Purchasing Computers – Letter to CT 29th Nov

The Rudd government is about to consider how to put a billion dollars worth of computers on school desks. The preferred method for government purchases is to let a tender for the purchase. In parallel to the tender approach it is suggested that the government set up an open electronic market place specifically and exclusively for schools and allow schools to equip themselves from the special market place. That is the government, establishes an electronic market place where approved vendors can put up the equipment they are able to supply and the conditions under which the supply will be made. The government gives schools the money to spend and the schools can choose the equipment they need. Because the market place is electronic and because it is only for schools the government can monitor sales and see how the money is being spent and can measure the outcomes. Each time a purchase is made the school will specify how many more students have “a computer on their desk”. Potentially usage of the computers can be automatically aggregated and monitored for effectiveness. Such a scheme could be in place within a few months and it will lead to innovative solutions from vendors and innovative suggestions from schools. The scheme will get over the inevitable state/federal squabbles that are always involved when the federal government helps fund state responsibilities.

chpt 4 methodology 121107

A methodology for policy implementation

The antecedents of special currencies;
Optimisation algorithms and economics;
The essentials of trading systems;
Eight steps to spending though trading


In the first three chapters we have looked at the Tragedy of the Commons, or the inherent conflict between self interest and the provision of public goods. We’ve explained the main reasons why current methods to resolve this conflict ultimately fail. We’ve seen how sub-economies can be established to address additional goals besides wealth creation and the essential role that currency plays in such a system. The next step is to consider one of the major requirements of any government or community policy initiative – the collection and expenditure of funds.

This chapter outlines a market based approach using special currencies for collecting, distributing and spending funds to support a given policy initiative. In the coming pages we will look at some examples of the use of special currencies and consider why markets are such an efficient method for allocating expenditures. We will discuss the importance of trust and identity in such a system and how these can be achieved in an online world, before detailing the steps needed for any government or community group to implement their own policy initiatives involving the expenditure of funds.

Special Money for Special Purposes

Within the private sector encouraging and directing consumer behaviour through the use of marketing rewards is now commonplace. The enticements to consumers range from “Frequent Flyer points” to cheaper petrol; from free cups of coffee to preferred seating at concerts and sporting events. They offer an opportunity to earn a future benefit in return for a desired outcome (such as reaching a certain level of expenditure at the one retail outlet). They are structured so that they may only be spent in designated ways that encourage loyalty or repeat business, further benefiting the sponsoring company. Given their effectiveness and popularity with consumers, such programs have become ubiquitous in many markets.

Such incentives are often used for promotional purposes instead of discounts because the money provided can be directed to expenditure that continues to benefit the giver. That is, these marketing rewards provide a mechanism to direct expenditure. They are in fact a special currency invented to achieve the goal set by the organisation giving the incentive.

Marketing reward programs are an example of the use of a special currency as a way of directing and controlling expenditure. The approach can be used by any organisation for many different purposes. These programs work because they identify a way to direct expenditure to meet an existing need. One important problem they can solve is to optimise the allocation of community resources to achieve a policy objective. People have become suspicious of the barrage of promises made by governments about how they are going to spend taxes to achieve outcomes. It is not that the population does not want money spent on education, health or other social goods. The problem is that they know from past experience that the expenditure of tax funds will almost certainly be inefficient and will often be directed to the purpose of re-electing governments.

The reason that governments have trouble allocating resources efficiently is that they try to do it through “command and control” or regulatory techniques rather than market systems. Market systems are ones where there are many buyers choosing from many suppliers, all competing to obtain the best deal. The element of competition helps to foster efficiencies while choice encourages innovation, resulting in an efficient allocation of resources.

Trading markets optimise wealth as measured by the total amount of goods. That is, in the terminology of economic rationalists, markets produce the most wealth and hence must be the best system. Systems can use markets to allocate resources. And, as discussed last chapter, by inventing special currencies it becomes possible to include factors other than the production of wealth in the reasons for allocations.

When governments intervene and politicians make promises they are invariably trying to satisfy these other societal aspirations – and not just increase wealth. The difficulty is that the allocation of money can be haphazard, often only occurring at times when the government is looking for a boost in the polls. Moreover, it is the apportionment of funds rather than the actual expenditure that becomes the focus, with little thought going to measuring the success or otherwise of the intervention.

