[constantpated]

Summary

Both author's limited track history in accounting and insurance research suggests the report is a product of largely insurance industry inputs and shaping, not independent BLS analysis. I conclude the report is trash and raises more questions than answers.

I discuss: Structural problems with the paper; author background; potential areas of conflict between the authors, BLS, and the actuarial industry; problems with data estimation methodology used in light of the Philipps curve and technology; flaws of adjusting measurements without adjusting valuation methods; and conclude with questions related to the usefulness of this information relative to valuation methods.

The report does more to justify why we had high growth without inflation, rather than looking at real reasons for the 1990-2004 "miracle": Excessive growth, low interest rates, and deflationary pressures that kept a lid on prices. The Fed received a false signal that interest rates could be kept low. In short, this report confirms we are still in a mania, and that the Federal Reserve railed to raise interest rates to shut off the money supply and cut back on excess capacity.

BLS has simply back-engineered history to show why there has been no collapse; but has done nothing to justify confidence that the sustainability of this growth is real, or that the insurance industry has undergone any systematic transformation. On the contrary, the lack of a needed correction in the stock market has simply sent a signal of "business as usual" all the while the underlying mania artificially inflates earnings. The insurance industry requires the catalyst of an Enron-Andersen scale disaster to bring the needed reform. BLS report simply delays admitting there is a structural problem.

Robustness: Weak

Report suffers from circular reasoning problems; data estimation problems; and the applicability of the conclusions is questionable. Study adjusts data measurement without considering how the fair valuation would have to be revised downward.

Fairness: Imbalanced

The report is inconsistent, adjusting only the data output, without also adjusting the thresholds on what is/is not acceptable. Report overstates GDP without adjusting "what a fair value of the underlying is relative to the new measurement." GDP has been overstated, and the fair downward revision of fair valuation has not occurred.

Use: Caution is warranted

Readers are cautioned against making assumptions about the sustainability of GDP; the valuation of the underlying; or the suitability of the accounting methodologies. Appears as though there are measurement and audit risks surfacing, warranting understanding per SAS 99 -- extent that accounting methodologies have been changed without fair review understanding by the boards or "independent auditors."

Research: Potential conflicts of interest

Remains to be seen to what extent which industry association has provided the inputs to BEA on "how do we make the insurance numbers look good". It remains to be seen to what extent BEA got inputs from the auditing industry, without considering the extent, if any, auditors arrived at their methodologies on the basis of inputs from the consulting clients who are insurance companies.

Assistance: Other areas

One are of interest are the names of those "who provided assistance." Doing a quick check yielded a report. We could question to what extent the "outside assistance" was provided to ensure the consistency of the BLS-themes, and not with data accuracy.

Questions raised while reading this 1999-version 'revision' include: Are the continued changes in growth rates justifiable; has there been a scrub on the 2004 report in light of what has been said before; are the changes in methodologies and definitions in BLS consistent, or are they unfairly changing definitions to give the precisions of exactness where none is warranted [given the estimation methodologies]. I have doubts.


Author background

I see no evidence that the authors of the study are necessarily experts in insurance accounting, they are more concerned with data crunching. They have no history of reports with the insurance industry. I question their credibility and background in providing comments on the insurance industry. I suspect they have been given inputs by those who have published and done research in the field. Although they may be fine econometric-analysts, neither of the authors have published research or papers that focus on the insurance industry issues. It takes a great leap to believe that the data-crunchers with BLS are astute enough to comprehend GAAP.

Fidler is linked with the UofMaryland, JPSM, which leads us to a cess pool of potential conflicts between academia and industry in re statistics and actuarial services. In my opinion, the same financial non-sense that justified the "don't worry about the 1996-7 Asian Financial crisis-bubble" have returned in BLS.

I'd want to know why the author moved from Indiana to Rutgers -- was there a conflict over methodology and research? This is interesting in that 2002-3 she was on unpaid leave of absence. Listed CV publications is only three, raising questions about her experience, publications. Note that a 2003 publication lists only 3 articles from 2001, indicating a big gap in publications. My editorial comment is that if someone wants to have the credibility of belief [government], those officials need to demonstrate a track record of accomplishments; this record, if outdated, sends the signal of, "I don't care enough to make sure the public knows about all that I've done." Either way, not a good sign.

Note that the Dr. John Worrall a colleague in the same Economics Department at Rutgers is the insurance-industry-related committees. "American Risk & Insurance Association (ARIA), Kulp Book of the Year Committee, the ARIA Mehr Award Committee, and the Social Security Administration’s Technical Research Committee." Based on this alone, I suspect there is a real possibility of conflict: Actuarial-consulting services; industry linkages; and the "independence" of the BLS through Chen.

Chen from Rutgers, and has written on rational expectation models. Remains to be seen how many interactions had with auditor-consultants or with cross pollination from the insurance industry.

Actuarial and Society of Computational Analysts have some intersects that I'd need to do some more research into.

Remains unclear to what extent Chen's sponsor has problematic links with actuarials. The Vienna-based Institute has medical links, which may raise issues: Are the medical foundation objectives [reduce costs, increase revenues for research] in conflict with the "independence" of the BEA [downplay the cashflow problem; overstate the GDP to benefit the President]or the actuarials [downplay the risk, increase premiums, reduce payouts]? Given the potential for overlap, see the risk that the research is based on pet theories from the industry hoping to achieve institutional financial, not public-data reporting, objectives.

Measuring growth

Contrasting this study with Gordon's paper on the Phillips curve leads to some interesting comparisons on methodology. Bluntly, if an author like Gordon can write clearly, I speculate that convoluted writing has something to do with speed, not accuracy. [Yes, I'll apply that standard to myself].

Interesting discussion in the blogs about politicization of BLS data. Godl Eagle shares in the humor.

Growth and technology research: How much pressure is there to justify conclusions that sell the "new paradigm" theory, without regard to real efficiency gains.One problem we find is the smoke and mirrors of GDP and output: There is a great deal of pressure to explain "high growth without inflation" -- was it due to productivity; was the growth real; or did we have high growth, high output not because of productivity/technology but because of deflationary pressures that kept the lid on prices despite low interest rates.

Problem with smoothing is that it smooths the data, but it doesn't also change the thresholds on the decision points.




Discussion

Note: The following is a quick-look at the report and very wordy-convoluted in writing.

Using the file, indicates the article, adobe 9 of 17.

Data: Point of interest that caught my eye.

