Making sustainability impacts universally identifiable, individually owned, efficiently exchanged, and profitable

Sustainability impacts plainly and obviously lack common product definitions, objective measures, efficient markets, and associated capacities for competing on improved quality. The absence of these landmarks in the domain of sustainability interests is a result of inattention and cultural biases far more than it is a result of the inherent characteristics or nature of sustainability itself. Given the economic importance of these kinds of capacities and the urgent need for new innovations supporting sustainable development, it is curious how even those most stridently advocating new ways of thinking seem to systematically ignore well-established opportunities for advancing their cause. The wealth of historical examples of rapidly emerging, transformative, disruptive, and highly profitable innovations would seem to motivate massive interest in how extend those successes in new directions.

Economists have long noted how common currencies reduce transaction costs, support property rights, and promote market efficiencies (for references and more information, see previous entries in this blog over the last ten years and more). Language itself is well known for functioning as an economical labor-saving device in the way that useful concepts representing things in the world as words need not be re-invented by everyone for themselves, but can simply be copied. In the same ways that common languages ease communication, and common currencies facilitate trade, so, too, do standards for common product definitions contribute to the creation of markets.

Metrologically traceable measurements make it possible for everyone everywhere to know how much of something in particular there is. This is important, first of all, because things have to be identifiable in shared ways if we are to be able to include them in our lives, socially. Anyone interested in obtaining or producing that kind of thing has to be able to know it and share information about it as something in particular. Common languages capable of communicating specifically what a thing is, and how much of it there is, support claims to ownership and to the fruits of investments in entrepreneurial innovations.

Technologies for precision measurement key to these communications are one of the primary products of science. Instruments measuring in SI units embody common currencies for the exchange of scientific capital. The calibration and distribution of such instruments in the domain of sustainability impact investing and innovation ought to be a top-level priority. How else will sustainable impacts be made universally identifiable, individually owned, efficiently exchanged, and profitable?

The electronics, computer, and telecommunications industries provide ample evidence of precision measurement’s role in reducing transaction costs, establishing common product definitions, and reaping huge profits. The music industry’s use of these technologies combines the science and economics of precision measurement with the artistic creativity of intensive improvisations constructed from instruments tuned to standardized scales that achieve wholly unique levels of individual innovation.

Much stands to be learned, and even more to be gained, in focusing sustainability development on ways in which we can harness the economic power of the profit motive by combining collective efforts with individual imaginations in the domains of human, social, and natural capital. Aligning financial, monetary wealth with the authentic wealth and genuine productivity of gains in human, community, and environmental value ought to be the defining mission of this generation. The time to act is now.

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Why economic growth can and inevitably will be green

So, approaching matters once again from yet another point of view, we have Jason Hickel explaining a couple of weeks ago “Why Growth Can’t Be Green.” This article provides yet another example of how the problem is the problem. That is, the way we define problems sets up particular kinds of solutions in advance, and sometimes, as Einstein famously pointed out, problems cannot be solved from within the same conceptual framework that gave rise to them. I’ve expanded on this theme in a number of previous posts, for instance, here.

Hickel takes up the apparent impossibility of aligning economic growth with environmental values. He speaks directly to what he calls the rebound effect, the way that “improvements in resource efficiency drive down prices and cause demand to rise—thus canceling out some of the gains.” But that rebound can happen only as long as the economy remains defined and limited by the alignment of manufactured capital and finance, ignoring the largely unexamined and unconsidered possibility that human, social, and natural capital could be measured well enough to be also aligned with finance.

Hence, as I say, the problem is the problem. Broadening one’s conceptualization of the problem opens up new opportunities that otherwise never come into view.

The Hickel article’s entire focus is then on top-down policy impositions like taxes or a Genuine Progress Index. These presume human, social, and natural capital can only ever exist in dead formations that have to be micromanaged and concretely manipulated, and that efficient markets bringing them to life are inherently and literally unthinkable. (See a short article here for an explanation of the difference between dead and living capital. There’s a lot more where that came from, as is apparent in the previous posts here in this blog.)

The situation could be vastly different than what Hickel imagines. If we could own, buy, and sell products in efficient markets we could reward the production of human, social, and environmental value. In that scenario, when improvements in environmental resource efficiency are obtained, demand for that new environmental value will rise and its price will go down, not the resource’s price.

We ought to be creative enough to figure out how to configure markets so that prices for environmental resources (oil, farmland, metals, etc.) can stay constant or fall without increasing demand for them, as could happen if that demand is counterbalanced and absorbed by rising human, social, and environmental quality capital values.

The question is how to absorb the rebound effect in other forms of capital that grow in demand while holding demand for the natural resource base in check. The vital conceptual distinction is between socialistic centralized planning and control of actual physical entities (people, communities, the environment, and manufactured items), on the one hand, and capitalistic decentralized distributed network effects on abstract transferable representations, on the other. Everyone defaults to the socialist scenario without ever considering there might be a whole other arena in which fruitful possibilities might be imagined.

What if, for instance, we could harness the profit motive to promote growth in genuine human, social, and environmental value? What if we were able to achieve qualitatively meaningful increases in authentic wealth that were economically contingent on reduced natural resource consumption? What if the financial and substantive value profits that could be had meant that resource consumption could be reduced by the same kinds of factors as have been realized in the context of Moore’s Law? What if a human economics of genuine value could actually result in humanity being able to adjust the global thermostat up or down in small increments by efficiently rewarding just the right combinations of policies and practices at the right times and places in the right volumes?

The only way that could ever happen is if people are motivated to do the right thing for the earth and for humanity because it is the right thing for them and their families. They have to be able to own their personal shares of their personal stocks of human, social, and natural capital. They have to be able to profit from investments in their own and others’ shares. They will not act on behalf of the earth and humanity only because it is the right thing to do. There has to be evidence and explanations of how everyone is fairly held accountable to the same standards, and has the same opportunities for profit and loss as anyone else. Then, and only then, it seems, will human, social, and environmental value become communicable in a viral contagion of good will.

Socialism has been conclusively proven unworkable, for people, communities, and the environment, as well as financially. But a human, social, and natural capitalism has hardly even been articulated, much less tried out. How do we make human, social, and natural capital fungible? How might the economy transcend its traditional boundaries and expand itself beyond the existing alignment of manufactured capital and finance?

It’s an incredibly complex proposal, but also seems like such a simple thing. The manufactured capital economy uses the common language of good measurement to improve quality, to simplify management communications, and to lower transaction costs in efficient markets. So what should we do if we want to correct the imbalanced negative impacts on people, communities, and the environment created by the misplaced emphasis on aligning only manufactured capital and financial capital?

As has been repeatedly proposed for years in this blog, maybe we should use the manufactured capital markets as a model and use good measurement to improve the quality of human, social, and environmental capital, to simplify communications and management, to lower transaction costs, and to align the genuine human, social, and environmental value created with financial value in efficient markets.

Of course, grasping that as viable, feasible, and desirable requires understanding that substantively meaningful precision measurement is something quite different from what usually passes for quantification. And that is an entirely different story, though one taken up repeatedly in previous entries in this blog, of course….

 

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 Ideas on How to Realize the Purpose of Capital

I’d like to offer the following in reply to James Militzer, at https://nextbillion.net/deciphering-emersons-tears-time-impact-investing-lower-expectations/.

Rapid advances toward impact investing’s highest goals of social transformation are underway in quiet technical work being done in places no one is looking. That work shares Jed Emerson’s sentiments expressed at the 2017 Social Capital Markets conference, as he is quoted in Militzer’s NextBillion.net posting, that “The purpose of capital is to advance a more progressively free and just experience of life for all.” And he is correct in what Militzer reported he said the year before, that we need a “real, profound critique of current practices within financial capitalism,” one that would “require real change in our own behavior aside from adding a few funds to our portfolios here or augmenting a reporting process there.”

