Wednesday, October 3, 2012

AI Bureaucracy

As a thought experiment, let us pretend that we are running a society via an AI bureaucracy.  The objective is to meet everyone's material and non-material demands as best as possible via the most efficient arrangement of labour through "soft" policies (ie. not forcing anyone to do anything but carefully arranging society to meet changing demands).  There is no money, only productivity rates to provide the goods needed.

Just pretend we're developing an AI for a game that has a running economy in it.  It wants to have a set of rules of how to arrange its people into various roles to provide a good challenge for a player.  It's not going to run "naturally" (ie. market like), it will run its society in a carefully managed economy.

We'll step through the thought scenario through an iterative process, making it more and more complex as we go along but start off with a solid and at least theoretically possible base.  This experiment makes a few immediate assumptions:

The AI is self-improving, so any errors that exist will slowly be corrected over time.
The AI bureaucracy is not corrupt, it simply runs its publicly available algorithm to provide for everyone and all information is available (like StatCan, SCB or Bureau of Labor Statistics).
The government costs zero dollars to redistribute goods
There is no crime or other factors affecting the economy

We'll strike down some of these assumptions as we go along, but for now, let's just start with a working example.  We can use this model later and compare against some real world economic arrangements and see how well they are doing to what we'll eventually develop as our "optimal" situation (for instance, comparing against different free market economies and mixed socialist-market economies)

We'll try to keep adding to this model until we can make it possible to conduct comparisons between different styles of arrangement and have this model look at how the market arrangement compares with the "optimal" arrangement.

In all the discussion, the idea is to spend as little as possible on "necessities" of life (things that without which you die), then spend as much as possible on luxuries.

The Simple Model


Okay, so let's say we have an incredibly simple economy with all workers equal in skill and completely interchangeable.

This is the output of each worker if they spent their entire time in that industry for a "cycle".

Farmer: 10 Food
Clay Digger: 100 Clay
Potter: 10 Pots, -20 Clay

We'll say that each person needs to eat 1 food.  That is, over indulgence in food doesn't matter right now.  Then we spend the rest as efficiently into luxuries as possible (because there are no other things to spend on).  Each unit of food requires 1/10 of a person's labour per cycle.  Each pot requires 1/10 person-labour to make the pot and 2/100 to get the clay for the pot.

Each Person
Food: 1 Food -> 10%
Pots: 90% -> 7.5 Pots

Industry labour arrangement:
Food: 10%
Clay Digger: 15%
Potter: 75%

Education

Everyone is paid 1 food, 7.5 pots regardless of profession and everyone works at the same level of productivity.  As everyone is putting forth exactly the same effort at exactly the same skill level and are completely interchangeable (a potter making 10 pots a day could instead make 10 food, thus if both create food or pots at that rate, then they are effectively the same), this is also "fair".  Let's make this scenario more complicated.  Let's add education requirements for each profession to add a cost to get a person able to do that job.

Farmer (10 Education): 10 Food
Clay Digger (20 Education): 100 Clay
Potter (40 Education): 10 Pots, -20 Clay

People being educated eat food but produce nothing.  We'll say that the conversion rate is 1 food = 1 education (that is, a person learning eats extra food, we could model this differently with teachers but we'll keep it simple for now).  So in essence, a farmer takes 10 food to train, a clay digger 20 food and so on.  This wouldn't change our calculations unless people died of old age (because whatever education costs exist, if people lived forever, any fixed cost would tend toward being negligible in any formula).  So let's say everyone lives for 100 cycles.

Life time production
Farmer: 10 Food * (100 - 10) - 10 Food = 890 Food
Clay Digger: 100 Clay * (100 - 20) - 20 Food = 8000 Clay, -20 Food
Potter: 10 Pots * (100-40) - 40 Food = 600 Pots, -40 Food, -1200 Clay

The calculation has obviously become immediately more complex but let's "average" out life time production over 100 cycles.  Now each pot costs 16.67% of potter time plus 2.5% of digger time.  Therefore, 19.17% combined total of a person-cycle.

Each Person:
Food: 1 Food -> ~11.24%
Pots: ~88.76% -> 4.63 Pots

We've adjusted production rates for education requirements, people are as productive as any other person, so long as they have the education spent and nobody switches industry (and thus no labour retraining costs need to be calculated).  Is this fair?  Well a pot's cost under this system took into account the education requirements and averaged out the decreased output due to the education needs, while also feeding the person while being educated.

But hey, we haven't calculated the cost of the food for education did we?  (Note that at this point, percentages might not add up due to rounding errors).  The brackets indicate if we split one person into a combo of a farmer/digger/potter, do the numbers add up properly?

Industry Arrangement (accounting for time lost due to education)
Food: 11.24% (1.00 food)
Clay: 11.58% (9.26 clay)
Pots: 77.17% (4.63 pots)

Due to the higher difficulty in getting pots and food, we've had to cut down on clay production and we end up with less things overall (which is expected).  But now, we have to consider a more difficult issue where industries require food for education, therefore we'll have to reduce and shift more production to food. 

Let's try to simplify this problem.  If we need 1 pot, we use up 1/600 of the lifetime of a potter.  That is equal to 1 pot, 2 clay and 0.067 food.  So, for every 1 pot made, you are also actually demanding some quantity of food.  Essentially, we've demanded 1/600 of the time of a potter, 2/8000 of a digger and 0.067/890 of a farmer.  Combined person-cycle time per pot is then 19.92%.  Cost has gone up, which passes a sanity test at least.  Let's keep it simple and do this:

Industry Arrangement
Food: ~11.24% -> 1 Food
Pots: ~88.76% -> 4.46 pots (0.29 food)

There's a slight decrease in pot production, which has become an increase in food production.  So the actual industrial arrangement after all that is:

Industry Arrangement
Food: 14.49% (1.29 food)
Digger: 11.15% (8.92 clay)
Potter: 74.33% (4.46 pots)

In the current model, education has its cost in food.  In essence it is stating that somehow education costs food.  We could also model this as "using" someone else's time (ie. using a teacher's time) for classroom or apprentice style education.  In this sense the cost is the opportunity cost of the person not producing anything else.  That is, say if one could have produced 10 food, instead they produce 10 education.  This would model the education costs better.  In the case of having education cost a single food, then we are saying one unit of education is equal to the time that could have been used to produce one unit of food and we've already reduced the output of the student to reflect the time they spend learning.

It would be easier to show education teaching/learning efficiency changes if we explicitly measured the amount of labour going into education and performing lifetime output calculations of average workers in each industry.  For example:

Food: 10%
Education: 10%
Luxuries: 80%

But we have to be careful with lifetime production output calculations.  The longer people need to study the less their lifetime outputs but the faster they can consume education points, the more output they can create even if education costs don't change (meaning that output increases with the same amount of labour put toward it).

For example, let's say people learn slowly:

Food: 10%
Education: 10%
Luxuries: 80% (produces 5000 pots)

Then there was some improvement in their ability to consume education:

Food: 10%
Education: 10%
Luxuries: 80% (produces 6000 pots)

There was an increase in production rates with no difference in labour applied.  All incomes go up as a result of the increased output.

Government


Well that was complicated.  But are we done?  No, there's plenty more complexity we can add!

If we add in administrative cost, it is similar to education cost.  Each good produced incurs some kind of administrative cost (for redistribution, transportation and accounting) and thus shifts an ever greater amount of production toward food production (to pay for the people who do administrative work). 

How might we capture this cost?  Let's create a table of distribution costs:

Food: 1 food per 100 food (Very easy to move around and you can be rough with it)
Clay: 1 food per 50 clay (Weighs more than food, costs more to transport)
Pot: 1 food per 10 pots (Have to be careful with the pots, transport costs are high)

We can see this as a sort of "tax" much like education was a general "tax" on production rates.  We'll have to start keeping more decimal places for this.  Well now, each pot costs 1/600 of a potter, 2/8000 of a digger, 0.067/890 of a farmer and it also costs 1/10 food for pot administration and 2/50 food for clay administration.  Oh but it's more confusing than that!  See, every unit of food incurs more food cost, which in turn incurs more food cost.

No, it doesn't go into infinity (otherwise our real world would be quite broken now wouldn't it?).  It's a infinite geometric series calculation.  Luckily, brilliant mathematicians have elegantly solved this issue centuries ago.  Let's see what that means for our model.

Essentially each unit of food incurs a 1% cost, which in turn incurs a 1% cost in food.  So it is a geometric series in the form of 1 + 1/100 + 1/10000... (the formula for the sum of such a series is 1 / (1 - r), and in this case r = 1/100) and the end result is that for each 1 food, the cost is really 1.01010101 food.  The joys of keeping decimal places...

Okay, so a pot is what now?  It is 1/600 of a potter, 2/8000 of a digger, 0.067/890 * 1.01010101 of a farmer plus 1/10 food (1/10 * 1/890 * 1.01010101 of a farmer's time) for pot administration and 2/50 food (2/50 * 1/890 * 1.01010101 of a farmer's time) clay administration.

