Archive for the ‘market frictions’ Category

Excerpts and Notes from Goldberg’s “Billions of Drops…”

December 23, 2015

Goldberg, S. H. (2009). Billions of drops in millions of buckets: Why philanthropy doesn’t advance social progress. New York: Wiley.

p. 8:
Transaction costs: “…nonprofit financial markets are highly disorganized, with considerable duplication of effort, resource diversion, and processes that ‘take a fair amount of time to review grant applications and to make funding decisions’ [citing Harvard Business School Case No. 9-391-096, p. 7, Note on Starting a Nonprofit Venture, 11 Sept 1992]. It would be a major understatement to describe the resulting capital market as inefficient.”

A McKinsey study found that nonprofits spend 2.5 to 12 times more raising capital than for-profits do. When administrative costs are factored in, nonprofits spend 5.5 to 21.5 times more.

For-profit and nonprofit funding efforts contrasted on pages 8 and 9.

p. 10:
Balanced scorecard rating criteria

p. 11:
“Even at double-digit annual growth rates, it will take many years for social entrepreneurs and their funders to address even 10% of the populations in need.”

p. 12:
Exhibit 1.5 shows that the percentages of various needs served by leading social enterprises are barely drops in the respective buckets; they range from 0.07% to 3.30%.

pp. 14-16:
Nonprofit funding is not tied to performance. Even when a nonprofit makes the effort to show measured improvement in impact, it does little or nothing to change their funding picture. It appears that there is some kind of funding ceiling implicitly imposed by funders, since nonprofit growth and success seems to persuade capital sources that their work there is done. Mediocre and low performing nonprofits seem to be able to continue drawing funds indefinitely from sympathetic donors who don’t require evidence of effective use of their money.

p. 34:
“…meaningful reductions in poverty, illiteracy, violence, and hopelessness will require a fundamental restructuring of nonprofit capital markets. Such a restructuring would need to make it much easier for philanthropists of all stripes–large and small, public and private, institutional and individual–to fund nonprofit organizations that maximize social impact.”

p. 54:
Exhibit 2.3 is a chart showing that fewer people rose from poverty, and more remained in it or fell deeper into it, in the period of 1988-98 compared with 1969-1979.

pp. 70-71:
Kotter’s (1996) change cycle.

p. 75:
McKinsey’s seven elements of nonprofit capacity and capacity assessment grid.

pp. 94-95:
Exhibits 3.1 and 3.2 contrast the way financial markets reward for-profit performance with the way nonprofit markets reward fund raising efforts.

Financial markets
1. Market aggregates and disseminates standardized data
2. Analysts publish rigorous research reports
3. Investors proactively search for strong performers
4. Investors penalize weak performers
5. Market promotes performance
6. Strong performers grow

Nonprofit markets
1. Social performance is difficult to measure
2. NPOs don’t have resources or expertise to report results
3. Investors can’t get reliable or standardized results data
4. Strong and weak NPOs spend 40 to 60% of time fundraising
5. Market promotes fundraising
6. Investors can’t fund performance; NPOs can’t scale

p. 95:
“…nonprofits can’t possibly raise enough money to achieve transformative social impact within the constraints of the existing fundraising system. I submit that significant social progress cannot be achieved without what I’m going to call ‘third-stage funding,’ that is, funding that doesn’t suffer from disabling fragmentation. The existing nonprofit capital market is not capable of [p. 97] providing third-stage funding. Such funding can arise only when investors are sufficiently well informed to make big bets at understandable and manageable levels of risk. Existing nonprofit capital markets neither provide investors with the kinds of information needed–actionable information about nonprofit performance–nor provide the kinds of intermediation–active oversight by knowledgeable professionals–needed to mitigate risk. Absent third-stage funding, nonprofit capital will remain irreducibly fragmented, preventing the marshaling of resources that nonprofit organizations need to make meaningful and enduring progress against $100 million problems.”

pp. 99-114:
Text and diagrams on innovation, market adoption, transformative impact.

p. 140:
Exhibit 4.2: Capital distribution of nonprofits, highlighting mid-caps

pages 192-3 make the case for the difference between a regular market and the current state of philanthropic, social capital markets.

p. 192:
“So financial markets provide information investors can use to compare alternative investment opportunities based on their performance, and they provide a dynamic mechanism for moving money away from weak performers and toward strong performers. Just as water seeks its own level, markets continuously recalibrate prices until they achieve a roughly optimal equilibrium at which most companies receive the ‘right’ amount of investment. In this way, good companies thrive and bad ones improve or die.
“The social sector should work the same way. .. But philanthropic capital doesn’t flow toward effective nonprofits and away from ineffective nonprofits for a simple reason: contributors can’t tell the difference between the two. That is, philanthropists just don’t [p. 193] know what various nonprofits actually accomplish. Instead, they only know what nonprofits are trying to accomplish, and they only know that based on what the nonprofits themselves tell them.”

p. 193:
“The signs that the lack of social progress is linked to capital market dysfunctions are unmistakable: fundraising remains the number-one [p. 194] challenge of the sector despite the fact that nonprofit leaders divert some 40 to 60% of their time from productive work to chasing after money; donations raised are almost always too small, too short, and too restricted to enhance productive capacity; most mid-caps are ensnared in the ‘social entrepreneur’s trap’ of focusing on today and neglecting tomorrow; and so on. So any meaningful progress we could make in the direction of helping the nonprofit capital market allocate funds as effectively as the private capital market does could translate into tremendous advances in extending social and economic opportunity.
“Indeed, enhancing nonprofit capital allocation is likely to improve people’s lives much more than, say, further increasing the total amount of donations. Why? Because capital allocation has a multiplier effect.”

“If we want to materially improve the performance and increase the impact of the nonprofit sector, we need to understand what’s preventing [p. 195] it from doing a better job of allocating philanthropic capital. And figuring out why nonprofit capital markets don’t work very well requires us to understand why the financial markets do such a better job.”

p. 197:
“When all is said and done, securities prices are nothing more than convenient approximations that market participants accept as a way of simplifying their economic interactions, with a full understanding that market prices are useful even when they are way off the mark, as they so often are. In fact, that’s the whole point of markets: to aggregate the imperfect and incomplete knowledge held by vast numbers of traders about much various securities are worth and still make allocation choices that are better than we could without markets.
“Philanthropists face precisely the same problem: how to make better use of limited information to maximize output, in this case, social impact. Considering the dearth of useful tools available to donors today, the solution doesn’t have to be perfect or even all that good, at least at first. It just needs to improve the status quo and get better over time.
“Much of the solution, I believe, lies in finding useful adaptations of market mechanisms that will mitigate the effects of the same lack of reliable and comprehensive information about social sector performance. I would even go so far as to say that social enterprises can’t hope to realize their ‘one day, all children’ visions without a funding allociation system that acts more like a market.
“We can, and indeed do, make incremental improvements in nonprofit funding without market mechanisms. But without markets, I don’t see how we can fix the fragmentation problem or produce transformative social impact, such as ensuring that every child in America has a good education. The problems we face are too big and have too many moving parts to ignore the self-organizing dynamics of market economics. As Thomas Friedman said about the need to impose a carbon tax at a time of falling oil prices, ‘I’ve wracked my brain trying to think of ways to retool America around clean-power technologies without a price signal–i.e., a tax–and there are no effective ones.”

p. 199:
“Prices enable financial markets to work the way nonprofit capital markets should–by sending informative signals about the most effective organizations so that money will flow to them naturally..”

p. 200:
[Quotes Kurtzman citing De Soto on the mystery of capital. Also see p. 209, below.]
“‘Solve the mystery of capital and you solve many seemingly intractable problems along with it.'”
[That’s from page 69 in Kurtzman, 2002.]

p. 201:
[Goldberg says he’s quoting Daniel Yankelovich here, but the footnote does not appear to have anything to do with this quote:]
“‘The first step is to measure what can easily be measured. The second is to disregard what can’t be measured, or give it an arbitrary quantitative value. This is artificial and misleading. The third step is to presume that what can’t be measured easily isn’t very important. This is blindness. The fourth step is to say that what can’t be easily measured really doesn’t exist. This is suicide.'”

Goldberg gives example here of $10,000 invested witha a 10% increase in value, compared with $10,000 put into a nonprofit. “But if the nonprofit makes good use of the money and, let’s say, brings the reading scores of 10 elementary school students up from below grade level to grade level, we can’t say how much my initial investment is ‘worth’ now. I could make the argument that the value has increased because the students have received a demonstrated educational benefit that is valuable to them. Since that’s the reason I made the donation, the achievement of higher scores must have value to me, as well.”

p. 202:
Goldberg wonders whether donations to nonprofits would be better conceived as purchases than investments.

p. 207:
Goldberg quotes Jon Gertner from the March 9, 2008, issue of the New York Times Magazine devoted to philanthropy:

“‘Why shouldn’t the world’s smartest capitalists be able to figure out more effective ways to give out money now? And why shouldn’t they want to make sure their philanthropy has significant social impact? If they can measure impact, couldn’t they get past the resistance that [Warren] Buffet highlighted and finally separate what works from what doesn’t?'”

p. 208:
“Once we abandon the false notions that financial markets are precision instruments for measuring unambiguous phenomena, and that the business and nonproft sectors are based in mutually exclusive principles of value, we can deconstruct the true nature of the problems we need to address and adapt market-like mechanisms that are suited to the particulars of the social sector.
“All of this is a long way (okay, a very long way) of saying that even ordinal rankings of nonprofit investments can have tremendous value in choosing among competing donation opportunities, especially when the choices are so numerous and varied. If I’m a social investor, I’d really like to know which nonprofits are likely to produce ‘more’ impact and which ones are likely to produce ‘less.'”

