain.

Longer Time Frames

Investors should look at the longer time frame, better represented by a weekly chart.  On this basis the selling seems like a minor setback.

Our modeling guru is Vince Castelli, a consultant who completed a distinguished career as a Navy scientist.  He has a method for trend-following situations.  It may lose something at turning points, but catches all of the big moves.  The time frame is relatively short, measured in days.  Vince's models remain bullish on all market indices.  He uses indicators similar to others, but measured in ways we regard as superior.

Our Take:  We remain long even in our short-term trading accounts.  Please note that the trading position is model driven.  The charts are just for illustration.

For another technical view and better charts, we always read Trader Mike, who today sees a bit of technical damage.  Worden also went to a downtrend on the shortest of their four time frames.

Psychology

Today's psychology illustrated exactly what we had predicted.  There are many active traders and hedge fund managers who want to be the first to anticipate a poor economy.  The highly negative sentiment has many poised to jump at any sign of economic weakness.

Fundamentals

Fundamental analysis should be the watchword for long-term investors.  That means looking at forward earnings projections compared to risk-adjusted returns from other asset classes.  As long as stocks are so cheap compared to bonds, the buy signal is in place.

Those who believe they are wiser than economic forecasters seize upon any piece of evidence to support that viewpoint.  At "A Dash" we are consumers of forecasts, including the following:

• The ECRI, repeatedly stating that leading indicators show strength in the economy.
• David Malpass, who continues to see economic strength, with risk coming from eventual inflation.
• Consensus economic forecasts, showing solid growth in the rest of the year.

At "A Dash" our emphasis is on education -- picking the best sources, choosing the right indicators, and interpreting data.  We do not offer trading advice.  So many who blog about trading do that better.  We do wish to help long-term investors get on the right side of major moves.

We remain quite happy with what our friend at Abnormal Returns calls a contrarian position.  This is good.

Why US Stocks Can Move Much Higher - Part One, Overview

It is our conclusion that stocks can move much higher during 2007.  This is no surprise to regular readers of "A Dash", but it is a good time to summarize the current situation.  We will do this in a multi-part series examining several issues.

This installment considers an overview of basic considerations.

Psychology and Sentiment

Over the last few weeks we have noted a changed attitude among many active traders and fund managers who state public positions.  We started to note these, planning to cite links, but decided against it.  It is so pervasive that it seems unnecessary.  Everyone is "taking something off the table" and trying to lock in gains, nervous about the seemingly relentless advance.

The TickerSense blogger sentiment poll captures this quite well,  with over 40% bears and 25% neutral.  It seems unusual for bearishness to be rising with the market.

One reason is that the bullish forecasters are seeing the market approach their original expectations  for the year.  Revisions to forecasts are modest.  Abby Joseph Cohen is going to 1600  on the  S&P for  2007.  That puts her on the bullish extreme, but it is only about 6%.  Ed Keon, whom we have cited in the past for his excellent analysis of market factors, remains the biggest bull with his forecast going to 1650.

Meanwhile, there are plenty of forecasts of a major blow for stocks.  Traders are reacting to perceived risk and reward.  That is how psychology works.

There is a lot of rhetoric about a "melt-up" or "ignoring the fundamentals."  Since we believe in analysis rather than rhetoric, it is necessary to look at technical and fundamental considerations.

Technical Indicators

Before accepting the "melt-up" talk, it is useful to look at a chart.  We recommend today's excellent analysis by TraderMike.   We  see in his charts some  strong trending markets, but nothing  parabolic.  Many active traders follow Worden, where today's  indicators show uptrends in every time frame they follow (subscription required).

Some technicians report "overbought" conditions.  It would take a very small pull back to relieve these overbought readings.  Moreover, overbought trending markets can move higher -- much higher.

Most importantly, our own technical models, devised by Vince Castelli, caught the end of last year and the current move.  They remain bullish on all of the major indices, a position that (unlike many others) we have reported contemporaneously on TickerSense.

Fundamentals

Some assert that the market has gotten ahead of fundamentals, since stocks have advanced more than recent earnings growth.  These analysts are focused on what we call "local efficiency."  They are assuming that last year's pricing was an accurate valuation.

In fact, stocks have lagged during a multi-year period where profits grew at double-digit rates.

There is a lot of catching up to do.

