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Archive => Which State? => Topic started by: JasonPSorens on January 07, 2003, 01:12:48 pm

Title: Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 07, 2003, 01:12:48 pm
The spreadsheet has been updated with new figures from the State Data page:
http://www.freestateproject.org/files/statecomparisons.xls
http://www.freestateproject.org/files/statecomparisons2.xls (Mac friendly version)

I've also written an essay using the new data to analyze the prospects for each state.  I don't argue for a single state as "best"; rather, I show what you would need to argue in order to argue that each state is best.
http://freestateproject.org/stateanalysis2.htm
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 08, 2003, 12:51:38 am
Thanks for the refresh on this matrix, Jason. Looks like you put a lot of work into it, and your analysis. I will now shoot holes through all your arguments.   :)

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If this analysis succeeds in its purpose, henceforth debates about the state the FSP should choose will be driven by certain regular arguments and considerations.

Quite the optimist, aren't you?  :D

The problems with the analysis or spreadsheet follows:
 
1) As Ted and I have discussed, the normalization function is, in our opinion, wrong. Therefore he and I (and others who agree with us) will have to rework the spreadsheet for our own normalization function, and we may come to different conclusions than you have, in the bottom section of your paper.

2) Still many rows of data missing, not even all of the items on the state data page, let alone all of the others that have been subsequently discovered (things like number of NEA members, a big item).

3) Urb row uses gross urbanization rather than the better measure which we discussed on that other thread. If we had a state with nothing but farms, it would be rated the best even though that is questionable given the high cost of campaigns that would result. Urbanization needs to be weighed heavily, too.

4) Some possible variables are quite important, yet hardly quantifiable. For example, land owned by federal government - a useful irritation factor, yet it can get to the point there is little private land available and therefore too much of a good thing.

5) FYI, the jobs criterion has a pretty good correllation with voting population (the only large deviation for this correlation is Maine, which has poor job creation considering its large population). Therefore if you want small voting population you must accept low job creation. But with low population, you don't need as many FSPers to affect things, so the tradeoff is acceptable. However, with the changes we hope to make to the state, we should drive job creation higher than projections, which will help us to support more FSPers. However, if we went into a high population/high job creation state, our positive economic effect will not help us (there already being enough jobs to support all FSPers) and may hurt us (driving the population even higher, including immigration of statists). So for FSP, it seems a low population/low job creation state would be better than a high population/high job creation state. One other point about job creation: we may have a significant percentage of retirees or people who can live with no visible source of income.  ;)  So maybe we don't need 20,000 jobs. Actually we may have two FSPers in a one-income family - has that been considered?

Another problem with Maine is its large population of NEA members (and probably a leftist-leaning teacher population as well). 18,288 of them, quite a large number of activist opponents (over 3 times as many as Wyoming's 5713). To me, Maine really seems to be out.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 08, 2003, 09:39:13 am

1) As Ted and I have discussed, the normalization function is, in our opinion, wrong. Therefore he and I (and others who agree with us) will have to rework the spreadsheet for our own normalization function, and we may come to different conclusions than you have, in the bottom section of your paper.

Well, the normalization function is right ;), but even if it weren't, your solution should yield exactly the same results, assuming that you've transformed the weightings correctly.

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2) Still many rows of data missing, not even all of the items on the state data page, let alone all of the others that have been subsequently discovered (things like number of NEA members, a big item).

I think it contains the most important items, but of course we could always add new ones.  Just think of those new variables as "non-quantifiable" factors in my analysis.  You can take them all roughly into account while looking at what we get with the numbers already there.

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3) Urb row uses gross urbanization rather than the better measure which we discussed on that other thread. If we had a state with nothing but farms, it would be rated the best even though that is questionable given the high cost of campaigns that would result. Urbanization needs to be weighed heavily, too.

I'll try out "urbanized areas" too, though I'm not convinced by your argument that urban clusters are not equally bad, politically.  I'm leery of expanding the # of variables to the point that the spreadsheet becomes unwieldy to the average user.  But the fact is that a couple more variables here or there make little difference in the final results. ;)

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4) Some possible variables are quite important, yet hardly quantifiable. For example, land owned by federal government - a useful irritation factor, yet it can get to the point there is little private land available and therefore too much of a good thing.

