Taxes, Economics, Rawls & Nozick

In the current fight between Democrats and Republicans concerning the debt limit increase, one hears the former primarily focus on the notion of 'fairness' of taxation.
That is, the president and his party's members of Congress will take a few favorite elements of the existing tax code, such as existing rates for higher-income earners, reduced under President Bush in his first term, and grudgingly extended last year, or special provisions for private business aircraft, and hold them up as 'unfair' to lower-income earners.

Of course, from a purely objective perspective, the reason for taxes is to raise money to fund governmental operations. As these posts on taxes that I've written discuss, tax policy has consequences on taxpayer behavior, regardless of whether politicians believe it to be so, or the CBO models such affected behavior.

It's common knowledge that the CBO uses what is known as 'static scoring,' wherein simple arithmetic changes are modeled for tax policy changes. That is, an hypothetical change is modeled as ex post on pre-existing incomes, spending, investing, etc., with no assumption that such a change may have, in reality, changed prior behavior.

Along with this myopic scoring goes the misguided concept of 'paying for tax cuts.' This peculiar view assumes that some tax revenue level is due to the government, so any change in tax law that results in the static scoring showing lower total tax revenues must be 'paid for' by either new taxes or higher rates elsewhere.

Of course, any fool who reads that second sentence instantly realizes its idiocy. You get less of what you tax, so trying to raise more tax revenues through higher rates or new taxes is, overall, self-defeating.

This is why, among the 22 tax-related posts I've written, you will find a couple detailing economic research leading to Hauser's Law, wherein, over time, a fairly consistent 18% of US GDP is collected via taxes, regardless of tax rate structures.

Once you understand and accept that relationship, it becomes obvious that the way to increase gross federal tax receipts is to set rates at levels that maximize GDP.

But this assumes one uses tax policy primarily as a means to fund government. And it distinguishes between tax rates, and tax receipts, which may be inversely related.

But many liberal elected federal government officials in Congress and the White House choose to discuss tax policy primarily as a tool to enforce "fairness."

Unfortunately, when you attempt to make a single policy, such as tax policy, serve two objectives, such as raising maximal or sufficient government funding, and enforcing some undefined notion of "fairness," you get, well, a mess. Especially when measures of fairness are not obvious.

Yes, there are various indices of differences between high and low incomes or taxes paid. As with the subject of concentration of market share in sectors, one can design various measures purported to indicate relative uniform distribution or distortions of any variable.

However, the basic notion that there is some "fair" amount of tax receipts, or their income, which "the rich" should pay, doesn't seem to be any sort of bedrock, fundamental Constitutional principle.

In fact, if you read the Constitution, as I did this morning, it was originally written rather vaguely and imprecisely on the subject of taxes. The only thing that was fairly clear about taxes in the original, pre-1912 Constitution, was that taxes were levied on business activity, not people.

Even today, one could choose to replace the income tax with a spending tax, if one so chose. There isn't really anything special, per se, about income-based taxes, except that it appears to penalize those who earn more.

By the way, which should be the subject of fairness- tax rates, or tax revenues, or percentage of toal taxes paid? Or is it subjective, i.e., whichever soaks the rich more is "fairer?"

On that subject, and this one, it so happened that I stumbled upon a discussion of this topic yesterday morning on CNBC. Due to the loss of Erin Burnett to CNN, and Mark Haines to death, the network has switched its co-anchor lineups, replacing Carlos Whathisname in the 6-9AM slot with Andrew Ross Sorkin, a NY Times liberal media darling.

At issue, with Michele Caruso-Cabrera defending the conservative viewpoint, was whether high-income taxpayers are "giving back" to the nation by paying a lot of gross dollars in taxes. Apparently the president recently called out Apple's Steve Jobs, by name, for failing to "give back" sufficiently to America via charity, as his rival, Bill Gates, has done.

This is an excellent example of why it is dangerous to allow government to begin to use concepts such as "fairness" in taxation policy.