So in percentages, each pot takes up, 16.67% person-cycle of a potter, 2.5% of a digger, 0.75662997% for potter education, 1.134944955% for pot administration, 0.453977982% for clay administration.  Or 21.512219574% in total.  Actually, we forgot about the clay digger's education.  Each unit of clay can be said to have cost 0.0025 food in education (20/8000), which means with administrative costs, it is 0.002525253 food.  So let's slap that onto the cost of pottery, it's another 2 clay * 0.002525253 food, which is 0.056747248% of a farmer's time per cycle.  Total time per pot is 21.568966822% of a person-cycle.

Industry Arrangement
Food: 11.24% for 1 food => 11.34945% for 1.01010101 food
Pots: 88.65055% (21.568966822% per pot, 4.110097193 pots)

Food:  11.34945%
Clay: 10.275242983%
Pot: 68.5016199%
Clay Education: 0.233236705%
Potter Education: 3.109822716%
Clay Administration: 1.86589363%
Pottery Administration: 4.664734074%

We can think of it like this
Food:  11.34945%
Clay: 10.275242983%
Pot: 68.5016199%
Government: 9.873687125%

Actually some of that food production is administration/education.  You could probably say it is more like:

Food: 10%
Clay: 10.275242983%
Pot: 68.5016199%
Government: 11.223137125%

We can say other things like, "for every 100 people we need so much infrastructure, police, military, fire protection and so on".  Some of it is industry agnostic, thus we simply take a percentage of industry away beforehand, like food, before dumping the rest into luxuries.  Others are industry specific and "tax-like", such as education, where we roll it into the production cost of a product (such as pottery) and then pull the number out after calculation (otherwise it's very hard to calculate anything).

For instance, we may say, we need "police services" and each person assigned policing duties can produce "100 policing", and each person consumes "1 policing" per cycle.  Then the percentage labour division becomes:

Food: 10%
Policing: 1%
Luxuries: 89%

But there are a large number of things to spend on.  So it could become rather complex...

Food: 10% + education costs + administrative costs
Policing: 1% + education costs + administrative costs
Military: 10% + education costs + administrative costs
General Infrastructure: 10% + education costs + administrative costs
Luxuries: 69% - previous education/administrative costs - more education/administrative costs

On the topic of bureaucracy, they can basically be seen as individuals who produce nothing and simply eat food and take a same-share of income.  That is, they are like people who have 0% productivity yet still take a full income and therefore cause a welfare-tax on productivity equal to a single person-cycle per bureaucrat.  However, that is not to say they are not necessary but that it is easier to model them mathematical as such.  It is fun to look at it this way but perhaps actually somewhat inaccurate.

Alternatively, we can view their output as "administration" and a certain amount of "administration" is required to redistribute goods and run projects.  Then we can adjust their income in the same way as other workers.  If they are not good administrators, they are paid less, if they are excellent administrators they are paid more.  This would be a more accurate and fair reflection of the administration industry (ie. government).

For example:

Bureaucrat: Requires 40 education, produces 100 administration per cycle, average life span of 100 cycles

Therefore...

Bureaucrat: 6000 administration, -40 education

And so, a bureaucrat who produces at 150% per cycle (Which means that after education is finished, they produce at a rate of 150 administration per cycle... or 60 administration on average per cycle across their lifetime) would receive 150% income.

It is difficult to escape the needs of administration.  A large number of projects that necessarily require resources to be pooled will inherently incur some administrative cost.  For instance, single individuals cannot build a road network but a large society can afford to do so.  In order to pool the necessary resources some administrative overhead cost will be incurred.  Better administrators have lower overhead costs.

Other Tax-Like Expenditure


Then there is corruption.  This could manifest itself in certain ways.  One way is government overhead costs increase.  That is, the "effective" administrative cost is higher because some amount of the food spent on administrators disappears into oblivion.  So the average output of administrators apparently drops.  We can see that this would merely be using the example calculation above except increasing administrative costs across the board (perhaps by say 10%).

What of people performing some form of illegal taxation, property seizing, theft or other breaches of property?  That is, powerful individuals seizing the output of others?  We can consider the goods taken as "out of the formula", that is, we don't consider them.  Whoever it ends up in has bonus income but from the perspective of the system the goods have disappeared into oblivion.  So the goods that are left over are worth more in terms of person-cycle time.  Calculations would be adjusted to see a drop in industrial output for a particular industry (let's say damned barbarians take, on average, one pot per worker each cycle, then the apparent effective output of a potter is now 5 pots on average per cycle rather than 6 pots).

But say some spending lowers this drop in output.  Military spending lowers the drop in effective industrial output due to external factors such as a barbarian invasion or an attacking foreign power.  Policing can lower property crimes.  Government audits can lower corruption.  Then one has to judge the "trade-off" costs.  For spending put into policing/military/auditing, does it offset enough of the loss in production to justify it?

So for example, a person can produce 10 food, or 100 policing and each policing eliminates 1 food lost to production.  That's a good trade, 10% of a person-cycle regained for 1% of a person-cycle spent, a net gain of 9% of a person-cycle at the current production levels (ie. it's obviously a bad trade if there's no corruption to eliminate).

Another example, barbarians come knocking on your door every person-cycle and take 200 pots from your store room.  But every military unit lowers that by 50 pots.  You trade 100% of a person-cycle for 500% of a person-cycle.  Of course, military calculations are hard.  People die in battle and that puts a real dent in your economy (because obviously that's all we care about, as we're being heartless monsters right now).  So indeed, lifetime calculations are important here.  A person's lifetime output as a soldier, on average, is judged against the person-cycles he recovers over the same time period.   Society would shift it all the way to net zero (ie. produce just enough soldiers until additional soldiers do not have their cost justified by a similar reduction of loss due to military threats).

Notice also that natural problems (eg. a hurricane) end up looking exactly like a tax.  Corruption is like a tax, natural disasters are like a tax, heck even barbarians are like a tax.  Interestingly, from a mathematical standpoint, an AI can treat all factors lowering productivity as a tax and average out the rate of loss.

But, what is different between those events is what it costs to lower the damage each may do (natural disasters can be mitigated through infrastructure development, barbarian invasions lowered by military spending etc.) and the standard deviation in the events they cause.  Dealing with more transient events require much more complicated calculations because it's not actually possible to average out spending over a long period of time to deal with impulse events.  We can deal with that issue later.

Worker Productivity and Income


So two things we've done so far: all workers are equally productive and all workers can be retrained to do another job at the expected productivity level (ie. a person who was once a coal miner can be retrained and then turned into a perfectly average computer programmer).  We'll tackle the first problem first, as it is easier to deal with.

Let us say that the productivity of a worker is solely a function of motivation and skill.  The distribution doesn't need to be symmetrical; we use average production rate as our baseline.

If we wish to have income correlate with productivity, the simplest solution is to give everyone a number of goods equal to their percentage of average productivity.  A farmer producing 15 food receives 150% goods, and a farmer producing 5 food only receives 50% of goods.  The economy would maintain its balance, since all output is consumed with net zero.

But, we may wish to distribute goods in a somewhat more complicated manner.  Satisfy food first, then adjust luxury distribution to maintain the correct percentage difference between each person.  This prevent starvation so everyone keeps working at their current level.

However, that causes a problem where people who are exceptionally unproductive creates deadweight because if they are to be paid 1 food per cycle, then people who are working very hard (or are very skilled) have to start turning some of that person-cycle into food rather to be given to the other person.  That is, they have some of their income taxed for those who have low skill/motivation.

If skill/motivation shifts over time (but the average is always maintained) then this makes sense.  Someone who might be working at 115% one day may, for some reason (say family problems) drop down to 5% productivity, which is insufficient for even 1 food per cycle.  We can view this percent of workers operating below the "sufficient productivity" line as creating a drop in apparent output, like that of a tax.  That is, we need more farmers than usual to make up for the low skill/motivation workers.  And it only makes sense to do this if we imagine skill/motivation can change over time.

But, then again, skill/motivation might not ever go above adequate productivity to justify the food.  Why would you provide food then?  Well in real life some people are equivalent to low skill/motivation individuals but have extenuating circumstances that justify the issue.  For instance, a person who is heavily disabled may not be able to provide much output.  This is more of a moral question but in general, most progressive societies believe it is a good trade-off for the cost (afterall, this model so far doesn't include non-material wealth such as social bonds).

Skill Shift


Over time, newer workers are likely to be more productive than older workers for various reasons with an increasingly sharp difference the further along the technology is due to the rate of improvement of productivity.  For instance, let's say there's a turnover rate of 10% of workers in an industry per 10 person-cycles.  The oldest 10% die of old age and the youngest 10% who enter the workforce are more productive.

This means that if say the newest 10% workers are 20% more productive, the industry overall sees an average production rate increase of 2%.  Older workers will see their income drop slightly (but mitigated by earning a lower percentage of a larger income).  The more industries that exist, the worse the problem (because they would suffer a 2% drop in income share, due to their productivity falling when compared to the average but the economic pie only increases by something less than 2%).