To give some examples:

  • we want to generate electricity but we also want to minimise the production of greenhouse gases;
  • we want to have cheap water supplies and we want to minimise the number of days we have water restrictions,
  • we want to allow people to buy any house they can afford but we still want to keep housing affordable for new entrants to the housing market,
  • we want to give everyone equal access to a minimum standard of education and health services but still allow people to buy more if they wish.


Systems based on special currencies offer a way to achieve these kinds of multiple objectives. We do this by building efficient trading systems where the trading system allocates the resources and where the money used has characteristics that enable not only wealth to be optimised but also enable other objectives to be built into the system. By creating special purpose currencies, it becomes possible to put constraints on how the money is spent. For a health system, for example, the money must be spent on health. For greenhouse gas reduction systems we can stipulate that the money is spent on ways to reduce greenhouse gases.

Optimisation Algorithms and Economics

Optimisation algorithms were invented to solve hard problems. Spending money in an optimum way is a hard problem.

A problem is hard if an algorithm for solving it can be translated into one for solving any other NP-problem (nondeterministic polynomial time problem). NP-hard therefore means “at least as hard as any NP-problem”, although it might, in fact, be harder. An example of an NP-hard problem is identifying the shortest path for a salesperson who has to travel to N cities. Another example is finding the factors of a number.

In the real world a problem that is greater than NP-hard is running an economy to satisfice conflicting goals of all members of society – where satisficing means to find an adequate solution rather than an optimal solution to a problem with multiple goals.

There are many well known algorithmic techniques for attempting to satisfice problems. Some example techniques from Wikipedia are

  • Genetic Algorithms (GA) maintain a pool of solutions rather than just one. The process of finding superior solutions mimics that of evolution, with mutations and combinations altering the total pool of solutions, and those of inferior quality eventually being discarded.
  • Simulated Annealing (SA) is a related global optimisation technique which traverses the search space by generating neighbouring solutions of the current solution. A superior neighbour is always accepted. An inferior neighbour is accepted probabilistically based on the difference in quality and a temperature parameter. The temperature parameter is modified as the algorithm progresses to alter the nature of the search.
  • Tabu search (TS) is similar to Simulated Annealing, in that both traverse the solution space by testing mutations of an individual solution. While simulated annealing generates only one mutated solution, tabu search generates many mutated solutions and moves to the solution with the lowest fitness of those generated. In order to prevent cycling and encourage greater movement through the solution space, a tabu list is maintained of partial or complete solutions. It is forbidden to move to a solution that contains elements of the tabu list, which is updated as the solution traverses the solution space.
  • Harmony search (HS) is an algorithm based on the analogy between music improvisation and optimisation. Each musician (variable) together seeks better harmonies (vectors).
  • The ant colony optimisation algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. They are inspired by the behaviour of ants in finding paths from the colony to food.


One of the common characteristics of all these algorithms is that they involve a large number of “agents” making small independent decisions that change an existing solution and that move the solution towards a better result. That is, we start with a base solution and make adjustments through a series of small decisions, each of which further evolves the solution. These decisions may (or may) not overlap in time and in their results with other decisions. The algorithms have what are called “objective functions” whose calculations tell how well the solution fits the problem.

Over the years Kevin Cox, one of this book’s authors, has used this approach to solve many problems including;

  • a University timetable problem,
  • scheduling of production lines to make bottles in a glass factory,
  • scheduling truck loads and deliveries,
  • assigning markers to students,
  • generating crossword puzzles,
  • finding the “best” results for a free text search


In the natural world evolution and natural selection fit this optimisation paradigm. Darwin’s “survival of the fittest” becomes the algorithmic rules for a system with survival of a species as its objective function. Each individual agent acts in its best interest in terms of surviving with the overall implicit objective of the survival of the species. (Although sometimes this does not work when a predator species is too efficient and destroys all its source of food.)