Who is to be our arbiter of what is "fair" for anyone to pay in taxes, or charity, to the nation? Why is it necessary that tax rates even rise with income level? Surely, if there were one flat rate of, say, 10%, then a person earning $1MM would already be paying 10 times the amount paid by someone earning only $100K.

Isn't that "fair?"

The Constitution is notably silent through most of its original language on the topic of citizens having direct relationships with the federal government. One surely does not get the idea, when reading it, that the Constitution had as any of its purposes to enshrine a climate of punishing those Americans who either earned high incomes or amassed large amounts of assets.

How odd, now, to hear one party continually beat a drum for all conversations involving government debt, deficits and spending, to immediately become about "the rich" paying "their fair (meaning higher) share" of taxes.

I find it helpful to step back and recall studying, as a graduate student, two well-known Harvard philosophy professors- John Rawls and Robert Nozick.

At the time, being young, I was enamored of Rawls' concepts as stated in A Theory of Justice. Being a good social liberal, Rawls was big on equity of distribution. I thought this was important at the time.

In contrast, Nozick, a libertarian, concentrated on minimalist states which provided the barest necessary levels and tools of government, in order to leave individuals with maximal liberty and responsibility for their own destinies, as he wrote about in Anarchy, State and Utopia.

I suspect because it's easier for most people to grasp the notion of dividing up an existing pie of resources, or tax obligations, they do not pay as much attention to the notion that some tax and government schemes create substantially larger pies of resources, such that either smaller assessments raise as much tax revenues, or equal assessments raise even more.

It seems that our current Democratic office-holders can't grasp the notion that the US economy would grow faster with simpler, lower tax rates, thus providing even more tax revenues than much higher rates which distort economic resource allocation and retard economic growth.

Besides the purely subjective nature of class-warfare style polemics characterizing whatever "the rich" pay in taxes as "insufficient" or "unfair," such approaches ignore the more basic, pressing function of tax policy, i.e., to fund our government.

And nowhere in the Constitution is there any language concerning what is "fair" about treating high income earners or the wealthy differently than anybody else.

Discipline: The Difference Between Amateur Investing & Professional Portfolio Management

I was recently reminded of a key difference between amateur investors and professional portfolio managers.


Several months ago, a former business partner who had failed to perform according to his obligations, obtained equity selection information for last November. Being information, I could not unsend it, and, with his continued failure to perform, I wasn't going to manage his equity investments for free.

As it happened, he had asked me to accept trading authorization for an equity account, which placed me on the firm's list for duplicate confirms and statements. Thus, I was able to observe his attempts at using the November information.

Despite his having been familiar with my portfolio management approach and discipline for over four years, as an amateur, he stumbled badly in his attempt to emulate my management of his portfolio.

First, he dithered for nearly four months before deciding to buy the equities which my process selected in November. Since each portfolio has a six-month duration, this was a significant mistake on his part. But he compounded that error by investing in some, but not all of the equities in the portfolio.

As I reviewed his holdings at the end of April, when the November portfolio would be traded to conform to May's selections, I noted that his account's performance was roughly 10%, or less than half of my November's portfolio's full term gross performance.

Significantly, one of the equities he failed to buy had the second-highest total return in the portfolio. Omitting that equity not only denied its excellent return, but, due to weighting effects, caused him to buy more of the lower-return equities in the portfolio. Only two of the other issues underperformed the S&P, and not by much, whereas the rest of the portfolio widely-outperformed the index since November, resulting in a gross total return nearly twice that of the S&P500 for the period.

I have taken heed of James O'Shaughnessy's advice to quantitatively-oriented portfolio investors that they should adhere to their model, not second-guess it. My former partner and I had discussed this important point often. Thus, I thought he understood the importance of disciplined investing.

But, in the final analysis, his amateur nature was displayed by his inability to practice the discipline of investing according to an approach which he knew would, when followed faithfully, significantly outperform the S&P.