But the efforts he and others are making toward fulfilling that purpose and articulating that critique are incomplete, insufficient, and inadequate. Why? How? Language is the crux of the matter, and the issues involved are complex and technical. The challenge, which may initially seem simplistic or naive, is how to bring human, social, and environmental values into words. Not just any words, but meaningful words in a common language. What is most challenging is that this language, like any everyday language, has to span the range from abstract theoretical ideals to concrete local improvisations.

That means it cannot be like our current languages for expressing human, social, and environmental value. If we are going to succeed in aligning those forms of value with financial value, we have a lot of work to do.

Though there is endless talk of metrics for managing sustainable impacts, and though the importance of these metrics for making sustainability manageable is also a topic of infinite discussion, almost no one takes the trouble to seek out and implement the state of the art in measurement science. This is a crucial way, perhaps the most essential way, in which we need to criticize current practices within financial capitalism and change our behaviors. Oddly, almost no one seems to have thought of that.

That is, one of the most universally unexamined assumptions of our culture is that numbers automatically stand for quantities. People who analyze numeric data are called quants, and all numeric data analysis is referred to as quantitative. That is the case, but almost none of these quants and quantitative methods involve actually defining, modeling, identifying, evaluating, or applying an substantive unit of something real in the world that can be meaningfully represented by numbers.

There is, of course, an extensive and longstanding literature on exactly this science of measurement. It has been a topic of research, philosophy, and practical applications for at least 90 years, going back to the work of Thurstone at the University of Chicago in the 1920s. That work continued at the University of Chicago with Rasch’s visit there in 1960, with Wright’s adoption and expansion of Rasch’s theory and methods, and with the further work done by Wright’s students and colleagues in the years since.

Most importantly, over the last ten years, metrologists, the physicists and engineers who maintain and improve the SI units, the metric system, have taken note of what’s been going on in research and practice involving the approaches to measurement developed by Rasch, Wright, and their students and colleagues (for just two of many articles in this area, see here and here). The most recent developments in this new metrology include

(a) initiatives at national metrology institutes globally (Sweden and the UK, Portugal, Ukraine, among others) to investigate potentials for a new class of unit standards;

(b) a special session on this topic at the International Measurement Confederation (IMEKO) World Congress in Belfast on 5 September 2018;

(c) the Journal of Physics Conference Series proceedings of the 2016 IMEKO Joint Symposium hosted by Mark Wilson and myself at UC Berkeley;

(d) the publication of a 2017 book on Ben Wright edited by Mark Wilson and myself in Springer’s Series on Measurement Science and Technology; and

(e) the forthcoming October 2018 special issue of Elsevier’s Measurement journal edited by Wilson and myself, and a second one currently in development.

There are profound differences between today’s assumptions about measurement and how a meaningful art and science of precision measurement proceeds. What passes for measurement in today’s sustainability economics and accounting are counts, percentages, and ratings. These merely numeric metrics do not stand for anything that adds up the way they do. In fact, it’s been repeatedly demonstrated over many years that these kinds of metrics measure in a unit that changes size depending on who or what is measured, who is measuring, and what tool is used to measure. What makes matters even worse is that the numbers are usually taken to be perfectly precise, as uncertainty ranges, error terms, and confidence intervals are only sporadically provided and are usually omitted.

Measurement is not primarily a matter of data analysis. Measurement requires calibrated instruments that can be read as standing for a given amount of something that stays the same, within the uncertainty range, no matter who is measuring, no matter what or who is measured, and no matter what tool is used. This is, of course, quite an accomplishment when it can be achieved, but it is not impossible and has been put to use in large scale practical ways for several decades (for instance, see here, here, and here). Universally accessible instruments calibrated to common unit standards are what make society in general, and markets in particular, efficient in the way of projecting distributed network effects, turning communities into massively parallel stochastic computers (as W. Brian Arthur put it on p. 6 of his 2014 book, Complexity Economics).

These are not unexamined assumptions or overly ideal theoretical demands. They are pragmatic ways of adapting to emergent patterns in various kinds of data that have repeatedly been showing themselves around the world for decades. Our task is to literally capitalize on these nonhuman forms of life by creating multilevel, complex ecosystems of relationships with them, letting them be what they are in ways that also let us represent ourselves to each other. (Emerson quotes Bruno Latour to this effect on page 136 in his new book, The Purpose of Capital; those familiar with my work will know I’ve been reading and citing Latour since the early 1980s).

So it seems to me that, however well-intentioned those promoting impact investing may be, there is little awareness of just how profound and sweeping the critique of current practices needs to be, or of just how much our own behaviors are going to have to change. There are, however, truly significant reasons to be optimistic and hopeful. The technical work being done in measurement and metrology points toward possibilities for extending everyday language into a pragmatic idealism that does not require caving in to either varying local circumstances or to authoritarian dictates.

The upside of the situation is that, as so often happens in the course of human history, this critique and the associated changes are likely to have that peculiar quality captured in the French expression, “plus ça change, plus c’est la même chose” (the more things change, the more they stay the same). The changes in process are transformative, but will also be recognizable repetitions of human scale patterns.

In sum, what we are doing is tuning the instruments of the human, social, and environmental sciences to better harmonize relationships. Just as jazz, folk, and world music show that creative improvisation is not constrained by–but is facilitated by–tuning standards and high tech solutions, so, too, can we make that the case in other areas.

For instance, in my presentation at the IMEKO World Congress in Belfast on 5 September, I showed that the integration of beauty and meaning we have within our grasp reiterates principles that date back to Plato. The aesthetics complement the mathematics, with variations on the same equations being traceable from the Pythagorean theorem to Newton’s laws to Rasch’s models for measurement (see, for instance, Fisher & Stenner, 2013). In many ways, the history of science and philosophy continues to be a footnote to Plato.

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.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

 

Current events in metrology for fun, profitable, and self-sustaining sustainability impacts

At the main event I attended last week at the Global Climate Action Summit in San Francisco, the #giveyouthachance philanthropic gathering at the Aquarium of the Bay, multiple people independently spoke to aligning social and environmental values with financial values, and explicitly stated that economic growth does not automatically entail environmental degradation.

As my new buddy David Traub (introduced as a consequence of the New Algorithm event in Stockholm in June with Angelica Lips da Cruz) was the MC, he put me on the program at the last minute, and gave me five minutes to speak my piece in a room of 30 people or so. A great point of departure was opened up when Carin Winter of MissionBe.org spoke to her work in mindfulness education and led a guided meditation. So I conveyed the fact that the effects of mindfulness practice are rigorously measurable, and followed that up with the analogy from music (tuning instruments to harmonize relationships),  with the argument against merely shouldering the burden of costs because it is the right thing to do, with the counter-argument for creating efficient competitive markets for sustainable impacts, and with info on the previous week’s special session on social and psychological metrology at IMEKO in Belfast. It appeared that the message of metrology as a means for making sustainability self-sustaining, fun, and profitable got through!

Next up: Unify.Earth has developed their own new iteration on blockchain, which will be announced Monday, 24 September, at the UN SDG Media Center (also see here) during the World Economic Forum’s Sustainable Development Impact Summit. The UEX (Unify Earth Exchange) fills the gap for human capital stocks left by the Universal Commons‘ exclusive focus on social and natural capital.

So I’ve decided to go to NY and have booked my travel.