For example:

If 50% of labour goes into pottery now, a 2% increase in the average due to better new workers sees only a 1% increase in total income for everyone but a (roughly) 2% drop in income for the older workers.

If we wish to have people not be concerned with a drastically dropping income over time because of newer technologies, we could fix income to productivity ranges.  Alternatively, income can be based on expected productivity rates (therefore the younger workers get a similar share of the pie despite being more productive because they are using the same amount of effort).

For example:

Old Potter: 600 pots lifetime production
New Potter: 620 pots lifetime production

The newer worker's income is based on the 620 calculation, but the old worker stays within the same calculation for income.

Income is simply the entire society's production (in real world terms this would be the GDP) split equally between each person and then adjusted for productivity rates.  All production should be equivalently consumed, with some production taxed in some way (either evenly or weighted toward more productive workers) to pay for individuals whose productivity falls below minimum levels needed to earn an income necessary for survival.


Skill Supply


There are several possible ways to model skill supply and we should go through each to see which might make the most sense to apply to the economic model. 

First, let's say each person is capable of doing each job with some random level of skill.  We could model this as a list of max productivity rates (compared to the average) per job.

Second, we could say each person has a general "competence" level.  This affects their productivity rate similarly between all jobs.

Third, we can mix the two.  A person has only broad competence levels, each affecting a wide range of tasks similarly.

When compared to the real world, we might hypothesize that people are much more like the third model.  Certainly, cavemen could have some hypothetical skill level for operating a robotics plant of modern society but more generally it would look more like humans have general intellectual capacities for different tasks and this translates into different industries depending on the technology of the society.  Education gears those general human capabilities into useful industrial skills.

That is to say, someone might be generally good at purely physical tasks, understanding their own body and it's capabilities and muscle control.  Another might be better at micro-control of muscles for more specific physical tasks (such as trade skills or sculpting).  Others would be good at abstract level thinking and problem solving (good for tasks such as a doctor).  But these skills might mix, for instance, a surgeon needs good hand control and a highly intelligent mind.

What would this mean exactly?  Well we could model this as a logarithmic function where f(x) defines their productivity level.  This would mean that the lower portion of workers are completely incapable of doing the job and then a slow increase and it levels off near 100%.

So, now we can have incredibly difficult industries and easier industries.  As usual, let's start off easy.  We apply a boolean threshold function to our original logarithmic model.  In simple terms, a certain percentage of the population can do the job and they otherwise cannot (ie. 0% productivity).

Okay, so now what issues might come up?

Skill Supply:
Farmer: 100% of people can be farmers
Miner: 70% of people can be miners
Potter: 25% of people can be potters

In this example, it has been specifically designed to create a skill shortage.  Only 25% of labour can be put toward pottery yet in our previous model:

(Education and Government calculated, no corruption)
Food: 10%
Clay: 10.275242983%
Pot: 68.5016199%
Government: 11.223137125%

We want 68.5% of labour put toward pottery.  We cannot.  It seems our economic pie will be suboptimal.  Okay what happens then?  Where do you put labour that cannot produce pottery?  If we had a more complex model where people could be not-quite-skilled for pottery (and also over-skilled) then we could put those people toward pottery anyway and suffer a decrease in productivity, while giving a very large share of income toward the properly skilled potters.

Typically, in a market style solution, the idea is to pay individuals more for more scarce skills to encourage the maximum number of people into that profession.  That would suggest a large number of people who can choose between professions (at some level of productivity) and then demand an income, for their effort expended, and thus would follow a different model.  This would be more like model number two.

Okay, let's see how that affects our situation.  Let's say that each job has a difficulty level and we've some distribution of skill per level. 

Let's say all populations are generally the same and throughout time remain the same (nothing would magically change humans in this setting) and so the split is always 50% low-skill, 25% medium skill, 25% high-skill.  Okay now let's assign a skill rating per job.

Farming is low skill.
Mining is medium skill.
Potmaking is high skill.

Being over-skilled adds 25% productivity per category (a high skilled individual would work at 150% productivity at a low-skill job).  And similarly, being under skilled is -25% productivity (a medium skilled worker at a high-skill job works at 75% productivity).

We'd like to maximize luxuries after satisfying our basic needs.  We'd also like to be optimal about how we assign our labour so that we get the most goods for our labour distribution.

Let's say, we use the lowest possible skill level that is adequate for a job before turning to other skill levels.

So let's ignore some of the more complex calculations since they do not affect any of the current considerations in this section.  That is, cost of government, corruption, education etc, do not affect how we would assign labour according to skill.  This makes it simple for us to work this into the model.

Original Arrangement from our Simple Model:
Food: 10%
Clay Digger: 15%
Potter: 75%

Well okay, let's satisfy food first.  We're left with 40% low-skill, 25% medium, 25% high.  Okay, let's satisfy our clay diggers next.  We're left with 40% / 10% / 25%.  Now we're left with a situation where if we pile everyone else into pots, now it starts getting a bit complex.  Since most of those workers are below-skill requirements they produce at a lower rate and due to the lowered rate, there is a clay surplus.  So then we have to lower the number of clay workers and shift it towards pot workers.  What is optimal?  Actually it becomes a polynomial of this sort

Total Number of Pots Produced = 2 * Copper Produced
Therefore,
6(0.5a + 0.75b + c) = 2 * 10(0.75d + e + 1.25f)

Where a,b,c,d,e,f are the workers of each skill level used for each industry.  (eg. a is low-skilled workers in pottery industry)

We have six variables and one equation.  The algebra Gods say we're pretty screwed here.  But, we can add in another equation or two, we are trying to maximise this afterall.  Let's say there's 100 people then...

a+d = 40
b+e = 25
c+f = 25

At this point, it's quite literally, let's use a computer to solve this.  I won't bother with coming up with an optimal solution for this, but we could try some linear algebra and come up with a solution.  For now, let's just ignore this and say that a computer can eventually figure out some number.

But we can see that an AI bureaucracy is starting to look more interesting.  At this point the equations are getting difficult enough to justify the use of simple computer tools.  Perhaps not anything with even a soft AI but it's still better to use a computer than a human (or more accurately use a programmer who makes software for a computer to run).

Do we do anything about income?  At this point that question is a bit philosophical but we could base income on effort or to base it on simple average productivity.  The former favours low-skilled workers and the latter favours high-skilled workers.  However, neither favours anybody working below expected productivity (ie. "being lazy", the ultimate horror of capitalists across the globe).

However, those methods have other issues with fairness.  Another solution is to have all income be based against the "low-skill" productivity rate of each industry.  This allows low-skilled labour to earn 100% income no matter their occupation and for high-skilled workers to earn greater than 100% income.  Of course, in the real world, how does one even judge what is high or low skill labour?  We could answer that question later.

Trade


Interesting, many of these topics can be considered separately and then combined into a single model.  With tax and corruption we can "build it into the cost", that is to say that we might say that a pot is worth 12.5% of a person-cycle, but that it actually is 7.5% to make the pot, 2.5% to get the clay and 1% for education, 1.5% for administrative costs.  What we are essentially doing is making it easy to calculate how much labour to allocate to each industry.  We build everything into the cost of an item, to know the "full" cost to produce a single unit of it.  If we imagine for instance that two luxuries each have equal "material happiness" value associate with it, then we would want equal quantity of each produced but we would then know what ratio of labour to assign to each by building in the full cost into each product unit.

For example:

Clay Pots: 12% person-cycle each
Wooden Chairs: 18% person-cycle each

And say we have 60% of our total labour to split between the two, then...

12a + 18a = 60

Therefore, a = 2, then we produce 2 of each, so the labour assignment becomes:

Clay Pots: 24%
Wooden Chairs: 36%

However, there is also an even more intriguing method of considering a cost of an item; trade.

One of the basic components of modern day economic theory is that of comparative advantage in trade.  The concept is simple but contains a lot of academic terms.  We'll explain each in turn.

Each society has a comparative advantage to produce a particular good if they have a lower opportunity cost to do so.  What is opportunity cost?  A careful look throughout the discussion reveals that a person spends their labour producing one good or another.  Therefore, if a person spends 50% of their labour into farming, they are then not spending that time on something else.  The opportunity cost is the next most valuable task that the person could have done with that time.

A comparative advantage exists when the opportunity cost of an item is lower in one society compared to another.  What is interesting is that if you look closely at the math, even if one society does everything better, it can still be in their best interest to trade away one good for another, in order to produce much more of other goods and end up with more in the end.  This is all thanks to opportunity cost issues.

Reusing our example, if we spend 24% of our labour into producing clay pots, we aren't spending it into producing wooden chairs.  We are giving up wooden chairs to get clay pots.  But what happens when there is trade?

You can view trade, in the context of our mathematical model, as simply having a different cost for producing a particular good.  If you are trading for wooden chairs, then the effective/apparent cost of a wooden chair is the cost of the good you traded for the wooden chairs.