On Research Design: Coffee Loyalty

Just about two weeks ago, the Wall Street Journal published an article by Julie Jargon (is that a cool reporter's name, or what?) discussing the results of coffee drinker loyalty research from CustomersDNA.

I kept the article because of the counter intuitive results presented in the piece, i.e., McDonalds had the highest scores on customer loyalty among the three major US chains- Starbucks, Dunkin' Donuts and the golden arches.

With my background in marketing research stretching back to my undergraduate studies in marketing, I was perplexed that an independent firm which, apparently, conducted objective research, would reach such surprising conclusions.

What would have to be true for that conclusion to make sense?

After all, nearly everyone I know who frequents Starbucks swears by it. Same for Dunkin' Donuts. My own experience at McDonalds, except for outlets located at major highway rest stops, is service so poor that their espresso-based coffees are simply not memorable.

That's when I reread the article for the second time and realized what was wrong.

CustomersDNA only surveyed patrons about coffee. Any and all coffee.

Well, for Christ' sake, McDonalds has been selling coffee for longer than Starbucks has been in business. That's not the point.

In a paragraph located near the end of her story, Ms. Jargon discussed pricing for basic, brewed coffee at the three chains, repeating the contentions of the researchers that McD's lower prices were the prime cause of their superior loyalty measures among customers.

Having realized this flaw in the study, the whole piece became of basically no importance to me. Nor, I would suspect, anyone else actually interested in how the three chains stack up competitively in espresso and non-coffee beverages.

What I can't figure out is why a research firm wouldn't understand this point and design their surveys and methodologies accordingly. After all, McDonalds entered the espresso-based coffee segment recently because of its higher margins and price points. Same with DD.

And, if you've been to Starbucks or Dunkin' Donuts very often, you would, like me, probably see very few basic, brewed coffee orders. Who cares about that segment? Sure, Starbucks introduced Via, but that's primarily for the home market.

It goes back to something my mentor at Penn's business school's marketing department, Jerry Wind, taught me so long ago. You should be able to specify your detailed research plan, down to the output tables and hypotheses tested, before going to the field with your research. But if you have failed to design the instrument and sampling plan correctly, you're already screwed.

In this case, hard as it is for me to believe, apparently CustomersDNA didn't bother to distinguish between espresso and brewed coffees.

Or did they, but one has to pay for those results?

Too bad if it's the latter, because as Jargon's article reads, and this isn't her fault, the results are, well, boring enough to make you need a cup of coffee to stay awake.

Academic Wayne Mascio Confirms My Proprietary Research Findings

Back in early May, the Wall Street Journal published an article entitled Recalculating the Costs of Big Layoffs.

In the piece, a business professor named Wayne Mascio, from the University of Colorado, was quoted as saying,

"You can't shrink your way to prosperity."

Why didn't I think of that?

Wait, I did! In 1996! And published a piece shortly thereafter in Directorship, a magazine for board members. Then I applied the proprietary results in consulting and equity portfolio management applications.

The Journal article goes on to say that Mascio,

"has studied how companies in the Standard & Poor's 500-stock index have performed over 18 years. His conclusion: those who cut deepest relative to industry peers, delivered smaller profits and weaker stock returns for as long as nine years after a recession."

Well, that's nice, but there are so many caveats in the statement as to make it virtually useless for pragmatic management action.

There's another quote that speaks to a nuance regarding layoffs,

"Companies that used the recession to weed out weaker performers and trim bloated bureaucracies will fare better than companies that slashed across the board, analysts say."

Probably true, but how would the analysts know? From my own research experience, that's an extremely difficult type of data element to reliably recover from primary sources.

However, Mascio's work has other significant problems and flaws.

For example, why dwell on a recession? Not every company faces similar market responses in a recession. So measuring based on the admittedly-flexible recognition of a recession's beginning and end will leave the resulting research comparing business performances which aren't necessarily comparable.