Back in February, Angelica Lips da Cruz recounted saying six months before that it would take two years to get to where we were at that time. Now another seven months have passed and I am starting to feel that the acceleration is approaching Mach 1! At this rate, it’ll be the speed of light in the next six months….

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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Metrics, Stocks, Shares, and Secure Ledger Accounts for Living Capital: Getting the Information into the Hands of Individual Decision Makers

Individual investments in, and returns from, shares of various kinds of human, social, and natural capital stocks will be tracked in secure online accounting ledgers, often referred to generically using the Blockchain brand name. A largely unasked and unanswered question is just what kind of data would best be tracked in secure ledgers. To be meaningful, entries in such accounts will have to stand for something real in the world that is represented in a common language interpretable to anyone capable of reading the relevant signs and symbols. Since we are talking about amounts of things that vary, measurement will unavoidably be a factor.

High quality measurement is essential to the manageability and profitability of investments of all kinds, whether in manufactured capital and property, or in literacy, numeracy, mental and physical health, sociability, and environmental quality (human, social, and natural capital). The measurability and manageability of these intangible factors has achieved significant levels of scientific precision and rigor over the last 90 and more years.

This development is of increasing interest to economists and accountants who have long envisioned ways of reinventing capitalism that do not assume the only alternative is some form of socialism or communism (see references listed below). Many of today’s economic problems may follow from capitalism’s incompleteness. More specifically, we may be suffering from the way in which manufactured capital alone has been been brought to life, economically speaking, while human, social, and natural capital have not (Fisher, 2002, 2007, 2009a/b, 2010a/b, 2011a/b, 2012ab, 2014, etc.).

One in particular who speaks directly to an essential issue that must be addressed in creating an economy of authentic wealth and genuine productivity is Paul Hawken (2007, pp. 21-22), who says that Friedrich Hayek foresaw

“a remedy for the basic expression of the totalitarian impulse: ensuring that information and the right to make decisions are co-located. To achieve this, one can either move the information to the decision makers, or move decision making rights to the information. The movement strives to do both. The earth’s problems are everyone’s problems, and what modern technology and the movement can achieve together is to distribute problem solving tools.”

Hayek (1945, 1948, 1988; Frantz & Leeson, 2013) is well known for his focus on a distinction between a mechanical definition of individuals as uniform and homogenous, and a more vital sense of economic “true individuals” as complex and interdependent. To create efficient markets for the production of authentic wealth, we need to figure out how to extend the “true individuals” of manufactured capital markets into new markets for human, social, and natural capital (Fisher, 2014).

The distributed problem solving tools we need to support the decision making of “true” individuals are secure online ledgers accounting for investments in measured amounts of authentic wealth. Efficient markets are functions of individual processes that create wholes greater than their sums. The multiplier effect that makes this possible depends on transparent communication. Words, including number words, have to mean something specific and distinct. This is where the value of systematic measurement and metrology comes to bear. This is why we need an Intangible Assets Metric System.

For as long as economists have been concerned with markets, philosophers have been pointing out that society is an effect of shared symbol systems. In both cases, economists and philosophers are focused on the fact that it is only when people have a common language that an idea, a meme, can go viral, that a market can seem to have a mind of its own, and science can maintain an ever-increasing pace of technical innovation.

Our aim is to create the information that will populate the entries in the secure ledger accounts people use to track and manage their investments in literacy, numeracy, health, social, and natural capital. These entries will be posted right alongside their existing entries for investments in manufactured capital and property, which includes everything from groceries to autos to electronics to homes.

But the new ledger accounts will be different from today’s in important ways. Many current accounting entries are ultimately written off as costs producing untracked and unaccountable returns. We simply spend the money on groceries or school tuition or a doctor visit. The income is logged, and so are the expenses. We can see that, yes, buying groceries is an investment of a kind, since we profit from it by enjoying the processes of cooking, sharing, and eating tasty food, by avoiding hunger, and by sustaining good health.

Investments are tracked in a different way, though. Money is not just spent and kissed goodbye. Instead, investment funds are loaned to or leased by someone else who is expected to be able to increase the value of those funds. There are often no guarantees of an increase, but the invested value is associated with a proportionate share in the total value of the business. As the business grows or fails, so does the investment.

In much the same way, if we had the information available to us, we could track the returns on the investments we make in food, education, or health care. If we track the impacts of our dietary choices, we would be able to see if and when the investments we make result in healthy outcomes. The information brought to bear will have to include systematic advice relevant to one’s age, sex, pre-existing conditions, genetic propensities, etc. Additional information on the returns on one’s investments in a healthy diet should also be made available, as might be found in the expected income or expenses associated with the consequences of what is eaten, and how much of it. Sometimes there will be room for improvement, for example, if the foods we eat are too sugary or fatty, or if we eat too much. Other times, maintaining a healthy, varied diet may be all that is needed to see a consistent positive return on investment.

Public reports will allow us all to learn from one another. The ability to communicate in a common language and to see what has worked for others will enable everyone to experiment with new ways of doing things. People with common food interests or problems, for instance, will be able quickly evaluate the relevance and benefits of other people’s approaches or solutions. Because of the ways in which communication and community go together, it may be reasonable to hope that new levels of innovation, diversity, tolerance, and respect will follow.

Many aspects of work, education and health care are already undergoing transformations that move their processes out of the usual office, school and hospital environments. These changes will be accelerated as distributed network effects take hold in each of these various markets.

It is easy to see how the Internet of things may evolve to be the medium in which we manage relationships of all kinds, from education and school to health and safety to work and career. Secure ledgers immune from hacking will be essential. And an important health factor will be to know how much relationship management is enough, and when it’s time to get out into the world. That balancing factor will be a key aspect of a successful approach to connecting information on authentic wealth with the individual decision makers growing it and living it.

References

Andriessen, D. (2003). Making sense of intellectual capital: Designing a method for the valuation of intangibles. Oxford, England: Butterworth-Heinemann.

Anielski, M. (2007). The economics of happiness: Building genuine wealth. Gabriola, British Columbia: New Society Publishers.

Cadman, D. (1986). Money as if people mattered. In P. Ekins &  Staff of The Other Economic Summit (Eds.), The living economy: A new economics in the making (pp. 204-210). London: Routledge & Kegan Paul.

Eisler, R. (2007). The real wealth of nations: Creating a caring economics. San Francisco, California: Berrett-Koehler Publishers, Inc.

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. (1999). Economic growth and environmental sustainability: The prospects for green growth. New York: Routledge.

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

Ekins, P., Hillman, M., & Hutchison, R. (1992). The Gaia atlas of green economics (Foreword by Robert Heilbroner). New York: Anchor Books.

Ekins, P., & Max-Neef, M. A. (Eds.). (1992). Real-life economics: Understanding wealth creation. London: Routledge.

Ekins, P., & Voituriez, T. (2009). Trade, globalization and sustainability impact assessment: A critical look at methods and outcomes. London, England: Earthscan Publications Ltd.

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. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-1093 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009a, November). 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 (Tech. Rep., 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. (2010a). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital., Bridge to Business Postdoctoral Certification, Freeman School of Business, Tulane University (p. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2340674).

Fisher, W. P., Jr. (2010b, 13 January). Reinventing capitalism: Diagramming living capital flows in a green, sustainable, and responsible economy. Retrieved from LivingCapitalMetrics.com: https://livingcapitalmetrics.wordpress.com/2010/01/13/reinventing-capitalism/.

Fisher, W. P., Jr. (2011a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), 49-66.

Fisher, W. P., Jr. (2011b). Measuring genuine progress by scaling economic indicators to think global & act local: An example from the UN Millennium Development Goals project. LivingCapitalMetrics.com. Retrieved 18 January 2011, from Social Science Research Network: http://ssrn.com/abstract=1739386.