“It isn’t necessary to replicate the complex working of the modern stock markets to fashion an intelligent and useful nonprofit capital allocation mechanism. All we’re looking for is some kind of functional indication that would (1) isolate promising nonprofit investments from among the confusing swarm of too many seemingly worthy social-purpose organizations and (2) roughly differentiate among them based on the likelihood of ‘more’ or ‘less’ impact. This is what I meant earlier by increasing [p. 209] signals and decreasing noise.”

p. 209:
Goldberg apparently didn’t read De Soto, as he says that the mystery of capital is posed by Kurtzman and says it is solved via the collective intelligence and wisdom of crowds. This completely misses the point of the crucial value that transparent representations of structural invariance hold in market functionality. Goldberg is apparently offering a loose kind of market for which there is an aggregate index of stocks for nonprofits that are built up from their various ordinal performance measures. I think I find a better way in my work, building more closely from De Soto (Fisher, 2002, 2003, 2005, 2007, 2009a, 2009b).

p. 231:
Goldberg quotes Harvard’s Allen Grossman (1999) on the cost-benefit boundaries of more effective nonprofit capital allocation:

“‘Is there a significant downside risk in restructuring some portion of the philanthropic capital markets to test the effectiveness of performance driven philanthropy? The short answer is, ‘No.’ The current reality is that most broad-based solutions to social problems have eluded the conventional and fragmented approaches to philanthropy. It is hard to imagine that experiments to change the system to a more performance driven and rational market would negatively impact the effectiveness of the current funding flows–and could have dramatic upside potential.'”

p. 232:
Quotes Douglas Hubbard’s How to Measure Anything book that Stenner endorsed, and Linacre and I didn’t.

p. 233:
Cites Stevens on the four levels of measurement and uses it to justify his position concerning ordinal rankings, recognizing that “we can’t add or subtract ordinals.”

pp. 233-5:
Justifies ordinal measures via example of Google’s PageRank algorithm. [I could connect from here using Mary Garner’s (2009) comparison of PageRank with Rasch.]

p. 236:
Goldberg tries to justify the use of ordinal measures by citing their widespread use in social science and health care. He conveniently ignores the fact that virtually all of the same problems and criticisms that apply to philanthropic capital markets also apply in these areas. In not grasping the fundamental value of De Soto’s concept of transferable and transparent representations, and in knowing nothing of Rasch measurement, he was unable to properly evaluate to potential of ordinal data’s role in the formation of philanthropic capital markets. Ordinal measures aren’t just not good enough, they represent a dangerous diversion of resources that will be put into systems that take on lives of their own, creating a new layer of dysfunctional relationships that will be hard to overcome.

p. 261 [Goldberg shows here his complete ignorance about measurement. He is apparently totally unaware of the work that is in fact most relevant to his cause, going back to Thurstone in 1920s, Rasch in the 1950s-1970s, and Wright in the 1960s to 2000. Both of the problems he identifies have long since been solved in theory and in practice in a wide range of domains in education, psychology, health care, etc.]:
“Having first studied performance evaluation some 30 years ago, I feel confident in saying that all the foundational work has been done. There won’t be a ‘eureka!’ breakthrough where someone finally figures out the one true way to guage nonprofit effectiveness.
“Indeed, I would venture to say that we know virtually everything there is to know about measuring the performance of nonprofit organizations with only two exceptions: (1) How can we compare nonprofits with different missions or approaches, and (2) how can we make actionable performance assessments common practice for growth-ready mid-caps and readily available to all prospective donors?”

p. 263:
“Why would a social entrepreneur divert limited resources to impact assessment if there were no prospects it would increase funding? How could an investor who wanted to maximize the impact of her giving possibly put more golden eggs in fewer impact-producing baskets if she had no way to distinguish one basket from another? The result: there’s no performance data to attract growth capital, and there’s no growth capital to induce performance measurement. Until we fix that Catch-22, performance evaluation will not become an integral part of social enterprise.”

pp. 264-5:
Long quotation from Ken Berger at Charity Navigator on their ongoing efforts at developing an outcome measurement system. [wpf, 8 Nov 2009: I read the passage quoted by Goldberg in Berger’s blog when it came out and have been watching and waiting ever since for the new system. wpf, 8 Feb 2012: The new system has been online for some time but still does not include anything on impacts or outcomes. It has expanded from a sole focus on financials to also include accountability and transparency. But it does not yet address Goldberg’s concerns as there still is no way to tell what works from what doesn’t.]

p. 265:
“The failure of the social sector to coordinate independent assets and create a whole that exceeds the sum of its parts results from an absence of.. platform leadership’: ‘the ability of a company to drive innovation around a particular platform technology at the broad industry level.’ The object is to multiply value by working together: ‘the more people who use the platform products, the more incentives there are for complement producers to introduce more complementary products, causing a virtuous cycle.'” [Quotes here from Cusumano & Gawer (2002). The concept of platform leadership speaks directly to the system of issues raised by Miller & O’Leary (2007) that must be addressed to form effective HSN capital markets.]

p. 266:
“…the nonprofit sector has a great deal of both money and innovation, but too little available information about too many organizations. The result is capital fragmentation that squelches growth. None of the stakeholders has enough horsepower on its own to impose order on this chaos, but some kind of realignment could release all of that pent-up potential energy. While command-and-control authority is neither feasible nor desirable, the conditions are ripe for platform leadership.”

“It is doubtful that the IMPEX could amass all of the resources internally needed to build and grow a virtual nonprofit stock market that could connect large numbers of growth-capital investors with large numbers of [p. 267] growth-ready mid-caps. But it might be able to convene a powerful coalition of complementary actors that could achieve a critical mass of support for performance-based philanthropy. The challenge would be to develop an organization focused on filling the gaps rather than encroaching on the turf of established firms whose participation and innovation would be required to build a platform for nurturing growth of social enterprise..”

p. 268-9:
Intermediated nonprofit capital market shifts fundraising burden from grantees to intermediaries.

p. 271:
“The surging growth of national donor-advised funds, which simplify and reduce the transaction costs of methodical giving, exemplifies the kind of financial innovation that is poised to leverage market-based investment guidance.” [President of Schwab Charitable quoted as wanting to make charitable giving information- and results-driven.]

p. 272:
Rating agencies and organizations: Charity Navigator, Guidestar, Wise Giving Alliance.
Online donor rankings: GlobalGiving, GreatNonprofits, SocialMarkets
Evaluation consultants: Mathematica

Google’s mission statement: “to organize the world’s information and make it universally accessible and useful.”

p. 273:
Exhibit 9.4 Impact Index Whole Product
Image of stakeholders circling IMPEX:
Trading engine
Listed nonprofits
Data producers and aggregators
Trading community
Researchers and analysts
Investors and advisors
Government and business supporters

p. 275:
“That’s the starting point for replication [of social innovations that work]: finding and funding; matching money with performance.”

[WPF bottom line: Because Goldberg misses De Soto’s point about transparent representations resolving the mystery of capital, he is unable to see his way toward making the nonprofit capital markets function more like financial capital markets, with the difference being the focus on the growth of human, social, and natural capital. Though Goldberg intuits good points about the wisdom of crowds, he doesn’t know enough about the flaws of ordinal measurement relative to interval measurement, or about the relatively easy access to interval measures that can be had, to do the job.]

References

Cusumano, M. A., & Gawer, A. (2002, Spring). The elements of platform leadership. MIT Sloan Management Review, 43(3), 58.

De Soto, H. (2000). The mystery of capital: Why capitalism triumphs in the West and fails everywhere else. New York: Basic Books.

Fisher, W. P., Jr. (2002, Spring). “The Mystery of Capital” and the human sciences. Rasch Measurement Transactions, 15(4), 854 [http://www.rasch.org/rmt/rmt154j.htm].

Fisher, W. P., Jr. (2003). Measurement and communities of inquiry. Rasch Measurement Transactions, 17(3), 936-8 [http://www.rasch.org/rmt/rmt173.pdf].

Fisher, W. P., Jr. (2005). Daredevil barnstorming to the tipping point: New aspirations for the human sciences. Journal of Applied Measurement, 6(3), 173-9 [http://www.livingcapitalmetrics.com/images/FisherJAM05.pdf].

Fisher, W. P., Jr. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. In M. Wilson, K. Draney, N. Brown & B. Duckor (Eds.), Advances in Rasch Measurement, Vol. Two (p. in press [http://www.livingcapitalmetrics.com/images/BringingHSN_FisherARMII.pdf]). Maple Grove, MN: JAM Press.

Fisher, W. P., Jr. (2009b, November). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement (Elsevier), 42(9), 1278-1287.

Garner, M. (2009, Autumn). Google’s PageRank algorithm and the Rasch measurement model. Rasch Measurement Transactions, 23(2), 1201-2 [http://www.rasch.org/rmt/rmt232.pdf].

Grossman, A. (1999). Philanthropic social capital markets: Performance driven philanthropy (Social Enterprise Series 12 No. 00-002). Harvard Business School Working Paper.

Kotter, J. (1996). Leading change. Cambridge, Massachusetts: Harvard Business School Press.

Kurtzman, J. (2002). How the markets really work. New York: Crown Business.

Miller, P., & O’Leary, T. (2007, October/November). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-34.

Comments on the New ANSI Human Capital Investor Metrics Standard

April 16, 2012

The full text of the proposed standard is available here.

It’s good to see a document emerge in this area, especially one with such a broad base of support from a diverse range of stakeholders. As is stated in the standard, the metrics defined in it are a good place to start and in many instances will likely improve the quality and quantity of the information made available to investors.

There are several issues to keep in mind as the value of standards for human capital metrics becomes more widely appreciated. First, in the context of a comprehensively defined investment framework, human capital is just one of the four major forms of capital, the other three being social, natural, and manufactured (Ekins, 1992; Ekins, Dresden, and Dahlstrom, 2008). To ensure as far as possible the long term stability and sustainability of their profits, and of the economic system as a whole, investors will certainly want to expand the range of the available standards to include social and natural capital along with human capital.