For my own work on this type of phenomenon, I took a much simpler approach. Among several basic patterns of performance, I studied companies whose performances had fallen precipitously, with multiple years of bad total returns, then recovered. This not only allowed me to isolate the particular performance pattern, irrespective of the general economy, but also to estimate probabilities of companies successfully returning to consistently superior performances.

Mascio's use of "industry peers" presents problems, as well. In many sectors, competitors are divisions of conglomerates. In those cases, you can't take the top-line profits or total returns of the company and assign them to a particular division. So the ability to use what I believe to be the best metric of business performance, total returns over multiple years, is unavailable.

Many years ago, I was taught by Jerry Wind, a marketing professor at the University of Pennsylvania, that useful research must take account of a myriad of details at the design stage. The availability and reliability of data are paramount, and fudging them will result in unreliable conclusions.

In this case, Mascio's conclusions, as reported by the Journal article, are likely directionally correct. But there's no ability to assign probabilistic confidence levels, or even really compare such results across companies, given the various constraints which, according to the piece, were built into his research.

More Bad Research On Corporate Performance From Deloitte

I read a reference in a recent Wall Street Journal column by Holman Jenkins to a recently-popular piece of research by two Deloitte consultants, Michael Raynor and Mumtaz Ahmed, along with a "researcher" from the University of Texas, Andrew Henderson.

The book they wrote is described here, and the paper from which it sprang, may be found here in a Deloitte website post, and downloaded/read.

Whenever I read of a reference to some new empirically-based work purporting to diagnose the bases of corporate performance that is desirable to emulate or duplicate, I naturally am curious to learn who did the work, the methodology employed, and their conclusions.

In this case, it appears that Raynor is the leader of the group. His bio can easily be found, as well as his own website. From what I've gathered, he is clearly an intelligent individual, but doesn't seem to be described as having any significant working experience in business, outside of his academic pursuits at Harvard (DBA) and as a consultant at Deloitte. Deloitte, it should be noted, is not exactly in the vanguard of management consulting. Neither is Harvard known as a source for the best empirical approaches to business performance analysis. And it would appear that Raynor is in a sort of 'of counsel' role at Deloitte, as he has his own speaker's bureau representative and website.

In the beginning of their article, the authors state that they believe most prior studies of excellent US businesses have, in fact, been portraits of lucky, rather than skillful firms.

It's also not all that surprising, to me, at least, to learn that Raynor's methodology has little relationship to the real world in which most businesses operate, i.e., a need to produce results that create wealth for business owners. The most easily-accessible data for this, which, conveniently, also is the business form which accounts for the bulk of US business activity, is total returns of publicly-held corporations.

Because I linked to the authors' original article, I won't duplicate their text with reposted passages here.


In their piece, the authors essentially put down total returns as too reflective of future performance, as anticipated by investors, than actual management skill.

Instead, they chose ROA as their preferred measure.

As I mentioned to a colleague, this choice, alone, virtually guarantees the uselessness of all of their efforts.

Yes, they got their article in HBR, won a prize, expanded it to a book. Fine. Tom Peters got a lot of accolades, too, at first. But his work sunk like a stone into the vast sea of strategy and management 'how to' tomes. As, I would expect, will this latest effort by Raynor, Ahmed and Henderson.

Their description of what total returns are is wrong. It's not simply a measure of future "surprises" to investors. Taken as a pattern, over time, total return measures, in a presumably reasonably efficient market of investors and analysts, the ability of a firm's performance to exceed expectations. It does involve expectations, but it also involves expectations based upon prior and evolving performance.

And, more importantly, it is the measure of wealth created by management of the firm, regardless of the exact source of that wealth. It may have been a fortuitous purchase of a patent, a discovery in the research labs, a marketing edge, the discovery of some mineral deposit, or other unpredictable competitive advantage.