Fisher, W. P., Jr. (2012a). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012b, May/June). What the world needs now: A bold plan for new standards [Third place, 2011 NIST/SES World Standards Day paper competition]. Standards Engineering, 64(3), 1 & 3-5 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr. (2014, Autumn). The central theoretical problem of the social sciences. Rasch Measurement Transactions, 28(2), 1464-1466.

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Hawken, P. (2007). Blessed unrest: How the largest movement in the world came into being and why no one saw it coming. New York: Viking Penguin.

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Hayek, F. A. (1955). The counter revolution of science. Glencoe, Illinois: Free Press.

Hayek, F. A. (1988). The fatal conceit: The errors of socialism (W. W. Bartley, III, Ed.) (Vol. I). The Collected Works of F. A. Hayek. Chicago: University of Chicago Press.

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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.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

What is the point of sustainability impact investing?

What if the sustainability impact investing problem is not just a matter of judiciously supporting business policies and practices likely to enhance the long term viability of life on earth? What if the sustainability impact investing problem is better conceived in terms of how to create markets that function as self-sustaining ecosystems of diverse forms of economic life?

The crux of the sustainability problem from this living capital metrics point of view is how to create efficient markets for virtuous cycles of productive value creation in the domains of human, social, and natural capital. Mainstream economics deems this an impossible task because its definition of measurement makes trade in these forms of capital unethical and immoral forms of slavery.

But what if there is another approach to measurement? What if this alternative approach is scientific in ways unimagined in mainstream economics? What if this alternative approach has been developing in research and practice in education, psychology, health care, sociology, and other fields for over 90 years? What if there are thousands of peer-reviewed publications supporting its validity and reliability? What if a wide range of commercial firms have been successfully employing this alternative approach to measurement for decades? What if this alternative approach has been found legally and scientifically defensible in ways other approaches have not? What if this alternative approach enables us to be better stewards of our lives together than is otherwise possible?

Put another way, measuring and managing sustainability is fundamentally a problem of harmonizing relationships. What do we need to harmonize our relationships with each other, between our communities and nations, and with the earth? How can we achieve harmonization without forcing conformity to one particular scale? How can we tune the instruments of a sustainability art and science to support as wide a range of diverse ensembles and harmonies as exists in music?

Positive and hopeful answers to these questions follow from the fact that we have at our disposal a longstanding, proven, and advanced art and science of qualitatively rich measurement and instrument calibration. The crux of the message is that this art and science is poised to be the medium in which sustainability impact investing and management fulfills its potential and transforms humanity’s capacities to care for itself and the earth.

The differences between the quality of information that is available, and the quality of information currently in use in sustainability impact investing, are of such huge magnitudes that they can only be called transformative. Love and care are the power behind these transformative differences. Choosing discourse over violence, considerateness for the vulnerabilities we share with others, and care for the unity and sameness of meaning in dialogue are all essential to learning the lesson Diotima taught Socrates in Plato’s Symposium. These lessons can all be brought to bear in creating the information and communications systems we need for sustainable economies.

The current world of sustainability impact investing’s so-called metrics lead to widespread complaints of increased administrative and technical burdens, and resulting distractions that lead away from pursuit of the core social mission. The maxim, “you manage what you measure,” becomes a cynical commentary on red tape and bureaucracy instead of a commendable use of tools fit for purpose.

In contrast with the cumbersome and uninterpretable masses of data that pass for sustainability metrics today, the art and science of measurement establishes the viability and feasibility of efficient markets for human, social, and natural capital. Instead of counting paper clips in mindless accounting exercises, we can instead be learning what comes next in the formative development of a student, a patient, an employee, a firm, a community, or the ecosystem services of watersheds, forests, and fisheries.

And we can moreover support success in those developments by means of information flows that indicate where the biggest per-dollar human, social, and natural capital value returns accrue. Rigorous measurability of those returns will make it possible to price them, to own them, to make property rights legally enforceable, and to thereby align financial profits with the creation of social value. In fact, we could and should set things up so that it will be impossible to financially profit without creating social value. When that kind of system of incentives and rewards is instituted, then the self-sustaining virtuous cycle of a new ecological economy will come to life.

Though the value and originality of the innovations making this new medium possible are huge, in the end there’s really nothing new under the sun. As the French say, “plus ça change, plus c’est la même chose.” Or, as Whitehead put it, philosophically, the innovations in measurement taking hold in the world today are nothing more than additional footnotes to Plato. Contrary to both popular and most expert opinion, it turns out that not only is a moral and scientific art of human measurement possible, Plato’s lessons on how experiences of beauty teach us about meaning provide what may well turn out to be the only way today’s problems of human suffering, social discontent, and environmental degradation will be successfully addressed.

We are faced with a kind of Chinese finger-puzzle: the more we struggle, the more trapped we become. Relaxing into the problem and seeing the historical roots of scientific reasoning in everyday thinking opens our eyes to a new path. Originality is primarily a matter of finding a useful model no one else has considered. A long history of innovations come together to point in a new direction plainly recognizable as a variation on an old theme.

Instead of a modern focus on data and evidence, then, and instead of the postmodern focus on the theory-dependence of data, we are free to take an unmodern focus on how things come into language. The chaotic complexity of that process becomes manageable as we learn to go with the flow of adaptive evolving processes stable enough to support meaningful communication. Information infrastructures in this linguistic context are conceived as ecosystems alive to changeable local situations at the same time they do not compromise continuity and navigability.

We all learn through what we already know, so it is essential that we begin from where we are at. Our first lessons will then be drawn from existing sustainability impact data, using the UN SDG 17 as a guide. These data were not designed from the principles of scientifically rigorous measurement, but instead assume that separately aggregated counts of events, percentages, and physical measures of volume, mass, or time will suffice as measures of sustainability. Things that are easy to count are not, however, likely to work as satisfactory measures. We need to learn from the available data to think again about what data are necessary and sufficient to the task.

The lessons we will learn from the data available today will lead to more meaningful and rigorous measures of sustainability. Connecting these instruments together by making them metrologically traceable to standard units, while also illuminating local unique data patterns, in widely accessible multilevel information infrastructures is the way in which we will together work the ground, plant the seeds, and cultivate new diverse natural settings for innovating sustainable relationships.

 

On social impact bonds and critical reflections

A new article (Roy, McHugh, & Sinclair, 2018) out this week in the Stanford Social Innovation Review echoes Gleeson-White (2015) in pointing out a disconnect between financial bottom lines and the social missions of companies whose primary objectives concern broader social and environmental impacts. The article also notes the expense of measurement, increased administrative burdens, high transaction costs, technical issues in achieving fair measures, the trend toward the negative implications of managing what is measured instead of advancing the mission, and the potential impacts of external policy environments and political climates.

The authors contend that social impact bonds are popular and proliferating for ideological reasons, not because of any evidence concerning their effectiveness in making the realization of social objectives profitable. Some of the several comments posted online in response to the article take issue with that claim, and point toward evidence of effectiveness. But the general point still stands: more must be done to systematically align investors’ financial interests with the citizens’ interest in advancing their financial, social, and environmental quality of life, and not just with the social service providers’ interest in funding and advancing their mission.

Roy et al. are correct to say that to do otherwise is to turn the people served into commodities. This happens because governance of, accountability for, and reporting of social impacts are shifted away from elected officials to the needs of private funders, with far less in the way of satisfactory recourse for citizens when programs go awry. The problem lies in the failure to create any capacity for individuals themselves to represent, invest in, manage, and profit from their skills, health, trust, and environmental service outcomes. Putting all the relevant information into the hands of service providers and investors, and making that information as low quality as it is, can only ever result in one-sided effects on people themselves. With no idea of the technologies, models, decades of results, and ready examples to draw from in the published research, the authors conclude with a recommendation to leave well enough alone and to pursue more traditional avenues of policy formation, instead of allowing the “cultural supremacy of market principles” to continue advancing into every area of life.