Second, though we manage what we measure, investment management is seriously compromised by having high quality scientific measurement standards only for manufactured capital (length, weight, volume, temperature, energy, time, kilowatts, etc.). Over 80 years of research on ability tests, surveys, rating scales, and assessments has reached a place from which it is prepared to revolutionize the management of intangible forms of capital (Fisher, 2007, 2009a, 2009b, 2010, 2011a, 2011b; Fisher & Stenner, 2011a, 2011b; Wilson, 2011; Wright, 1999). The very large reductions in transaction costs effected by standardized metrics in the economy at large (Barzel, 1982; Benham and Benham, 2000) are likely to have a similarly profound effect on the economics of human, social, and natural capital (Fisher, 2011a, 2012a, 2012b).

The potential for dramatic change in the conceptualization of metrics is most evident in the proposed standard in the sections on leadership quality and employee engagement. For instance, in the section on leadership quality, it is stated that “Investors will be able to directly compare all organizations that are using the same vendor’s methodology.” This kind of dependency should not be allowed to stand as a significant factor in a measurement standard. Properly constructed and validated scientific measures, such as those that have been in wide use in education, psychology and health care for several decades (Andrich, 2010; Bezruzcko, 2005; Bond and Fox, 2007; Fisher and Wright, 1994; Rasch, 1960; Salzberger, 2009; Wright, 1999), are equated to a common unit. Comparability should never depend on which vendor is used. Rather, any instrument that actually measures the construct of interest (leadership quality or employee engagement) should do so in a common unit and within an acceptable range of error. “Normalizing” measures for comparability, as is suggested in the standard, means employing psychometric methods that are 50 years out of date and that are far less rigorous and practical than need be. Transparency in measurement means looking through the instrument to the thing itself. If particular instruments color or reshape what is measured, or merely change the meaning of the numbers reported, then the integrity of the standard as a standard should be re-examined.

Third, for investments in human capital to be effectively managed, each distinct aspect of it (motivations, skills and abilities, health) needs to be measured separately, just as height, weight, and temperature are. New technologies have already transformed measurement practices in ways that make the necessary processes precise and inexpensive. Of special interest are adaptively administered precalibrated instruments supporting mass customized—but globally comparable—measures (for instance, see the examples at http://blog.lexile.com/tag/oasis/ and that were presented at the recent Pearson Global Research Conference in Fremantle, Australia http://www.pearson.com.au/marketing/corporate/pearson_global/default.html; also see Wright and Bell 1984, Lunz, Bergstrom, and Gershon, 1994, Bejar, et al., 2003).

Fourth, the ownership of human capital needs clarification and legal status. If we consider each individual to own their abilities, health, and motivations, and to be solely responsible for decisions made concerning the disposition of those properties, then, in accord with their proven measured amounts of each type of human capital, everyone ought to have legal title to a specific number of shares or credits of each type. This may transform employment away from wage-based job classification compensation to an individualized investment-based continuous quality improvement platform. The same kind of legal titling system will, of course, need to be worked out for social and natural capital, as well.

Fifth, given scientific standards for each major form of capital, practical measurement technologies, and legal title to our shares of capital, we will need expanded financial accounting standards and tools for managing our individual and collective investments. Ongoing research and debates concerning these standards and tools (Siegel and Borgia, 2006; Young and Williams, 2010) have yet to connect with the larger scientific, economic, and legal issues raised here, but developments in this direction should be emerging in due course.

Sixth, a number of lingering moral, ethical and political questions are cast in a new light in this context. The significance of individual behaviors and decisions is informed and largely determined by the context of the culture and institutions in which those behaviors and decisions are executed. Many of the morally despicable but not illegal investment decisions leading to the recent economic downturn put individuals in the position of either setting themselves apart and threatening their careers or doing what was best for their portfolios within the limits of the law. Current efforts intended to devise new regulatory constraints are misguided in focusing on ever more microscopically defined particulars. What is needed is instead a system in which profits are contingent on the growth of human, social, and natural capital. In that framework, legal but ultimately unfair practices would drive down social capital stock values, counterbalancing ill-gotten gains and making them unprofitable.

Seventh, the International Vocabulary of Measurement, now in its third edition (VIM3), is a standard recognized by all eight international standards accrediting bodies (BIPM, etc.). The VIM3 (http://www.bipm.org/en/publications/guides/vim.html) and forthcoming VIM4 are intended to provide a uniform set of concepts and terms for all fields that employ measures across the natural and social sciences. A new dialogue on these issues has commenced in the context of the International Measurement Confederation (IMEKO), whose member organizations are the weights and standards measurement institutes from countries around the world (Conference note, 2011). The 2012 President of the Psychometric Society, Mark Wilson, gave an invited address at the September 2011 IMEKO meeting (Wilson, 2011), and a member of the VIM3 editorial board, Luca Mari, is invited to speak at the July, 2012 International Meeting of the Psychometric Society. I encourage all interested parties to become involved in efforts of these kinds in their own fields.

References

Andrich, D. (2010). Sufficiency and conditional estimation of person parameters in the polytomous Rasch model. Psychometrika, 75(2), 292-308.

Barzel, Y. (1982). Measurement costs and the organization of markets. Journal of Law and Economics, 25, 27-48.

Bejar, I., Lawless, R. R., Morley, M. E., Wagner, M. E., Bennett, R. E., & Revuelta, J. (2003, November). A feasibility study of on-the-fly item generation in adaptive testing. The Journal of Technology, Learning, and Assessment, 2(3), 1-29; http://ejournals.bc.edu/ojs/index.php/jtla/article/view/1663.

Benham, A., & Benham, L. (2000). Measuring the costs of exchange. In C. Ménard (Ed.), Institutions, contracts and organizations: Perspectives from new institutional economics (pp. 367-375). Cheltenham, UK: Edward Elgar.

Bezruczko, N. (Ed.). (2005). Rasch measurement in health sciences. Maple Grove, MN: JAM Press.

Bond, T., & Fox, C. (2007). Applying the Rasch model: Fundamental measurement in the human sciences, 2d edition. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Conference note. (2011). IMEKO Symposium: August 31- September 2, 2011, Jena, Germany. Rasch Measurement Transactions, 25(1), 1318.

Ekins, P. (1992). A four-capital model of wealth creation. In P. Ekins & M. Max-Neef (Eds.), Real-life economics: Understanding wealth creation (pp. 147-155). London: Routledge.

Ekins, P., Dresner, S., & Dahlstrom, K. (2008). The four-capital method of sustainable development evaluation. European Environment, 18(2), 63-80.

Fisher, W. P., Jr. (2007). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009a). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287.

Fisher, W. P.. Jr. (2009b). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P.. Jr. (2010). Rasch, Maxwell’s method of analogy, and the Chicago tradition. In G. Cooper (Chair), https://conference.cbs.dk/index.php/rasch/Rasch2010/paper/view/824. Probabilistic models for measurement in education, psychology, social science and health: Celebrating 50 years since the publication of Rasch’s Probabilistic Models.., University of Copenhagen School of Business, FUHU Conference Centre, Copenhagen, Denmark.

Fisher, W. P., Jr. (2011a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. In N. Brown, B. Duckor, K. Draney & M. Wilson (Eds.), Advances in Rasch Measurement, Vol. 2 (pp. 1-27). Maple Grove, MN: JAM Press.

Fisher, W. P., Jr. (2011b). Measurement, metrology and the coordination of sociotechnical networks. In  S. Bercea (Chair), New Education and Training Methods. International Measurement Confederation (IMEKO), http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24491/ilm1-2011imeko-017.pdf, Jena, Germany.

Fisher, W. P., Jr. (2012a). Measure local, manage global: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. in press). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012b). What the world needs now: A bold plan for new standards. Standards Engineering, 64, in press.

Fisher, W. P., Jr., & Stenner, A. J. (2011a). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). Retrieved 25 October 2011, from National Science Foundation: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011b). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

Fisher, W. P., Jr., & Wright, B. D. (Eds.). (1994). Applications of probabilistic conjoint measurement. International Journal of Educational Research, 21(6), 557-664.

Lunz, M. E., Bergstrom, B. A., & Gershon, R. C. (1994). Computer adaptive testing. International Journal of Educational Research, 21(6), 623-634.

Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests (Reprint, with Foreword and Afterword by B. D. Wright, Chicago: University of Chicago Press, 1980). Copenhagen, Denmark: Danmarks Paedogogiske Institut.

Salzberger, T. (2009). Measurement in marketing research: An alternative framework. Northampton, MA: Edward Elgar.

Siegel, P., & Borgia, C. (2006). The measurement and recognition of intangible assets. Journal of Business and Public Affairs, 1(1).

Wilson, M. (2011). The role of mathematical models in measurement: A perspective from psychometrics. In L. Mari (Chair), Plenary lecture. International Measurement Confederation (IMEKO), http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24178/ilm1-2011imeko-005.pdf, Jena, Germany.

Wright, B. D. (1999). Fundamental measurement for psychology. In S. E. Embretson & S. L. Hershberger (Eds.), The new rules of measurement: What every educator and psychologist should know (pp. 65-104 [http://www.rasch.org/memo64.htm]). Hillsdale, New Jersey: Lawrence Erlbaum Associates.

Wright, B. D., & Bell, S. R. (1984, Winter). Item banks: What, why, how. Journal of Educational Measurement, 21(4), 331-345 [http://www.rasch.org/memo43.htm].

Young, J. J., & Williams, P. F. (2010, August). Sorting and comparing: Standard-setting and “ethical” categories. Critical Perspectives on Accounting, 21(6), 509-521.