In fact, the very unpredictability of the advantage is what generates surprises and wealth. If all gains or excellent performance stemmed from reproducible methods, then those methods would quickly be copied, implemented, and all competitive advantage due to them would vanish.

Such performance can't, won't, and doesn't typically last for very long. But that timeframe can be years, not days or months.

In fact, my own research began with my simple quest to learn what the distribution of company performances was on the basis of being able to consistently outperform the equity markets averages on total return. From that knowledge, I was able to discern a range which constitutes an average length of time of outperformance.

In the same research, I tested ROA's association with patterns and levels of market outperformance, and found it absent for firms which grew revenues at above-average rates. Simply put, ROA is a point estimate of little value in deducing ongoing behavior of firms that are growing at a healthy pace.

And ROA doesn't automatically or tautologically translate into shareholder wealth. So it's going to be of passing interest to both investors and CEOs.

Thus, for all their extensive, hard quantitative work, the authors of the Deloitte study have pretty much doomed it to insignificance because it doesn't generate operable conclusions which directly lead to increased wealth for shareholders or their CEOs.

Then there's the matter of choice of patterns of outperformance.

In my research, I first reviewed real corporate performance over time. From these analyses, I constructed patterning variables which grouped companies by the pattern which their performance exhibited.

By contrast, the Deloitte study authors began by arbitrarily deciding to set a threshold of occurrence of 9 out of 10 years for a variety of unspecified fundamental performance measures.

Why should 9 out of 10 be the appropriate screening value? Why impose a value on the date a priori, instead of simply letting the data describe the true situation?

Thus, the authors proceeded down a path which features their own subjectively-chosen patterns for outperformance on a measure, ROA, which has no direct relationship to the growth of shareholder value in most companies.

As I read their paper, I reflected on my own background being a curious confluence of several important streams of influence. Over many years and with different companies, as a marketing and strategy professional, internal consultant, external consultant and research director, in several different sectors, including financial services, I happened to absorb several key lessons for this type of research.

Being in consulting at Oliver, Wyman & Co., I didn't approach research on the sources of consistently superior shareholder wealth creation with the scepticism that a true believer in efficient financial markets. When I produced my financial services sector results and presented them to retiring Chairman Alex Oliver, he exclaimed, to paraphrase,

'For years we've been saying we had knowledge of what drives superior performance, but we never really did. Now, with this, we do. This is a strategy consultant's ultimate tool.'

Alex was a lot of things, including cheap and petty, but he was arguably one of the best strategy consultants of his time. In his day, he headed Booz Allen Hamilton's strategy practice, leaving to co-found Oliver, Wyman. I took his praise as justifiable proof that my research approach was unique, effective and applicable in a very pragmatic manner.

When I extended the research, on my own, to the entire S&P 500, the results were even more powerful and applicable.

What Raynor, Ahmed and Henderson have produced has no real applicability other than a sort of minor confirmation that what can be easily duplicated is of little lasting value. And that what typically creates significant shareholder wealth can't be reduced to easily-duplicated management dicta.

So, there you have it. The Deloitte study authors and I agree that unexpected innovation can't be easily duplicated as a management style.

But I already knew that, and, if you read this blog regularly, so did you.

Earnings vs. Revenues

Sometimes I have difficulty believing how simple and shallow business writers can be. Even at the Wall Street Journal.

Monday's edition carried a Money & Investing Section lead article seriously discussing whether the recent equity market rally, founded upon the belief of an economic recovery, can be sustained on profit increases without concomitant revenue growth.

Duh.

There's no discussion here. The answer is a resounding, absolute "NO."

In my proprietary research on large-cap equities over several decades, I discovered that there is a large and clear-cut fault line between those companies which can grow revenues, and those which cannot.

The latter exist, and some can actually consistently outperform the S&P500 Index for several years at a time. In the past, Colgate's Ruben Mark did this for about a decade- the longest of any slow/no-growth company which I observed.