QUOTE: "The aggregated average annual output of the
22 lines increased 35 percent; 32 percent of this increase
is attributable to the inclusion of data on premium
supplements, and 3 percent is attributable to the
inclusion of data on reinsurance services.
As was expected, the change to normal losses from
actual losses and the use of expected investment income
rather than the actual investment income as premium
supplements did not significantly affect the
aggregated output. The increase in the aggregated annual
average output amounted to 0.8 percent." UNQUOTE

Definitions: Less volatility -- keep this in mind when we talk about assumptions, methodologies, and how they estimate missing data.

QUOTE: "The definitional change has also resulted in significantly
less volatility in the annual output of the insurance
lines that experienced catastrophic losses. The
reduction in volatility is largely attributable to the use
of normal losses rather than actual losses."

Couple of questions: You asking for...


• an explanation of the equations;
  
  
• a discussion of the merits of the conclusions;
  
  
• a summary of the merits of the conclusions?
  
  
• discussion on the merits of their approach;
  
  
• an assessment GDP is over-reported, or underreported;
  
  
• whether the report falls into one of two buckets: either {a} the "who cares, yawn" or {b} "wow, this is important, and nobody realizes that world is going to implode..."
  
  
• flaws with the approach in terms of data? [variables have different years, time spans; data was extrapolated for the missing years -- they could have used the "missing data theory" but chose not to do so, which is less rigorous]
  
  "The extrapolator is based on the assumption that direct premiums earned (direct losses incurred) grew at the same annual rate as net premiums
  earned (net losses incurred) from 1930 to 1950." In short, it looks as though they're "using their expected conclusion" [that there was nothing unusual] to justify how the "missing data" should look; this is called circular reasoning.

Overview

The report, with just a quick glance, suffers from a fundamental flaw of circular reasoning. To what extent-magnitude this is problematic remains to be seen.

Given their conclusions arrive at the magnitude of small percentage differences, it is possible to argue that "the flaws of the data" and the "associated methods used to fill in the holes" generated the outcome that they expected: More of the "oh, there's no problem."

At this point, I share your concern that the accounting methodology has yet to be understood in terms of "What impact would the assumptions have" in terms of GDP changes; and to what extent rewriting history is occurring.

Yet, regardless the results of this study, let us take a step back and consider something.

I shall use a simple analogy. First, let us consider the made up variable called "inventory-sales as a percentage of GDP" [IPG] as a proxy for "how do we evaluate the value of a stock". Suppose the historical average is "15" [made up number].

Now, supposing we have been collecting this data since 1900 to 2004. Further suppose that the "average IPG" has been 15, but suddenly, because we are in a mania, the math wizards are tasked with "explain how the variable is rising well above 15" but stock prices are going up. Theoretically, if the IPG was above 20, there "should be a correction; but we see none, so let's send in the math wizards to explain the rising insurance company stock values despite a deteriorating cashflow." [not saying that is what BEA did; just using this as an analogy for the disconnect between the average and threshold value; and the possible motivation why the study was conducted]

Did they hope to find a reason to ignore unsustainable growth rates and thinning revenues streams?

Presto. The math wizards go back in time, adjust the data, and then move through the data between 1900 to 2004 and come up with a "new average measurement method" that justifies "the current stock prices are well withing normal range." The new number may be 22, well above 15; and therefore they say, "See, we have a new average value that is better; so the growth rate relative to this value is OK."

Did they argue for new methodologies without changing threshold and valuation criteria?

Small problem. If we were to "go back through history" to 1900 and use the "revised methodology" to assess the reasonableness of stock prices relative to IDG, we would find that the "actual value" of the IDG was lower; meaning: That the "fair value of the stock relative to IDG" would have to be adjusted; meaning: It is OK to change the way we measure IDG, but we would also have to go back and adjust the threshold of what differentiates a "fair value" from an "unfair value."

Suppose we were to go back to 1900 and find that the "new calculated fair value" has a threshold value of 10, and that the "new average" with the "new methodology" justified a "fair value of 17." We have a major disconnect: They've changed the threshold to justify a lower value between "what is fair value, and what is not," and at the same time done the opposite with the average value.

In short, using the above analogy of IDG, it is possible to justify a higher value, and then use a methodology that creates a lower threshold. Yet, if this "new threshold" were valid, then we'd have to also go back through time and compare the actual prices, versus the "new calculated prices." This is not done in the study.

Meaning: It is ok to change the methodology, but it is not OK to leave the thresholds unchallenged. Because the "new thresholds and averages" look to have changes from X to Y, that is all well and good if the "old and new thresholds for fair value" are appropriately changed.

Book value

Now that I've rambled on a hypothetical IDG, let's talk about a real number that was changed and fiddled with: The book to value ratio. Recently there was discussion that the inventory to book value needed updating; so going back in history if the inventory calculation were changed, the "fair value" of the book value was adjusted.

The problem was when we actually look at the "measure of fair value" by only changing the measurement, and not also changing the "threshold of fair value" they ended up changing the book-value threshold for "fair value," but didn't look at the "price relative to that new fair value."

In short, the effort to "retroactively" change the definition of the data in history to say "look, today's data is not all that extreme" was another way of saying, "We're going to come up with a new methodology to justify changing the measurement without changing the threshold."

What does this mean

Well, if we go back in history and look at the book value of a stock and find that the "fair value" when adjusted is "more in the acceptable zone" after recalculating the metric [adjusting measurements for inventory], then we're simply coming up with new reasons to justify "why the current over valuation is acceptable."

However, if we're going to change the "way we assess the relative risks of today's data" by changing the way we look at the old data, we need to also consider "are we also downwardly adjusting the threshold" to accommodate the new measurement.

In terms of book-value and inventory, this was not done. Meaning: Although they came up with a new measurement to look at the old data and say, "Hay, book value is not all high..." the problem they had is if they applied the new calculation to the "fair valuation method" they would've found that the "fair value threshold" was going to fall.

This means that although "today's valuation of the stock relative to book value was considered more reasonable" that "reasonableness" only was arrived at by failing to also adjust the threshold value between what is reasonable or unreasonable.

Meaning: If they're going to exclude items from inventory to justify "a more extreme book value is acceptable" then, the "threshold value of the acceptable book-value" needs to be revised downward, ergo meaning that today's valuation relative to the "new method of calculation[/b] is simply "the same magnitude outside the threshold value for the fair value.

In short, it is OK to change the way we measure things; but if we're going to use new methodologies to arrive at a conclusion about "what is OK," then we also need to change the valuation and threshold method of "what is fair value."

In my view, the BEA study suffers from this defect. Although the study doesn't explicitly say [based on a cursory reading] that "if we adjust the insurance return methodology" then the GDP and profit streams are more reliable by X-amount. Rather, I believe such a conclusion is outside the bounds of what is a fair use of report.

