I appreciate first stabs at improvements in governance; upvoted. Would I be correct in inferring you are thinking about this largely through a computer science lens, rather than an economic one?
What do you think about dealing with price discontinuities? I have in mind things like: major housing development in formerly rural areas due to urban expansion; the construction of a new industrial facility; the discovery of natural resources beneath the land; the major local industry collapsing; critical infrastructure failures like the water supply being contaminated.
I’m confused about the relationship between the bids on the property (the value) and the output of the prediction engine (the predicted value) as a consequence of the above. It looks like the prediction software is designed to exclude price discontinuities in its value estimate, which is how it preserves the incentive to improve the land; but this means we are systematically predicting wrong on purpose, which feels weird. The bids themselves don’t appear to have any importance.
Would I be correct in inferring you are thinking about this largely through a computer science lens, rather than an economic one?
I don’t really know what lenses are… but I am a computer scientist.
If a formerly rural area is developed, they *should* be paying taxes as if the land’s only value was as rural land, at least until nearby land gets developed too. I don’t understand what the industrial facility example is illustrating, unless its the opposite of “local industry collapse”. Time discontinuities like the local water supply being contaminated or a local industry collapsing aren’t a problem at all, since the value of neighboring properties goes down, so the predicted value of the property probably will as well. If you mean the water supply only to that property becomes contaminated, then if it’s not their fault, they can sue, and if it is their fault, their tax burden shouldn’t go down.
The bids themselves are just a system by which the market value of every property can be discovered and aggregated.
Should undevelopable land adjacent to a formerly rural developed area pay taxes as though it were developed, while giving the developed adjacent land two tax breaks?
If the land is undevelopable, it doesn’t really matter who does what with it. If the tax exceeds the value anyone can get out of it, it will default to the government (who will always buy land at $0). The government may not be a great land manager, but there’s nothing to be done with this land anyway. If there’s rural land nearby that is developable, maybe the land is actually a bit more valuable than the way it is currently being used, so it’s not such a problem if the property tax is higher.
“Undevelopable” does not mean “utterly without use”. An area that can’t be paved over and built up because it would cause watershed damage might still be usable for grazing cattle. A city block surrounded by blocks that have variances from the building height code is worth less, not worthless.
A lens is a more structured form of perspective, the way we use the term in the community; the emphasis is on being able to move between different ones. We tend to use it for different analytical frameworks (CS, econ, engineering, finance, etc).
The industrial facility effects will be variable depending on what the facility is. For example, a nuclear power plant or a microchip factory will tend to increase property values because of an influx of good paying jobs but a coal power plant or a meat factory will tend to decrease property values because they reek and are miserable to live near.
But the broader point is that the predictions are based on the price history of the last 10 years, when there was no such major price impact. I expect the prediction software to continue predicting stable prices, which means the people who live with a new meat factory are paying taxes based on too high a value, and the people who live next to a new microchip factory are paying based on too low a value. These would eventually even out as the actual sales enter the price history, but this is a long lead time. I also expect that the price would be distorted by the understanding that some places are tax bargains, and some tax banes, which would extend the time for the predictions to correct back to true value.
It looks to me like the same mechanism that preserves the incentive to improve your land works to exclude significant changes in land value more generally; all the directions I can envision for solving this look suspiciously like solving the problem of assessing the unimproved value of land.
But the broader point is that the predictions are based on the price history of the last 10 years
This is just extra information. If you don’t think it will be of much additional use beyond the information about the current prices of neighboring properties, then you’d predict that the best predictors will ignore the historical data. To be sure, no one is forcing the predictors to just output the mean property value of neighbors’ properties over the last 10 years.
the understanding that some places are tax bargains
If a whole neighborhood is understood to be a tax bargain, prices will go up, and so will the taxes. (Good predictors will probably focus mostly on these new prices of the neighbors’ properties).
It looks to me like the same mechanism that preserves the incentive to improve your land works to exclude significant changes in land value more generally
If I build a microchip factory on empty land, the value of my property goes up by a much larger factor than the value of neighboring properties. And it is the increase in the value of neighboring properties that (roughly) determines the increase in property tax I pay. So I don’t quite get to keep 100% of the value I created for myself, but I think it’s close to 100%.
Okay that makes sense, but now I’m confused on exactly how the real prices relate to the predictions. I expect the details of that mechanism to be the crux of the issue; exactly how the price updating is done will determine who the winners and losers are relative to the desired outcome.