But as is so commonly the case when it comes to technical issues of quantification, the authors’ conclusions and criticisms skip over the essential role that high quality measurement plays in reducing transaction costs and supporting property rights. In general, measurement standards inform easily communicated and transferable information about the quantity and quality of products in markets, thereby lowering transaction costs and enabling rights to the ownership of specific amounts of things. The question that goes unasked in this article, and in virtually every other article in the area of ESG, social impact investing, etc., is this: What kind of measurement technologies and systems would we need to be able to replicate existing market efficiencies in new markets for human, social, and natural capital?

That question and other related ones are, of course, the theme of this blog and of many of my publications. Further exploration here and in the references to other posts (such as Fisher, 2011, 2012a, 2012b) may prove fruitful to others seriously interested in finding a way out of the unexamined assumptions stifling creativity in this area.

In short, instead of turning people into commodities, why should we not turn skills, health, trust, and environmental services into commodities? Why should not every person have legal title to scientifically and uniformly measured numbers of shares of each essential form of human, social, and natural capital? Why should individuals not be able to profit in both monetary and personal terms from their investments in education, health care, community, and the environment? Why should we allow corporations to continue externalizing the costs of social and environmental investments, at the expense of individual citizens and communities? Why is there so much disparity and inequality in the opportunities for skill development and healthy lives available across social sectors?

Might not our inability to obtain good information about processes and outcomes in the domains of educational, health care, social service, and environmental management have a lot to do with it? Why don’t we have the information infrastructure we need, when the technology for creating it has been in development for over 90 years? Why are there so many academics, researchers, philanthropic organizations, and government agencies that are content with the status quo when these longstanding technologies are available, and people, communities, and the environment are suffering from the lack of the information they ought to have?

During the French revolution, one of the primary motivations for devising the metric system was to extend the concept of universal rights to individual commercial exchanges. The confusing proliferation of metrics in Europe at the time made it possible for merchants and the nobility to sell in one unit and buy with another. Universal rights plainly implied universal measures. Alder (2002, p. 2) explains that:

“To do their job, standards must operate as a set of shared assumptions, the unexamined background against which we strike agreements and make distinctions. So it is not surprising that we take measurement for granted and consider it banal. Yet the use a society makes of its measures expresses its sense of fair dealing. That is why the balance scale is a widespread symbol of justice. .. Our methods of measurement define who we are and what we value.”

Getting back to the article by Roy, McHugh, and Sinclair, yes, it is true that the measures in use in today’s social impact bonds are woefully inadequate. Far from living up to the kind of justice symbolized by the balance scale, today’s social impact measures define who we are in terms of units of measurement that differ and change in unknown ways across individuals, over time, and across instruments. This is the reason for many, if not all, of the problems Roy et al. find with social impact bonds: their measures are not up to the task.

But instead of taking that as an unchangeable given, should not we do more to ask what kinds of measures could do the job that needs to be done? Should not we look around and see if in fact there might be available technologies able to advance the cause?

Theory and evidence have, in fact, been brought to bear in formulating approaches to instrument calibration that reproduce the balance scale’s fair and just comparisons of weight from data like that from tests and surveys (Choi, 1998; Massof, 2011; Rasch, 1960, pp. 110-115). The same thing has been done in reproducing measures of length (Stephanou & Fisher, 2013), distance (Moulton, 1993), and density (Pelton & Bunderson, 2003).

These are not isolated and special results. The methods involved have been in use for decades and in dozens of fields (Wright, 1968, 1977, 1999; Wright & Masters, 1982; Wright & Stone, 1979, 1999; Andrich, 1978, 1988, 1989, 2010; Bond & Fox, 2015; Engelhard, 2012; Wilson, 2005; Wilson & Fisher, 2017). Metric system engineers and physicists are in accord with psychometricians as to the validity of these claims (Pendrill & Fisher, 2015) and are on the record with positive statements of support:

“Rasch models belong to the same class that metrologists consider paradigmatic of measurement” (Mari and Wilson, 2014, p. 326).

“The Rasch approach…is not simply a mathematical or statistical approach, but instead [is] a specifically metrological approach to human-based measurement” (Pendrill, 2014, p. 26).

These statements represent the attitude toward measurement possibilities being applied by at least one effort in the area of social impact investing (https://www.aldcpartnership.com/#/cases/financing-the-future). Hopefully, there will be many more projects of this kind emerging in the near future.

The challenges are huge, of course. This is especially the case when considering the discontinuous levels of complexity that have to be negotiated in making information flow across locally situated individual niches, group-level organizations and communities, and global accountability applications (Fisher, 2017; Fisher, Oon, & Benson, 2018; Fisher & Stenner, 2018). But taking on these challenges makes far more sense than remaining complicitly settled in a comfortable rut, throwing up our hands at how unfair life is.

There’s a basic question that needs to be asked. If what is presented as measurement raises transaction costs and does not support ownership rights to what is measured, is it really measurement? How can the measurement of kilowatts, liters, and grams lower transaction costs and support property rights at the same time that other so-called measurements raise transaction costs and do not support property rights? Does not this inconsistency suggest something might be amiss in the way measurement is conceived in some areas?

For more info, check out these other posts here:

Living Capital Metrics for Financial and Sustainability Accounting Standards

Another Take on the Emerging Paradigm Shift

https://wordpress.com/post/livingcapitalmetrics.wordpress.com/1812

https://wordpress.com/post/livingcapitalmetrics.wordpress.com/497

References

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Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43(4), 561-573.

Andrich, D. (1988). Sage University Paper Series on Quantitative Applications in the Social Sciences. Vol. series no. 07-068: Rasch models for measurement. Beverly Hills, California: Sage Publications.

Andrich, D. (1989). Constructing fundamental measurements in social psychology. In J. A. Keats, R. Taft, R. A. Heath & S. H. Lovibond (Eds.), Mathematical and theoretical systems. Proceedings of the 24th International Congress of Psychology of the International Union of Psychological Science, Vol. 4 (pp. pp. 17-26). Amsterdam, Netherlands: North-Holland.

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

Bond, T., & Fox, C. (2015). Applying the Rasch model: Fundamental measurement in the human sciences, 3d edition. New York: Routledge.

Choi, E. (1998). Rasch invents “ounces.” Popular Measurement, 1(1), 29. Retrieved from https://www.rasch.org/pm/pm1-29.pdf

Engelhard, G., Jr. (2012). Invariant measurement: Using Rasch models in the social, behavioral, and health sciences. New York: Routledge Academic.

Fisher, W. P., Jr. (2011). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), 49-66.

Fisher, W. P., Jr. (2012a). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012b, May/June). What the world needs now: A bold plan for new standards [Third place, 2011 NIST/SES World Standards Day paper competition]. Standards Engineering, 64(3), 1 & 3-5 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr. (2017). A practical approach to modeling complex adaptive flows in psychology and social science. Procedia Computer Science, 114, 165-174. Retrieved from https://doi.org/10.1016/j.procs.2017.09.027

Fisher, W. P., Jr., Oon, E. P.-T., & Benson, S. (2018). Applying Design Thinking to systemic problems in educational assessment information management. Journal of Physics Conference Series, pp. in press; [http://media.imeko-tc7-rio.org.br/media/uploads/s/wfisher@berkeley.edu_1497049869_781396.pdf].