Both amount of private land and federal land ownership are quantifiable.

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5) FYI, the jobs criterion has a pretty good correllation with voting population (the only large deviation for this correlation is Maine, which has poor job creation considering its large population). Therefore if you want small voting population you must accept low job creation. But with low population, you don't need as many FSPers to affect things, so the tradeoff is acceptable. However, with the changes we hope to make to the state, we should drive job creation higher than projections, which will help us to support more FSPers. However, if we went into a high population/high job creation state, our positive economic effect will not help us (there already being enough jobs to support all FSPers) and may hurt us (driving the population even higher, including immigration of statists). So for FSP, it seems a low population/low job creation state would be better than a high population/high job creation state. One other point about job creation: we may have a significant percentage of retirees or people who can live with no visible source of income.  ;)  So maybe we don't need 20,000 jobs. Actually we may have two FSPers in a one-income family - has that been considered?

Well, and there may be one FSPer in a 2-income family in a lot of cases... Job creation does correlate with voting population, but when you run a regression line between the two, some states fall above the line and some below.  Idaho is way above the line, and WY, ND, and VT are a little below the line, meaning they get less job creation than they should for their size.  However, I'm not convinced this is a deal-breaker for those states, since fewer than 20,000 may end up moving.  The purpose of my analysis was simply to show both sides: what would be the case if you thought that was a deal-breaker, and what would be the case if you thought that was not a deal-breaker.
Title: Re:Re-Examination of the Spreadsheet
Post by: TedApelt on January 08, 2003, 12:27:27 pm
Well, the normalization function is right ;), but even if it weren't, your solution should yield exactly the same results, assuming that you've transformed the weightings correctly.

Where exactly did you get the "normalization function"?  I have never heard of that before.  How is this normally used?

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Quote
2) Still many rows of data missing, not even all of the items on the state data page, let alone all of the others that have been subsequently discovered (things like number of NEA members, a big item).

I think it contains the most important items, but of course we could always add new ones.  Just think of those new variables as "non-quantifiable" factors in my analysis.  You can take them all roughly into account while looking at what we get with the numbers already there.


I would like to see:

1.  Climate (done somewhat the way geography is done)
2.  The distance that must be driven to reach half the population.  This data can be gotten from another thread.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 08, 2003, 01:17:34 pm
Where exactly did you get the "normalization function"?  I have never heard of that before.  How is this normally used?

It's frequently used in statistics whenever you need to rebase variables so that they can be compared to each other.  It isn't the only normalization function you can use, but it has some advantages, such as being unaffected by scale.

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I would like to see:

1.  Climate (done somewhat the way geography is done)
2.  The distance that must be driven to reach half the population.  This data can be gotten from another thread.


OK.  The wish list is getting long... ;)

Maybe the appropriate solution is to create 1 small spreadsheet with only the 'most important' variables and then 1 big one with everything that might be useful.
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 08, 2003, 04:47:12 pm
I am working on an "everything but the kitchen sink" spreadsheet, so you don't have to add these requested rows to the old one. I have already taken every item on the state data page and put that into it (I realize some of those items are either derived or not so interesting, but I got it all for the sake of completeness). I will now start looking through the threads for other criteria. In general most of this stuff will be turned off via weight=0, so it doesn't add too much to the confusion, but it will be there for use if people want it.

I am also doing the normalization within the sheet, using Ted's normalization. You can replace that with your own easily enough, Jason, with a cut and paste. The advantage of doing the normalization in the sheet (besides avoiding errors) is that with the raw data in the sheet, rows can be replaced with updated raw data as that becomes available, and adding new rows is straightforward.

BTW my updated version of Ted's normalization allows for middle values as most desireable. An example might be state area, where DE is too small for various reasons, and AK way too large. I personally picked a size between ME and ND. This column will be available for modification if others (Ted, for instance likes really small states  ;)  ) have different criteria for goodness.

If people would point me at the various threads with their favorite additional criteria, it would be a help.
Title: Re:Re-Examination of the Spreadsheet
Post by: TedApelt on January 08, 2003, 05:14:04 pm
Where exactly did you get the "normalization function"?  I have never heard of that before.  How is this normally used?