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Externalities are to markets as anomalies are to scientific laws

October 28, 2011

Economic externalities are to efficient markets as any consistent anomaly is relative to a lawful regularity. Government intervention in markets is akin to fudging the laws of physics to explain the wobble in Uranus’ orbit, or to explain why magnetized masses would not behave like wooden or stone masses in a metal catapult (Rasch’s example). Further, government intervention in markets is necessary only as long as efficient markets for externalized forms of capital are not created. The anomalous exceptions to the general rule of market efficiency have long since been shown to themselves be internally consistent lawful regularities in their own right amenable to configuration as markets for human, social and natural forms of capital.

There is an opportunity here for the concise and elegant statement of the efficient markets hypothesis, the observation of certain anomalies, the formulation of new theories concerning these forms of capital, the framing of efficient markets hypotheses concerning the behavior of these anomalies, tests of these hypotheses in terms of the inverse proportionality of two of the parameters relative to the third, proposals as to the uniform metrics by which the scientific laws will be made commercially viable expressions of capital value, etc.

We suffer from the illusion that trading activity somehow spontaneously emerges from social interactions. It’s as though comparable equivalent value is some kind of irrefutable, incontestable feature of the world to which humanity adapts its institutions. But this order of things plainly puts the cart before the horse when the emergence of markets is viewed historically. The idea of fair trade, how it is arranged, how it is recognized, when it is appropriate, etc. varies markedly across cultures and over time.

Yes, “’the price of things is in inverse ratio to the quantity offered and in direct ratio to the quantity demanded’ (Walras 1965, I, 216-17)” (Mirowski, 1988, p. 20). Yes, Pareto made “a direct extrapolation of the path-independence of equilibrium energy states in rational mechanics and thermodynamics” to “the path-independence of the realization of utility” (Mirowski, 1988, p. 21). Yes, as Ehrenfest showed, “an analogy between thermodynamics and economics” can be made, and economic concepts can be formulated “as parallels of thermodynamic concepts, with the concept of equilibrium occupying the central position in both theories” (Boumans, 2005, p. 31).  But markets are built up around these lawful regularities by skilled actors who articulate the rules, embody the roles, and initiate the relationships comprising economic, legal, and scientific institutions. “The institutions define the market, rather than the reverse” (Miller & O’Leary, 2007, p. 710). What we need are new institutions built up around the lawful regularities revealed by Rasch models. The problem is how to articulate the rules, embody the roles, and initiate the relationships.

Noyes (1936, pp. 2, 13; quoted in De Soto 2000, p. 158) provides some useful pointers:

“The chips in the economic game today are not so much the physical goods and actual services that are almost exclusively considered in economic text books, as they are that elaboration of legal relations which we call property…. One is led, by studying its development, to conceive the social reality as a web of intangible bonds–a cobweb of invisible filaments–which surround and engage the individual and which thereby organize society…. And the process of coming to grips with the actual world we live in is the process of objectivizing these relations.”

 Noyes (1936, p. 20, quoted in De Soto 2000, p. 163) continues:

“Human nature demands regularity and certainty and this demand requires that these primitive judgments be consistent and thus be permitted to crystallize into certain rules–into ‘this body of dogma or systematized prediction which we call law.’ … The practical convenience of the public … leads to the recurrent efforts to systematize the body of laws. The demand for codification is a demand of the people to be released from the mystery and uncertainty of unwritten or even of case law.” [This is quite an apt statement of the largely unstated demands of the Occupy Wall Street movement.]

  De Soto (2000, p. 158) explains:

 “Lifting the bell jar [integrating legal and extralegal property rights], then, is principally a legal challenge. The official legal order must interact with extralegal arrangements outside the bell jar to create a social contract on property and capital. To achieve this integration, many other disciplines are of course necessary … [economists, urban planners, agronomists, mappers, surveyers, IT specialists, etc]. But ultimately, an integrated national social contract will be concretized only in laws.”

  “Implementing major legal change is a political responsibility. There are various reasons for this. First, law is generally concerned with protecting property rights. However, the real task in developing and former communist countries is not so much to perfect existing rights as to give everyone a right to property rights–‘meta-rights,’ if you will. [Paraphrasing, the real task in the undeveloped domains of human, social, and natural capital is not so much the perfection of existing rights as it is to harness scientific measurement in the name of economic justice and grant everyone legal title to their shares of their ownmost personal properties, their abilities, health, motivations, and trustworthiness, along with their shares of the common stock of social and natural resources.] Bestowing such meta-rights, emancipating people from bad law, is a political job. Second, very small but powerful vested interests–mostly repre- [p. 159] sented by the countries best commercial lawyers–are likely to oppose change unless they are convinced otherwise. Bringing well-connected and moneyed people onto the bandwagon requires not consultants committed to serving their clients but talented politicians committed to serving their people. Third, creating an integrated system is not about drafting laws and regulations that look good on paper but rather about designing norms that are rooted in people’s beliefs and are thus more likely to be obeyed and enforced. Being in touch with real people is a politician’s task. Fourth, prodding underground economies to become legal is a major political sales job.”

 De Soto continues (p. 159), intending to refer only to real estate but actually speaking of the need for formal legal title to personal property of all kinds, which ought to include human, social, and natural capital:

  “Without succeeding on these legal and political fronts, no nation can overcome the legal apartheid between those who can create capital and those who cannot. Without formal property, no matter how many assets they accumulate or how hard they work, most people will not be able to prosper in a capitalist society. They will continue to remain beyond the radar of policymakers, out of the reach of official records, and thus economically invisible.”

Boumans, M. (2005). How economists model the world into numbers. New York: Routledge.

De Soto, H. (2000). The mystery of capital: Why capitalism triumphs in the West and fails everywhere else. New York: Basic Books.

Miller, P., & O’Leary, T. (2007, October/November). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-34.

Mirowski, P. (1988). Against mechanism: Protecting economics from science. Lanham, MD: Rowman & Littlefield.

Noyes, C. R. (1936). The institution of property. New York: Longman’s Green.

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Reimagining Capitalism Again, Part III: Reflections on Greider’s “Bold Ideas” in The Nation

September 10, 2011

And so, The Nation’s “Bold Ideas for a New Economy” is disappointing for not doing more to start from the beginning identified by its own writer, William Greider. The soul of capitalism needs to be celebrated and nourished, if we are to make our economy “less destructive and domineering,” and “more focused on what people really need for fulfilling lives.” The only real alternative to celebrating and nourishing the soul of capitalism is to kill it, in the manner of the Soviet Union’s failed experiments in socialism and communism.

The article speaks the truth, though, when it says there is no point in trying to persuade the powers that be to make the needed changes. Republicans see the market as it exists as a one-size-fits-all economic panacea, when all it can accomplish in its current incomplete state is the continuing externalization of anything and everything important about human, social, and environmental decency. For their part, Democrats do indeed “insist that regulation will somehow fix whatever is broken,” in an ever-expanding socialistic micromanagement of every possible exception to the rules that emerges.

To date, the president’s efforts at a nonpartisan third way amount only to vacillations between these opposing poles. The leadership that is needed, however, is something else altogether. Yes, as The Nation article says, capitalism needs to be made to serve the interests of society, and this will require deep structural change, not just new policies. But none of the contributors of the “bold ideas” presented propose deep structural changes of a kind that actually gets at the soul of capitalism. All of the suggestions are ultimately just new policies tweaking superficial aspects of the economy in mechanical, static, and very limited ways.

The article calls for “Democratizing reforms that will compel business and finance to share decision-making and distribute rewards more fairly.” It says the vision has different names but “the essence is a fundamental redistribution of power and money.” But corporate distortions of liability law, the introduction of boardroom watchdogs, and a tax on financial speculation do not by any stretch of the imagination address the root causes of social and environmental irresponsibility in business. They “sound like obscure technical fixes” because that’s what they are. The same thing goes for low-cost lending from public banks, the double or triple bottom lines of Benefit Corporations, new anti-trust laws, calls for “open information” policies, added personal stakes for big-time CEOs, employee ownership plans, the elimination of tax subsidies for, new standards for sound investing, new measures of GDP, and government guarantees of full employment.

All of these proposals sound like what ought to be the effects and outcomes of efforts addressing the root causes of capitalisms’ shortcomings. Instead, they are band aids applied to scratched fingers and arms when multiple by-pass surgery is called for. That is, what we need is to understand how to bring the spirit of capitalism to life in the new domains of human, social, and environmental interests, but what we’re getting are nothing but more of the same piecemeal ways of moving around the deck chairs on the Titanic.

There is some truth in the assertion that what really needs reinventing is our moral and spiritual imagination. As someone (Einstein or Edison?) is supposed to have put it, originality is simply a matter of having a source for an analogy no one else has considered. Ironically, the best model is often the one most taken for granted and nearest to hand. Such is the case with the two-sided scientific and economic effects of standardized units of measurement. The fundamental moral aspect here is nothing other than the Golden Rule, independently derived and offered in cultures throughout history, globally. Individualized social measurement is nothing if not a matter of determining whether others are being treated in the way you yourself would want to be treated.

And so, yes, to stress the major point of agreement with The Nation, “the new politics does not start in Washington.” Historically, at their best, governments work to keep pace with the social and technical innovations introduced by their peoples. Margaret Mead said it well a long time ago when she asserted that small groups of committed citizens are the only sources of real social change.

Not to be just one of many “advocates with bold imaginations” who wind up marginalized by the constraints of status quo politics, I claim my personal role in imagining a new economic future by tapping as deeply as I can into the positive, pre-existing structures needed for a transition into a new democratic capitalism. We learn through what we already know. Standards are well established as essential to commerce and innovation, but 90% of the capital under management in our economy—the human, social, and natural capital—lacks the standards needed for optimal market efficiency and effectiveness. An intangible assets metric system will be a vitally important way in which we extend what is right and good in the world today into new domains.

To conclude, what sets this proposal apart from those offered by The Nation and its readers hinges on our common agreement that “the most threatening challenge to capitalism is arguably the finite carrying capacity of the natural world.” The bold ideas proposed by The Nation’s readers respond to this challenge in ways that share an important feature in common: people have to understand the message and act on it. That fact dooms all of these ideas from the start. If we have to articulate and communicate a message that people then have to act on, we remain a part of the problem and not part of the solution.