Going forward

I'd have to do some more thinking about "how one might wish to use the BEA report" in terms of assessing the merits of the GDP, profit streams, and estimation methods.

Clearly, you hit the nail on the head: That the accounting wizards are using some sleight of hand to come up with a new way of ultimately arriving at fair value of the underlying.

My suspicion is that the writers of the report have not considered the issue of "if we use this new methodology going forward to assess the data volatility, are we invariably inducing people to believe that the actual problem is less." In my view, they're falling into the trap of inducing people to believe a problem is less than what it could be; and failing to go back in time and look at the extent to which the "actual valuation relative to the newly calculated GDP" needs to be revised.

Use of the data: Cashflows as a percentage of GDP

Let us suppose that there is a variable called "cashflow streams as a % of DGP" that is historically defined as having an average value of 20, and the threshold value is 10 of "what is fair-unfair value," with a value of 9 being a good number, and 11 being overpriced.

If insurance cash-flow streams as a % of GDP is arbitrarily defined as having a "fair value" of 4 [made up] using the new methodology; then the "threshold between the fair and unfair valuations" needs to be revised downward from our 10 level, down to say, 8.

But if the "new way of looking at the data" fails to change the threshold value, then going forward we have a "new way of calculating insurance impacts on GDP" without assessing "to what extent the historical valuation needs to be adjusted" and, in turn, the extent that the current valuation as a percentage of GDP is that much more unreasonable.

Conclusion

At this point, I remain skeptical of the report. Although they've done some interesting math, I am concerned that the valuation methodologies of "fair value" have not also been updated. Moreover, I'm concerned that the methodology used to arrive at the missing data used assumptions that were to be tested, not assumed.

Going forward, I would have to give some though to the issues of:

• Does the report send an implicit message that insurance company revenue streams have an unfair impact on GDP;
  
  
• Is GDP being overestimated;
  
  
• Regardless the impact of GDP over/underestimation, does the new methodology ask us to discount bad news about the insurance company revenue streams going forward, without also looking at the extent valuation thresholds have not been adequately updated;
  
  
• To what extent is the market pricing in a new methodology not because it better characterizes the data, but the extent that the new methodology explains why insurance company prices are above the threshold value without a correction.

In my view, the study is a sign that the mania is still here: We have new theories and methodologies to calculate the measures of interest, without also adjusting the threshold values on what is a fair price.

In short, BEA in my view, is simply sending a confirming signal: They're coming up with more numbers to justify why the "high growth without inflation" is to be explained away, all the while flailing to look at the sustainability of those revenue streams; nor have they looked at the historical valuations that would have to be adjusted once we use the new methodologies.

[nobody]

Propaganda is best ignored, not analyzed.

[mjkst27]

surprise surprise the govt is forced to lie to prop the unproppable. The system is built on lies and once enough folks either figure it out or get burned by it, the required debt creaton to float this mess will cease. Momma always said ya can't live a lie - it'll eat you up.

[Goldmember]

When it comes to calling a spade a spade, I must congratulate Major Crapper, and the thorough analysis by Constantpated, as true mastery of shoveling through the sod. Turning over a shovel-full of sod can usually at least find a worm or two with which to catch a fish, but this BEA sod turned over reveals not but excrement that is too rank to even bear a worm.

[constantpated]

The next step in the analysis is to actually scrub the report. For purposes of full disclosure, I shall enter the discussion with the assumptions from above that the insurance-actuarial industry is the primary driver behind the change in methodology, and examine the various points in the reports.

To be clear, at this point I make no effort to describe the validity of the data; rather, this effort is simply to organize the range of "nonsense" that BLS is creating, in the hopes of Identifying patterns. This is not to say that the information from BLS is good or bad; rather, that the BLS report can be used as an indicator of government assumptions, and the extent to which the government is knowingly spewing out non-sense.

At this point, I have no clear idea of what I may find; yet, I shall simply post the findings real time so that others might benefit from the observations. To be clear, the objective of this post is not to give weight to the BLS report; nor is it to imply that BLS data is good or bad. Rather, it is simply to "see what we find" and share comments.

Also, in response to the original post, let us be clear with where we are. We have not actually discussed, nor answered, the original question: "What is going on with the math." I thought it would be useful to do a scrub on the report mechanics first; then simply go through the terminology and wording in this post.

Phase III, for the purposes of thoroughness would be to actually re-run the data through various models; compare the differences; and identify the risks of accepting the data/conclusions relative to an arbitrary definition of reality. Also, phase III would involved comparing the methodologies in the original BLS report relative to others, point out differences; and then highlight how this reports conclusions "when run through that methodology" arrives at conclusions; then comparing the differences. Whether we take that step remains to be seen; however, if the findings from Phase II are interesting, others may choose to bring in new models and rip the BLS report apart.

Prospects of Congressional Staff oversight problems

I venture the findings would be of interest to the Commerce Committees; yet, to be clear, the Senate and House also rely on the same "independent studies" to evaluate the merits of the Executive Branch. In short, contrary findings to BLS would highlight breakdowns in the Senate and House oversight; to which their response is likely to be one of "there is no problem" as admitting an error would result in questions of "how long has this trash gone unchallenged."

Indeed, the media can be guaranteed to cheer with, "We were fooled" and "this is too complicated." Exactly why we have Enron-Andersens, and poor responses from the US attorney who simply says, "We've heard nothing; and we take no action against the Executive Branch because that would be suing ourselves." The system is more designed to not respond than actually consider the merits of the points to be raised. I can guarantee you that based on the initial scrub in Phase I, the results are not going to be pretty.

The analysis

"Comprehensive revision" incorrectly communicates that the new data is correct; or that the report is an improvement. The authors fail to source the data and ideas that drive the new terminology; given their weak background in insurance, it is a concern when econometric-people ["actuaries"] start introducing new terms without adequately identifying their sources. Indeed, we should not be surprised by this lack of disclosure given the Cheney Energy Commission lack of responses on "who was involved in the Energy discussions."

Proxy

Of interest would be to compare the degree of politicization under BLS relative to other administrations; and then use this a proxy for the responsiveness of government; and compare these indicators to the responses and feedback we are getting from Iraq; then assess the extent that Iraq is merely a "faster feedback mechanism" to what fails in the US capital-republic model.

Basis for evaluation

Paragraph one of the BLS report infers that there will be an "improvement" in the treatment of insured losses; yet we find no basis to believe that an industry-sourced effort to change the data is necessarily an improvement; nor do we get a clear definition of what an "improvement" means, or for whom: Industry, actuaries, government, investors, or corporate boards.