It's frequently used in statistics whenever you need to rebase variables so that they can be compared to each other.  It isn't the only normalization function you can use, but it has some advantages, such as being unaffected by scale.

Isn't there a problem with small differences being magnified?

Quote

Maybe the appropriate solution is to create 1 small spreadsheet with only the 'most important' variables and then 1 big one with everything that might be useful.

I like that idea.  Another thing you could do is have a spreadsheet that only has states that have enough jobs or something else that is very critical.

For example, right now, I have eliminated WY, ND, and VT from further consideration, because if we can't get enough jobs in those states the project will fail.  I also think that we will never get 20,000 people if ND or AK is chosen.  (I'm also unsure how many jobs we can get in AK, because of the kind of jobs you get there.  Also, many AK jobs are highly seasonal.)  This leaves six states - DE, SD, MT, ID, NH, ME.  Since three are western and three are eastern, it seems to be a pretty fair mix.

Of course, once the state is chosen, you still might have those who have opted out of it to start a FSP in another state.  In that case, they might pick WY if an eastern state is chosen and they don't want to go east, or VT if a western state is chosen and they don't want to go west.  (In each case they might concentrate on a county.)  If that happened, there would be fewer people, and the lack of jobs might not be such a problem.

Title: Re:Re-Examination of the Spreadsheet
Post by: TedApelt on January 08, 2003, 05:29:02 pm

If people would point me at the various threads with their favorite additional criteria, it would be a help.

These are good:

http://forum.freestateproject.org/index.php?board=5;action=display;threadid=1137
http://forum.freestateproject.org/index.php?board=5;action=display;threadid=569
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 08, 2003, 06:50:42 pm
Quote
Well, the normalization function is right , but even if it weren't, your solution should yield exactly the same results, assuming that you've transformed the weightings correctly.

Well, they don't yield the same results, that is my problem with the 10-0 system.

Take this example. We are down to two states, A and B, and 3 equally-important criteria (in an abstract sense), a, b and c. Let's further state that A is (very) slightly less good on criteria a and b, and B is very much less good on criterion c.

The correct answer is state A, of course; we know that intuitively. And that is what Ted's normalization gives, with no fudging of weights (which we assume here are all 1):

  Criteria ->         a       b       c         Total
State A              9.9   9.9      10        29.8
State B              10     10       2         22


The 10-0 normalization gives the wrong answer, State B:

  Criteria ->         a       b       c         Total
State A               0       0      10         10
State B              10     10        0         20

Now you will say, we need to boost the weight for criterion c (or depress a and b) to give the right answer, and of course we can do that. But this is a simple example, we already know what the right answer is intuitively, so we pick the appropriate criterion and keep boosting away until the spreadsheet yields the correct answer.

But then, why bother with the spreadsheet? The whole point of the thing is for it to tell us the right answer, not the other way around. We don't know the right answer, and we don't know which criteria weight to fudge and how much, and anyway when we are fudging to get one state in line we inadvertently get another state out of line, so the whole thing becomes an unwieldy mess.

Sorry, Jason, I just don't believe the function of weights is to compensate for unhelpful normalizations. It is to decide what is important to you, and that's it.

you wrote in that other thread,
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I don't think it's possible to consider how to weight variables without some knowledge of the base numbers & what they mean.
OK, I'll buy that, now that I think about it. You can get some idea what your weight should be by knowing what the data are saying. But that is a far cry from fudging them to compensate for inadvertently having knocked a viable state out of contention!

You also wrote this:
Quote
But even if you think you should just consider variables abstractly to determine their weightings, the current method of interpolation is better than Ted's suggested method, which requires not just a consideration of the variables' importance "abstractly" or "in themselves" but also how the scale of the base variable is affecting the transformation of the data."
I don't know what that means. The normalization is supposed to deal with the scale.

You wrote this, which I didn't look at too closely at the time:
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But Ted's solution can create paradoxes if you're not very sophisticated about the way in which you do the ranking.  For example, imagine the ranking is "government ownership above 48%."  Then state A scores 2% and state B scores 1% even though the fundamental, underlying concept is the same.  Ted's solution would give B a 5 and A a 10.  But any good normalization should not change if the scale of the fundamental variable changes.
Examining this again, I see that your implementation of Ted's method in fact does give a more reasonable result. The 10-0 algorithm would assign a 10 to A and a 0 to B. A and B are really near equivalent, and Ted's algorithm more closely approximates that reality than the 10-0 algorithm does. But of course the real way this would be normalized would be proportionately (referenced to 0, not 48), with a simple extra provision that zero is returned if the value is 48 or under.