For example, let's say that for each clay pot, you can trade a wooden chair.  That means that a wooden chair actually costs a clay pot.  In which case, now wooden chairs cost 12% of a person-cycle, not 18% as it did before.  Imagine, first, that there is no limit to the quantity that can be traded.

Clay Pots cost 12%, Wooden Chairs cost "Clay Pots" which are 12%, the equation becomes

12a + 12a = 60
a = 2.5

Clay Pots: 30%
Wooden Chairs: "30%"

The actual industrial assignment is

Clay Pots: 60%
Wooden Chairs: 0%

Of course there are several things we did not consider here: transportation cost, any additional tax costs (such as tariffs, port docking fees etc), limit on quantity that can be traded (due to quotas or just that there's a limit to how much the other guy can consume).

For taxes, tariffs and transportation costs we could try to build it into the cost of a product.  For instance, if the combined tax/tariff/transportation cost per unit added 2.5% person-cycles to the cost, then the cost of a wooden chair is a clay pot plus 2.5%.

12a + 14.5a = 60
a=2.264150943

The industrial assignment becomes
Clay Pots: 27.17%
Wooden Chairs: 32.83%

We're still better off than without the trade, though not as much as before.  Now if we consider something interesting, it's that of a restricted quantity of trade allowed.  Or perhaps, there's a complex trade network where there are a large number of ways to trade for resources.

The first problem is finding the different ways one can obtain a good at different costs and the quantity it can be restricted at and then finding the optimal solution.

We first rate the "material value" of each product.  Normally, a market solution would be used but this doesn't really tell you the dollar value per material happiness anything gives.  For instance, a marble countertop is more expensive than a granite countertop but which makes people happier?  Of course, material wealth happiness is incredibly difficult to calculate because each person values everything different. 

Let's simplify our issue a little bit.  We will say we do have some method of judging the average happiness gained from each luxury good.  Non-material happiness will be considered later.  This gives us an idea of how to build a good ratio of each luxury we want to provide.  In our example in this section we have clay pots and wooden chairs.  Let's add a third item to make this issue more apparent.  There will now be ivory horns on the market.

Clay Pot = 1 happiness
Wooden Chair = 1 happiness
Ivory Horns = 2 happiness

We could also, rate objects by other aspects depending on what we are trying to maximise, such as health.  We'll also state that a person gains decreasing happiness for additional items of the same type, with a simple monotonic linear decrease, such that what you want is an equal amount of each item.  In simpler terms, that means in our example we want a ratio of 2 clay pot: 2 wooden chair: 1 ivory horn.  The ivory horns are twice the happiness each so we only need half as many.

Now picture a complex trade network.  We can trade clay pots for wooden chairs but we can also trade wooden chairs for ivory horns.  So an ivory horn can be described by its cost in clay pots.  But say there's a limit on how much you can trade between two different societies and at different costs.  You'd get a big equation.

Society A: Takes Clay Pots for Wooden Chairs (only up to 20 pots)
Society B: Takes Wooden Chairs for Ivory Horns (only up to 15 chairs)

Say your actual society has 100 people.  Well let's see what the equation might look like...

Your Society, 60% spare labour capacity for luxuries
Clay Pot costs 12% of a person cycle
Wooden Chair costs 18% of a person cycle
Ivory Horn costs 40% of a person cycle

Normally we would simply have
12a + 18a + 40(a/2) = 60

Let's do the calculation for the whole society (adding up the person cycles), so our total production will be 6000% of a person cycle
12a + 18a + 40(a/2) = 6000

We can trade some pots for chairs instead
12a + (12b + 18(a-b)) + 40(a/2) = 6000
b < 20

12a + (18a - 6b) + 40(a/2) = 6000
Where b is the number of chairs "produced" via trading away clay pots

But we can turn the chairs we just got into ivory horns.
12a + (18a - 6b) + ( 40(a/2 - c - d) + 12c + 18d) = 6000
c < 15

Where c is the number of pots we've traded for chairs that we've then traded for ivory horns.
d is the number of chairs we've produced to trade for ivory horns
Obviously, it is difficult to come up with a solution without using a computer in this case, so we won't bother.  Suffice to say, that if you just did brute force you'd eventually come up with numbers on exactly what to produce to get 2:2:1 ratio of all goods producing the maximum number of goods with available labour.

So what our society might become is something like

Pottery: 50%
Chairs: 5%
Ivory Horns: 5%

And yet, we're actually getting a large number of chairs and ivory horns due to trade.

Research


In the real world, research spending has a completely unknown improvement possibility.  Some fields aren't directly tied with technology, such as mathematics, but enable the ability for new research to occur that can be used to create technology.  Because of the difficulty in judging the improvement gained through research, knowing what to spend on research is difficult.

In a computer game it is simple.  A certain amount of research gets you technologies which give you a known improvement.  But what if the game were designed such that, the amount you research gives you a variable amount of improvement?  All you know is that, more research gets you more improvements and less research gets you less improvements.

There are several methods we can choose to judge the "correct" spending level for research.  We can split research into different categories and they may have different average costs each (cost of materials for the research).

Let's say pottery research could result in nicer pottery or faster pottery production.  Both would affect your economic arrangement (nicer pottery would have higher happiness levels or trade better and therefore you can get more out of the same production level, it might affect trade calculations etc).

So we take a guess at the research level.  We put it at 10% of the pottery industry as research.

We keep it at this level for a number of cycles, say 20 cycles.  We'll see an average rate of return for this investment.  Let's say that we discover that at 10% of pottery industry as research we see a 0.2% gain in aggregate happiness out of our industry as a result of pottery improvements (that calculation is a bit tricky, since with trade and other aspects, we need to see only the total improvement that is directly tied to pottery production).

Then we get into the issue of deciding whether we should increase spending or decrease spending.  This is primarily an issue of short-term gain versus long-term gain.  A compound increase of 0.2% for 10% spending would mean that such a spending level only pays for itself over 47.7 cycles.  That's a pretty long time.

So, next step is to increase or decrease spending levels and watch the change in average rate of return.  We do this and we aim for a 15 cycle return on investment time frame.  In real life, usually the aim is for between 12-15 year return on investment for long-term investments.  We could treat research the same way but of course in real life, the standard deviation and the complex economy makes it nearly impossible to tell what benefits are garnered from any particular research project.

In a market economy, typically, because research spending only sees pay out across a 12-15 year period (or at least that is the time period aimed for), and most entities barely last 5 years (at least from a cursory glance at business statistics), the vast majority of entities will spend 0% on research because it would not make any sense.  Of course, from a high level view of the economy, it means slowed productivity increase over the 12-15 year period compared to an economy that can manage to spend that money.

Plus, research is typically a highly collaborative field of work.  Studies show that most research achieve its discoveries after discussing results with colleagues and having the colleagues challenge results (one of the usual reasons being "errors in data" ignored by a researcher would not be ignored by a fellow researcher of a different project, leading to investigation of the irregularities).  So, what does this mean?  Imagine the economic arrangement of two models.

Industrial Arrangement
Food: 10%
Clay: 15%
Pottery: 60%
Pottery Research: 10%
Clay Research: 5%

From the AI bureaucracy, a portion of people are simply assigned to conducting research.  They do it however they can.  In the market arrangement there are many sets of scientists working in isolation from one another and would in fact never cooperate, if they played within business boundaries.  Of course you can have businesses cooperate to conduct joint research programs but then, in the context of the model, that would be simply be stepping closer toward the AI bureaucracy approach; everybody working together in joint research.

Non-material Wealth


We'll finish up the first stab at this model with a look at how we might include non-material wealth.  In many cases non-material wealth (family health, work stress, leisure time, friends, ability to find romance) are tied with economic health.  That is, direct spending doesn't usually translate into non-material wealth but spending enables people to be able to gain non-material wealth.

For example, let's say it is the middle ages, in which case it was very common for the local lord to spend material wealth for festivals.  This has the immediate benefit of material wealth (people receiving fancy food, entertainers and games) but also has additional non-material wealth for some (ability to find love, although of course in the actual middle ages romance didn't really exist in practice).

In all our previous examples there was an unstated concept, that of culture as a form of technology.  As technology is just an application of concepts, we could technically consider culture as that as well.  What do we mean?  Let's say you have only one known category of non-material wealth.

For example: Family Health

Okay, so now we go into the subject of, how do you improve family health?  Now we say we have certain "technologies" that allow us to improve it.

For example: Festivals

But festivals cost material wealth to conduct.  We'll say our festivals are quite simple.  It involves eating food and looking at some pottery.  Real exciting stuff.  So let's look at a simple economic model.

Industrial Arrangement:
Food: 10% (provides 1 food per person)
Clay: ?
Pottery: ?
Festivals: ?

We'll say that to "enable" the effect of festivals, you must provide at least 0.1 food and 0.1 pottery per person on average.  Anything greater than that doesn't improve the festival, only individual preferences can improve the effect.  We ignore the individual differences and average out the increase in happiness, afterall there's nothing we can actually do about it.  Let's say that once enabled, festivals, on average, provide 1 happiness.