Economic systems also fit the paradigm. These can be thought of as many agents trading with each other. The rules of the trade, as explained in chapter two, are that each side of a trade is satisfied with the value each obtains from the trade and that the trades are seen as fair. Trading systems have resulted in an amazing increase in the wealth and living standards of much of humankind and are good systems for wealth creation. The optimisation function for economic rationalists is for each individual to maximise their own wealth. Unfortunately each individual trying to maximise their own wealth leads to the “tragedy of the commons” and so societies attempt to modify economic systems through regulations and restrictions outside trading. These regulations and restrictions are rarely economically efficient in the narrow sense of immediate wealth increases for individuals and lead to continual calls for their reform. The standard mechanism for reform is to create more regulations and restrictions which only compound the problems.

As a species we have devised trading as a way to increase wealth. This works remarkably well but as a species we understand that the simple unfettered increase in individual wealth measured by the consumption of resources may lead to our extinction. (Think of the too-efficient predator species that’s just eaten its last prey).

Solutions to this problem where we try to impose restrictions outside trading systems are not working well. The approach recommended in this book is to change the optimisation algorithm implicit in trading systems to allow the incorporation of other goals through the imposition of constraints. That is, trading systems learn how to adapt and change to meet new circumstances while still maximizing wealth. We are more likely to succeed in meeting multiple goals if we can adapt trading schemes to work towards multiple goals via constraints embedded in the trading system rather than restrict the operation of trading schemes through rules and regulations external to the trading system.

Trust and Identity

An important component in any trading system is trust in dealings with other parties. For special currency systems to work as efficient trading systems the participants must also have faith in the integrity of the system. To that end currencies should be backed by regular currencies, held in special bank accounts. This ensures that if it is ever necessary to redeem the special currency, participants can readily exchange their currency for regular dollars.

Special currency systems are always voluntary. That is participants do not have to join the system. This means that when people join they agree to abide by the rules of trading and the rules established for the currency involved. Compliance with rules is enforced by removing people from the system if they continue to violate the system.

For efficiency reasons currency systems are electronic. This enables a broader geographic coverage for the system, ensures immediacy of reporting of trades, provides an audit trail of trading activity that allows assessment of the effectiveness of a scheme, and encourages participants by tapping into the online economy. However, it also means for special currency systems to work there have to be good electronic means of proving identity and trustworthiness.

Eight steps to designing a program

Devising a special currency system is no different to constructing any other kind of information system that enables people to solve a particular problem. It’s just that in this instance we want to build an information system to solve the problem of water restrictions or reducing greenhouse gases or affordable housing. Each of these problems needs an information system to support the solution that happens to fall into domain of knowledge called economics.

The starting point is to recognise that it is not necessary to know the solution to the problem before beginning. Like the optimisation algorithms mentioned earlier, we just need to start with any solution (the existing system) and build an information (economics) system that will adapt itself and “find” a good solution to the problem.

It’s a process involving a series of steps and is perhaps best illustrated by thinking of it as a problem comparable to creating a crossword puzzle. The first step is to define the grid and give the purpose of the crossword (thematic, fun, cryptic, etc). The second step is to find the words while the third step is to create the clues. Each crossword is unique. We do not know what the solution is going to be before we start and we do not know which bits will be done first. All we can be certain of is that we have a method of getting there and that we’ll know when we have achieved what we want.

With most economics systems we;

  • define the problem to be solved and specify the objective function of maximizing wealth to measure success;
  • draw the boundary to the problem by creating special money and stipulating the use of that money – the constraints,
  • work out how money gets into the system
  • work out how money gets out of the system.


With special currencies we have modified these steps to make our economic systems adaptive. No matter what kind of policy initiative is to be funded and no matter what objectives and constraints are imposed, the following eight steps will lead to an economic system capable of uncovering the optimal solution or least cost solution.