To be clear, this definition is important given the Blue Ribbon Committees review of audit committees; and the issue of "materiality" that occurs under PSLRA. At this juncture it is clear that "materiality" as practiced has nothing to do with "what the public needs to make informed investment decisions", and everything to do with "how far from reality can the numbers drift before CEOs end up in jail after 10b-5 rule violations. If we are not clear on "materiality" and the relationship to BLS's "improvement"-paradigm, we're simply doing more of what failed prior to Enron-Andersen: Falling for a "buzzword" like "improvement", yet failing to realize that the author-consultant-industry version of "improvement" is at odds with the spirit of the intent behind 10b-5: That the information, when disclosed, is useful in making informed investment decisions.

I shall not pretend that the information provided in the SEC-documents like the 10K is suddenly "better" given the BLS updates; to be clear the SEC is undermanned, and the responses they get back from industry leave much to be desired. More bluntly, because SEC has so few checks of the 10K/Qs [they only look at a small sample], the chance of "industry stuffing the MDAs with non-sense" is real. In short, if everyone is singing the same non-sense, and the consultants from the actuary business can point to the "evidence of the BLS" report, they get top cover when their CEOs are called before the courts; and the multi-district litigation [MDL] ends up going into discovery which amounts to pennies on the dollar. Woe to those who read the 10Ks without understanding the risks and benefits of stop-losses.

More consistent with the economic behavior of the insurer

To be clear, we are still in paragraph 1 of the report, and simply taking a very cursory review of the report. To those who may be wondering how long this will take, you can multiply the current progress to date, times the number of paragraphs on page 1, and then multiple by 17. I promise to leave nobody unscathed with this analysis.

Use of terminology

Interestingly, the report suggest that it will adopt a new terminology. Of interest would be to evaluate independently the spectrum of actuary reports, conference meeting minutes/slides, and written-data outputs to measure the extent that BLS terminology matches the actuarial industry. I would suspect that if we were to graph the use of terms relative to time, we would see an interesting relationship between the buzzwords used at the various conferences, and the "new terminology" appearing in the BLS report.

BLS sponsors: Media messages confirmed by "independent industry analysts"

Anytime a report like this is produced, before it sees the light of day, there are executive department and academic sponsors. I'm not talking about the disclosed university and reviewers; rather I'm talking about the Senior Executive Service [SES} personnel in commerce who have the power to guide, sponsor, and promote various themes. This information is readily available.

I mention it only so that you keep in the back of your mind the "behind the scenes" lobbying that goes on to promote various themes that are consistent with the Administration/OMB objectives, and to what extent these themes are promoted in a manner analogous what to the office of special plans [OSP] used to promote the "WMD" theory; and the strategy used to identify willing media outlets for the BLS-Commerce-OMB theme.

On a broader scale it will be interesting to track how the BLS-Commerce concepts are flowed through the "media channels" and to what extent the media relies on "other views in industry" that are potentially the very source of the original inputs to BLS, ala do what should have been done once Judith Miller at the NYT was found to be "so good" at reporting Iraqi WMD data.

Notion of services

One disturbing trend is to explain away "blips" in information by saying, "Our cost structure is not inflation, we're just giving you more benefits." In practice, the 'new benefit" is simply "doing what they're required to do, but shifting it from the cost side, to the asset side. To what extent this occurs, I shall not speculate; merely to illustrate how easy the charade occurs in accounting: That a cost is not a cost when the "burden of work" [cost of doing business] can be magically repackaged as a "service" that is "above and beyond" what is already provided" [actually not] and then sold as a "new service" when it is actually "the same service that can only be provided by relabeling the costs."

Put another way, as the overhead costs of a "required service" that depends on "cost benefits realized through productivity gains" [that are illusory], and actually linked not with real improvements but with the expectation of improvements [as derived through expected paybacks/ROI related to IT], when the actual work required to do a task increases due to technology [and there is no real improvement], then the only way to explain away the "inefficiency" isn't to say "Computers are bad" [contrary to the IT-industry paradigm]; rather the solution is to describe the higher cost-structure associated with the same service [rising costs, falling margins, not inflation, but inefficiency] as a new service.

Yet, if we look at the old way of doing things: The service was reliable, it may be slower, but it also was "because it was slower" less prone to errors; and at the same time related to a sustainable growth rate. If we have excessive growth above 2.4% [arbitrary number for GDP] then the growth rate is "too fast" and the "actual demand for services strips the supply". This is not inflation, but an admission that the capacity of the system to support the faster moving economy had assumptions that were at odds with the unfolding reality.

The key to note at this point is that there is a difference between expectations and reality already built into the framework as a necessary input to keep the bubble going; at the same time, the purpose of the BLS paper is to describe the disconnect between expectations and reality without mentioning the words, "excess capacity," "more cursory reviews," "higher cost structure," and "mania." If the economy is going "more slowly" than the 2.4%+ growth rate, that is not bad: As we have the necessary revenue streams to sustain the needed training to monitor internal controls [aka Comply with the SEC Blue Ribbon Committee goal of increasing oversight on internal controls, via SAS99].

That the economy may be going at a rate that is above the 2.4% "sustainable rate," implies not that we are in an era to say "we have a need to explain this reality with new terms," but we have the real prospect that the downside risks with this excessive growth are occurring at the very time that the probability of fraud is going up. Again, rather than assign the risk as an increased-burden that is unchecked via SAS99, the easy way is to redefine the risk as an opportunity, benefit, and cause for celebration; all the while hoping to fend off the SES analysts, and explain away the disconnect in the media by doing what "they do" when interacting with analcysts. We need not speculate on their trips to Flagstaff, Az or the starchiness of their pressed shirts while swooning on the Phoenix Golf Courses.

Bluntly, when we think of "insurance service" we must recall the extent that insurance companies actively abuse, dissuade, and deny valid claims. If there is the prospect that someone is going to lose their home insurance for filing a claim, the problem driving the claim isn't solved; rather, the reporting falls. We have no way of knowing the extent that various insurance industry newsletters about "the threat of loosing homeowner insurance" is driving down the claims. Rather, have a hidden level of claims that are underreported. I'm sure the BLS-weenies will be quick to parrot the industry and say, "This is not material" or that there is "no way of calculating this." Actually, there is; yet, we'll save that until after their CEOs commit in the SEC-documents otherwise.