But, due to the lack of revenue growth, Colgate's margin of total return over the S&P was only a few percentage points per annum. Far, far below the average total return that the most consistent high revenue-growth companies achieved.

It's a stunningly simple theoretical argument which is borne out in empirical results.

While revenue growth allows all of the rest of the income statement, and, thus, balance sheet, to grow at a rapid clip, revenue stagnation or shrinkage does the reverse.

You can't cut 100% of operating expenses. Neither overhead, nor direct labor or materials. It's a long walk on a short pier.

Thus, without steady growth in consumer demand, low-/no-growth companies will quickly reach the end of what gains are feasible using only cost-cutting. After that, margins are pretty much purely a function of volume.

It's pretty simple. There's no need for a long article or hopeful conjecture.

No, the equity rally of the past few months will not survive another quarter of no revenue growth.

Bad Research: From The Pages of The Wall Street Journal

Two weeks ago, the Wall Street Journal's "Managing" page carried an article by Phred Dvorak entitled, "Dangers Can Lurk in Clinging to Solutions of the Past."

This particular column seems to be, in my opinion, cursed to provide opaque or nonsensical advice on purportedly serious topics. The idea that a one-third page synopsis in the Journal can deliver valuable, actionable management prescriptions seems, on its face, preposterous.

Consider this passage from the article in question.

"Vijay Govindarajan, a professor at Dartmouth College's Tuck School of Business, started looking into experience 25 years ago, when considering why some companies failed at long-range strategy. After studying businesses like Encyclopedia Britannica and Sears, Roebuck & Co., he concluded that some managers are so set in their past ways that they can't cope with new situations."

The author then goes on to cite the professor's conclusions in the cases of Sears vs. Wal-Mart.

But, just from reading the quoted passage, you can see the error both in the companies' approaches, and Mr. Govindarajan's.

Wouldn't you assign long-range strategy to, well, a strategist, rather than hidebound managers who are "so set in their past ways?"

This is why businesses schools purport to teach strategy. It's supposed to be an abstract skill or practice which can be applied by those without a deep experience in a particular function, business or sector.

If not, why do McKinsey, Bain and Mercer exist and prosper? Isn't their entire raison d'etre one of objectivity, external perspective, and the ability to gather and process relevant information without necessarily having 20 years of experience in the product/market at hand?

So, perhaps Professor Govindarajan has it all wrong. Maybe he's looking in the wrong places for the wrong examples.

Could it be that he suffers from, well, too much past experience researching the success or failure of long-range strategy development?

In truth, this is not a simple subject. Having been a strategist, consultant, and the first head of research for what is now the financial sector arm of Mercer Management consulting, I can attest to the difficulty of separating strategy development from implementation. And to the written documents alleging to be strategies, versus the processes by which they were developed.

The activity of strategy development for major businesses is much more about imagination, fresh perspectives and bold vision then about mere product line extensions. If there is any place in a company where you probably don't want veteran line managers, it's in corporate strategy development.

I'm surprised that a professor from Tuck would have been so narrow-minded as to miss this distinction.

Alleged Research On Judgment Versus Experience

Last Thursday's Wall Street Journal featured an editorial by two professors of management, Noel Tichy and Warren Bennis. Tichy used to be Jack Welch's HR guru, way back when he was in the middle of changing GE's once-vaunted management education systems.

I wrote a review of this article in my linked political blog, here, which includes more pointed partisan comments from which I attempt to refrain in this blog.

Rather, in this post, I'd like to reiterate and extend my comments about Tichy's and Bennis' suspect research. In the other post, I wrote, in part,

"Just how does one study 'leadership covering virtually all sectors of American life?'What was their sample size? Their research instrument? How did they test the instrument for content and predictive validity? How does one measure 'judgment,' or 'experience?' How does one measure outcomes of various levels of each quality?