Therefore, 1 pot is equivalent to having festivals, so unless we're unable to even enable festivals, we're better off with producing partial pottery per person to get a partial unit of happiness rather than zero.

We'll say that pots cost 12% of a person cycle, 10% for the pot, 2% for the clay.

First let's enable festivals.
Food: 10%
Clay: ?
Pottery: ?
Festivals: 1% for food, 1.2% for pots.

Now let's try to get as many pots as possible.
Food: 10%
Clay: 14.6%
Pottery: 73.2%
Festivals: 1% for food, 1.2% for pots.

But what if, we didn't have enough labour to enable festivals?  Let's say per person, a festival takes 10 pots and 10 food.

We try to enable festivals but we cannot afford it.
Food: 10%
Clay: ?
Pottery: ?
Festivals: 100% for food, 120% for pots

So instead we simply ignore festivals.

Beyond this, there might be certain considerations such as limiting a "person-cycle" to a certain portion of a person's time per day (say, people are expected to work 6-8 hours per day, average of 7 hours per day).  But, the vast majority is personal preference outside the realm of economic management.  Still, there could be various spending in social programs such as

For example:
Anti-discrimination Education and the associated cost
Religious harmony programs

Well that's it for now.  There's still many other considerations, the largest one being that society changes over time with technological and skill improvements and how we might include this into the model (or how it affects the model in peculiar ways).  We'll also take a look at how the needs/wants of society can be modelled much better than a "I want equal amounts of all possible luxuries".

Friday, September 21, 2012

Housing Policy

This is an extension to previous posts:
  • http://politicallyuntenable.blogspot.com/2012/09/objective-of-housing-policy.html
  • http://politicallyuntenable.blogspot.com/2012/09/landless-housing.html

Taxes in place of property Tax

A property tax is a tax levied based on the value of the land and structures built on top. But if land is no longer traded, then property tax is levied only against the value of the structures built. However, this is hardly the only way to levy tax for real estate owned.

Land Value Tax

In short, a land value tax is based on an estimation of the market value of land based on its potential in residential or non-residential use (whichever is better). This tax ignores any current existing structures on the land, so if it is used "inefficiently", then the land value tax penalises this inefficient use. The idea is that a property tax penalises capital investment (and housing is now in the same category as capital investment).

The idea is to promote market efficiency and eliminate the deadweight caused by property taxes. Because the LVT is charged regardless of development, leaving land undeveloped is highly undesirable as you pay taxes on land that provides no revenue.

The ultimate objective of LVT is lower house prices, more development and higher population density. All of these fit the objectives of housing policy outlined in the previous post.

As an example, Pennsylvania uses this concept to levy a land tax that is much heavier than property tax. While statistical evidence goes to show all of the objectives achieved, there was great difficulty in maintaining proper land assessment across the nine decades it was in use. Some local government would maintain proper assessment that were timely and accurate, others would not. The question is likely what the cost of maintaining proper assessment versus the cost of sub-optimal property tax effects.

Examples in Australia and New Zealand are more compelling, with their use since the 19th century, they've mostly achieved the same objectives.

Statistical evidence in all cases suggests a light to heavy increase in urban development due to LVT.

However, it seems that LVT in practice must also be combined with competent zoning laws and good timely (likely yearly is good enough) property assessment. A variation for no land exchange is that a rent is charged for using land, much like a LVT, either for living purposes or commercial/industrial purposes. Like Australia, there can be a threshold above which tax is levied. The LVT could fully replace property tax.

Government management of land in history

Individual ownership of land in western democracies is a concept developed slowly over the last few centuries with the move toward land titles. This is likely due to the growth of the middle class over the same timeframe and the dissolution of old agrarian economies. Agricultural use of land tended toward community based ownership with informal contract over use between parties (each party could use the land in different ways or at different times). Modern use of land tends toward individual/single family ownership.

It's important to ask the simple question of whether this is desirable and evidence speaks to it generally being a "yes". A more nuanced explanation relates land ownership with modern industrial use of land. Since land is not as directly used for revenue (agricultural output) than in the past, more importance is placed on the structures built on top. Whether it is a software company that owns an office building (and thus, most of its revenue depends on the human capital owned, not the structural capital) or a car company with a robotic factory, the land itself doesn't matter as much except for how hard it is to build a structure there and whether they can hire the necessary labour force from the surrounding area.

So, if the issue now is no longer agricultural output, then land management should likewise change. Governments have largely shifted toward free market mechanisms to lower the administrative cost of assigning land but this has resulted in inner city dilapidation, land speculation (and the associated real estate bubble problems, a phenomena that should be well feared in today's heavily damaged economy from the sub-prime mortgage debacle) and uneven distribution of government services (such as education or road systems).

It's difficult to avoid the "tech park" issue because of the economy of scale that develops from the concept. That is, like businesses which depend mostly on human capital (which is most modern industries such as tech and finance) build in the same area. Then, the talent pool that they depend upon slowly moves into the area which reduces personnel and other operating costs. However, this means that local property prices start to shift dramatically according to the success of any particular industry.

Steel does well? Then the cities with steel mills get a significant spike in property values, the associated increase in tax revenue, increased development which is, as we've seen today, followed by the drop in steel manufacturing revenue and the rapid dilapidation of the neighbourhoods involved in the economy.

But what we see is that the specific location matters little for almost all of these industries, or that there are many locations in which they can exist but they can only choose a few. For instance, steel industry would like to be near water to cool their machinery but there are many bodies of water to choose from, however, they chose to be mostly around the Great Lakes. Another example would be the financial industry. They would like to be near a lot of people and money, so it has developed in locations key locations in each country such as "Wall St" in the United States and "Bay St" in Canada.

With this in mind, what land taxes and property prices should reflect is this reality in which locations matter little but what is on the land matters more.

Price does not reflect land value

If price reflects only the structure built and not the location, it more closely resembles the decision process of most modern industries. Whether you build your investment banking firm in Dallas or in Chicago, what matters are the people working in the building, not the land underneath it. Your investment bankers aren't growing corn after all.

Assessment problems are not likely to be difficult. The real estate industry already separates land price and house price in its analysis of pricing across any piece of property. It would be a bit strange but the change would have individuals pay for property prices but be taxed against land price.

Tax is property agnostic

If taxes on property were levied based only on the land and not the structures on top, then it encourages individuals to build the structure which generates the most revenue on the land. If that is a steel mill then a steel mill would be constructed. If it is a financial firm, then a financial firm is built. A property-agnostic tax would help to prevent discouraging high cost capital investment (like large expensive multi-billion dollar factories).

As a note, although not explored here, it could be worth investigating if property taxes discourages the construction of high cost capital facilities leading to out-sourcing issues in America. For instance, the construction of a ten billion dollar robotics plant to create smart phones also incurs a property tax on ten billion dollars of property value. That would be a major disincentive to construct such a facility in the United States.

As land value tax has been used in practice successfully in nearly two dozen countries for well over a century, it would seem to be a workable concept in areas not using land value tax.

Zoning law effects on property prices

In general, according to the previously stated objectives of housing policy, zoning would be used to increase housing supply to keep rent and property prices stable over the long term. Of course, zoning law is an intricate relationship between a competent bureaucracy and the land needs of the population. Therefore it's a question of good government.

A look at Hong Kong, we have an example of Comprehensive Development Area zoning. In heavily CDA zones, environmental complaints is somewhere between 4x to 6x less frequent, per capita, than areas with no CDA. There was also lessened price variance. Although one of the goals of CDA was to increase property prices compared to non-CDA areas (to reflect the superior urban planning). That is likely to be a complex subject as it likely a result of unfavourable development not occurring close to homeowners that help keeps prices higher than non-CDA zones.

There are some analysis that suggests the United States developed a bottom-up approach, with many different local governments managing various districts, that attempted to hedge the unsustainable cost of urban sprawl through zoning versus consolidation with dense central cities. This creates the implication that American experience with zoning laws was that to promote very high prices and low population density. Then the answer, for American homeowners, is to buy newer and newer development to keep the cost of home ownership low. But, this creates other problematic costs such as environmental pollution due to increased car use and commuting, increased stress and mental issues due to traffic congestion, decreased economy of scale in the use of water/electricity/snow removal and other local services. So, on the converse, zoning law can substantially increase property prices, lower population density and create many problems.

In particular if we look at California, many suburb communities adopted zoning policy in the 1970s to simply prevent new development. The result appears to be very old housing (using the lead paint and asbestos as an indication of age) and exceptionally high property prices despite lower population growth than the rest of America (which experienced lower house price growth). This would be an example of zoning policy working against the stated objective of providing a greater supply of housing and keeping prices affordable (as a percentage of median household income).