Disconnect between output and services

We must consider the extent that the "service" is actually inefficiency that was not captured by the original workforce; and the extent that the "looser internal controls driven by growth above the sustainable growth rate/foretasted level" is increasing the risk of poor internal controls.

Example: If an insurance company conducts internal audits, yet those internal audits lack sufficient manpower because of "higher number of cost centers" [audit budget falling, while the audit requirements are rising], the easy solution is to produce reports and data that get rid of the "disconnect between audit requirements and resources" and redefine the disconnect as an improvement in X, Y, Z. Variable. Presto--BLS shows up with the report, and the needed increase in corporate governance via SAS99 is explained away; and the SEC analysts read the same thing and the "outside experts" from academia confirm the paradigm. 10b-5 be damned.

Services provided

It's all well and good to talk about the insurance industry's service and 'what they provide" [above and beyond the fundamentals of insurance]. We run into a problem when we have the Enronization of an industry.

Bluntly, insurance companies are not in the business of helping anyone; they're there to collect premiums, and make money for the CEO to raid. If the CEO can create a financial "cost center" that can create money of nothing, they'll do it.

When insurance companies talk about "services" nobody should be fooled into thinking that this means "assistance." Rather, it means "new means to generate numbers" that create the illusion of progress [ignoring operating cashflows for the moment.] Let us look in general terms at the "service" that an insurance company is "supposed to provide" vs what they actually do.

Insurance companies [from the perspective of a policy holder] is there to help out with a problem; insurance companies [from the perspective of the CEO] is there to deny payments, slow roll action, and come up with excuses to retain cash; and at this * same time time use the premiums collected to dive into new ventures unrelated to insurance: Enron-like entities in Cayman Islands; exotic new ventures. Hence, the pressure to "be part of the team" [kitchen cabinet] to take over countries like Iraq.

Of interest is the extent that a core industry will transmogrify itself into a new industry, justify the "new ventures" on the basis of a "new service" and all the while repeat the errors of the past: Expand into areas that they should not be in; focus on profit centers unrelated to their core purpose. In short, the Enronization of industry is merely letting the beat get out of control; the extent that the insurance industry engages in the practice is not the point. The issue is the extent to which a "core service" is defined as being "core" when it is actually part of the wider net of activities unrelated to providing insurance-assistance to policy holders.

With respect to the BLS report, the key phrase that appears to have industry input is the "does not include all the services provided" meaning: Money is showing up; its unrelated to "traditional op cash," and the "other services" are actually part of the Enronization-phenomena: Money is appearing, but the "real story" would make the Board scream. So rather than actually send a signal of "we've got funny stuff going on via SAS99", the solution is to redefine the "service" of the industry along lines that will expand the 'allowable definitions" to include things that are unrelated to what the "average investor" thinks of when they think of the core industry. In short, the BLS is helping to create a smokescreen that will assist the CEO to generate "new revenue streams that really cannot be explained through traditional accounting" and come up with a new tool to create magic where there is simply non-sense.

Matching principle

Note the limited experience the authors have in accounting and GAAP. When BLS starts its handwaving about "reserves" and "holding" what they're actually getting read to do is to get the camels nose under the tent and come up with new reasons to justify why reserves [that are there to be used] should be considered as "not needing to be required" and "can be used elsewhere."

Do you see the smoke and mirrors? The key point is that reserves are not there to be "smoothed around" and "used to generate returns" [which they are], but the idea of reserves is that they actually be there to be used as a reserve. The best analogy is the current mess going on in Iraq [rest assured, I know the difference between insurance reserves and military reserves]. If the BLS is proposing new definitions that permit reserves to be booked differently, then like Iraq, 'when the reserves are really needed," they're not going to be there unless the bubble continues. This is called success-oriented planning.

If this government "gets away with cursory planning in Iraq in re post-active combat stability" then I would also venture to say that the same analysts-contractors that are pressing for a new market, also have the same pressure to "expand more quickly" regardless the sustainability of those markets, and the real probability that the reserves are going to be used. In short, the "success oriented approach" to reserves needs to be understood when evaluating the reasonableness of a particular company's assumption; and more broadly the BLS assumptions used in the definitions.

Solutions vs risk

One assumption BLS posits is that risk is reduced by pooling; this is problematic in that the assumptions driving the growth can change. Although the assumptions can be tested under sensitivity analysis, pooling in itself does not necessarily mean "a solution"; rather, to be balanced, "pooling" is a stop gap measure so long as the past conditions continue.

Herein lies the flaw of BLS in re the mania. That pooling may have worked as a historical solution to risk does not mean that the solution will work in the worst case. This is not to say that "we require 100% solutions" to all risks; only that the risk BLS is discussing as being 'solved" by pooling is only "solved" so long as the historical assumptions continue. Herein lies the hint of circular reasoning--for if we truly had a cataclysmic event" there is the real prospect that the "magic solution" will fail; like the Japanese banks that "cross collateral's" to spread risks, when one goes down with a bang, a major failure can bring down all the mountain climbers.

This is not to say that US insurance companies are on the precipice like intoxicated-drunken mountain climbers on Everest [they may be, but that's not the point]. I only posit the example to suggest that the inherent assumptions behind the BLS approach is that "what worked in the past" in re pooling is going to continue working. This is something to be proven and discussed, not necessarily assumed for the purposes of "creating new metrics to explain away anomalies and indicators of problems" which I sense the BLS report does.

Real services

BLS also discusses a number of terms related to services and interestingly differentiated between "real services" and something else that is apparently "not real." Whether the activities defined as "real services" are necessarily "services" t the CEO; to the board; or to the customer is of interest.

If the cost is borne by the customer, but the real service is to the CEO, this is not a service, but a management internal control procedure: It is unreasonably defining a "higher cost of business" as a service, when it is actually an overhead cost that should be booked as a cost of doing business. This is not an asset or good will; but an indirect cost that will drive down operating cashflows. The incorrect method booking would be to increase the asset value, and make the assets and 'ability to service loans" appear larger than capable.

Again, we're only in the third paragraph. And to be clear it is evident that the BLS report is opening up the floodgates to new definitions that will permit a shifting of costs-expenses out of the cost pool, and transition them into the asset pool. To what extent this is happening in the "real world" is beyond my interest; my only concern is the extent that the BLS report is starting an industry effort to redefine the actual higher costs as an illusory asset in order to justify growth rates and debts that are beyond their ability to actually service.

Financial gains

In para three [3] page one [1], BLS aptly discusses the net gains associated with reserves. My concern is that there be a sufficient linkage between the "concept of real sustainable income" [premiums]; "operating cashflows" [real number]; "foretasted premiums" [a guess]; and "most likely returns in various market scenarios" [I shall not get into hedging].