It still feels like solving that problem well would be tantamount to solving the unimproved value problem, but I’m perfectly happy to be wrong.
I appreciate first stabs at improvements in governance; upvoted. Would I be correct in inferring you are thinking about this largely through a computer science lens, rather than an economic one?
What do you think about dealing with price discontinuities? I have in mind things like: major housing development in formerly rural areas due to urban expansion; the construction of a new industrial facility; the discovery of natural resources beneath the land; the major local industry collapsing; critical infrastructure failures like the water supply being contaminated.
I’m confused about the relationship between the bids on the property (the value) and the output of the prediction engine (the predicted value) as a consequence of the above. It looks like the prediction software is designed to exclude price discontinuities in its value estimate, which is how it preserves the incentive to improve the land; but this means we are systematically predicting wrong on purpose, which feels weird. The bids themselves don’t appear to have any importance.
I don’t really know what lenses are… but I am a computer scientist.
If a formerly rural area is developed, they *should* be paying taxes as if the land’s only value was as rural land, at least until nearby land gets developed too. I don’t understand what the industrial facility example is illustrating, unless its the opposite of “local industry collapse”. Time discontinuities like the local water supply being contaminated or a local industry collapsing aren’t a problem at all, since the value of neighboring properties goes down, so the predicted value of the property probably will as well. If you mean the water supply only to that property becomes contaminated, then if it’s not their fault, they can sue, and if it is their fault, their tax burden shouldn’t go down.
The bids themselves are just a system by which the market value of every property can be discovered and aggregated.
Should undevelopable land adjacent to a formerly rural developed area pay taxes as though it were developed, while giving the developed adjacent land two tax breaks?
If the land is undevelopable, it doesn’t really matter who does what with it. If the tax exceeds the value anyone can get out of it, it will default to the government (who will always buy land at $0). The government may not be a great land manager, but there’s nothing to be done with this land anyway. If there’s rural land nearby that is developable, maybe the land is actually a bit more valuable than the way it is currently being used, so it’s not such a problem if the property tax is higher.
“Undevelopable” does not mean “utterly without use”. An area that can’t be paved over and built up because it would cause watershed damage might still be usable for grazing cattle. A city block surrounded by blocks that have variances from the building height code is worth less, not worthless.
A lens is a more structured form of perspective, the way we use the term in the community; the emphasis is on being able to move between different ones. We tend to use it for different analytical frameworks (CS, econ, engineering, finance, etc).
The industrial facility effects will be variable depending on what the facility is. For example, a nuclear power plant or a microchip factory will tend to increase property values because of an influx of good paying jobs but a coal power plant or a meat factory will tend to decrease property values because they reek and are miserable to live near.
But the broader point is that the predictions are based on the price history of the last 10 years, when there was no such major price impact. I expect the prediction software to continue predicting stable prices, which means the people who live with a new meat factory are paying taxes based on too high a value, and the people who live next to a new microchip factory are paying based on too low a value. These would eventually even out as the actual sales enter the price history, but this is a long lead time. I also expect that the price would be distorted by the understanding that some places are tax bargains, and some tax banes, which would extend the time for the predictions to correct back to true value.
It looks to me like the same mechanism that preserves the incentive to improve your land works to exclude significant changes in land value more generally; all the directions I can envision for solving this look suspiciously like solving the problem of assessing the unimproved value of land.
This is just extra information. If you don’t think it will be of much additional use beyond the information about the current prices of neighboring properties, then you’d predict that the best predictors will ignore the historical data. To be sure, no one is forcing the predictors to just output the mean property value of neighbors’ properties over the last 10 years.
If a whole neighborhood is understood to be a tax bargain, prices will go up, and so will the taxes. (Good predictors will probably focus mostly on these new prices of the neighbors’ properties).
If I build a microchip factory on empty land, the value of my property goes up by a much larger factor than the value of neighboring properties. And it is the increase in the value of neighboring properties that (roughly) determines the increase in property tax I pay. So I don’t quite get to keep 100% of the value I created for myself, but I think it’s close to 100%.
Okay that makes sense, but now I’m confused on exactly how the real prices relate to the predictions. I expect the details of that mechanism to be the crux of the issue; exactly how the price updating is done will determine who the winners and losers are relative to the desired outcome.
It still feels like solving that problem well would be tantamount to solving the unimproved value problem, but I’m perfectly happy to be wrong.
Well bidders bid for the property, so they’ll “update” the prices by making higher or lower bids. And the predictions just use those bids as data.