Between these two examples there is one very large difference: population density. It can be easily seen that Hong Kong suffers more greatly due to land scarcity than the United States which can expand along the edges of every single city to accommodate more inhabitants. This makes a significant difference in the "need" for zoning laws. Specifically, Americans can constantly choose new development rather than pre-existing housing to alleviate high demand in certain areas. However, this urban sprawl has additional environmental and infrastructure costs. People who live further from central job hubs need to commute to work and add to infrastructure woes whose costs may not be covered by any taxes/fees levied against these new commuters. Further, it also likely that these individuals are purchasing more affordable accommodation outside of a city due to lower income/wealth and thus taxing them more heavily will disproportionately affect the poor (though to what extent is debatable).

For the United States, there may be yet another two centuries of cheap land, thereby delaying the need for any government interference in anywhere but a few key urban centres. This is the same with Canada. So, stopping the trade and sale of land is not likely to make a large difference in prices except in major cities. This fall in prices should be then met with a construction drive. In particular, the United States regularly uses zoning law to restrict areas for higher income individuals, but if this works, then one expects the converse to work. Zoning laws push up housing density to prevent urban sprawl (and the associated environmental and infrastructure costs) and lower housing prices.

Urban Planning, Price Control and Segregation

In the absence of government, the level of segregation (based on statistical data) is likely to become primarily based on class and wealth strata than it does with ethnicity or skin colour. That is, a white community would be willing to accept blacks in their neighbourhood, provided the blacks were of sufficient wealthiness (and past wealthiness in the case of new money vs old money). But, in fact, wealthier individuals have a greater capacity to influence local government in order to obtain government interference to increase the level of wealth segregation in communities.

Likely somewhat ironic, given the tone of the discussion, but less government interference with regards to setting zoning laws in America would actually depress prices in many parts of the country. The primary reason for high prices in California is due to the "high price" restriction in areas such as Cupertino or Palo Alto, a tactic both for the wealthy to be near wealthy and for certain ethnicities to be excluded from the neighbourhood.

But, more accurately, it is the type of government interference that matters. Generally, if it does not match the objectives of housing policy (maximise house ownership, decrease price variance and increase density of land use for environmental reasons) then it should be rejected legislation. Competent bureaucracies can exist but most of these communities would find this type of government policy to be highly politically untenable.

Some aspects that may cause urban sprawl is the requirement for American universities to only select a maximum number of students per school. The expected result, for the rich to obtain more university slots, is urban sprawl to have more schools and thus more slots. This is only a cursory analysis of that policy and so may be inaccurate.

Australia and Canada both consider 30% of income to be the maximum threshold for affordable housing. This considers all costs, CMHC (Canada's housing federal housing agency) is in fact quite strict, as the cost includes mortgage, utilities and insurance (that is, it considers all expenses associated with owning a home, not simply the mortgage). Also, ideally, a family should earn above the statistically defined (by Statistics Canada) low-income cut-off (LICO). The LICO is not a poverty measure and Statistics Canada unfortunately has not been tasked with any particular paradigm for measuring poverty specifically.

Data for 2010, from the Bureau of Labor Statistics (USA), mean before-tax income is $62,481 and $16,557 spent on housing, and total expenditure of $48,109. If we calculate as a percentage of total expenditure (a good measure for after-tax income, tax makes up most of that mysterious hole between income and expenditure), then that is 34.4% of the household budget. This is, on average, above what Canada or Australia would recommend and is a sign of "high" or "unaffordable" housing.

Data for 2010, from Statistics Canada states that average expenditure is $70,574 and of that $20,693 relates to housing ($14,997 shelter, $3773 household operation, $1923 furnishings and equipment). This is at 29.3%, just under the government imposed concept of no more than 30% of income. Actually, that is quite an amazing result; a government program to meeting its objective (go CMHC?).

Data for 2010, from Australian government, indicates that 27% of expenditure is housing, also meeting their objective. From Statistics Sweden, the SCB, housing costs hovers between 27.4% to 31.7% depending on whether you live in sparsely populated areas (cheapest) or metropolitan municipalities (most expensive). Compared with the rest of Europe, Swedish housing expenses are near the highest but they also enjoy the highest quality of housing, so it is likely in line with the rest of Europe.

Australia, Canada and Sweden engaged heavily in assisted housing programs, moreso than the United States, although all countries do so in some aspect. The decreased share of income used for housing in the non-American countries is most likely due to the increased federal expenses involved in housing projects. The United States only a few percentage points higher than the other countries but there is also indication that American incomes are also substantially lower for the middle class compared to Canada, Australia and Sweden (between $20 000 to $30 000 USD lower). Some of that lower income can be mitigated by the fact that many Americans tend to live in sparsely populated areas with much lower cost of living but as the calculation of housing expenditure is in terms of percentage, Americans have lower disposable income both by an absolute measure and a relative measure.

Several major differences arise in the policies between Sweden/Canada and the United States. Housing projects in the United States suffered greatly from the "not in my backyard" political problem, whereas the Swedish and Canadian governments were more forceful about "mixing" neighbourhoods. As a result, housing projects in the United States, much like the housing projects of France, rapidly fell into economic ruin and dilapidation as concentrated poverty caused an economic downward spiral. On the other hand, Canadian and Swedish efforts were highly successful both at increasing home ownership rates but also by placing impoverished individuals into middle class neighbourhoods had increased class mobility. All measures of class mobility for Canada and Sweden are far superior to that of the United States.

Wednesday, September 19, 2012

Objective of Housing Policy

Summary

Landless housing is a concept where individuals purchase housing but land is never bought or sold, so that house prices correlated only with the material/labour cost of constructing the house. The idea centers around the concept that price should reflect the quality of the good. Location, inextricably tied with any housing built on top of it, would affect price and so this concept breaks that pricing model. Then, it may be asked, would that make sense?

As an extension to the idea that the quality of housing is the only determinant of price and not the location, the objective of housing policy is explored. In reality, most people would not explore history for economic policies but the concept of private land ownership has been one of the most significant factors in destroying large empires in the past. From the Roman Empire to the Qing Dynasty, the most successful societies have been ones that heavily regulated and provisioned housing on intelligent policy, carried out by a competent bureaucracy. Private landownership typically led to the "Crassus" problem, where a single person could own most of the land and force large swathes of the population into poverty.

Long Description

This article considers these housing policy objectives:

  • Maximize Number/Quality of Land Owners
  • Matching Individuals with Desired Housing
  • Equally Distributing Social Services
  • Avoiding Economic or Social segregation
Maximize Number/Quality of Land Owners

It's preferable for people and for the government tax system for everyone to be land owners, that it is affordable to be so and that they are of the highest quality possible. All of this, for the least amount of resources expended. This is the primary reason for eliminating land trade; a lot of money would go into purchasing land but other than this it does not translate into real material wealth.

Essentially, money that goes into the sale of land does not convert into anything. It does not improve the land; it only gives the right to improve land. It does not produce any products; in fact, it takes away available money from purchasing luxury goods. It does not make use of the land; a highly free land market means that people are also free to purchase land and then do nothing with it.

So, the elimination of the land market frees up money for development and luxuries, a portion of which will translate into superior housing (either more space and/or higher build quality). At worst, there is no decrease in quality/quantity of land owners since all housing is strictly cheaper, however if individuals are willing to pay half a million dollars for a home now, then logic would dictate that they would continue to be willing for a superior house.

There are several methods of tackling this issue:

  • Reducing the Cost of Housing
  • Improving Income

Taking away the land market would cause a definite decrease in house prices but it also removes the ability to "invest" in housing. Real estate ends up being much like capital purchases, individuals will spend money like businesses construct offices because housing depreciates over time (rather than appreciate despite the decreasing quality of the structure). This would result in old housing becoming low in price and thus becoming regularly replaced by more modern housing.

The expected result is an increase in construction work, renovations and development. There can be several issues that mitigate the benefit. First is corruption in the construction industry. As a rule, there's no way to separate government interference and the construction industry because everyone requires getting permits to build anything. Remove those permits and you have significant urban planning and environmental problems. Then, really the solution is to reduce corruption. The best tools in this regard is transparency (publicly accessible records on the web for all construction, all bidding done openly on a publicly accessible website, an auditor general with a yearly report) and a public that cares.

Second, varying incomes of individuals during their life time may cause hardship later in life when they are still paying rent. Generally, people would have to lower the amount of rent they pay. Rent control and proper zoning would tend to create sufficient housing at a reasonable price (an aim to keep rent prices below 20% of income, or so). This requires good urban planning. It would be useful for government to produce an urban plan and for a standard statistics agency and budget office to produce the expected outcomes of that plan. Western democracies are at a point where it no longer needs to have government state projected numbers for plans because there is sufficient number of skilled individuals who can work in budget offices and statistic bureaus to produce all these numbers.

On the flip side of controlling house prices and pushing for continuous new construction (of higher and higher density structures as population increases), government can work to improve income. This is a broad topic not addressed here but essentially, generally attempting to improve the economy would alleviate land ownership problems.