To be clear the "opportunity cost" is a burden that falls on the policy holder; it remains to be understood what relevance this factor has with BLS measurement of insurance industry data. I suspect this has something to do with marketing the product in terms of "benefits and costs" that insurance salesmen will use when promoting new products; it remains to be determined to what extent this BLS report is used as promotional material by the industry to create the illusion of "confirming evidence" for the consumer.

Let us consider, by way of analogy the speech Mr Bremer gave immediately after the attacks in Filuja to the new police officers; the speech was in English, the troops spoke Arabic; the words talked about "what is going to occur" relative the needed turnaround after the attacks on Filuja. Bremer's speech wasn't directed toward the Iraqis; but toward the US population. In the same spirit, it appears as though the BLS report has nothing to do with validating data changes, and everything to do with creating a "research report" that will be used to pitch insurance products, or be used to sell analcysts on the idea that the insurance industry has a new paradigm. Oh, the sirens of Enron-Road-Shows are wailing, "Those were not independent reports" and "it was all smoke and mirrors" and "the math was there to give it the illusion of precision where none was warranted."

My concern with the BLS report is that the terminology used has nothing to do with econometrics, and has everything to do with accounting sleights of hand; this is additional evidence that econometric-actuaries are using inputs from industry experts and accounting "professionals." It remains to be seen to what extent the "new terminology" is then repeated in the SEC-documents; reported in the media; and bantered about as "further proof" to give the insurance industry "immunity" from GAAP.

Various studies on performance and output

In the spirit of "quizzical looks," it is noteworthy that BLS refers to "various studies" but then only provides one study. Indeed, had BLS been truly accurate, it would not say "various" but would say "one."

The next question is to ask "how reliable is the Cummins and Weiss, 2000 report; what merits does it have; how was the report used/not used by industry; to what extent does the report provide weight to "greater calls for the insurance company immunity from GAAP" and how closely situated were the authors to the insurance industry. This is analogous to readers of the New York Times saying, "Well, Judith Miller says...so it must be true," without going back and checking the original material.

Given this documents authors have signs of conflicts, it is reasonable to assume that the "cited proof of evidence" is also cited because it shares the same view and is equally associated with the industry being covered. Whether the authors are or are not remains to be seen; but it is interesting to evaluate the merits of the claims on "performance and output" not with reference to the data [that's Phase III], but simply to focus on the claim in light of the author's apparent conflicts; and the possibility that we have cross pollination similar to OSP and the WMD issue.

Innovation

This BLS report posits the idea that a "change" is an "innovation." Again, putting aside for the moment the data, we are asked to believe that something "that we have yet to have explained" is an improvement, without discussing the basis for the improvement; who the improvement is for; and whether the improvement is really a benefit, or a hidden risk.

Again, BLS posits that a proposed accounting change is an "improvement" without citing any accounting literature; nor does it reference GAAP/GAAS; nor is there any discussion of the materiality in re 10b-5. Thus, I conclude that the "issue to be proven" is initially being couched in positive terms with the hopes of ensuring that the information that deserves questions in re GAAP gets some special immunity.

Definition

Of interest in the approach the BLS report takes to changes in definitions. Rather than discuss the basis for the claims, or make reference to the later supporting information, the BLS reports the "benefits" as if they are a truism. This is problematic.

A report that is proposing changes would reference the supporting material that backs up the claims. Again, BLS appears to offer the favorable words without actually providing a clear linkage to the supporting data; nor does it adequately discuss the opposing views. Indeed, who would expect to see opposing views when the insurance industry keeps the naysayers out of the kitchen.

Reporting: Normal/estimated/forcasted losses v actual losses

The BLS report proposes a definition change to calculated services provided. There are two points here: Whether the service is truly a service; and what impact the new definition has in terms of GAAP, matching principle. The original post on this topic covered this concern well.

Notice that the BLS report doesn't actually discuss the impact this has on GAAP; or whether the GAAP principles are met; or whether the "numbers game" [SEC Chairman Levitt, speech, Nov 1998] are considered. BLS simply says "the result is better" without discussing GAAP; the matching principle; whether the revenue streams are adequately booked when earned; or the possibility that premiums collected might have to be returned to policy holders or other parties despite being booked as earned.

Sleight of hand

One thing that BLS does not adequately discuss is "how has the insurance industry been able to get along all these years without a change" and "what's the real pressure to push for this change now." Insurance companies are not some new, dynamic, and cutting-edge industry that they are going through the initial stages of growth that we saw in the dot.com mania days. Rather, these are mature industries, with fairly well established business practices.

Of concern is the notion that "despite this history of doing X, Y, Z" suddenly they have to change. I give up. What, besides a mania, suddenly appeared on the horizon to create the pressure to require this change be made now; how were earlier requests for the change handled by FASB; and have we truly entered a phase of the business cycle where the "impact of not making the change is so high, that the insurance industry will collapse."

To be blunt, "actual losses" have always been known to occur after the premium is paid; this is not new information. Nor is it a "new evaluation" that 'actual Numbers' are different than estimates. What is new is that despite providing no new information, BLS and the insurance industry are creating pressure to say "despite what we've done in the past, and what was claimed before FASB, we really need this change because if we don't get it we're going to have bad things happen."

I propose that the "new change" has nothing to do with "smoothing" and everything to do with "getting around the previous obstacles and concerns" that should have been raised about the reasonableness of booking losses on the basis of expectations, vice actuals. Indeed, the industry for whatever reason, appears to have gotten itself into a snag; and if it can put pressure on the public to not make claims, then the "perceived/foretasted losses" will go down, thereby increasing their expected future option cashflows, and presto...their goodwill and asset valuation.

Whether the actual claims fall is irrelevant; if BLS can "make the case" that the smoothing is better, it remains to be seen to what extent FASB will be receptive to the accounting change. The issue becomes "smoother is better for whom": The investor [more information less related to reality is what we already have], the CEO [increased asset valuation means stock options are higher], the accountant [alleviates uncertainties as the uncertainty will be confided as OK], the consultant [they create the media strategy to lobby for this change before FASB], or the board [avoid nasty questions in re SAS99]?

Large swings

BLS would like the world to believe that "large swings" are anomalies. On the contrary, "swings" are in the scope of possibility. Using metrics that "downplay the swings" does little to give the public an accurate picture of "what is likely to occur" with respect to true valuation risk; operating cashflows; or the probability of catastrophic loss requiring re-insurance payouts.