As I argue in my “The Problem is the Problem” blog post of some months ago, this way of defining problems is itself the problem. That is, we can no longer think of ourselves as separate from the challenges we face. If we think we are not all implicated through and through as participants in the construction and maintenance of the problem, then we have not understood it. The bold ideas offered to date are all responses to the state of a broken system that seek to reform one or another element in the system when what we need is a whole new system.

What we need is a system that so fully embodies nature’s own ecological wisdom that the medium becomes the message. When the ground rules for economic success are put in place such that it is impossible to earn a profit without increasing stocks of human, social, and natural capital, there will be no need to spell out the details of a microregulatory structure of controlling new anti-trust laws, “open information” policies, personal stakes for big-time CEOs, employee ownership plans, the elimination of tax subsidies, etc. What we need is precisely what Greider reported from Innovest in his book: reliable, high quality information that makes human, social, and environmental issues matter financially. Situated in a context like that described by Bernstein in his 2004 The Birth of Plenty, with the relevant property rights, rule of law, scientific rationality, capital markets, and communications networks in place, it will be impossible to stop a new economic expansion of historic proportions.

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Reimagining Capitalism Again, Part II: Scientific Credibility in Improving Information Quality

September 10, 2011

The previous posting here concluded with two questions provoked by a close consideration of a key passage in William Greider’s 2003 book, The Soul of Capitalism. First, how do we create the high quality, solid information markets need to punish and reward relative to ethical and sustainable human, social, and environmental values? Second, what can we learn from the way we created that kind of information for property and manufactured capital? There are good answers to these questions, answers that point in productive directions in need of wide exploration and analysis.

The short answer to both questions is that better, more scientifically rigorous measurement at the local level needs to be implemented in a context of traceability to universally uniform standards. To think global and act local simultaneously, we need an efficient and transparent way of seeing where we stand in the world relative to everyone else. Having measures expressed in comparable and meaningful units is an important part of how we think global while acting local.

So, for markets to punish and reward businesses in ways able to build human, social, and environmental value, we need to be able to price that value, to track returns on investments in it, and to own shares of it. To do that, we need a new intangible assets metric system that functions in a manner analogous to the existing metric system and other weights and measures standards. In the same way these standards guarantee high quality information on volume, weight, thermal units, and volts in grocery stores and construction sites, we need a new set of standards for human abilities, performances, and health; for social trust, commitment, and loyalty; and for the environment’s air and water processing services, fisheries, gene pools, etc.

Each industry needs an instrumentarium of tools and metrics that mediate relationships universally within its entire sphere of production and/or service. The obvious and immediate reaction to this proposal will likely be that this is impossible, that it would have been done by now if it was possible, and that anyone who proposes something like this is simply unrealistic, perhaps dangerously so. So, here we have another reason to add to those given in the June 8, 2011 issue of The Nation (http://www.thenation.com/article/161267/reimagining-capitalism-bold-ideas-new-economy) as to why bold ideas for a new economy cannot gain any traction in today’s political discourse.

So what basis in scientific authority might be found for this audacious goal of an intangible assets metric system? This blog’s postings offer multiple varieties of evidence and argument in this regard, so I’ll stick to more recent developments, namely, last week’s meeting of the International Measurement Confederation (IMEKO) in Jena, Germany. Membership in IMEKO is dominated by physicists, engineers, chemists, and clinical laboratorians who work in private industry, academia, and government weights and measures standards institutes.

Several IMEKO members past and present are involved with one or more of the seven or eight major international standards organizations responsible for maintaining and improving the metric system (the Systeme Internationale des Unites). Two initiatives undertaken by IMEKO and these standards organizations take up the matter at issue here concerning the audacious goal of standard units for human, social, and natural capital.

First, the recently released third edition of the International Vocabulary of Measurement (VIM, 2008) expands the range of the concepts and terms included to encompass measurement in the human and social sciences. This first effort was not well informed as to the nature of widely realized state of the art developments in measurement in education, health care, and the social sciences. What is important is that an invitation to further dialogue has been extended from the natural to the social sciences.

That invitation was unintentionally accepted and a second initiative advanced just as the new edition of the VIM was being released, in 2008. Members of three IMEKO technical committees (TC 1-7-13; those on Measurement Science, Metrology Education, and Health Care) cultivate a special interest in ideas on the human and social value of measurement. At their 2008 meeting in Annecy, France, I presented a paper (later published in revised form as Fisher, 2009) illustrating how, over the previous 50 years and more, the theory and practice of measurement in the social sciences had developed in ways capable of supporting convenient and useful universally uniform units for human, social, and natural capital.

The same argument was then advanced by my fellow University of Chicago alum, Nikolaus Bezruczko, at the 2009 IMEKO World Congress in Lisbon. Bezruczko and I both spoke at the 2010 TC 1-7-13 meeting in London, and last week our papers were joined by presentations from six of our colleagues at the 2011 IMEKO TC 1-7-13 meeting in Jena, Germany. Another fellow U Chicagoan, Mark Wilson, a long time professor in the Graduate School of Education at the University of California, Berkeley, gave an invited address contrasting four basic approaches to measurement in psychometrics, and emphasizing the value of methods that integrate substantive meaning with mathematical rigor.

Examples from education, health care, and business were then elucidated at this year’s meeting in Jena by myself, Bezruczko, Stefan Cano (University of Plymouth, England), Carl Granger (SUNY, Buffalo; paper presented by Bezruczko, a co-author), Thomas Salzberger (University of Vienna, Austria), Jack Stenner (MetaMetrics, Inc., Durham, NC, USA), and Gordon Cooper (University of Western Australia, Crawley, WA, Australia; paper presented by Fisher, a co-author).

The contrast between these presentations and those made by the existing IMEKO membership hinges on two primary differences in focus. The physicists and engineers take it for granted that all instrument calibration involves traceability to metrological reference standards. Dealing as they are with existing standards and physical or chemical materials that usually possess deterministically structured properties, issues of how to construct linear measures from ordinal observations never come up.

Conversely, the social scientists and psychometricians take it for granted that all instrument calibration involves evaluations of the capacity of ordinal observations to support the construction of linear measures. Dealing as they are with data from tests, surveys, and rating scale assessments, issues of how to relate a given instrument’s unit to a reference standard never come up.

Thus there is significant potential for mutually instructive dialogue between natural and social scientists in this context. Many areas of investigation in the natural sciences have benefited from the introduction of probabilistic concepts in recent decades, but there are perhaps important unexplored opportunities for the application of probabilistic measurement, as opposed to statistical, models. By taking advantage of probabilistic models’ special features, measurement in education and health care has begun to realize the benefit of broad generalizations of comparable units across grades, schools, tests, and curricula.

Though the focus of my interest here is in the capacity of better measurement to improve the efficiency of human, social, and natural capital markets, it may turn out that as many or more benefits will accrue in the natural sciences’ side of the conversation as in the social sciences’ side. The important thing for the time being is that the dialogue is started. New and irreversible mutual understandings between natural and social scientists have already been put on the record. It may happen that the introduction of a new supply of improved human, social, and natural capital metrics will help articulate the largely, as yet, unstated but nonetheless urgent demand for them.

Fisher, W. P., Jr. (2009, November). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287.

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Reimagining Capitalism Again, Part I: Reflections on Greider’s Soul of Capitalism

September 10, 2011

In his 2003 book, The Soul of Capitalism, William Greider wrote, “If capitalism were someday found to have a soul, it would probably be located in the mystic qualities of capital itself” (p. 94). The recurring theme in the book is that the resolution of capitalism’s deep conflicts must grow out as organic changes from the roots of capitalism itself.

In the book, Greider quotes Innovest’s Michael Kiernan as suggesting that the goal has to be re-engineering the DNA of Wall Street (p. 119). He says the key to doing this is good reliable information that has heretofore been unavailable but which will make social and environmental issues matter financially. The underlying problems of exactly what solid, high quality information looks like, where it comes from, and how it is created are not stated or examined, but the point, as Kiernan says, is that “the markets are pretty good at punishing and rewarding.” The objective is to use “the financial markets as an engine of reform and positive change rather than destruction.”

This objective is, of course, the focus of multiple postings in this blog (see especially this one and this one). From my point of view, capitalism indeed does have a soul and it is actually located in the qualities of capital itself. Think about it: if a soul is a spirit of something that exists independent of its physical manifestation, then the soul of capitalism is the fungibility of capital. Now, this fungibility is complex and ambiguous. It takes its strength and practical value from the way market exchange are represented in terms of currencies, monetary units that, within some limits, provide an objective basis of comparison useful for rewarding those capable of matching supply with demand.

But the fungibility of capital can also be dangerously misconceived when the rich complexity and diversity of human capital is unjustifiably reduced to labor, when the irreplaceable value of natural capital is unjustifiably reduced to land, and when the trust, loyalty, and commitment of social capital is completely ignored in financial accounting and economic models. As I’ve previously said in this blog, the concept of human capital is inherently immoral so far as it reduces real human beings to interchangeable parts in an economic machine.

So how could it ever be possible to justify any reduction of human, social, and natural value to a mere number? Isn’t this the ultimate in the despicable inhumanity of economic logic, corporate decision making, and, ultimately, the justification of greed? Many among us who profess liberal and progressive perspectives seem to have an automatic and reactionary prejudice of this kind. This makes these well-intentioned souls as much a part of the problem as those among us with sometimes just as well-intentioned perspectives that accept such reductionism as the price of entry into the game.

There is another way. Human, social, and natural value can be measured and made manageable in ways that do not necessitate totalizing reduction to a mere number. The problem is not reduction itself, but unjustified, totalizing reduction. Referring to all people as “man” or “men” is an unjustified reduction dangerous in the way it focuses attention only on males. The tendency to think and act in ways privileging males over females that is fostered by this sense of “man” shortchanges us all, and has happily been largely eliminated from discourse.