  • Eliminating land trade will free up money for housing quality and ownership
  • Zoning to drive toward higher density in more contested areas
  • Transparent construction bidding/permit granting process using new technologies (such as the Internet) to lower corruption
Matching Individuals with Desired Housing

Ideally, people would get the exact housing they desire. Practically, land is scarce and there may not necessarily be sufficient housing to provision it to all individuals who want it. It's important to note that free market for land is merely a way to decide how this housing is provisioned (an important consideration if someone is of the mindset of "but if you don't have a price, how much do you pay for the housing?", the question ignores the assumption of a premise: that housing needs floating price component).

Pushing for higher density housing in areas that are more contested would be a government policy. This would help to, over time, provide more housing for people who desire it. Normally, with a price system, locations that are more desirable (due to natural geography) would fetch a higher price. The higher price forces individuals with lower income to stop consideration those locations. It does not, however, as many seem to believe actually change the supply of housing. Whether housing costs ten times the material/labour cost or one time the material/labour cost, it is land owners who reap the benefits and they have no incentive to build additional housing with additional income.

Many individuals may not actually have a preference and care only about the quality of housing. Most natural geographic conditions only vary with proximity to water and nature preserves. All other artificial conditions (quality of school, rate of crime) are caused by pricing issues and should not exist in the first place. Putting price pressure to perpetuate the problems would be counter-productive.

But, how much free market is reasonable? Is it more pragmatic to have government construct housing? Historically, housing arrangement has always been somewhat government controlled but mostly with respect to land and not the actual housing. So then, is it more efficient to provision land via a government program or through a semi-free market?

If it was done through a government program, in order to match the objectives listed, then we should expect that provisioning is done by stated desire and then by socio-economic background of each family. The aim would be a fairly even distribution of the income ranges in an attempt to create greater class mobility.

  • Drive higher density housing in more desired locations
  • Provisioning land by desire and socio-economic status
Equally Distributing Social Services

Even in more socialist countries such as Sweden, neighbourhoods tend to have areas with richer social services and those with poorer social services. In the case of Sweden, all schools are equally funded initially but then additional local grants are provided and distributed by local government. That secondary distribution is uneven. In the case of Canada, schools receive local income from local government based on municipal taxes (property tax for instance) in addition to provincial funding. Provincial funding might be very equitable but obviously local tax income will not be so.

In the United States it is even worse. Though there is a state education budget, local taxes make up a much larger proportion of school income than it does in Canada, leading to significant differences in house prices. Buying the same quality of house in Palo Alto (California), due to school quality, will be nearly triple or quadruple the price of a home in north Waterloo (Ontario). Yet, the school quality in Waterloo is not inferior to that in Palo Alto because of superior government policy. Palo Alto is not waterfront property, it is not a pristine beach, it is not near some magical nature preserve. In fact, it's pretty crappy land near a bit of marsh. On the other hand, north Waterloo is near open fields, forests and a slow flowing river. So, we can see that artificial environmental conditions cause just as much price fluctuation as natural ones but there is one difference: we can control artificial conditions.

What is there to do? One of the primary solutions is evolution of power versus devolution of power. That is, we move tax income up to the state/provincial level and then redistribute based on local cost of living and per capita equalisation. That is, a person living in Cupertino (California) would receive the same school funding per capita (adjusted for cost of living) as someone in San Francisco. The greater expectation is that funding difference due to cost of living is specifically due to issues with remoteness, transportation costs and economy of scale due to population density.

To believe that "location" is a set of factors outside the control of a democratic population is to ignore the power that people wield. Government is there to do a job for the people, to make their lives better, not to sit and watch and ensure the "free market" exists. The free market is a tool used to make lives better and if there is a better tool then it should be used. Unequal funding of schools is not acceptable. Class mobility is an important aspect of the American economic system.

  • Equalise funding of schools, roads, police through state/provincial level funding
  • Preferable to have a digital public online accounting book for funding per school, funding for roads in an area and so on (some places may have already implemented this)
Avoiding Economic or Social segregation

One of the effects of free market price of land is that it necessarily provisions housing accord to income/wealth strata (more the latter than the former). This means the creation of neighbourhoods of specific wealth levels. Economic segregation of this nature leads to differing crime rates, higher level of corruption in the government (it's easier to identify rich neighbourhoods to focus political efforts on) and other social problems that manifest itself in the long term as a decrease in social mobility and the entrenchment of poverty.

There are a number of tactics to alleviate this issue in a "fair" manner.

The government could sprinkle different quality of housing in the same neighbourhood to allow people of different wealth strata to coexist in close proximity. Then policing resources, education funding and infrastructure building would have to be spread evenly as there is no specific location for political capital to be focused upon.

The government could institute price controls, or specifically, rent control. Keeping rent in line with mortgage rates for buildings keeps prices stable. Profit for landlords then becomes a question of quantity of housing. With rent control they can only increase profit by providing more housing rather than providing the same and charging a higher price. Without rent control, the incentive is to price rent as high as possible until people can no longer afford to live. However, rent control must be instituted in wide areas, such as at the county scale.

The government could change permit grants. Specifically, as house prices start moving upward, zoning laws should shift to start including the construction of higher density housing. Many price issues in the United States arise simply due to enforced low density housing to keep a certain "style" in a city. That is an admirable goal, but it is problematic if rent prices increase to the point, as they are now in San Francisco, to be one of the highest in the world for housing quality comparable to that of places for a tenth the price. It is not as if incomes have gone up similarly so the only result is pricing out the poor from having housing.

Land could be provisioned on a multi-slot basis. There are a specific number of slots for each type of wealth strata (it's a fuzzy line between any strata of course, a public algorithm may be helpful, or perhaps a public application system). Any particular neighbourhood cannot "tip" into a specific wealth strata. The algorithm should take into account the monthly changing economic structure of the population (such as a growing number of upper middle class, as a percentage of the population, means any specific area can have more of them). Of course, the provisioning should be blind to the usual list of characteristics (skin colour, religion, etc). That normally should be obvious but as single ethnic neighbourhoods still exist for reasons due to social exclusion, it should still be a consideration in government policy.

  • Mixed neighbourhoods of varying house quality levels
  • Rent control and zoning as a combination policy to keep price levels low
  • Provisioning housing based on socio-economic status to keep neighbourhoods mixed
Overall Policy

So what is the incomplete list of ideas?

  • Eliminating land trade will free up money for housing quality and ownership
  • Zoning to drive toward higher density in more contested areas
  • Transparent construction bidding/permit granting process using new technologies (such as the Internet) to lower corruption
  • Drive higher density housing in more desired locations
  • Provisioning land by desire and socio-economic status
  • Equalise funding of schools, roads, police through state/provincial level funding
  • Preferable to have a digital public online accounting book for funding per school, funding for roads in an area and so on (some places may have already implemented this)
  • Mixed neighbourhoods of varying house quality levels
  • Rent control and zoning as a combination policy to keep price levels low

There are probably more policies to throw into this package, land is a contentious issue. It has been one of the largest factors causing the decline of many previous empires. Free markets for land typically brought about their downfall, so it would be wise to ensure that land ownership does not result in the same problems for the United States.

In the modern world these problems are mitigated for the United States because it is a young country and thus has a lot of open free space. Three hundred million people may seem like a lot for a population, but picture that China, of somewhat smaller size than the United States, has 1.3 billion inhabitants. Suddenly, three hundred million sounds like a lot of free space. Land issues arise when it becomes more scarce.

Also heavily mitigating the issue is that land is not the primary wealth generator today than it was just a few centuries ago. So then, super-landowners aren't as much of an issue as they would have been when agricultural income made up the vast proportion of national gross domestic product.

Rationale

Living location is a sticky issue. Individuals don't simply choose to say that today they will live in New York City and tomorrow they will live in Chicago and the next day they will live in Seattle. A person's living location is a function of the property they desire, the location of their job and the wealth they have at their disposal to use for moving expenses. Those are, at the least, some of the large factors that affect living location.

So, living location is a matter of choice of small variations. Whether to live in one neighbourhood or another two streets away. It is not a matter of "New York City rent is high, I will move to Dallas". And will your family move with you? Your relatives? Your job? No, they will not. So it is not a decision one can simply make. But, free market for housing makes that exact assumption.

However, if price simply reflected material/labour cost, that is fair. Material costs usually varies only by transportation costs. Labour does not vary much either. And, you are paying for the quality of the house. That is expected, at some point, someone must pay for this. You can ignore land prices but you cannot ignore construction prices.

Most people, especially in lower wealth strata, never move far from where they are born. They simply don't have the wealth. So to state that they should choose to live somewhere cheaper ignores... everything. If someone is in the tech industry there's really only a few cities to choose to live within. You cannot choose to live in Hamilton (Ontario) and expect that you will have a job magically.

Of a more pragmatic nature, there is the issue of "relative" and "absolute" prices. When land is no longer a consideration in price it is somewhat "unfair" that someone living in the middle of a desert out in Nevada pays the same price for the same quality of housing as someone in prime real estate in the middle of San Francisco. The keyword is "unfair" because the relative price difference of the two locations is zero.