Fisher, W. P., Jr., & Stenner, A. J. (2018). Ecologizing vs modernizing in measurement and metrology. Journal of Physics Conference Series, pp. in press [http://media.imeko-tc7-rio.org.br/media/uploads/s/wfisher@berkeley.edu_1496875919_204672.pdf].

Gleeson-White, J. (2015). Six capitals, or can accountants save the planet? Rethinking capitalism for the 21st century. New York: Norton.

Mari, L., & Wilson, M. (2014, May). An introduction to the Rasch measurement approach for metrologists. Measurement, 51, 315-327.

Massof, R. W. (2011). Understanding Rasch and Item Response Theory models: Applications to the estimation and validation of interval latent trait measures from responses to rating scale questionnaires. Ophthalmic Epidemiology, 18(1), 1-19.

Moulton, M. (1993). Probabilistic mapping. Rasch Measurement Transactions, 7(1), 268 [http://www.rasch.org/rmt/rmt71b.htm].

Pelton, T., & Bunderson, V. (2003). The recovery of the density scale using a stochastic quasi-realization of additive conjoint measurement. Journal of Applied Measurement, 4(3), 269-281.

Pendrill, L. (2014, December). Man as a measurement instrument [Special Feature]. NCSLi Measure: The Journal of Measurement Science, 9(4), 22-33.

Pendrill, L., & Fisher, W. P., Jr. (2015). Counting and quantification: Comparing psychometric and metrological perspectives on visual perceptions of number. Measurement, 71, 46-55.

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.

Roy, M. J., McHugh, N., & Sinclair, S. (2018, 1 May). A critical reflection on social impact bonds. Stanford Social Innovarion Review. Retrieved 5 May 2018, from https://ssir.org/articles/entry/a_critical_reflection_on_social_impact_bonds?utm_source=Enews&utm_medium=Email&utm_campaign=SSIR_Now&utm_content=Title.

Stephanou, A., & Fisher, W. P., Jr. (2013). From concrete to abstract in the measurement of length. Journal of Physics Conference Series, 459, http://iopscience.iop.org/1742-6596/459/1/012026.

Wilson, M. (2005). Constructing measures: An item response modeling approach. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Wilson, M., & Fisher, W. (2017). Psychological and social measurement: The career and contributions of Benjamin D. Wright. New York: Springer.

Wright, B. D. (1968). Sample-free test calibration and person measurement. In Proceedings of the 1967 invitational conference on testing problems (pp. 85-101 [http://www.rasch.org/memo1.htm]). Princeton, New Jersey: Educational Testing Service.

Wright, B. D. (1977). Solving measurement problems with the Rasch model. Journal of Educational Measurement, 14(2), 97-116 [http://www.rasch.org/memo42.htm].

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., & Masters, G. N. (1982). Rating scale analysis: Rasch measurement. Chicago, Illinois: MESA Press.

Wright, B. D., & Stone, M. H. (1979). Best test design: Rasch measurement. Chicago, Illinois: MESA Press.

Wright, B. D., & Stone, M. H. (1999). Measurement essentials. Wilmington, DE: Wide Range, Inc. [http://www.rasch.org/measess/me-all.pdf].

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

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.

Living Capital Metrics for Financial and Sustainability Accounting Standards

I was very happy a few days ago to come across Jane Gleeson-White’s new book, Six Capitals, or Can Accountants Save the Planet? Rethinking Capitalism for the 21st Century. The special value for me in this book comes in the form of an accessible update on what’s been going on in the world of financial accounting standards. Happily, there’s been a lot of activity (check out, for instance, Amato & White, 2013; Rogers & White, 2015). Less fortunately, the activity seems to be continuing to occur in the same measurement vacuum it always has, despite my efforts in this blog to broaden the conversation to include rigorous measurement theory and practice.

But to back up a bit, recent events around sustainability metric standards don’t seem to be connected to previous controversies around financial standards and economic modeling, which were more academically oriented to problems of defining and expressing value. Gleeson-White doesn’t cite any of the extensive literature in those areas (for instance, Anielski, 2007; Baxter, 1979; Economist, 2010; Ekins, 1992, 1999; Ekins, Dresner, & Dahlstrom, 2008; Ekins, Hillman, & Hutchins, 1992; Ekins & Voituriez, 2009; Fisher, 2009b, 2009c, 2011; Young & Williams, 2010). Valuation is still a problem, of course, as is the analogy between accounting standards and scientific standards (Baxter, 1979). But much of the sensitivity of the older academic debate over accounting standards seems to have been lost in the mad, though well-intentioned, rush to devise metrics for the traditionally externalized nontraditional forms of capital.

Before addressing the thousands of metrics in circulation and the science that needs to be brought to bear on them (the ongoing theme of posts in this blog), some attention to terminology is important. Gleeson-White refers to six capitals (manufactured, liquid, intellectual, human, social, and natural), in contrast with Ekins (1992; Ekins, et al., 2008), who describes four (manufactured, human, social, and natural). Gleeson-White’s liquid capital is cash money, which can be invested in capital (a means of producing value via ongoing services) and which can be extracted as a return on capital, but is not itself capital, as is shown by the repeated historical experience in many countries of printing money without stimulating economic growth and producing value. Of her remaining five forms of capital, intellectual capital is a form of social capital that can satisfactorily be categorized alongside the other forms of organization-level properties and systems involving credibility and trust.

On pages 209-227, Gleeson-White takes up questions relevant to the measurement and information quality topics of this blog. The context here is informed by the International Integrated Reporting Council’s (IIRC) December 2013 framework for accounting reports integrating all forms of capital (Amato & White, 2013), and by related efforts of the Sustainability Accounting Standards Board (SASB) (Rogers & White, 2015). Following the IIRC, Gleeson-White asserts that

“Not all the new capitals can be quantified, yet or perhaps ever–for example, intellectual, human and social capital, much of natural capital–and so integrated reports are not expected to provide quantitative measures of each of the capitals.”

Of course, this opinion flies in the face of established evidence and theory accepted by both metrologists (weights and measures standards engineers and physicists) and psychometricians as to the viability of rigorous measurement standards for the outcomes of education, health care, social services, natural resource management, etc. (Fisher, 2009b, 2011, 2012a, 2012b; Fisher & Stenner, 2011a, 2013, 2015; Fisher & Wilson, 2015; Mari & Wilson, 2013; Pendrill, 2014; Pendrill & Fisher, 2013, 2015; Wilson, 2013; Wilson, Mari, Maul, & Torres Irribarra, 2015). Pendrill (2014, p. 26), an engineer, physicist, and past president of the European Association of National Metrology Institutes, for instance, states that “The Rasch approach…is not simply a mathematical or statistical approach, but instead [is] a specifically metrological approach to human-based measurement.” As is repeatedly shown in this blog, access to scientific measures sets the stage for a dramatic transformation of the potential for succeeding in the goal of rethinking capitalism.

Next, Gleeson-White’s references to several of the six capitals as the “living” capitals (p. 193) is a literal reference to the fact that human, social, and natural capital are all carried by people, organizations/communities, and ecosystems. The distinction between dead and living capital elaborated by De Soto (2000) and Fisher (2002, 2007, 2010b, 2011), which involves making any form of capital fungible by representing it in abstract forms negotiable in banks and courts of law, is not taken into account, though this would seem to be a basic requirement that must be fulfilled before the rethinking of capitalism could said to have been accomplished.