Making language more inclusive does not, however, mean that words lose the singular specificity they need to be able to refer to things in the world. Any given word represents an infinite population of possible members of a class of things, actions, and forms of life. Any simple sentence combining words into a coherent utterance then multiplies infinities upon infinities. Discourse inherently reduces multiplicities into texts of limited lengths.

Like any tool, reduction has its uses. Also like any tool, problems arise when the tool is allowed to occupy some hidden and unexamined blind spot from which it can dominate and control the way we think about everything. Critical thinking is most difficult in those instances in which the tools of thinking themselves need to be critically evaluated. To reject reduction uncritically as inherently unjustified is to throw the baby out with the bathwater. Indeed, it is impossible to formulate a statement of the rejection without simultaneously enacting exactly what is supposed to be rejected.

We have numerous ready-to-hand examples of how all reduction has been unjustifiably reduced to one homogenized evil. But one of the results of experiments in communal living in the 1960s and 1970s, as well as of the fall of the Soviet Union, was the realization that the centralized command and control of collectively owned community property cannot compete with the creativity engendered when individuals hold legal title to the fruits of their labors. If individuals cannot own the results of the investments they make, no one makes any investments.

In other words, if everything is owned collectively and is never reduced to individually possessed shares that can be creatively invested for profitable returns, then the system is structured so as to punish innovation and reward doing as little as possible. But there’s another way of thinking about the relation of the collective to the individual. The living soul of capitalism shows itself in the way high quality information makes it possible for markets to efficiently coordinate and align individual producers’ and consumers’ collective behaviors and decisions. What would happen if we could do that for human, social, and natural capital markets? What if “social capitalism” is more than an empty metaphor? What if capital institutions can be configured so that individual profit really does become the driver of socially responsible, sustainable economics?

And here we arrive at the crux of the problem. How do we create the high quality, solid information markets need to punish and reward relative to ethical and sustainable human, social, and environmental values? Well, what can we learn from the way we created that kind of information for property and manufactured capital? These are the questions taken up and explored in the postings in this blog, and in my scientific research publications and meeting presentations. In the near future, I’ll push my reflection on these questions further, and will explore some other possible answers to the questions offered by Greider and his readers in a recent issue of The Nation.

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The Path to a New Consensus: A Practical Procedure for Resolving the Opposition Between Absolute and Relative Standards

August 26, 2011

The possibility of a new nonpartisan consensus on social and economic issues has been raised from time to time lately. I’ve had some ideas fermenting in this area for a while, and it seems like they might be ready for recording here. What I want to take up concerns one of the more contentious aspects of the cultural and political disputes of recent decades. There are important differences between those who want to impose one or another kind of moral or religious standard on society as a whole and those who contend that, within certain limits, such standards are arbitrary and must be determined by each individual or group according to its own values and sense of what makes a community.The oppositions here might seem to be irreconcilable, but is that actually true?

Resolving deep-seated disagreements on this scale requires that all parties accept some baseline rules of engagement. And herein lies the rub, eh? For even something as seemingly obvious and simple as defining factual truth has proven beyond the abilities of some highly skilled and deeply motivated negotiators. So, of course, those who adhere rigidly to preconceived notions automatically remove themselves from dialogue, and I cannot presume to address them here. But for those willing to entertain possibilities following from ideas and methods with which they may be unfamiliar, I say, read on.

What I want to propose differs in several fundamental respects from what has come before, and it is very similar in one fundamental respect. The similarity stems from the realization that essentially the same thing can be authoritatively stated at different times and place by different people using different words and different languages in relation to different customs and traditions. For instance, the versions of the Golden Rule given in the Gospels of Matthew or Luke are conceptually identical with the sentiment expressed in the Hindu Mahabarata, the Confucian Analects, the Jewish Talmud, the Muslim 13th Hadith, and the Buddhist Unada-Varga (http://www.thesynthesizer.org/golden.html; http://philosophy.tamu.edu/~gary/bioethics/ethicaltheory/universalizability.html).

So, rather than defining consensus in terms of strict agreement (with no uncertainty) on the absolute value of various propositions, it should be defined in terms of probabilities of consistent agreement (within a range of uncertainty) on the relative value of various propositions. Instead of evaluating isolated and decontextualized value statements one at a time, I propose evaluating value statements hypothesized to cohere with one another within a larger context together, as a unit.Instead of demanding complete data on a single set of propositions, I propose requiring and demonstrating that the same results be obtained across different sets of propositions addressing the same thing. Instead of applying statistical models of group level inter-variable relations to these data, I propose applying measurement models of individual level within-variable relations. Instead of setting policy on the basis of centrally controlled analytic results that vary incommensurably across data sets I propose setting policy on the basis of decentralized, distributed results collectively produced by networks of individuals whose behaviors and decisions are coordinated and aligned by calibrated instruments measuring in common commensurable units. All of these proposals are described in detail in previous posts here, and in the references included in those posts.

What I’m proposing is rooted in and extends existing practical solutions to the definition and implementation of standards. And though research across a number of fields suggests that a new degree of consensus on some basic issues seems quite possible, that consensus will not be universal and it should not be used as a basis for compelling conformity. Rather, the efficiencies that stand to be gained by capitalizing (literally) on existing but unrecognized standards of behavior and performance are of a magnitude that would easily support generous latitude in allowing poets, nonconformists, and political dissenters to opt out of the system at little or no cost to themselves or anyone else.

That is, as has been described and explained at length in previous posts here, should we succeed in establishing an Intangible Assets Metric System and associated genuine progress indicator or happiness index, we would be in the position of harnessing the power of the profit motive as an economic driver of growth in human, social, and natural capital. Instead of taking mere monetary profits as a measure of improved quality of life, we would set up economic systems in which the measurement and the management of quality of life determines monetary profits. The basic idea is that individual ownership of and accountability for what is, more than anything else, our rightful property–our own abilities, motivations, health, trustworthiness, loyalty, etc.–ought to be a significant factor in promoting the conservation and growth of these forms of capital.

In this context, what then might serve as a practical approach to resolving disputes between those who advocate standards and those who reject them, or between those who trust in our capacity to function satisfactorily as a society without standards and those who do not? Such an approach begins by recognizing the multitude of ways in which all of us rely on standards every day. We do not need to concern ourselves with the technical issues of electronics or manufacturing, though standards are essential here. We do not need even to take up the role of standards as guides to grocery or clothing store purchasing decisions or to planning meetings or travel across time zones.

All we need to think about is something as basic as communication. The alphabet, spelling, pronunciation, and grammatical rules, dictionaries, and educational curricula are all forms of standards that must be accepted, recognized and adhered to before the most basic communication can be achieved. The shapes of various letters or symbols, and the sounds associated with them, are all completely arbitrary. They are conventions that arose over centuries of usage that passed long before the rules were noted, codified, and written down. And spoken languages remain alive, changing in ways that break the rules and cause them to be rewritten, as when new words emerge, or previously incorrect constructions become accepted.

But what is the practical value for a new consensus in recognizing our broad acceptance of linguistic standards? Contrary to the expectations of l’Academie Francaise, for instance, we cannot simply make up new rules and expect people to follow them. No, the point of taking language as a key example goes deeper than that. We noted that usage precedes the formulation of rules, and so it must also be in finding our way to a basis for a new consensus. The question is, what are the lawful patterns by which we already structure behavior and decisions, patterns that might be codified in the language of a social science?

These patterns are being documented in research employing probabilistic measurement models. The fascinating thing about these patterns is that they often retain their characteristic features across different samples of people being measured, across time and space, and across different sets of questions on tests, surveys, or assessments designed to measure the same ability, behavior, attitude, or performance. The stability and constancy of these patterns are such that it appears possible to link all of the instruments measuring the same things to common units of measurement, so that everyone everywhere could think and act together in a common language.

And it is here, in linking instruments together in an Intangible Assets Metric System, that we arrive at a practical way of resolving some disputes between absolutists and relativists. Though we should and will take issue with his demand for certainty, Latour (2005, p. 228) asks the right question, saying,

“Standards and metrology solve practically the question of relativity that seems to intimidate so many people:
Can we obtain some sort of universal agreement? Of course we can! Provided you find a way to hook up your local instrument to one of the many metrological chains whose material network can be fully described, and whose cost can be fully determined. Provided there is also no interruption, no break, no gap, and no uncertainty along any point of the transmission. Indeed, traceability is precisely what the whole of metrology is about!”

Nowhere does Latour show any awareness of what has been accomplished in social research employing probabilistic measurement models, but he nonetheless grasps exactly how the results of that research will not realize its potential unless it is expanded into networks of interconnected instrumentation. He understands that his theory of networked actors coordinated via virtual threads of standardized forms, metrics, vocabularies describes how scientific metrology and standards set the benchmark for universal consensus. Latour stresses that the focus here is on concrete material practices that can be objectively observed and replicated. As he says, when those practices are understood, then you know how to “do the same operation for other less traceable, less materialized circulations” (p. 229).

Latour’s primary concerns are with the constitution of sociology as a science of the social, and with the understanding of the social as networks of actors whose interests are embodied in technical devices that mediate relationships. Throughout his work, he therefore focuses on the description of existing sociotechnical phenomena. Presumably because of his lack of familiarity with social measurement theory and practice, Latour does not speak to ways in which the social sciences could go beyond documenting less traceable and less materialized circulations to creating more traceable and more materialized circulations, ones capable of more closely emulating those found in the natural sciences.

Latour’s results suggest criteria that may show some disputes regarded as unresolvable to have unexplored potentials for negotiation. That potential depends, as Latour says, on calibrating instruments that can be hooked up in a metrological chain in an actual material network with known properties (forms, Internet connections and nodes, a defined unit of measurement with tolerable uncertainty, etc.) and known costs. In the same way that the time cannot be told from a clock disconnected from the chain of connections to the standard time, each individual instrument for measuring abilities, health, quality of life, etc. will also have to be connected to its standard via an unbroken chain.

