planometrics, planning, and the interface with market determining conditions
One of the unsolved problems that plagued Soviet-style planometric theoreticians, today, in somewhat modified form, continues to confront urban and regional planners: at the implementation stage, how do guidelines and prescriptions developed by urban planners interface with action-directives receiving their impetus from market forces? Often, the two conflict. The self-organizing market dynamic has no inherent mechanism through which to respond to urban planning initiatives, while the planning process and its implementation devices are sufficiently cumbersome as to prevent timely response to the effects of rapidly changing real-time market processes. Market forces and on-the-ground political realities often leave the city or regional plan behind.

But, not only is there a correspondence between problematics of economic planometrics and urban planning methodologies, certain unresolved dilemmas in economic theory also relate to factors similar to those underlying these very problematics. In Soviet-style planometrics, a linear equation set is employed and the emphasis is on input-output analysis. Planning prescriptions and regulatory controls are used in an attempt to impose linearity on non-linear processes. A linear process is equal to the sum of its parts, and thus may be fragmented for study without significant modification. In a non-linear process, however, the whole is greater than the sum of its parts; fragmentation, thus, introduces consequential distortions. Incorporated into capitalist econometric models, on the other hand, is an attempt to deal with stochastic processes; the sets of econometric behavior equations try to explicitly incorporate random variations which go unexplained. One could accurately say that the submerged non-linearity in Soviet-style planometrics relates to the same underlying factors treated as stochastic in capitalist econometrics.

non-linearity, stochastic instability, and extrasystemic factors
Soviet planometrics attempted to deal with these factors by using optimality criteria. It was a hotly debated issue. Traditionalists said there can be only one such criterion, derived from use-value theory; others wanted different criteria for various subsystems. The latter chose criteria more subjective in nature and thereby attempted more directly to deal with random variables unacknowledged by the traditionalists. In either case, the preference functions chosen selected the optimum solution from the nsolution-curves associated with the differential equation set constituting the model. Capitalist econometric theory begins with knowledge of the prevailing circumstance (the “initial conditions”) and quantitative laws (the “behavior equations”) based upon the principle of maximization (“economic growth”). With these, econometricians predict the future state of the economy. But as mixed-economy capitalism proliferated and complexified, behavioral instabilities of every sort multiplied necessitating increasing recourse to stochastic methods. Both planometrics and econometrics have tried unsuccessfully, each in its own way, to deal with non-equilibrium states resulting from extrasystemic influences. Superimposition of extrasystemic upon intrasystemic factors is the underlying condition which planometrics struggled with as a submerged non-linearity and econometrics treats as stochastic instability.

As this problem still exists in the era subsequent to collapse of the Soviet Union, a new approach is warranted. Is it possible 1) to identify and parameterize extrasystemic factors driving non-linearity and stochastic instability; (2) to interface the information carried by these factors -- via some device -- with the market micro-environment in such a way as to promote coherent modal macro-behavior? If so -- given the parallels with urban and regional planning -- not only will a method have been found to enhance economic stability, but a paradigm will have emerged which shows how urban and regional planning guidelines can effectively be interfaced with action-directives emanating from market forces. In other words, the need for government regulatory activity will have been greatly reduced.

preference functions, alternative indicators, and feedback into the market
micro-environment
The above-stated question gives rise to an approach similar to that taken by economist Adolph Lowe [On Economic Knowledge, M.E. Sharp, 1977] in developing his method of “instrumental inference” or analysis -- only our intention is not, like his, to fine-tune government regulatory activity, but to take the additional information gained about total system function (that non-linear and stochastic “more than the sum of its parts”) and feed it back into the market determining conditions, such that it increases subtlety of incentives and sanctions predisposing implementation of market action-directives by influencing modal micro-goals of economic actors. The primary innovation of Lowe’s instrumental inference was to add a parameter to the econometrician’s tool box. Not only would there be initial conditions and behavior equations, but also a “desired terminal position” or macro-goal. The job of economic analysis, for Lowe, thus centered upon identifying “goal-adequate” patterns of change and methods to insure these transpire. Economic analysis, in Lowe’s conception, thereby becomes a form of planning. Our question, by contrast, is : Can planning become a form of coherent free market behavior?