Our own preview of 2007 informed investors that market valuations were low when one took the current low interest rates into consideration.  Those who ignore interest rates in their analysis of  fundamentals are adopting a method that we find distinctly inferior.

We have explained why this is true.  Articles in this series will show how it is playing out before our eyes.

Summary

There are also plenty of miscellaneous arguments lacking evidence.  Our favorite radio commentators on Car Talk have a term for such claims concerning car repairs.  They call them "BOGUSSSSS".  We will try to identify and discuss several instances including the following:

• "Peak" earnings
• Ignoring interest rates
• The market record of umpteen up days and the need for balance
• Stock buybacks as "inferior" earnings
• Poor recession forecasting
• Earnings mean reversion

Our work is laid out and our position is clear.  Obviously, the stock market can decline at any time for many different reasons.  Our technical models can change our trading positions, and we shall report if that happens.

These would be short-term factors.  Our fundamental conclusion is that stocks have plenty of room to run.  We remain leveraged up in trading accounts and close to full investment in individual accounts.

Avoiding the Time Frame Mistake

Once again Brett Steenbarger has provided invaluable advice to traders.  (We make note of his themes where we want to pursue the discussion, but we are hopelessly behind the prolific Dr. Steenbarger.  We will never catch up!  Most traders know that they should read his site every day, as we do.)

Let us recap his analysis and then try to add to the discussion.

Dr. Brett recounts the case of a real trader (fictional name of Chris) who had a long-only system.

Chris has developed a trading method that is long only. He looks at the Bollinger Bands (volatility envelopes) surrounding the 20-day moving average for the S&P 500 Index (SPY). If we close above the upper band/envelope, he buys the market on close. If we return to the area between the bands, he exits the position to limit losses. His idea is to participate in strong trending markets.

As we read this, we were quite skeptical.  Discussing it in our office, we noted that it was close to the opposite of what our models suggested.  We try to participate in trends by watching long-term moving averages and short-term crossovers.  While this is a gross over-simplification of our system, developed by our astute modeler Vince Castelli  (results currently report weekly on the TickerSense Blogger Sentiment Poll), it captures the general idea.  Meanwhile, Vince's models find mean-reversion in over-extended stocks for short-term trades of the type Chris did.

So how did Chris do?

Brett reports the following:

He had an effective system--if he had traded it in reverse. Traders need to understand how markets move on *their* time frame. Much losing of money among short-term traders can be traced to the mistake made by Chris.  What occurs on the longer time frame and at shorter time frames can be quite, quite different.

Brett's analysis pursues a theme that he and we have discussed before -- good games and time frames.  If you do it wrong, this is what happens:

Overall, Chris lost about 90 S&P points trading long positions in a bull market with perfect market discipline and psychology.

WOW!  This is an exceptionally well-put and dramatic assessment of how a trading system can go wrong -- without proper testing and time frames.

Meanwhile, there is an important lesson for investors.  For the average person, being in the right asset class at the right time is the most important investment decision.  You do not need to catch the top or the bottom, but missing big moves is costly.  If you are a long-term investor, your entry and exit should reflect the time frame.  Do not miss the big moves by attempting short-term market timing.

If you are a trader, the indicators may be quite different, and system testing is absolutely necessary.

Our guess is that many traders fall into the "Chris trap", so vividly described by Brett.  We also suspect that many long-term investors prematurely sell stocks and reduce positions because they focus too much on short-term timing.

Economic Indicators and the Market: Interesting Data from a Great New Site

How does the market respond to "better than expected" economic data?

Some may be surprised at the research finding reported by Bespoke Investment Group.  Paul Hickey and Justin Walters look at economic releases from the last sixteen months.  There is actually a slight negative correlation between better-than-expected data and gains in the S&P 500.  Check out their site for the complete results.

The names of the Bespoke authors should sound familiar, since Paul and Justin are known for developing the popular TickerSense site.  Paul has earned one of our highest accolades:  We turn off the mute button when he is on CNBC!  In just a few days they have already created a lot of interesting content.  The articles at Bespoke (now on our blogroll) feature the nice-looking charts that are a hallmark of their work.

Our Take

Trading based upon economic indicators is quite treacherous, as we discussed in our article on this week's ISM manufacturing report.  As Bespoke points out, stock traders have been preoccupied with concern about Fed policy.