However, what of the absolute prices under free market? The desert location would be (for instance) ten times cheaper than the prime real estate in San Francisco. That is "fair". But what are the actual prices under the free market system versus that of the semi-free market system (the material/labour cost is still free market)? Without land in the price, prices would drop. Or, people are willing to pay up more money and thus acquire higher quality housing in prime locations and so housing quality rises in both the desert and the prime real estate. So, does it matter?

A good analogy would be healthcare. A mid-range US healthcare plan costs 7000 for a single individual. A plan comparable to that of any Canadian healthcare government plan costs in the range of 12000-15000 depending on the state. Canadian healthcare plan costs on average 2300 for the government and another 500 for private spending. So we'll say that it is $12000 (USD) vs $2800 (CAD, which at the time of this writing is worth slightly more than USD). But the Canadian healthcare plan is unfair. No matter your risk factor, age and such, it still costs $2800. But, obviously, it is four times less the cost for the same quality. So, does the relative price unfairness really matter?

Although it might seem like a question of "end justifies the means", it's not quite so. It's hardly diabolical to ask people "do you wish to pay the same but much lower price?". People are suffering less due to the means and suffering less due to the accomplished ends. It is superior in all ways.

Tools

A website for transparent and public tracking of construction bidding, permit granting to create a paper trail for auditing (either by the media or an auditor general).

Tracking house prices and rent relative to local income. Preferably detail down to the neighbourhood (aggregated data to avoid personal information leak).

Tracking home ownership levels and amount of housing owned per capita.

Website to track housing availability, showing housing acquired and wealth strata distribution per neighbourhood.

Online tracking of state/provincial budget, with detail down to the funding of each school. Preferable, but obviously would take time to create an automated system for this.

Wednesday, September 12, 2012

Landless Housing

Summary:

The economic realities of housing wrestles with concepts such as rent control, land value, renting and assisted housing.  All of these policy ideas are different methods of provisioning housing to different people according to different criteria.  The concept of landless housing has one primary goal: provide the most housing at the cheapest possible price with no loss in quality.

In short, the concept forgoes assigning land value, it always belongs directly to the government, but the property built on top can be owned privately (if privately purchased) with price dependent only on the labour/materials that had gone into the construction of the structure.  If a house was built for $600 000 CAD or USD, then it was due to the labour/material cost totalling $600 000.  Market price still affects labour and material costs.

A person only pays for what is built, for a price at which it was built and nothing else.

Long Description:

Housing management is typically a package of policies that deal with land management, fees with land use, taxes on owning land, tax breaks on renting/leasing, taxes on commercial land owners, taxes/fees associated with different uses on land, rent controls, government transfers based on economic goals or assisted housing etc.  The list is long and complicated.

Landless housing is a concept that envelopes the policies that revolve around purchase price.  Essentially, the shift in the current model of housing management is to eliminate the idea of "owning" land.  Generally speaking, housing development typically involves paying a fee to the local municipal government for development rights, as well as purchasing the land from previous owners.  Speaking in contemporary terms, this has resulted in farmland being sold off for suburban development due to the low income of farmland.

Environmentally speaking and also with respect to economy of scales, municipal governments typically lose money on large sprawling communities in the long term.  Due to the short term nature of city politics, most politicians/city councillors do not take this into consideration.  Instead they rely on the short-term income earned from development fees and land transfer tax income (and other fees/taxes collected) despite the long-term loss due to services provided to the urban sprawl (snow removal in cold areas in northern United States and Canada, sewage and trash removal and so on, also look toward the string of city bankruptcies due to poor development choices by Californian cities).  What would be more optimal is to maintain farmland (better even if let fallow) for future food production to guarantee food security in the future and to have high density housing to gain the benefits from mass transit and provide more economic opportunity for small/medium size businesses to thrive (such as small daily bakeries).

The decreased cost of purchasing housing, due to the absence of land value, means that more of the money spent on housing goes directly into quality.  This frees up private wealth to be put towards better, higher quality housing, either larger housing or simply higher quality materials.

If the concept of landless housing is combined with assisted housing and rent control then the ultimate result would be a policy package that would do the following:

  • Housing prices reflect the material/labour value of the home constructed
  • Rent is based on initial house price, with the ability to increase rent with inflation (such as the CPI + 1 percent maximum increase per year)
  • Assisted housing allowance can be targeted for a percentage of the housing in the area in order to prevent poverty from becoming geographically concentrated

In order to move from the current model of land value to valueless land, the government (likely provincial governments in Canada and state governments in the United States) can slowly purchase land and then leave construction bids open.  The simplest method would be have construction bids open, people to express interest and the winning bid goes ahead on the land (as chosen by potential buyers who risk a deposit with the winning bid).  The government is only enforcing that land does not factor into the price (there are likely other ways to perform this).

Economic theory, in various schools, usually predict a "lack of housing supply" if there is rent control, or that repairs are not conducted properly etc.  In reality, rent control allows landowners to charge prices far above the value of the housing (if it was initially built for $500 000, they charge a rent of $8000 a month, far beyond what a mortgage would cost) and the increase in income would unlikely be used for anything but profit.  It is more likely that rent control merely correlates rent prices with the price of the housing, with respect to the cost of the mortgage.  In fact, it is more likely that due to the lowered price of housing, a higher number of individuals would become home owners and for renters, their prices can be predicted to help housing stability.

With landless housing implemented, people would purchase homes from contractors or the government at a price that reflects only the price of labour and materials.  Renters pay a rent that would correlate only to the mortgage payments and inflation, rather than market fluctuations.  The most important difference is that older homes depreciate in value because land holds no value.  This would significantly shift economic behaviour since housing is no longer an investment (after all, a house requires greater repairs or renovations as time goes on, why would it make sense to go up in value against inflation?).  This last point has significant implications.

In general, commercial/industrial businesses should benefit from structures whose value is separated from land.  For instance, a manufacturer would think when a factory needs to be replaced (say every 25 years), then the factory depreciates in value each year (capital depreciation).  Then at 25 years, (if for some reason this occurs) the factory owner does not need to purchase land to build another factory.  Another example could be small businesses such shops, which would likely benefit much more.  A failing business can have their shop (say it is a restaurant) sold but only at the actual value of the material/labour (basically initial cost, with inflation calculated, subtract the necessary repair costs unless the repairs were already done) and then the business is replaced.  This allows greater fluidity in the small/medium business sector.
Looking to the far end of the concept, no land is traded any more. Businesses construct and own structures until they are no longer useful and then decide to either redevelop the area or release it to another business to develop if they cannot do so (such as lacking the financial resources). Housing and small shops will be as high density as possible to leave as much land open for future farmland or left fallow for ecological purposes. Private construction is likely to be left to private entities but the government can assist using new web technologies to provide a simple platform for open construction bidding (probably most useful for housing projects). Government construction projects would strictly be required to be done under the openness of the Internet to prevent as much corruption as possible (although this by itself will not eliminate corruption it gives a handy paper trial for the auditor general).


Rationale:
The primary rationale is to have individuals pay for the actual cost of what they purchase.  As structures become older and require greater repairs to keep stable, they will depreciate in value rather than appreciate, eliminating a strange economic phenomena in current society in which housing of lower quality can sell for a higher price than housing of a higher quality.

Property values and house prices do not track with neighbourhood conditions any longer.  Instead, it tracks with exactly the quality of housing.  Much like buying a cast iron pot in Richmond is not any different from buying the exact same cast iron pot in Scarborough, buying houses of the same quality will not shift in price.  Land value would normally increase or decrease with respect to community conditions (such as crime or school quality) but Canada is meant to be a country of equal opportunity.  No matter where you are born or raised, you should have the same opportunities.  Property taxes will likely be replaced with a slight increase in a combination of sales tax, income tax and corporate tax rates (likely easiest to simply raise the highest income tax bracket, or increase sales tax slightly or hike large corporate tax rates, all of which probably requires a fraction of a percent increase to cover the loss of property tax income).  Or property taxes are simply flat, based on the square footing of property owned, used to pay for services (waste collection, sewage/water, snow removal).  Ideally, roads/school would be handled solely by the province/state in order to more evenly distribute financial resources.


Tools:

Anywhere it says "Statistics Canada" replace it with Bureau of Statistics for the United States and pretend that the department has already been formed in the United States Government.
Statistics Canada should begin to track housing prices and the associated portion of the price being the price of the land of the property rather than the housing itself.  This gives a good sense of how much money is actually going into labour/material costs of building these structures.
Housing prices are already tracked by various real estate agencies, so whether Statistics Canada tracks housing prices for stability issues may not matter.

There should already be statistics on house ownership but it would be good to keep track of house ownership quality (rooms in a house, square footage, lot size and amenities).  This would require a return to the mandatory long form census, which will hopefully return in the event of a more scientifically-minded Canadian government coming to power in the future.

It would be nice for government structures to depend only on material/labour cost to construct once land has been purchased by the government.