I will provide in my cut of the spreadsheet, a cell with a 10-0 algorithm so you can cut and paste it as you like.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 08, 2003, 07:09:41 pm
Isn't there a problem with small differences being magnified?

Well, it depends on the context.  Since we're adding together variables, the appropriate way to deal with that is to give a very small weighting to variables where the substantive differences are very small.  There's no non-arbitrary way to deal with the substantiveness of differences.  Creating a scale based on 0 to highest value is just as arbitrary as creating a scale based on lowest to highest value.  Neither method is wrong; you just have to be clever about how you assign the weightings.

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For example, right now, I have eliminated WY, ND, and VT from further consideration, because if we can't get enough jobs in those states the project will fail.

Well, that's a legitimate view, but a very controversial one of course!  The counterargument is that if fewer than 20,000 people move, we can still have big political influence in these states & jobs may be available for all those who do move.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 08, 2003, 07:30:03 pm

Well, they don't yield the same results, that is my problem with the 10-0 system.

They do if you weight the criteria a and b in your example very small. ;)  Neither method is wrong, but if we use Ted's method, then we have to be equally clever about the weightings.  For example, if states are scored 0-10 on my normalization on a very important variable, but they're scored 3.5 to 10 on Ted's normalization, then using Ted's spreadsheet we should give that variable 65% of the weighting that we gave it on my spreadsheet.  More fundamentally, Ted's normalization doesn't take substantive differences into account any more than mine does. You've created your example so that the difference between 9.9 and 10 or 9 and 10 is the same no matter what raw variable you're looking at.  But maybe the difference between 9 and 10 on variable a is more important or relevant than the difference between 5 and 10 on variable b.

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Sorry, Jason, I just don't believe the function of weights is to compensate for unhelpful normalizations. It is to decide what is important to you, and that's it.

But this is impossible to do in abstraction.  You have to look at what the raw variables mean substantively.  Weightings cannot, under any normalization system, have to do simply with how important you think that variable is, without knowing something about what those data look like.  

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Quote
I don't think it's possible to consider how to weight variables without some knowledge of the base numbers & what they mean.
OK, I'll buy that, now that I think about it. You can get some idea what your weight should be by knowing what the data are saying. But that is a far cry from fudging them to compensate for inadvertently having knocked a viable state out of contention!

But it's not fudging.  You're basing the weighting on how important you think the differences among the states are.  Maybe states vary from 5 to 5 billion on some raw measure.  But maybe that kind of difference is not very important.  So you give it a low weighting.  That's how it works: you weight the variables on the basis of how important you perceive the observed variation to be.  No fudging involved.  Let me use an example directly from the State Data page.  How important is state & local government spending?  Well, moderately important, I guess.  It's a cultural factor.  So we look at the data: 6.2% of state GDP to 10.8%.  Those are some moderate but probably meaningful differences.  So we give the variable a medium-to-low weighting.  But imagine now that there are some pure communist states under consideration, with spending as % of GDP up around 70%.  Suddenly this variable becomes quite important: we don't want to pick a communist state!  So we give the variable a higher weighting, after normalization of course.  Now imagine the reverse: state government spending ranges from just 6.2 to 6.3% of GDP.  We decide that's not meaningful variation, and we give the variable a very low weighting.  That's exactly what I'm suggesting we do with the spreadsheet: and we will have to do that no matter what normalization method is used, Ted's or mine.  You automatically have to consider the range of data before making a weighting decision: that's not fudging, and there's no way around it.

Quote
You also wrote this:
Quote
But even if you think you should just consider variables abstractly to determine their weightings, the current method of interpolation is better than Ted's suggested method, which requires not just a consideration of the variables' importance "abstractly" or "in themselves" but also how the scale of the base variable is affecting the transformation of the data."
I don't know what that means. The normalization is supposed to deal with the scale.

Ted's method assumes that 0 is the natural minimum.  It's arbitrary to scale.  But some variables may have possible negatives, or maybe they have above-zero floors.  Population density is an example of this: a population density of zero is impossible.  Hence the example below...