In a time period when everyone is watching to see if the Fed can hit the Glide Path, economic strength may not be perceived as bullish.  It would be interesting to look at a longer time period and separate inflation measures (high inflation is always bad) from general economic strength (which can actually be "too hot").

Meanwhile, this is a good research question and an interesting first look at the topic.

Payroll Employment Report and the Birth/Death Model

How should we interpret today's employment report, showing a growth in non-farm payrolls of 88K, a bit less than expected?  There is also an increase in the unemployment rate and a different picture of job growth from the survey of individuals.

This is the real story, with as little technical stuff as we can manage.  If traders or investors want to understand the data -- viewed by many as most important -- this is as good as we can make it for those without technical background.

Background:  The BLS in Action

The most important thing for investors and traders to understand is that the reports are prepared by civil service employees using professional statistical methods.  They do not change staff or opinions with shifts in partisan control.  They are not biased in favor of a particular outcome.

Nearly all of those commenting on today's report, and particularly the Birth/Death Model, have never worked in a government agency and never done any forecasting using statistical methods.  Do not listen to them!  Since this is a subject where we can add value for the investment community, we have written extensively on this topic.

[Digression for the record -- I was "loaned" from the University of Wisconsin to the Wisconsin Department of Revenue for a couple of years a long time ago.  The DOR did these forecasts for the state.  I also taught graduate classes to mid-career government  professionals.  The courses covered public finance and research methods, among other things.  So I know how these public officials think and what they try to do.]

Imagine that you are attempting to count all of the jobs in the U.S. economy, and you must do it EVERY MONTH.  There is no way to count them.  Compare this to voting, where in the 2000 election we had trouble actually counting the votes of people who showed up at the polls.  (Remember the "hanging chad"?)  There are 130 million jobs.  The result you get is an estimate based upon surveys and statistical techniques.

The monthly job count is the result of a survey, using as your sampling frame the businesses that existed at the start of the year.  This is subject to various sources of error, as follows:

• Sampling error.  Even when you have a large sample size, there is always sampling error.  It is small in percentage terms, but large in the aggregate.  The sampling error for the jobs report has a standard deviation of about 60k jobs.  (Check here for the best standard English description of this you will see online via my colleague Allen Russell).  That means that 2/3 of the time the reported result will be +/- 60K.  If you want a 95% confidence interval, you need to double that.  This is the result after ALL businesses in the sample send in their forms.
• Revisions.  As we discussed in our Employment Report Preview, the source of the revision is not any tinkering by the government.  It is the result of businesses reporting late.  Did you ever take an extension in filing your tax return?  It has no meaning, unless you think there is a systemic bias to businesses that are late in filing.
• Non-sampling error.  The original sample does not include new businesses, and it includes other businesses that have failed.  Briefly put, this is a major problem unless there is an exact offset between the two.

So what does our earnest and professional government statistician do?  The only major place to improve is the non-sampling error.  The BLS discovered that they had serious errors without making some adjustment to the original survey.  This was the reason for creating the Birth/Death model.

They state in the description of the methodology that there is a fairly constant relationship between births and deaths of businesses.

Earlier research indicated that while both the business birth and         death portions of total employment are generally significant, the net         contribution is relatively small and stable. To account for this net         birth/death portion of total employment, BLS is implementing an         estimation procedure with two components: the first component uses         business deaths to impute employment for business births. This is         incorporated into the sample-based link relative estimate procedure by         simply not reflecting sample units going out of business, but imputing         to them the same trend as the other firms in the sample. 

It seems counter-intuitive to use business deaths to predict births, but they are looking at the data and we are not.  None of the critics are either.  Perhaps the BLS needs to share more about the underlying data.

The major point is that the BLS economists are making an honest and earnest effort to capture job changes missed by the survey.

They check their results with a benchmark revision.  Eventually, they have an actual count of jobs from state data, and they update their model regularly to reflect this.  They do an annual revision for the benchmark and a quarterly revision of their ARIMA time series modeling.  (This is a standard method.  Like other forecasters, we use it frequently.  Readers should look with suspicion on the comments of anyone who does not seem to understand this method).

In short, the BLS staff is using standard professional methods to make the best possible estimate of job growth.  It could be off by 60K on the sampling error, or more if the Birth/Death model is wrong.  None of the critics offer a better method.