Gleeson-White raises the pointed question as to exactly how integrated reporting is supposed to provoke positive growth in the nontraditional forms of capital. The concept of an economic framework integrating all forms of capital relative to the profit motive, as described in Ekins’ work, for instance, and as is elaborated elsewhere in this blog, seems just over the horizon, though repeated mention is made of natural capitalism (Hawken, Lovins, & Lovins, 1999). The posing of the questions provided by Gleeson-White (pp. 216-217) is priceless, however:

“…given integrated reporting’s purported promise to contribute to sustainable development by encouraging more efficient resource allocation, how might it actually achieve this for natural and social capitals on their own terms? It seems integrated reporting does nothing to address a larger question of resource allocation….”

“To me the fact that integrated reporting cannot address such questions suggests that as with the example of human capital, its promise to foster efficient resource allocation pertains only to financial capital and not to the other capitals. If we accept that the only way to save our societies and planet is to reconceive them in terms of capital, surely the efficient valuing and allocation of all six capitals must lie at the heart of any economics and accounting for the planet’s scarce resources in the twenty-first century.
“There is a logical inconsistency here: integrated reporting might be the beginning of a new accounting paradigm, but for the moment it is being practiced by an old-paradigm corporation: essentially, one obliged to make a return on financial capital at the cost of the other capitals.”

The goal requires all forms of capital to be integrated into the financial bottom line. Where accounting for manufactured capital alone burns living capital resources for profit, a comprehensive capital accounting framework defines profit in terms of reduced waste. This is a powerful basis for economics, as waste is the common root cause of human suffering, social discontent and environmental degradation (Hawken, Lovins, & Lovins, 1999).

Multiple bottom lines are counter-productive, as they allow managers the option of choosing which stakeholder group to satisfy, often at the expense of the financial viability of the firm (Jensen, 2001; Fisher, 2010a). Economic sustainability requires that profits be legally, morally, and scientifically contingent on a balance of powers distributed across all forms of capital. Though the devil will no doubt lurk in the details, there is increasing evidence that such a balance of powers can be negotiated.

A key point here not brought up by Gleeson-White concerns the fact that markets are not created by exchange activity, but rather by institutionalized rules, roles, and responsibilities (Miller & O’Leary, 2007) codified in laws, mores, technologies, and expectations. Translating historical market-making activities as they have played out relative to manufactured capital in the new domains of human, social, and natural capital faces a number of significant challenges, adapting to a new way of thinking about tests, assessments, and surveys foremost among them (Fisher & Stenner, 2011b).

One of the most important contributions advanced measurement theory and practice (Rasch, 1960; Wright, 1977; Andrich, 1988, 2004; Fisher & Wright, 1994; Wright & Stone, 1999; Bond & Fox, 2007; Wilson, 2005; Engelhard, 2012; Stenner, Fisher, Stone, & Burdick, 2013) can make to the process of rethinking capitalism involves the sorting out of the myriad metrics that have erupted in the last several years. Gleeson-White (p. 223) reports, for instance, that the Bloomberg financial information network now has over 750 ESG (Environmental, Social, Governance) data fields, which were extracted from reports provided by over 5,000 companies in 52 countries.  Similarly, Rogers and White (2015) say that

“…today there are more than 100 organizations offering more than 400 corporate sustainability ratings products that assess some 50,000 companies on more than 8,000 metrics of environmental, social and governance (ESG) performance.”

As is also the case with the UN Millennium Development Goals (Fisher, 2011b), the typical use of these metrics as single-item “quantities” is based in counts of relevant events. This procedure misses the basic point that counts of concrete things in the world are not measures. Is it not obvious that I can have ten rocks to your two, and you can still have more rock than I do? The same thing applies to any kind of performance ratings, survey responses, or test scores. We assign the same numeric increase to every addition of one more count, but hardly anyone experimentally tests the hypothesis that the counts all work together to measure the same thing. Those who think there’s no need for precision science in this context are ignoring the decades of successful and widespread technical work in this area, at their own risk.

The repetition of history here is fascinating. As Ashworth (2004, p. 1,314) put it, historically, “The requirements of increased trade and the fiscal demands of the state fuelled the march toward a regular form of metrology.” For instance, in 1875 it was noted that “the existence of quantitative correlations between the various forms of energy, imposes upon men of science the duty of bringing all kinds of physical quantity to one common scale of comparison” (Everett, 1875, p. 9). The moral and economic  value of common scales was recognized during the French revolution, when, Alder (2002, p. 32) documents, it was asked:

“Ought not a single nation have a uniform set of measures, just as a soldier fought for a single patrie? Had not the Revolution promised equality and fraternity, not just for France, but for all the people of the world? By the same token, should not all of the world’s people use a single set of weights and measures to encourage peaceable commerce, mutual understanding, and the exchange of knowledge? That was the purpose of measuring the world.”

The value of rigorously measuring human, social and natural capital includes meaningfully integrating qualitative substance with quantitative convenience, reduced data volume, augmenting measures with uncertainty and consistency indexes, and the capacity to take missing data into account (making possible instrument equating, item banking, etc.)  In contrast with the usual methods, rigorous science demands that experiments determine which indicators cohere to measure the same thing by repeatedly giving the same values across samples, over time and space, and across subsets of indicators. Beyond such data-based results, advanced theory makes it possible to arrive at explanatory, predictive methods that add a whole new layer of efficiency to the generation of indicators (de Boeck & Wilson, 2004; Stenner, et al., 2013).

Finally, Gleeson-White (pp. 220-221) reports that “In July 2011, the SASB [Sustainability Accounting Standards Board] was launched in the United States to create standardized measures for the new capitals.” “Founded by environmental engineer and sustainability expert Jean Rogers in San Francisco, SASB is creating a full set of industry-specific standards for sustainability accounting, with the aim of making this information more consistent and comparable.” As of May 2014, the SASB vice chair is Mary Schapiro, former SEC chair, and the chairman of SASB is Michael Bloomfield, former mayor of NYC and founder of the financial information empire. The “SASB is developing nonfinancial standards for eighty-nine industries grouped in ten different sectors and aims to have completed this grueling task by February 2015. It is releasing each set of metrics as they are completed.”

Like the SASB and other groups, Gleeson-White (p. 222) reports, Bloomberg

“aims to use its metrics to start ‘standardizing the discourse around sustainability, so we’re all talking about the same things in the same way,’ as Bloomberg’s senior sustainability strategist Andrew Park put it. What companies ‘desperately want,’ he says, is ‘a legitimate voice’ to tell them: ‘This is what you need to do. You exist in this particular sector. Here are the metrics that you need to be reporting out on. So SASB will provide that. And we think that’s important, because that will help clean up the metrics that ultimately the finance community will start using.’
“Bloomberg wants to price environmental, social and governance externalities to legitimize them in the eyes of financial capital.”

Gleeson-White (p. 225) continues, saying

“Bloomberg wants to do more generally what Trucost did for Puma’s natural capital inputs: create standardized measures for the new capitals–such as ecosystem services and social impacts–so that this information can be aggregated and used by investors. Park and Ravenel call the failure to value clean air, water, stable coastlines and other environmental goods ‘as much a failure to measure as it is a market failure per se–one that could be addressed in part by providing these ‘unpriced’ resources with quantitative parameters that would enable their incorporation into market mechanisms. Such mechanisms could then appropriately ‘regulate’ the consumption of those resources.'”

Integrating well-measured living capitals into the context of appropriately configured institutional rules, roles, and responsibilities for efficient markets (Fisher, 2010b) should indeed involve a capacity to price these resources quantitatively, though this capacity alone would likely prove insufficient to the task of creating the markets (Miller & O’Leary, 2007; Williamson, 1981, 1991, 2005). Rasch’s (1960, pp. 110-115) deliberate patterning of his measurement models on the form of Maxwell’s equations for Newton’s Second Law provides a mathematical basis for connecting psychometrics with both geometry and natural laws, as well as with the law of supply and demand (Fisher, 2010c, 2015; Fisher & Stenner, 2013a).