How in the heck do you study qualities like 'judgment,' and believe you know good from bad, for the purposes of projecting the results to America, in its every aspect?Could there not be some interaction effects? Perhaps some level of judgment, mixed with some level of experience, might be better than either one alone? How would you measure those?

This piece was, on the whole, completely unconvincing to me. It suggests the sort of 'research' that emanates from the 'management' field in business schools that give the discipline such a bad name. It seems to me that 'management' degrees are to business schools what 'communications' degree is for liberal arts.

And that's not a compliment.

I found this piece to be an embarrassment in terms of calling Tichy's and Bennis' effort 'research.' It would take a far more detailed explanation of this sort of work for me to accept the methodology and conclusions. Qualitative areas such as these invite poor research to be performed and communicated, without readers of the results fully understanding how it was attempted."

In business, such research would likely require financial performance measures that the authors don't divulge in their editorial, yet they claim to have studied all sectors of American life. Presumably, this includes business. If not, of what value is this to readers of the Journal?

But, let's look at their work from a different angle. In terms of Schumpeterian dynamics, environments change quickly, requiring adaptation and response from businesses. Failure to do so usually means a more rapid decline in the business' fortunes. Thus, just from Schumpeter's work, which first appeared some eighty years ago, we would tend to value informed judgment over pure experience in a dynamic economic system.

That is to say, pure experience is probably not good at leading companies to consistent prosperity in a rapidly-changing competitive environment. Yet, pure judgment, without any experiential information, while perhaps better, is not necessarily superior. Change must be informed and purposeful to lead to good decisions.

Common sense would already suggest that a bias for good judgment, with the support of experience, perhaps among a business' staff, would probably result in the highest probability of long term organizational success for businesses in our modern competitive environment.

With that as my null hypothesis, I'd appreciate research that provided more detail as to what mix, at what organizational levels, of judgment and experience, led to better results.

Instead, Bennis and Tichy give us a rather simplistic finding that judgment 'always trumps.'

That's just not good enough. It adds little, if any value to what any decent board would already suspect. That is, hire a CEO for his/her ability to anticipate and take advantage of change, i.e., judgment. Experience needs to reside somewhere in the organization. But, surely, a board is not going to hire a CEO knowing the candidate has abysmal judgment, but plenty of experience in the business.

To me, the Tichy-Bennis piece reinforces my growing belief that the value of an MBA is lessening, and that 'management' teaching in those programs continues to have little relevance to real world applications.

Equivocation from the Pages of The Wall Street Journal

Last week, the Wall Street Journal published a rather equivocating piece by one of it's columnists, Justin Lahart. I found the piece to be, at best, a waste of time and, at worst, supporting and advocating specious analysis regarding Fed rate cuts and subsequent investment performance.

Consider these quotes from the Lahart's piece,

"Perhaps some of the rules are changing. Investors tend to believe that interest-rate cuts are good for stocks. Research seems to bear that out....

But interest rate cycles don't always appear to be a great guide to stock performance. In the 1960's, for example, stocks did well even as interest rates were rising. It would be unwise to ignore the past 33 years of history, but it might also be unwise to put too much weight on them."

Gee, thanks Justin. Glad you could add value on this issue.

Does Lahart fill us in on inflation rates during the periods involved? That might help us understand the effect of Fed rate cuts, in that the overall market and economic contexts clearly matter. How about GNP growth during the periods, too?

Oh, and what about the market impact of technology in at least three ways: the advent of derivatives trading; computerized trading technology, and; availability of information via computerized technology, to more rapidly and thoroughly react to fundamental and technical information?

Does anyone really believe that you can just compare one activity or measure, such as Fed rate cuts, over time, and assume it will soak up/account for total variance of something like overall stock prices?

Not only is Lahart's piece of no actionable use, it questions credulity as to its reasonability.

I wonder if this thesis would even rate a grade of "D" in any graduate economics course. I expect better from the Money Section of the Wall Street Journal.

Don't you?