The eight steps are:

  1. Define the desired outcome as a measurable policy statement. This typically involves supply of a Public Good such as public health or availability of education. Examples already mentioned include decreasing the output of greenhouse gases; improved allocation of public health dollars; or achieving a sustainable level of water use.
  2. Apply other constraints via measures that will allow you to know how the system is performaing such as a specified reduction in carbon emissions; a reduction in hospital waiting lists; or measuring the quantity of water used per day in a catchment.
  3. Determine the consumer behaviours that will help achieve the outcome. These will be actions that need to be encouraged or altered to achieve the desired outcome and might include cycling to work and car pooling, or reducing the amount of water used for a garden.
  4. In some cases devise a Reward that encourages these behaviours, such as a limited currency that can only be spent on public transport, water efficiencies, or health care. Rewards should appeal as a mechanism for the transfer of funds between consumers rather appear as a punitive tax. The rules and information associated with this currency create a preferable alternative to cash because they offer a way of directing funds towards the desired outcome.
  5. Enlist participants but keep it voluntary! As previously explained punitive or regulatory systems rarely enjoy widespread public cooperation and tend to result in creative measures to avoid the regulations. Rewards currencies are designed to encourage those people helping to solve the problem. It provides the extra incentive for early adopters to “do the right thing” – a step they may very likely have wanted to take in the past, but which may have proven too difficult or costly. As more people join the scheme, the public and private benefits become more obvious and the currency becomes more widespread, further encouraging enrolments and creating an ever-widening market for innovations and solutions to the defined problem.
  6. If possible fund the currency creation through the consumption of a related good. One way is to increase the base charge to all consumers for a good (such as water), but to then offer Rewards as a form of rebate to those participants limiting their use to a predetermined, sustainable quantity.
  7. Specify capital projects or items in which money may be invested. These projects and items should appeal to currency holders by helping them to achieve their objectives. For water sustainability this could mean money being spent on water efficiency devices within the home, or investment in capital projects that save or recycle water.
  8. Measure the outcomes and tune parameters to achieve the objective. This requires that the measures are constantly monitored and the rules of the system tweaked until the required results are obtained. It may involve raising the base charge for a good – which will result in lowering demand and a greater conversion of money into the special currency, enabling reinvestment in the technologies and projects that will help to alleviate the problem and satisify the constraints. If the constraints are regularly being met or exceeded, new levels of measures may be set and the rules relaxed or tightened accordingly.

Budgets as a variation


Any organisation that has a budget has the elements of a special currency system. Budgets are allocations of funds to achieve a particular purpose. The implied objective function for the allocation of funds to a particular purpose is to spend the money in the most efficient way. The buyers are the people authorised to purchase from the budget and the sellers are suppliers of the budget items. The amount of currency is defined by the budget account. Money is restricted to the goods and services required to achieve the budget function.

Implementing budget expenditures through Rewards becomes economic when there are a large number of buyers and when there is a large amount of money to be spent.

Affordable Housing

History has shown that the house market has a tendency to cycle between boom and bust. In boom times the value of a house is greater than that justified by the rent the house can obtain. That is the asset class of housing becomes inflated when compared to other assets and with respect to debt. When the boom eventually makes housing unaffordable, it is followed by a period of stagnation and the resulting correction is often a recession or even a depression.

Steve Keen at http://www.debtdeflation.com/blogs/?p=41 gives an explanation of this general phenomena phenomenon in his paper “Developing a monetary model of financial instability”.

The inflation in house prices is mainly caused by inflation in the price of land more than inflation in the cost of building a new house. Addressing the problem of land price inflation will make houses affordable.

The following outlines a system to reduce the impact of the inevitable deflation of Australian residential properties by putting some new houses with “reasonable” prices on the market in such a way that the prices will remain “reasonable” and without deflating the prices of existing houses.

The Australian Housing Market – 1996-2003

The average price of houses throughout Australia doubled in the seven years from 1996 to 2003, even though it was a period of low inflation. The valuation put on houses in this period went up at a compound rate of 10% compared to general inflation of 2 to 3%. While the reasons are many, there is a strong argument that the main underlying cause was lenders encouraging borrowers to purchase existing houses. Why did lenders wish to provide money to people to buy existing houses? It was because the money that people lend is not tied to the underlying value of the houses, but to the ability of the borrower to repay. In other words, the lenders were able to generate loans that had to repaid – not with houses but with other assets and most notably, the future income of borrowers. Lenders are able to isolate themselves from the risk of house prices falling.

Such an increase in the availability of funds for housing will result in an increase to the price of existing homes, because many homeowners are able to “upgrade”. This in turn raises market expectations, whereby land owners can increase the price of new land and so increase the price of new houses, which in turn means that they become too expensive for new entrants to the housing market. This causes a slump in new houses which now feeds into the equation with prices starting to increase because of lack of supply. The end result is unaffordable housing.