This perspective on measurement is informed by an unmodern or amodern, post-positivist philosophy (Dewey, 2012; Latour, 1990, 1993), as opposed to a modern and positivist, or postmodern and anti-positivist, philosophy (Galison, 1997). The essential difference is that neither a universalist nor a relativist perspective is necessary to the adoption of practices of traceability to metrological standards. Rather, focusing on local, situated, human relationships, as described by Wilson (2004) in education, for instance, offers a way of resolving the false dilemma of that dichotomous contrast. As Golinski (2012, p. 35) puts it, “Practices of translation, replication, and metrology have taken the place of the universality that used to be assumed as an attribute of singular science.” Haraway (1996, pp. 439-440) harmonizes, saying “…embedded relationality is the prophylaxis for both relativism and transcendance.” Latour (2005, pp. 228-229) elaborates, 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! No discontinuity allowed, which is just what ANT [Actor Network Theory] needs for tracing social topography. Ours is the social theory that has taken metrology as the paramount example of what it is to expand locally everywhere, all while bypassing the local as well as the universal. The practical conditions for the expansion of universality have been opened to empirical inquiries. It’s not by accident that so much work has been done by historians of science into the situated and material extension of universals. Given how much modernizers have invested into universality, this is no small feat.
“As soon as you take the example of scientific metrology and standardization as your benchmark to follow the circulation of universals, you can do the same operation for other less traceable, less materialized circulations: most coordination among agents is achieved through the dissemination of quasi-standards.”

As Rasch (1980: xx) understood, “this is a huge challenge, but once the problem has been formulated it does seem possible to meet it.” Though some metrologically informed traceability networks have begun to emerge in education and health care (for instance, Fisher & Stenner, 2013, 2015; Stenner & Fisher, 2013), virtually everything remains to be done to make the coordination across stakeholders as fully elaborated as the standards in the natural sciences.

References

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

Anielski, M. (2007). The economics of happiness: Building genuine wealth. Gabriola, British Columbia: New Society Publishers.

Ashworth, W. J. (2004, 19 November). Metrology and the state: Science, revenue, and commerce. Science, 306(5700), 1314-1317.

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Fisher, W. P., Jr., & Stenner, A. J. (2015). Theory-based metrological traceability in education: A reading measurement network. Measurement, in review.

Fisher, W. P., Jr., & Wilson, M. (2015). Building a productive trading zone in educational assessment research and practice. Pensamiento Educativo, in review.

Fisher, W. P., Jr., & Wright, B. D. (1994). Introduction to probabilistic conjoint measurement theory and applications (W. P. Fisher, Jr., & B. D. Wright, Eds.) [Special issue]. International Journal of Educational Research, 21(6), 559-568.

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Pendrill, L., & Fisher, W. P., Jr. (2013). Quantifying human response: Linking metrological and psychometric characterisations of man as a measurement instrument. Journal of Physics: Conference Series, 459, http://iopscience.iop.org/1742-6596/459/1/012057.

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Stenner, A. J., & Fisher, W. P., Jr. (2013). Metrological traceability in the social sciences: A model from reading measurement. Journal of Physics: Conference Series, 459(012025), http://iopscience.iop.org/1742-6596/459/1/012025.

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An Entrepreneurial Investment Model Alternative to Picketty’s Taxation Approach to Eliminating Wealth Disparities

Is taxation the only or the best solution to inequality? The way discussions of wealth disparities inevitably focus on variations in how, whom or what to tax, it is easy to assume there are no viable alternatives to taxation. But if the point is to invest in those with the most potential for making significant gains in productivity, so as to maximize the returns we realize, do we not wrongly constrain the domain of possible solutions when we misconceive an entrepreneurial problem in welfare terms?

Why can’t we require minimum levels of investment in social capital stocks and bonds offered by schools, hospitals, NGOs, etc? In human capital instruments offered by individuals? Why should not we expect those investments to be used to create new value? What supposed law of nature says it is impossible to associate new human, social and environmental value with stable and meaningful prices? And if there is such a law (such as Kenneth Arrow (1963) proposed), how can we break it? Why can’t we reconceive human and social capital stocks and flows in new ways?

There is one very good reason why we cannot now make such requirements, and it is the same reason why liberals (including me) had better become accustomed to accepting the failure of their agenda. That reason is this: social and environmental externalities. Inequality is inevitable only as long as we do not change the ways we deal with externalities. They can no longer be measured and managed in the same ways. They must be put on the books, brought into the models, measured scientifically, and traded in efficient markets. We have to invent accountability and accounting systems that harness the energy of the profit motive for the greater good—that actually grow authentic wealth and not mere money—and we have to do this far more effectively than has ever been done before.

It’s a tall order. But there are resources available to us that have not yet been introduced into the larger conversation. There are options to consider that need close study and creative experimentation. Proceeding toward the twin futilities of premature despair or unrealistic taxation will only set up another round of self-fulfilling prophecies inexorably grinding to yet another unforeseen but fully foretold disaster. Conversations about how to shape the roles, rules and institutions that make markets what they are (Miller and O’Leary, 2007) need to take place for human, social, and natural capital (Fisher and Stenner, 2011b). Indeed, those conversations are already well underway, as can be seen in the prior entries in this blog and in the sources listed below.

Arrow, K. J. (1963). Uncertainty and the welfare economics of medical care. American Economic Review, 53, 941-973.

Fisher, W. P., Jr. (2007). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-1093 [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 (11 pages).

Fisher, W. P., Jr. (2010a, 22 November). Meaningfulness, measurement, value seeking, and the corporate objective function: An introduction to new possibilities. Sausalito, California: LivingCapitalMetrics.com (http://ssrn.com/abstract=1713467).

Fisher, W. P. J. (2010b). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital (http://ssrn.com/abstract=2340674). Bridge to Business Postdoctoral Certification, Freeman School of Business: Tulane University.

Fisher, W. P., Jr. (2010c, June 13-16). Rasch, Maxwell’s method of analogy, and the Chicago tradition. In G. Cooper (Ed.), 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. FUHU Conference Centre, Copenhagen, Denmark: University of Copenhagen School of Business.

Fisher, W. P., Jr. (2011a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), 49-66.

Fisher, W. P., Jr. (2011b, Thursday, September 1). Measurement, metrology and the coordination of sociotechnical networks. In S. Bercea (Ed.), New Education and Training Methods. International Measurement Confederation (IMEKO). Jena, Germany: http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24491/ilm1-2011imeko-017.pdf.

Fisher, W. P., Jr. (2012a). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012b, May/June). What the world needs now: A bold plan for new standards [Third place, 2011 NIST/SES World Standards Day paper competition]. Standards Engineering, 64(3), 1 & 3-5 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr., & Stenner, A. J. (2011a, January). Metrology for the social, behavioral, and economic sciences. http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011b, August 31 to September 2). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium. Jena, Germany: http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf.

Fisher, W. P., Jr., & Stenner, A. J. (2013a). On the potential for improved measurement in the human and social sciences. In Q. Zhang & H. Yang (Eds.), Pacific Rim Objective Measurement Symposium 2012 Conference Proceedings (pp. 1-11). Berlin, Germany: Springer-Verlag.

Fisher, W. P., Jr., & Stenner, A. J. (2013b). Overcoming the invisibility of metrology: A reading measurement network for education and the social sciences. Journal of Physics: Conference Series, 459(012024), http://iopscience.iop.org/1742-6596/459/1/012024.

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), 701-734.