"Swing caused by catastrophes" is another way of saying, "We in the insurance industry have gotten away with success-oriented planning, so rather than adjust our forecasts on cashflows [revenues, leftovers after costs, income], let's adjust the forecast on costs [expenses, outflows]. Rather than update their models to better forecast profits and margins, the insurance company wants to shift attention away from the "potential bad news impact on profits" and focus attention on 'ways to goose the valuation based on adjusting the margins by adjusting what we payout."

In short, the industry is proposing shifting the attention from "risks associated with profits and valuation" and changing the definition to have a success-oriented approach to the outflows. Thus, valuation is being adjusted not by changes in expectations of future income, but by the changes in expected outflows. This is inconsistent with the fundamental notion of "cashflows relative to asset valuation."

They propose changing the method of valuation from a measure of merit related to income and profits, to a new variable that can be goosed and is related more toward estimates and outflows or costs. If they get into a period where their estimated losses were lowballed, they don't want to take responsibility for the failed planning; rather, they want to back-engineer the numbers to shift attention from the "total premiums and returns" that are fixed or falling; and tweak the side of the income sheet that will reduce costs, regardless the probability that those costs will fall.

In short, if the estimates of premiums prove worthless but cannot be goosed because incomes and premiums are in the past, then we would expect an accountant to put pressure on FASB to adjust what last option they have to change future valuations: Change the costs, back into the estimates. We can only speculate to what extent the "desired costs" and the "expected losses" are not driven by actual data, or actual risks, but by "management driven objectives and targets" that are less related to risk, and more related to desired profits centers. Are you starting to hear the Ghosts of Enron; their chains are rattling down the halls of the Cayman Islands.

Analogy: Medical research

I will not name specific drug companies, only mention that sponsored research in the medical industry is widespread. This is useful information for drug companies to provide to doctors to drive up sales of new products. It remains to be understood to what extent BLS is part of a similar effort to put pressure on FASB and the Senate Banking Committee.

International Bodies

When the domestic lobbying fails, the next step is to move to an international body. Just as the SEC has faced pressure form international accounting standards to "update the US standards," it remains to be understood to what extent the US insurance industry is using the IASC to put pressure on entities that have remained unresponsive to insurance industry pressure.

"new information" is added to the definition and numbers; but is the basis for this inclusion based on real data? No, BLS study extrapolates data to fill in holes, thereby arriving at the conclusions "the historical data is smooth, therefore going forward the data is smooth." That is called circular reasoning.

A more credible approach would be to develop a rigorous model that works with the past data, and then various risk scenarios are pushed through the model that include these "anomalies" and then compare the baseline results to the new accounting. The validation phase of the model isn't simply saying, "What looks better," but more robust: Which assumptions in the accounting produce more meaningful data in light of GAAP and FASB; does the data user [the investing public] get more reliable information; and how robust is the model in handling and planing for these extreme conditions that are low on the list of desirability, and require high reserves, but part of the core function that an insurance company is supposed to plan for.

Planning for risk isn't supposed to be about ignoring the inconvenient data; but in managing the risk so that is is planned for. BLS and the insurance industry are proposing methodologies that are more success oriented, the same bungled logic that got us into trouble in Iraq.

Generally recognize

I have yet to understand how an actuary with little understanding of the accounting rules would know to say 'what is generally recognized' unless they had some help from the accountants in the insurance industry.

Note: They've changed the measure of merit

BLS was supposed to be in the business of providing data. This BLS report is clearly driving into the "how can we create a better picture of profit maximization," a function totally unrelated to "how to we present risk." Again, this is not to say that profits is outside the consideration; rather it is to suggest that BLS is making statements that are inappropriate with respect to data measurement.

Sleight of hand

One trick that we notice is when they discuss a "needed change," [something that has not happened], and then later refer to that "change" as if it were a widespread practice [something that is happening, or a historical precedent."

Note the BLS paper initially started with the assumption that "a change was needed" in re "how we plan risks," moving from actual losses, to expected losses. That was their contention, to be proved. Yet, by the last paragraph of page 17, this "desired risk" is now being posited as a "practice."

let me say that again: The BLS paper starts off with the premise that "the change is needed in how we plan for risk" [unproven, future change]; and now is using that "unproven premise] as a characterization of what is occurring [practice, history]. This is a major signal of concern and warrants understanding. Then BLS states that the "change" is "intended to"..... [do something that sounds good] but is actually driven by desires by the insurance industry to control the cost side of the equation by adjusting the future when their income side is fixed by reality and history.

In no way is the "economic behavior of the insurer" better captured by shifting from actual numbers to estimates. Pure and simple. The data may be "smoother" but doesn't "better capture" anything-- can't capture the future, when the objective of the industry is to adjust the last option they have to avoid paying the piper.

Focus: Shifting from the market to the entity

Another sleight of hand is to forget the history of the industry and attempt to characterize the changes as "something for a company". Yet, GAAP is intended to be applied across all entities; the objective is not to have the industry cherry pick from data and identify favorable results, then use that information to justify "look at this sample, the results are better, so let's change GAAP."

Measuring the variables not the logo

BLS has also fallen into the trap of suggesting that "data measurement improves" if we focus not on the variables that affect the market, but focus on reducing the variability of data for a particular entity. Aggregate BLS data is not gathered to measure a particular entity or company, but to measure aggregate of the economy and macro-economic behavior.

That BLS is focusing on the "benefits derived for the particular corporation by changing definitions" misses the point of what BLS should be doing [Alas, we live in reality]: Focusing on what more accurately measures economic activity, not excuse for failing to fall below that standard; or options to avoid facing the wrath of the market should management plans prove to be success oriented.

End of Page 1

Summary of findings.

BLS is overstating the basis for the change, and fails to provide a compelling case that the results are to be applied to proposed changes in accounting; or that corporate boards need not be concerned with apparent poor performance in the insurance industry. BLS is also allowing itself to be used as a selling tool to put pressure on corporate boards to assent to changes that are unrelated to true economic activity.

Rather than hold management accountable for bloated cost structures, the BLS report simply endorses redefining rising overhead rates as an illusory service so as to justify accepting bloated asset valuations relative to real falls income and margins.

BLS is engaging in an effort to justify changing data based on success; that there is an effort under way to adjust GAAP; and that the situation is Iraq is a good example of the success-oriented approach the insurance company hopes to take: Take credit for the good things, and find excuses for failed plans.

Such is not prudent data representations; and the muddied waters is material information; whether the SEC, FASB, or lead plaintiffs in re securities class action lawsuits link the puffery with the imploding margins remains to be seen. It is unlikely the ABA will be the catalyst for needed change in the discovery procedures or cross examination of "expert" witnesses; and is likely the excessive valuations will be explained away using new metrics.