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You wrote this, which I didn't look at too closely at the time:
Quote
But Ted's solution can create paradoxes if you're not very sophisticated about the way in which you do the ranking.  For example, imagine the ranking is "government ownership above 48%."  Then state A scores 2% and state B scores 1% even though the fundamental, underlying concept is the same.  Ted's solution would give B a 5 and A a 10.  But any good normalization should not change if the scale of the fundamental variable changes.
Examining this again, I see that your implementation of Ted's method in fact does give a more reasonable result. The 10-0 algorithm would assign a 10 to A and a 0 to B. A and B are really near equivalent, and Ted's algorithm more closely approximates that reality than the 10-0 algorithm does. But of course the real way this would be normalized would be proportionately (referenced to 0, not 48), with a simple extra provision that zero is returned if the value is 48 or under.

Well, I was working with an example you gave of states that are very close together.  But why should 0 be the reference point?  In my view, the appropriate reference point is whatever the lowest value is.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 08, 2003, 07:42:27 pm
Here's an example of how Ted's normalization method can trap the unwary, using actual State Data numbers.

Let's suppose in a very abstract sense you consider gun freedom and # of jobs to be equally important variables, and you give them both a weighting of 2 on this basis, assuming that the spreadsheet allows you to make this judgement on the basis of an abstract consideration of the variables.

The spreadsheet you're creating will yield the following values for the high and low states on the gun freedom and jobs variables:

Top on gun freedom: New Hampshire, 10
Bottom on gun freedom: Delaware, 6.7
Top on jobs: Idaho, 10
Bottom on jobs: Wyoming, 1.7

If you give an equal weighting to both, then Wyoming gets hurt bad, and Delaware doesn't get hurt much.  But then you look at the raw data.  Even though the differences in gun ratings are small, from Delaware at 7 to New Hampshire at 10.5, they represent pretty substantial departures in policy on the most important gun issue, concealed carry.  So those differences are important.  By contrast, you look at the jobs variable and (let's suppose) realize that all states have enough jobs and that Idaho's benefit in this area is superfluous.  If that's your view, then you want to rate gun freedom a good bit higher than jobs, but if the person hadn't looked at the raw data & assumed that there were real differences that matter among the states in jobs, then your spreadsheet would yield the exact wrong result.  The fatal assumption is that the difference between 6.7 and 10 on one variable is substantively less than the difference between 1.7 and 10 on another.

So you always have to look at the raw data to determine a weighting, whether you use Ted's normalization procedure or mine to create the spreadsheet.
Title: Re:Re-Examination of the Spreadsheet
Post by: TedApelt on January 08, 2003, 10:43:29 pm
Before I say anything else, I would like to say that I have always considered myself pretty good on number logic, ways of measuring things, and statistical fallicies that trip people up.

Having said that, I must admit to being over my head now.  I am befuddled.

The only thing I can think of is that bright mathematicians before me must have studied this problem many years, probably even centuries, before and have come up with the answer.  Can someone quote me it from a statistics book or other book that deals with this very thing?
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 09, 2003, 02:20:26 am
Ted, I'm beginning to get the impression you have a "hard science" background, like me. This is not hard science, it is pretty mooshy, with lots of guesses and judgement calls. So we are having difficulty with this point (I don't think it's math, but some soft science like social studies or whatever the terminology is these days). But I'm getting a faint glimmering at what Jason is talking about.

Well, since as Jason pointed out, the two normalizations will yield the same results given that you compensate appropriately with the weighing, and that you do have to fiddle with it, then I might just stick with yours anyway since it is easier to put into the spreadsheet!

Unless Jason slaps me around again.  ;)
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 09, 2003, 09:23:17 am
haha I don't mean to slap you around. ;)  I guess this is more 'soft science' since the hard sciences don't often rely on tallying up variables to make predictions.  If the initial conditions hold, the result is a given, in the hard sciences.  If there's demand for it, I can ask around statistical circles to see what they say.
Title: Re:Re-Examination of the Spreadsheet
Post by: TedApelt on January 09, 2003, 12:06:39 pm
haha I don't mean to slap you around. ;)  I guess this is more 'soft science' since the hard sciences don't often rely on tallying up variables to make predictions.  If the initial conditions hold, the result is a given, in the hard sciences.  If there's demand for it, I can ask around statistical circles to see what they say.