The preference functions linked to planometric optimality criteria are in many respects similar to “alternative economic indicators”. These indicators have in large part been conceived to influence government regulatory activities and tax-structure legislation -- so as to induce “goal-adequate” patterns of change. They also can be formulated as measures -- retrospective or real-time -- used to inform the urban and regional planning process, and to assess its implementation effectiveness. Alternative economic indicators frequently relate more directly to extrasystemic factors (“externalities”, that is) than did planometric preference functions and optimality criteria -- though it must be realized that the precise meaning of the word “extrasystemic” is in large part relative to the scale-of-partitioning point of view chosen in the subsystem-system-supersystem hierarchy. “Extrasystemic” from the perspective of a given partitioning is “intersystemic” from the perspective of a larger-scale partitioning network, and “intrasystemic” from yet a larger scale perspective. What we hypothesize, then, is that these alternative indicators can be parameterized so as to produce concealed non-linear or stochastic intersystemic information for feedback into the market micro-environment. This feedback will involve a modification of the exchange unit used for commercial transactions.

multivalued functions and their exchange units
Systems exhibiting relatively simple non-linearities can be described with deterministic equation sets involving secondary and tertiary time-differentiated variables (i.e., processes that change over time not only with constant velocities, but also with accelerations and time-rates-of-change of acceleration). But a threshold of complexity is reached where the descriptive equation sets are no longer solvable. The erratic behavior of such systems is then characterized as stochastic instability. However, in both cases -- non-linear deterministic and stochastic -- the variables involved in the mathematical description are single-valued (for a given value of x, there is a unique single corresponding value for y: which is to say that y is a single-valued function of x). Another approach to mathematical description of such systems is with equations using multivalued variables (for a given value of x, there are many corresponding values for y: which is to say that y is a multivalued function of x).

Money in motion pulls activity after itself; it organizes allocation of resources. When money stands still, economic organization deteriorates. Money moves through markets at various velocities, and this movement can accelerate and decelerate. When accelerations become part of the movement, unstable market behaviors emerge: non-linear or stochastic. Money, as an exchange unit, when in motion, is an economic variable. Exchange units as currently conceived and implemented carry only single-valued information, thus, in part, concealing factors giving rise to non-linearity and stochastic instability. With the advent of electronic exchange, however, exchange units could carry multivalued information. Each value stacked on the exchange-unit base could be tied to a parameterized alternative economic indicator such that the unit’s purchasing power and wage-rate value fluctuates according to variations of the given indicator. In this fashion, not only scale-related extrasystemic factors like health parameters dependent upon environmental quality, but full-blown scale-independent externalities like sociological variables could conceivably be fed back into the market micro-environment to subtly modulate action-directives -- thus minimizing the need for governmental regulatory activities. Moreover, indicators used as measures guiding urban and regional planning implementation could similarly be parameterized, tied to values on the exchange-unit stack, and thus become market-mediated feedback mechanisms.

amenity migration studies and the shift to multivalued exchange
Complexities involved in shifting to a multivalued exchange unit would be enormous, if instituted from the top down. From the bottom up, however, the shift could take place locally and by stages. A local currency (like the “Ithaca dollars” of Ithaca, New York, and the dozen or so other local currencies recently created in LETS [Local Exchange Trading System] locations) would be the first step. The effect of stacking values on a local currency-base would be localized; such effects would not bleed into surrounding communities so long as the currency was not accepted outside its originating locale. And if “amenity migration sites” (places people migrate to because of the amenities they offer, e.g. Santa Fe, Chiang Mai, Bangalore, Bagio, Cesky Krumlov, et cetera) were chosen as initiating cases, simplified models of the complexity later to be encountered in mega-urban regions would be available for study and trial-and-error implementation. Amenity migration sites, by their very defining characteristics, have economies deeply involved with extrasystemic driving forces, and associated planning problematics focused upon the need to modulate dynamic effects of these forces. Much simulation analysis, modeling, and public education would be required, however, before even local activation of a multivalued exchange unit could be attempted. This would minimally include: (1) discovery of the mathematical techniques required to parameterize the alternative indicators-measures such that they could effectively be tied to the multiple values of an exchange-unit stack; (2) adaptation and testing of existing electronic exchange technologies (hardware, software, smartcards) for processing multivalued-exchange-unit transactions and associated banking procedures; (3) creation of the required pricing and wage-value algorithms; and (4) development of interactive instructional tools (CD-ROMs) for public education concerning the procedures required for shift to a multivalued exchange unit, and how that shift would enhance community efforts to self-organize local goal-adequate patterns of change.

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