The relative value of houses in relation to other assets has become distorted and to “solve” the problem the relative value has to be restored. Traditionally this adjustment comes through a combination of the period of stagnation in house prices plus inflation which restores the relative value of house assets to other assets. The simplest way to restore value is to release new land at low prices. This would make new houses cheaper, demand would reduce and prices would adjust. Unfortunately this does not happen for two reasons. The first is that it would be political suicide for any government to set out to reduce the price of existing houses. The majority of the population own their homes and many have paid of their house debt. They now count the nominal (inflated) value of their land as part of their wealth. The second reason – particularly in the ACT – is that governments of all persuasion are addicted to revenue from the profit of the sale of new land.

Inflated values make it worthwhile for people to turn house assets into other assets, but because people have to continue to live somewhere it only benefits those who do not have to purchase or rent another house, or those who can “downsize”. Thus there is an effective transfer in wealth to those who own houses from those who will pay from their future wages for their housing needs. In a global economy this means the main beneficiary of the Australian housing bubble are the overseas investors in Australian debt.

Other beneficiaries of rising house prices are the owners of under-utilised land and, as alluded to earlier, the governments that benefit from charges and taxes on change of land use for new dwellings. Most home owners do not benefit because they rarely have “under-utilised” land and they always need a place to live.

Another way to bring all house prices down is to reduce the price of changing land use as occurs when we change “greenfields” to housing, or land from single dwelling to multiple dwelling usage. These changes are under the control of governments through their planning agencies. However for it to be politically acceptable, the price reduction would have to be introduced in a way that ensured existing house prices would not collapse.

A solution to the problem for the ACT and later Australia

The ACT government could release a percentage of new land at the price of development. When houses that have been built on this land are sold, they must be sold for what we can call “house dollars”. House dollars are special in that they can only be used to purchase services and goods that are used to build new dwellings in the ACT. That is, the money raised from the sale of a house on cheap land has to be used to build a new dwelling in the ACT. Thus anyone buying a house on cheap land will know that they will receive house dollars when it becomes time to sell. The requirement to sell for house dollars would remain in place for the lifetime of the dwelling. This means that the price of houses built on cheap land will continue to remain close to the price of building a new house anywhere else.

This will ensure a supply of houses in the ACT that will remain affordable and that are divorced from land price inflation. Instead their value will be tied to the cost of goods and services to build houses.

House dollars are created by depositing unrestricted dollars into a backing account. House dollars can be sold for unrestricted dollars for whatever the market will bring but house dollars can be converted to unrestricted dollars when the dollars are spent on materials and services to build a new house.

The system will be simple to introduce – because house sales are already well recorded. It will be easy to police because suppliers who provide goods and services will be expelled from the system (and from a ready market) if they accept house dollars for reasons other than materials and services used in building a new house.

People who genuinely wish to trade houses are not disadvantaged as they can use their house dollars to pay to build a new house, or they can buy another house that is also subject to the house dollars restriction. If they have no use for house dollars they can sell them to someone who wishes to build a new house.

The impact of the system will depend on how much cheap land is released. One of the advantages is that the scheme is not just restricted to low cost housing but can be spread across all block sizes and does not create pockets of low cost housing.

It is expected that the system will rapidly adjust so that the exchange rate between house dollars and unrestricted dollars will reflect the extent that land prices are inflated. Over time as land inflation drops the exchange difference between house dollars and unrestricted dollars will become near zero in which case the government can stop releasing land at low prices. That is the government will now have a strategy for controlling land inflation. As well as providing a stock of affordable housing across all income groups, and ensuring a supply of money for new dwellings, it will mean that prices of housing in the ACT will tend to be lower than prices of houses in other jurisdictions that do not have similar schemes.
The scheme could be started within weeks as the government could sell a proportion of new land releases – some of its existing house public housing stock and some community land released from school closures – with the same conditions. It could approach the Federal Government to fund the difference in the land costs that it loses because, if it works as expected, it has the potential to bring affordable housing to the whole of Australia.

In summary the ACT government could put in place in a matter of weeks a simple scheme to create affordable housing with no immediate impact on the price of existing houses.