Conclusions

There are compelling reasons not to change the measurements, most importantly the need to be consistent with GAAP. There are other data runs that would contradict the BLS study and show the opposite conclusions: That information and materiality objectives for the investors and corporate boards would be achieved by not changing the BLS-measurement.

The insurance industry is facing cost pressures during a time when excessively low interest rates have fueled excess capacity. The more cursory training is translating into abysmal internal controls, higher default rates, and greater risks for the insurance providers.

Rather than plan for the needed "weeding out" that comes when a market becomes bloated with inefficiencies, the insurance companies have bloated their balance sheets and valuations on the basis of success, and have hoped to ignore the downside of the business cycle: Business failures, problems, accidents. These are known problems to risk managers.

The insurance industry's approach is to shift the costs of poor planning onto the public in the form of higher promises of services; however, these "services" are simply functions that any insurance company should provide.

Rather than absorb the higher costs over the lifetime of fixed premiums [rising costs, falling margins], the insurance industry is promoting basis services as "value added" and "something that deserves greater premiums." These are hidden cost increases. Higher interest rates will naturally weed out the inefficiencies, the very reason that there remains pressure to delay acknowledging these inefficiencies through creative accounting.

Further reading

Consider how an industry can goose the asset valuations to offload poor performers onto banks hoping to hide losses.

Bluntly, with OPEC Euro-denominated earnings falling, we might ponder the extent to which insurance companies are specifically dressing themsleves up for European Banks as "good investment alternatives" for the Euopreans [to hide their losses because of the lower than expected Euro-earnings from Oil exporters], all the while knowing that the insurance industry is really a dog. Caveat emptor!

[NWD]

Major Crapper;

Clicked your first pdf file link: "file not found."

[DrStool]

Delete the end parenthesis.

[NWD]

Thanks, Doctor.

[DrStool]

Fixed it.

[beardrech]

Permit my comment ,Constant
The next time some sob makes one of those lame remarks about Accountants(or auditors or real analysts) being as boring as dentists,figuratively dentists in disguise ) I would love to be in a position to hit him/her over the head with a rolled up bundle of what i hope will be the final version of what iconsider ,after amateurishly reading, a magnificent essay bordering on art--
If you knew me personally you'd probably say to yourself:What in the hell is this guy doing reading my reports on the insurance industry??And late at nightat that? What gives?
I don't think I can tell you where and whence my amateur interest comes from except perhaps from some occasions where I managed to meet accountants whose being was entirely different from the stereotype
An Armenian poet from Egypt writing his PHD on the Philosophy of the asset was one instance--Wallace Stevens,one of the greatest poets ever,earned his living as a VP of I believe Hartford Mutual; the citation in Goethe's writings somewhere where he cited Paolucci's(sp?) discovery of double entry bookkeeping as possibly the greatest contribution towards an evolving modern civilization--and continuous references to high crimes and misdemeanors in American Businees(1929 and all that) may serve as a short catalog of possible inspiring moments leading to my interests --but geneological inquiries of my interests are of no moment compared to the wonderful essay of yours
I could go on and on but wont--did you see my post somewhere ins toolville where i ask the question about the US having separate military academies for each service while we,the greatest Business culture that ever exxxxisted and the maintenance of its integrity upon which we depend upon for survibal has no equivalent??? Did you?
If you do fill in the absent reference to the first Leader of a West Point Academy of Accounting and forensic Auditing by Nominating Yourself---
Every Stoolie is I believe obligated to read at least a portion of your article if nothing else to at least get a smattering of what forensics are all about
beardrech

[constantpated]

Disconnect between page numbers, equation numbers: i'm not going to guess

Before I go into a detailed analysis of a particular formula, feel free to let me know which equation you are referring to. Specifcially, it is not clear which forumala you are referring to.

MajorCrapper, on Jun 6 2004, 03:01 AM, said:

I wonder if you’ll have the chance to do a detailed evaluation of equation 6 at the top of page 7?

Equation 6 on page 17 of the Oct 2003 report, [adobe 8 of 17]? [Are you referring to Equation 6 on page 8 [not 7]; or are you referring to Equation 5 on page 7 [not page 8]?


Is this the equation you want analyzed?

(6) 1 + t = E (it+1 i(t), i(t-1) , . . .

= βΣ(i-->∞) = 0 (1 - β)t i(t-1),


Other areas of interest: Would assist in providing a complete response

It would help me understand your concern. Feel free to let me know why you're interested in this equation over the others in the article:

• was there a particular comment that you read in the article that made this equiation stick out;
  
• perhaps you have other studies/analysis related to a particular area of interest that are driving your concerns;
  
• perhaps you have the results from another analysis of this report and choose to compare restults from this analysis to the information you may already have;
  
• perhaps there was another study that you have read before that seems to mirror what these writers are doing [by way of illusions, crafting, agendas].

Which areas interested in: The scope of a response is infinite.

I'm inetrested in knowing what types of areas you want comments on, or which areas listed below are "low priority" and "don't care about that". Feel free to let me know which of the following items are most important, and which you do not care about. Perhaps there are other issues/concerns/interest areas not listed that you want to have reviewed.

Analysis could address...

• Methodlogy
  
  - What was not chosen
  - What did they exclude
  - How have their choices resulted in unfair conclusions
  - Have they, by choosing this approach, arrived at a default conclusion is simply consistent with their research objective
  - Had they chose another approach, could they have arrived at another conclusion
  
  
  
• Definitions
  
  Has what they've done fallen outside the range of what the formulas are intended to be applied?
  
  
  
• Appropirateness
  
  - Were the models and formulas appropriate used; have they been derived correctly;
  - have original challenges with the baseline formulas gone unaddressed?
  
  
  
• Risks
  
  - What are the inherent flaws with the forumals/models;
  - have the equations been applied to areas that were not appropriate, or outside the range of what is reasonably to use/apply
  
  
  
• Alternatives
  
  - What other options were more appropriate; why were these methods not used;
  - by not choosing the alernative equations, what can we deduce about the author's assumptions and agendas?
  
  
  
• Factor analysis
  
  - Criteria authors appeared to use to justify choosing this aproach over others;
  - Apparent reasons authors chose this methodology, approach over other reasons
  - Other factors not considered
  - Implications of not considering these other factors
  - Factors, had they been considerd, that wuold have lead to another choice or approach
  
  
  
• Author's Writeup/comments
  
  Inconsistencies between what they said in their report, versus the above findings/discussion on this particular equation.