What the Birth/Death Model Contributes

The Birth/Death Model has improved the estimates.  In fact, despite the constant criticism from those who claim that it adds "fictional jobs" the model actually underestimated job growth in recent years.  That is why the benchmark revisions added jobs.  It was an attempt to correct the non-sampling error, and it improved the estimate.  The critics who said that the model over-estimated job growth were proven wrong by actual state data, used in the benchmark revision.  The reaction of the critics was to ignore the actual count and criticize the BLS for "finding jobs."  These critics should walk a mile in the moccasins of someone trying to provide useful data.

Please note that the Birth/Death model does not make a single jarring adjustment to the number of jobs in a particular month.  The BLS goes back and spreads the jobs growth over the year, using the ARIMA model, in proportion to the year's data.  Critics are challenged to offer a better approach....

The BLS warns that the methods are based upon the continuation of past trends.  They do not look at any other sources of data about economic growth.

Conclusions

• Those drawing inferences from revisions do not understand the process, as we explained in the  preview for this report.  Doug Kass (we like him, we respect him, we read him, and we often profit from his short-term advice) made the point both on his daily blog and on Kudlow (video here) that there was the first downward revision in many months.  This is meaningless and Doug should know better.
• There were various mis-statements about the Birth/Death Model.  Some analysts tried to add the adjustment to the final NFP report.  The BLS explicitly states that one should not add Birth/Death adjustments to seasonally adjusted data.  Anyone doing this does not understand the method.

Q: Can I subtract the birth/death adjustment from the seasonally adjusted over-the-month change to determine what it is adding to employment?

A: No.  Birth/death factors are a component of the not seasonally adjusted estimate and therefore are not directly comparable to the seasonally adjusted monthly changes.  Instead, the birth/death factor should be assessed in the context of its effect on the not seasonally adjusted estimate.

• Some observers tried to focus on the construction job component, especially suggesting that the Birth/Death Model added an unrealistic number of jobs in this sector.  The model does not specify the sector for job growth, so this statement is simply wrong.  Many of those looking at the "internals" of the report lose track of a simple fact:  This is a survey.  There is an error band around any reported category.  They tried to count all of 9 million jobs in construction and mining and such in one month and compare it to the count in the next month.  There is a wide error band.

Our Conclusions

While we do think that the BLS is using a professional and technically sound method, it was obviously slow in catching growth during the expansion.  We would not be surprised to see some modest downward benchmark revision when we have an actual job count for this year.  This point was made by Tony Crescenzi today in his excellent blog on TheStreet.com's RealMoney (a paid site, but worth it for any serious investor).  Tony uses the household employment survey to assist his analysis, since he thinks it might catch factors missed in the payroll report.  We agree.

Econobrowser, a site that we read daily on RSS, takes a different approach.  James Hamilton blends data from several report estimates to get a different projection.  While this differs dramatically from our own forecast using Michigan Consumer Confidence, initial jobless claims, and the ISM manufacturing index, it is interesting and professional. 

Meanwhile, the Fed is looking at these data in a long-term trend, in conjunction with other indicators.  Chairman Bernanke, the Open Market Committee, and the 350 Fed economists all know how to interpret employment data.  They do it much better than those on TV.

We would all like to have a monthly read on employment.  I would also like to know how the Sox will do tomorrow or the Bulls will do versus the Pistons.  It is important to realize the limitations of the data.  There is a difference between the data we want and the data we need.  It requires interpretation.

Prediction

Many of the interpretive mistakes cited here will appear in Alan Abelson's column tomorrow.....

Little Known Facts about the Payroll Employment Report

Here are a few facts that you probably do not know about the Payroll Employment Report (unless you are a regular reader of "A Dash").  You should know them, because the Fed does.

• The Bureau of Labor Statistics (BLS) does not actually measure the change in jobs from month to month!  We know this may seem confusing.  The change in jobs is what everyone talks about, but it is not what the BLS measures.  They try to estimate the total number of jobs, using survey techniques.  They then compare the estimate from one month to the estimate from the next to calculate the change.

The result:  They can be great at estimating the total, and still have a huge error band for the change.  If you want more explanation on this point, we covered it here.