True, most of my background is in astronomy, engineering, and physics.

Please ask around statistical circles, as well as people who study how to make rational business decisions.

I am reminded about the time I was fooling around with my computer many years ago, and "discovered" a revolutionary new system of mapping coordinates I called "rotatable grids".  Worked at it a long time.  Later, I found out that it was called "polar coordinates", and was centuries old.

I have a feeling the same thing is happening here.  The math is out there.  I'm sure that we are not the first to need it.  I am sure that other people before us have solved problems simular to ours, and came up with a method that works.  Let's find out what they did.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 09, 2003, 01:26:51 pm
A-ha!  I've found something.  Check this out:
http://www.cis.hut.fi/Opinnot/T-61.181/s99/presentations/oct27_MK.ppt

It's a Powerpoint presentation by a Finnish computer & information scientist named Markus Koskela.  The first normalization method he deals with is called "linear scaling transform," which exactly what I've done in my spreadsheet, but on a 0-1 instead of 0-10 scale.  The advantages of this method:

* introduces no distortion to the variable distribution
* has a one-to-one relationship between the original and normalized values

However, there is a caveat:

"In data preparation, the data used is only a sample of the population.  Therefore, it is not certain that the actual minimum and maximum values of the variable have been discovered when minimizing the ranges.  If some values that turn up later in the mining process are outside the limits discovered in the sample, they are called out of range values."

But we do have the whole population in this case, because we are interested only in the 10 candidate states.  This presentation is given in the contest of "mining" for data to get a sample population when it is impossible to get data on the full population.  We will never have any out-of-range values because the population we're looking at is fixed.

The presentation also deals with how to fix skewed distributions: this is mostly a problem in statistical applications assuming a normal distribution, for example, regression analysis.  So we don't need to worry about that.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 09, 2003, 03:03:22 pm
Taking the cue from Zxcv, I've expanded the spreadsheet to contain quite a few more rows, and I've added some more variables to the State Data page too.
http://www.freestateproject.org/files/statecomparisons.xls
http://www.freestateproject.org/files/statecomparisons2.xls
(Macs)
http://www.freestateproject.org/state.htm
Finally, I've updated my latest analysis:
http://www.freestateproject.org/stateanalysis2.htm

Delaware generally does worse with the new data (at least, how I've weighted them), while Montana and Wyoming do better.  The reason for this is probably the inclusion of federal land % as a good thing and absolute amount of private land as a good thing.  If you differ with these interpretations, you should give these variables a negative weighting.

I haven't announced these new files on the front page of the website yet, because I want to make sure they will stay in reasonably the same form for a little while. ;)
Title: Re:Re-Examination of the Spreadsheet
Post by: freedomroad on January 09, 2003, 04:28:51 pm
Delaware generally does worse with the new data (at least, how I've weighted them), while Montana and Wyoming do better.  The reason for this is probably the inclusion of federal land % as a good thing and absolute amount of private land as a good thing.  If you differ with these interpretations, you should give these variables a negative weighting.

I like that many things are now being considered.  However, I changed it a little to make it more fair, IMHO.

I feel voter size is important but a 14 is just too high.  I lowered it to a 8.

 I think dependence is important but I think a 10 is just to high.  I lowered it to a 6.

I gave the two new sections of Federal land and private land a -1 for federal land ownership and a 1 for private land ownership.

I thought the entire geography part was poorly scored.
What Jason had "Geography   
ME 10
AK 10
DE 10
NH 7.5
ND 5
MT 5
VT 2.5
ID 2.5
SD 0
WY 0"

My geography rankings come from Weather, closeness to large cities, and least isolated from other states.
Higher numbers are better
Weather: DE 10, ID 8, MT 6, WY 6, NH 6, VT, 4, SD 4, ME 4, ND 0, AK 0
Closeness to large cities: DE 10, WY 7, NH 6, VT 5, ME 4, SD 4, ID 2, ND 2, MT 1, AK 0
Least isolated: DE 10, SD 6, WY 6, ID 5, NH 5, VT 3, MT 1, ND 1, ME 0, AK 0

States with a combined score of 30-26 = 10
States with a combined score of 25-20 = 7.5
States with a combined score of 19-12 = 5
States with a combined score of 13-8 = 2.5
States with a combined score less than 8 = 0
State scores:
DE = 30 = 10
WY = 19 = 5
NH = 17 = 5
ID = 15 = 5
SD = 14 = 5
VT = 12 = 2.5
ME = 8 = 0
MT = 8 = 0
ND = 3 = 0
AK = 0 = 0

(This arguement totally ignores the closeness to the ocean and CA arguements.  However, I do not find those arguements the least bit useful.