But however intimidating these problems might be, they are far less imposing than the ignorance that prevents any framing of the relevant issues in the first place. Addressing the need for rigorous measurement in general, Rasch (1980, pp. xx) agreed that “this is a huge challenge, but once the problem has been formulated it does seem possible to meet it.” Naturally enough, the needed work will have to be done by those of us calibrating the instruments of education, health care, sociology, etc. Hence my ongoing involvement in IMEKO, the International Measurement Confederation (http://www.tu-ilmenau.de/fakmb/Home.2382.0.html).

References

Latour, B. (2005). Reassembling the social: An introduction to Actor-Network-Theory. Clarendon Lectures in Management Studies). Oxford, England: Oxford University Press.

Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests (Reprint, with Foreword and Afterword by B. D. Wright, Chicago: University of Chicago Press, 1980). Copenhagen, Denmark: Danmarks Paedogogiske Institut.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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New Opportunities for Job Creation and Prosperity

August 17, 2011

What can be done to create jobs and revive the economy? There is no simple, easy answer to this question. Creating busywork is nonsense. We need fulfilling occupations that meet the world’s demand for products and services. It is not easy to see how meaningful work can be systematically created on a broad scale. New energy efficiencies may lead to the cultivation of significant job growth, but it may be unwise to put all of our eggs in this one basket.

So how are we to solve this puzzle? What other areas in the economy might be ripe for the introduction of a new technology capable of supporting a wave of new productivity, like computers did in the 1980s, or the Internet in the 1990s? In trying to answer this question, simplicity and elegance are key factors in keeping things at a practical level.

For instance, we know we accomplish more working together as a team than as disconnected individuals. New jobs, especially new kinds of jobs, will have to be created via innovation. Innovation in science and industry is a team sport. So the first order of business in teaming up for job creation is to know the rules of the game. The economic game is played according to the rules of law embodied in property rights, scientific rationality, capital markets, and transportation/communications networks (see William Bernstein’s 2004 book, The Birth of Plenty). When these conditions are met, as they were in Europe and North America at the beginning of the nineteenth century, the stage is set for long term innovation and growth on a broad scale.

The second order of business is to identify areas in the economy that lack one or more of these four conditions, and that could reasonably be expected to benefit from their introduction. Education, health care, social services, and environmental management come immediately to mind. These industries are plagued with seemingly interminable inflationary spirals, which, no doubt, are at least in part caused by the inability of investors to distinguish between high and low performers. Money cannot flow to and reward programs producing superior results in these industries because they lack common product definitions and comparable measures of their results.

The problems these industries are experiencing are not specific to each of them in particular. Rather, the problem is a general one applicable across all industries, not just these. Traditionally, economic thinking focuses on three main forms of capital: land, labor, and manufactured products (including everything from machines, roads, and buildings to food, clothing, and appliances). Cash and credit are often thought of as liquid capital, but their economic value stems entirely from the access they provide to land, labor, and manufactured products.

Economic activity is not really, however, restricted to these three forms of capital. Land is far more than a piece of ground. What are actually at stake are the earth’s regenerative ecosystems, with the resources and services they provide. And labor is far more than a pair of skilled hands; people bring a complex mix of abilities, motivations, and health to bear in their work. Finally, this scheme lacks an essential element: the trust, loyalty, and commitment required for even the smallest economic exchange to take place. Without social capital, all the other forms of capital (human, natural, and manufactured, including property) are worthless. Consistent, sustainable, and socially responsible economic growth requires that all four forms of capital be made accountable in financial spreadsheets and economic models.

The third order of business, then, is to ask if the four conditions laying out the rules for the economic game are met in each of the four capital domains. The table below suggests that all four conditions are fully met only for manufactured products. They are partially met for natural resources, such as minerals, timber, fisheries, etc., but not at all for nature’s air and water purification systems or broader genetic ecosystem services.

 Table

Existing Conditions Relevant to Conceiving a New Birth of Plenty, by Capital Domains

Human

Social

Natural

Manufactured

Property rights

No

No

Partial

Yes

Scientific rationality

Partial

Partial

Partial

Yes

Capital markets

Partial

Partial

Partial

Yes

Transportation & communication networks

Partial

Partial

Partial

Yes

That is, no provisions exist for individual ownership of shares in the total available stock of air and water, or of forest, watershed, estuary, and other ecosystem service outcomes. Nor do any individuals have free and clear title to their most personal properties, the intangible abilities, motivations, health, and trust most essential to their economic productivity. Aggregate statistics are indeed commonly used to provide a basis for policy and research in human, social, and natural capital markets, but falsifiable models of individually applicable unit quantities are not widely applied. Scientifically rational measures of our individual stocks of intangible asset value will require extensive use of these falsifiable models in calibrating the relevant instrumentation.

Without such measures, we cannot know how many shares of stock in these forms of capital we own, or what they are worth in dollar terms. We lack these measures, even though decades have passed since researchers first established firm theoretical and practical foundations for them. And more importantly, even when scientifically rational individual measures can be obtained, they are never expressed in terms of a unit standardized for use within a given market’s communications network.

So what are the consequences for teams playing the economic game? High performance teams’ individual decisions and behaviors are harmonized in ways that cannot otherwise be achieved only when unit amounts, prices, and costs are universally comparable and publicly available. This is why standard currencies and exchange rates are so important.

And right here we have an insight into what we can do to create jobs. New jobs are likely going to have to be new kinds of jobs resulting from innovations. As has been detailed at length in recent works such as Surowiecki’s 2004 book, The Wisdom of Crowds, innovation in science and industry depends on standards. Standards are common languages that enable us to multiply our individual cognitive powers into new levels of collective productivity. Weights and measures standards are like monetary currencies; they coordinate the exchange of value in laboratories and businesses in the same way that dollars do in the US economy.

Applying Bernstein’s four conditions for economic growth to intangible assets, we see that a long term program for job creation then requires

  1. legislation establishing human, social, and natural capital property rights, and an Intangible Assets Metrology System;
  2. scientific research into consensus standards for measuring human, social, and natural capital;
  3. venture capital educational and marketing programs; and
  4. distributed information networks and computer applications through which investments in human, social, and natural capital can be tracked and traded in accord with the rule of law governing property rights and in accord with established consensus standards.

Of these four conditions, Bernstein (p. 383) points to property rights as being the most difficult to establish, and the most important for prosperity. Scientific results are widely available in online libraries. Capital can be obtained from investors anywhere. Transportation and communications services are available commercially.

But valid and verifiable means of representing legal title to privately owned property is a problem often not yet solved even for real estate in many Third World and former communist countries (see De Soto’s 2000 book, The Mystery of Capital). Creating systems for knowing the quality and quantity of educational, health care, social, and environmental service outcomes is going to be a very difficult process. It will not be impossible, however, and having the problem identified advances us significantly towards new economic possibilities.

We need leaders able and willing to formulate audacious goals for new economic growth from ideas such as these. We need enlightened visionaries able to see our potentials from a new perspective, and who can reflect our new self-image back at us. When these leaders emerge—and they will, somewhere, somehow—the imaginations of millions of entrepreneurial thinkers and actors will be fired, and new possibilities will unfold.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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A Framework for Competitive Advantage in Managing Intangible Assets

July 26, 2011

It has long been recognized that externalities like social costs could be brought into the market should ways of measuring them objectively be devised. Markets, however, do not emerge spontaneously from the mere desire to be able to buy and sell; they are, rather, the products of actors and agencies that define the rules, roles, and relationships within which transaction costs are reduced and from which value, profits, and authentic wealth may be extracted. Objective measurement is necessary to reduced transaction costs but is by itself insufficient to the making of markets. Thus, markets for intangible assets, such as human, social, and natural capital, remain inefficient and undeveloped even though scientific theories, models, methods, and results demonstrating their objective measurability have been available for over 80 years.

Why has the science of objectively measured intangible assets not yet led to efficient markets for those assets? The crux of the problem, the pivot point at which an economic Archimedes could move the world of business, has to do with verifiable trust. It may seem like stating the obvious, but there is much to be learned from recognizing that shared narratives of past performance and a shared vision of the future are essential to the atmosphere of trust and verifiability needed for the making of markets. The key factor is the level of detail reliably tapped by such narratives.

For instance, some markets seem to have the weight of an immovable mass when the dominant narrative describes a static past and future with no clearly defined trajectory of leverageable development. But when a path of increasing technical capacity or precision over time can be articulated, entrepreneurs have the time frames they need to be able to coordinate, align, and manage budgeting decisions vis a vis investments, suppliers, manufacturers, marketing, sales, and customers. For example, the building out of the infrastructure of highways, electrical power, and water and sewer services assured manufacturers of automobiles, appliances, and homes that they could develop products for which there would be ready customers. Similarly, the mapping out of a path of steady increases in technical precision at no additional cost in Moore’s Law has been a key factor enabling the microprocessor industry’s ongoing history of success.

Of course, as has been the theme of this blog since day one, similar paths for the development of new infrastructural capacities could be vital factors for making new markets for human, social, and natural capital. I’ll be speaking on this topic at the forthcoming IMEKO meeting in Jena, Germany, August 31 to September 2. Watch this spot for more on this theme in the near future.

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Translating Gingrich’s Astute Observations on Health Care

June 30, 2011

“At the very heart of transforming health and healthcare is one simple fact: it will require a commitment by the federal government to invest in science and discovery. The period between investment and profit for basic research is too long for most companies to ever consider making the investment. Furthermore, truly basic research often produces new knowledge that everyone can use, so there is no advantage to a particular company to make the investment. The result is that truly fundamental research is almost always a function of government and foundations because the marketplace discourages focusing research in that direction” (p. 169 in Gingrich, 2003).