• The original report is revised for two reasons, but not because the government is cooking the books.  The first reason is that many of the businesses in the survey do not send their reports in on time.  What a surprise!  Some businesses NEVER respond.  The BLS does two revisions, based on more complete returns, and then declares the result to be final -- for a time.  The second reason for revision is that the BLS sample for the survey includes only businesses that existed at the start of the year.  The dynamic economy is gaining and losing businesses all of the time.  The BLS eventually takes actual data from state employment offices and compares it to their own count.  They adjust the methodology based upon the actual count, using something called a birth/death model.

Result #1:  Anyone who claims to see "a trend in the revisions" is being fooled by randomness.  You can tune that person out, and move on to useful work.  The revisions reflect businesses that were late.  Who knows the reason for that?

Result #2:  Critics of the birth/death model generally provide a very lame analysis.  Any such critic should step up to the plate and suggest a better method.  The BLS takes the actual state count at the end of the year.  They go back to their methods and try to improve them by building this in.  Many critics do not like the need for this revision, but they have nothing better to offer.

• The so-called "internals" are also a survey result.  All of the data that people talk about -- the job growth by sector, the hours worked, or whatever -- are also survey results.  The error range for subsets is even greater than for the overall number, since the surveyed population is smaller.

Big-time commentators do not understand this.  It is a pretty cheap shot to criticize the government, claim that revisions are political, and offer one's own view of something like a "birth/death  model".  The BLS economists do not go on CNBC to defend anything, so it is an easy way to look smart and sell research to institutions.  Do not be fooled by this!

• We will never know the real truth--the actual change in payroll employment.  The final result, entered more than a year later into official statistics will be the outcome of two surveys.

The result:  Even if you knew the actual change (my old stat prof said "God whispers in your ear and tells you TRUTH") you could be seriously wrong.  Why?  The market is trading on the BLS survey estimate -- something that has a wide error band.  This is true even though the survey is professionally designed and has a large sample.

You can test this for yourself!  My long-time friend and colleague Allen Russell has assisted us in devising the Payroll Employment Game.  Those of you reading this can get inside information, the actual figure entered as "truth" for this month -- 129,000 jobs.  This is the result of our excellent regression model using the various key indicators charted at the PEG site.  If you repeatedly enter this number as your guess, you will have the best possible result.  You might even win our prize.

Conclusion

The information described here is useful because most of the Street does not get it, but the Fed does.  You may not be able to guess the number in advance, but you will have a better sense for the way it is viewed in the FOMC.  As we have described in detail, the Fed knows better.

Mortgage Availability and Personal Consumption: The Dubious Relationship Breaks Down

What happens to Personal Consumption Expenditures when banks tighten up mortgage lending standards?  With the release of April PCE data, we can now check out a dubious, but widely publicized prediction.

Background

Two months ago the influential Doug Kass repeatedly published a chart that purported to show a near perfect correlation between lending standards as measured in a quarterly Fed survey and year-over-year PCE.  The chart was also posted and discussed at the widely read Calculated Risk blog site.

In a three-part series on "A Dash", we went to the original data sources and performed our own analysis.

Part One. We showed readers that the correlation was exaggerated, that the scale had been manipulated in a deceptive fashion, and that the causation argument did not fit the data.  The existing correlation was probably spurious, the change in each resulting from changes in prevailing economic conditions.

Part Two.  We explained the difference between a confidence interval and a correlation, helping readers to understand the difference between substantive significance and statistical significance.

Part Three.  We compared the chart to various optical illusions, showing why accurate measurement is better than the eye.

The Prediction and the Result

The original Kass chart showed an ominous tightening in lending standards, suggesting that we were on the verge of a similarly precipitous decline in personal consumption.

As one can see from the updated chart, (the new segment indicated by a red line around it) the PCE change was modestly lower.  The rate of PCE growth continues well within the range from the last two years.

The Kass prediction was incorrect.

Conclusion

As we concluded in our original analysis:

The current mortgage market is much different from that of 1990. Nearly everyone -- especially Doug Kass -- believes that recent standards have become quite loose.  Some tightening is a logical reaction.  There is nothing in the data he presents that shows that this should result in a decline in consumer spending.

Such a decline might occur, of course.  There may be other reasons to link housing and the economy.  That is beyond the scope of Doug Kass's argument and this response.  The point here is that the data in the original Kass chart do not support his conclusion.

The next Fed survey of bank officers should be reported any day, so there will be a new data point to add to the chart.