At the very least, I suggest Jason use the weather part on the actual spreadsheet.  I still think isolation from the rest of the state is very important.  Not many people will want to move to AK, ME, ND, or MT because they are so isolated from the rest of the states.  That means things will be more expensive in these states (certainly in AK), it will take longer and be more expensive to move to these states, and people will likely be more isolated from their family and old friends.)

After my 5 changes to make things more far, IMHO....

New top 6
WY = 365
DE = 331
VT = 325
SD = 304
ID = 301
NH = 294

The old top 6
WY = 463
AK = 411.5
DE = 411.1
VT = 405
ND = 376.7
ID = 376.5


Factors not included likely give WY another 5 points and take away 5 points from DE and VT.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 09, 2003, 07:38:45 pm
Remember that when you take away from # of voters & federal dependence, you start to make political culture more important for our purposes than Size or Viability - which I think is a tough argument to make, but I suppose it can be made.

You remind me about weather - I meant to include something about that.  Maybe use something like "average high in January in largest city" as a proxy for how cold a state is.
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 10, 2003, 01:26:34 am
Jason, some suggested changes before putting this matrix to bed, take 'em or leave 'em:

1) Group rows according to category. (To be honest, the categories seem to be arbitrary and meaningless to me. I am just going to ignore them when I use the matrix.)

2) Order states alphabetically (note, when new data rows are added they are most often arranged alphabetically, so it eases entry).

3) We still need a row for number of voting-age residents, a better indicator for the size of our task than the population or number of voters in the 2000 election (actually the latter is not bad if we don't stir up too much opposition, but voting-age population is if we do stir it up).

4) I'm a bit worried about the taxes row. There is some variation about what are called taxes. Oregon rates low in some measures of taxes because they hide their revenue-generation behind different terminology, and have a lot of "user fees". I can dig some more info up on this if you want.

5) I still don't like the fact I can't control "optimum value" as in my spreadsheet, because I don't agree (for example) that "UrbanClus" are bad, or that there is no such thing as a variable with a best value not at the extremes. For this reason alone I will keep using my spreadsheet, although I might mine yours for rows!   :)

6) Each row needs a reference to where the data was found.

7) The variable names in the sheet and on the state data page should be the same. I understand this causes problems as you are length-limited...

8 ) Your definition (cell comment) of urban clusters and urban areas needs more info (pop limits, etc) in spreadsheet, and also in state data page.

9) You could use the @RANK function underneath the ratings row; I've done this in mine.

10) If we are going to have a row for household income, we probably ought to have one for cost of living too, since low income states often correlate with low cost of living...

11) For that NEA row, I don't think you should use percentage of population (since they are not significant that way - that is, in throwing the vote due only to their portion of the vote), but number of NEA members (since they are activists we will be fighting).

12) You have some columns and rows bolded, I wonder why?

Quote
Delaware generally does worse with the new data (at least, how I've weighted them), while Montana and Wyoming do better.

In my sheet I got WY as strong winner followed by SD and ND. Now I'm happy.   :D

Before, I had DE in first place; now it's in 9th. Amazing what the addition of a few rows can do, ha ha. Makes me wonder if there aren't more rows we ought to have...
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 10, 2003, 01:48:44 am
Quote
True, most of my background is in astronomy, engineering, and physics.

Ted, if you are an astronomer, you should really like Wyoming. The state is half-way up through the pea soup, due to altitude, and there's not much light pollution either! Not much astronomy going on in Delaware, I bet.   ;)
Title: Re:Re-Examination of the Spreadsheet
Post by: Solitar on January 10, 2003, 02:51:27 am
For astronomers and plain old fans of dark skies, here are a couple maps.