Gingrich says this while recognizing (p. 185) that:

“Money needs to be available for highly innovative ‘out of the box’ science. Peer review is ultimately a culturally conservative and risk-averse model. Each institution’s director should have a small amount of discretionary money, possibly 3% to 5% of their budget, to spend on outliers.”

He continues (p. 170), with some important elaborations on the theme:

“America’s economic future is a direct function of our ability to take new scientific research and translate it into entrepreneurial development.”

“The [Hart/Rudman] Commission’s second conclusion was that the failure to invest in scientific research and the failure to reform math and science education was the second largest threat to American security [behind terrorism].”

“Our goal [in the Hart/Rudman Commission] was to communicate the centrality of the scientific endeavor to American life and the depth of crisis we believe threatens the math and science education system. The United States’ ability to lead today is a function of past investments in scientific research and math and science education. There is no reason today to believe we will automatically maintain that lead especially given our current investments in scientific research and the staggering levels of our failures in math and science education.”

“Our ability to lead in 2025 will be a function of current decisions. Increasing our investment in science and discovery is a sound and responsible national security policy. No other federal expenditure will do more to create jobs, grow wealth, strengthen our world leadership, protect our environment, promote better education, or ensure better health for the country. We must make this increase now.”

On p. 171, this essential point is made:

“In health and healthcare, it is particularly important to increase our investment in research.”

This is all good. I agree completely. What NG says is probably more true than he realizes, in four ways.

First, the scientific capital created via metrology, controlled via theory, and embodied in technological instruments is the fundamental driver of any economy. The returns on investments in metrological improvements range from 40% to over 400% (NIST, 1996). We usually think of technology and technical standards in terms of computers, telecommunications, and electronics, but there actually is not anything at all in our lives untouched by metrology, since the air, water, food, clothing, roads, buildings, cars, appliances, etc. are all monitored, maintained, and/or manufactured relative to various kinds of universally uniform standards. NG is, as most people are, completely unaware that such standards are feasible and already under development for health, functionality, quality of life, quality of care, math and science education, etc. Given the huge ROIs associated with metrological improvements, there ought to be proportionately huge investments being made in metrology for human, social, and natural capital.

Second, NG’s point concerning national security is right on the mark, though for reasons that go beyond the ones he gives. There are very good reasons for thinking investments in, and meaningful returns from, the basic science for human, social, and natural capital metrology could be expected to undercut the motivations for terrorism and the retreats into fundamentalisms of various kinds that emerge in the face of the failures of liberal democracy (Marty, 2001). Making all forms of capital measured, managed, and accountable within a common framework accessible to everyone everywhere could be an important contributing factor, emulating the property titling rationale of DeSoto (1989, 2000) and the support for distributed cognition at the social level provided by metrological networks (Latour, 1987, 2005; Magnus, 2007), The costs of measurement can be so high as to stifle whole economies (Barzel, 1982), which is, broadly speaking, the primary problem with the economies of education, health care, social services, philanthropy, and environmental management (see, for instance, regarding philanthropy, Goldberg, 2009). Building the legal and financial infrastructure for low-friction titling and property exchange has become a basic feature of World Bank and IMF projects. My point, ever since I read De Soto, has been that we ought to be doing the same thing for human, social, and natural capital, facilitating explicit ownership of the skills, motivations, health, trust, and environmental resources that are rightfully the property of each of us, and that similar effects on national security ought to follow.

Third, NG makes an excellent point when he stresses the need for health and healthcare to be individual-centered, saying that, in contrast with the 20th-century healthcare system, “In the 21st Century System of Health and Healthcare, you will own your medical record, control your healthcare dollars, and be able to make informed choices about healthcare providers.” This is basically equivalent to saying that health capital needs to be fungible, and it can’t be fungible, of course, without a metrological infrastructure that makes every measure of outcomes, quality of life, etc. traceable to a reference standard. Individual-centeredness is also, of course, what distinguishes proper measurement from statistics. Measurement supports inductive inference, from the individual to the population, where statistics are deductive, going from the population to the individual (Fisher & Burton, 2010; Fisher, 2010). Individual-centered healthcare will never go anywhere without properly calibrated instrumentation and the traceability to reference standards that makes measures meaningful.

Fourth, NG repeatedly indicates how appalled he is at the slow pace of change in healthcare, citing research showing that it can take up to 17 years for doctors to adopt new procedures. I contend that this is an effect of our micromanagement of dead, concrete forms of capital. In a fluid living capital market, not only will consumers be able to reward quality in their purchasing decisions by having the information they need when they need it and in a form they can understand, but the quality improvements will be driven from the provider side in much the same way. As Brent James has shown, readily available, meaningful, and comparable information on natural variation in outcomes makes it much easier for providers to improve results and reduce the variation in them. Despite its central importance and the many years that have passed, however, the state of measurement in health care remains in dire need of dramatic improvement. Fryback (1993, p. 271; also see Kindig, 1999) succinctly put the point, observing that the U.S.

“health care industry is a $900 + billion [over $2.5 trillion in 2009 (CMS, 2011] endeavor that does not know how to measure its main product: health. Without a good measure of output we cannot truly optimize efficiency across the many different demands on resources.”

Quantification in health care is almost universally approached using methods inadequate to the task, resulting in ordinal and scale-dependent scores that cannot take advantage of the objective comparisons provided by invariant, individual-level measures (Andrich, 2004). Though data-based statistical studies informing policy have their place, virtually no effort or resources have been invested in developing individual-level instruments traceable to universally uniform metrics that define the outcome products of health care. These metrics are key to efficiently harmonizing quality improvement, diagnostic, and purchasing decisions and behaviors in the manner described by Berwick, James, and Coye (2003) without having to cumbersomely communicate the concrete particulars of locally-dependent scores (Heinemann, Fisher, & Gershon, 2006). Metrologically-based common product definitions will finally make it possible for quality improvement experts to implement analogues of the Toyota Production System in healthcare, long presented as a model but never approached in practice (Coye, 2001).

So, what does all of this add up to? A new division for human, social, and natural capital in NIST is in order, with extensive involvement from NIH, CMS, AHRQ, and other relevant agencies. Innovative measurement methods and standards are the “out of the box” science NG refers to. Providing these tools is the definitive embodiment of an appropriate role for government. These are the kinds of things that we could have a productive conversation with NG about, it seems to me….

References

 Andrich, D. (2004, January). Controversy and the Rasch model: A characteristic of incompatible paradigms? Medical Care, 42(1), I-7–I-16.

Barzel, Y. (1982). Measurement costs and the organization of markets. Journal of Law and Economics, 25, 27-48.

Berwick, D. M., James, B., & Coye, M. J. (2003, January). Connections between quality measurement and improvement. Medical Care, 41(1 (Suppl)), I30-38.

Centers for Medicare and Medicaid Services. (2011). National health expenditure data: NHE fact sheet. Retrieved 30 June 2011, from https://www.cms.gov/NationalHealthExpendData/25_NHE_Fact_Sheet.asp.

Coye, M. J. (2001, November/December). No Toyotas in health care: Why medical care has not evolved to meet patients’ needs. Health Affairs, 20(6), 44-56.

De Soto, H. (1989). The other path: The economic answer to terrorism. New York: Basic Books.

De Soto, H. (2000). The mystery of capital: Why capitalism triumphs in the West and fails everywhere else. New York: Basic Books.

Fisher, W. P., Jr. (2010). Statistics and measurement: Clarifying the differences. Rasch Measurement Transactions, 23(4), 1229-1230 [http://www.rasch.org/rmt/rmt234.pdf].

Fisher, W. P., Jr., & Burton, E. (2010). Embedding measurement within existing computerized data systems: Scaling clinical laboratory and medical records heart failure data to predict ICU admission. Journal of Applied Measurement, 11(2), 271-287.

Fryback, D. (1993). QALYs, HYEs, and the loss of innocence. Medical Decision Making, 13(4), 271-2.

Gingrich, N. (2008). Real change: From the world that fails to the world that works. Washington, DC: Regnery Publishing.

Goldberg, S. H. (2009). Billions of drops in millions of buckets: Why philanthropy doesn’t advance social progress. New York: Wiley.

Heinemann, A. W., Fisher, W. P., Jr., & Gershon, R. (2006). Improving health care quality with outcomes management. Journal of Prosthetics and Orthotics, 18(1), 46-50 [http://www.oandp.org/jpo/library/2006_01S_046.asp].

Kindig, D. A. (1997). Purchasing population health. Ann Arbor, Michigan: University of Michigan Press.

Kindig, D. A. (1999). Purchasing population health: Aligning financial incentives to improve health outcomes. Nursing Outlook, 47, 15-22.

Latour, B. (1987). Science in action: How to follow scientists and engineers through society. New York: Cambridge University Press.

Latour, B. (2005). Reassembling the social: An introduction to Actor-Network-Theory. (Clarendon Lectures in Management Studies). Oxford, England: Oxford University Press.

Magnus, P. D. (2007). Distributed cognition and the task of science. Social Studies of Science, 37(2), 297-310.

Marty, M. (2001). Why the talk of spirituality today? Some partial answers. Second Opinion, 6, 53-64.

Marty, M., & Appleby, R. S. (Eds.). (1993). Fundamentalisms and society: Reclaiming the sciences, the family, and education. The fundamentalisms project, vol. 2. Chicago: University of Chicago Press.

National Institute for Standards and Technology. (1996). Appendix C: Assessment examples. Economic impacts of research in metrology. In Committee on Fundamental Science, Subcommittee on Research (Ed.), Assessing fundamental science: A report from the Subcommittee on Research, Committee on Fundamental Science. Washington, DC: National Standards and Technology Council

[http://www.nsf.gov/statistics/ostp/assess/nstcafsk.htm#Topic%207; last accessed 30 June 2011].

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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