This one showing actual nighttime view of USA.
http://www.darksky.org/ida/darksky/darksky_map.html

This one has a very fine resolution tiff file of all of North America, but it is huge -- 130MB.
You can zoom in from the web page or download the above file.
http://www.lightpollution.it/worldatlas/pages/fig1.htm

Delaware sucks.
Vermont is poor.
New Hampshire is better.
Central Maine is great -- as are the western states outside of the cities (which is another bad thing about cities. I can even zoom in and spot my little town of a few thousand on the second map above. There are three in a row in Colorado SW of Denver. Leadville, Buena Vista, and Salida.
What is that bright spot south of Gilette, Wyoming?
Oil fields, refinery, prison? (they light the latter up like daylight)

The following is a directory and map of "Dark Sky Sites" which have been evaluated for limiting magnitude. Just because a state has no sites does not mean it has no dark sky. Look at the western states vs eastern. Delaware folks had to identify a specific site.  Wyoming and North Maine folks have dark skies in their back yard -- unless they are in a city.
http://ourworld.compuserve.com/homepages/pharrington/Dssd.htm
Title: Re:Re-Examination of the Spreadsheet
Post by: Justin on January 10, 2003, 03:33:50 am
Woohoo!  My first post!  ;D


The following quote snippets from Jason got me thinking (rearranged to help make my point):

Quote
You're basing the weighting on how important you think the differences among the states are.  ... you weight the variables on the basis of how important you perceive the observed variation to be.

Quote
Maybe states vary from 5 to 5 billion on some raw measure.  ... So we look at the data: 6.2% of state GDP to 10.8%. … You automatically have to consider the range of data before making a weighting decision

And this is the result of my thoughts on this issue (though it might turn out to be my “rotatable grid”):

Quote
Pre-conditions: The dimensions being measured are quantitative in nature.  The goal of the resulting analysis of those dimensions is to determine “desirability”, and as such is inherently qualitative.

First postulate: the weight given to a dimension being measured is only valid when comparing dimensions that share a common range of desirability.

Second postulate: the range of desirability of any single dimension is a set bounded by “rational best value” and “rational worst value”, and is equal to, or a subset of, the set of all possible values.

Third postulate: values of the observed data set that fall outside the desirability set are counted as equal to the nearest desirability boundary.

What is this new kid talking about???

Basically it is an attempt at rational consistency.  What the current method lacks is a context in which to judge the desirability of a single dimension.  â€œLower is better”, “higher is worse” is insufficient since you effectively abstain from deciding what is best and worst, and leave it up to what exists. It is only after we actively decide upon a range of desirability for each dimension that we can begin to compare them within and against each other.

I’ll attempt to clarify by using some raw data from Jason’s spreadsheet.

Comparing crime and taxes for the states of AK, NH, and ME.

Raw data:
Quote
AKNHMEMinMax
Crime:42362322268823224236
Taxes:6.38.612.86.312.8


Current analysis (using min and max as best and worst, zero weighting) :
Quote
AKNHME
Crime:0.0010.008.09
Taxes:10.006.460.00
Total:5.008.234.05


The following are also normalized to fall between 0 and 10, inclusive.

Postulate analysis 1:
Quote
Rational Bounds (subjective, but independent of observation):
BestWorst
Crime:10005000
Taxes:315

Results:
AKNHME
Crime:1.916.705.78
Taxes:7.255.331.83
Total:4.586.023.81

Postulate analysis 2:
Quote
Rational Bounds:
BestWorst
Crime:10004000
Taxes:315

Results:
AKNHME
Crime:0.005.594.37
Taxes:7.255.331.83
Total:3.635.463.10

Postulate analysis 3:
Quote
Rational Bounds:
BestWorst
Crime:10005000
Taxes:310

Results:
AKNHME
Crime:1.916.705.78
Taxes:5.292.000.00
Total:3.604.352.89

In the postulate analyses, what we are now dealing with is a range of acceptable values, as opposed to the previous range of actual values.  Note the change in postulate results in the analysis where Crime has a worst case of 4000; this means that 4000 is so bad that we choose not to allow values over 4000 to make 4000 any more favorable.  Likewise, the last example shows the results of a worst-case 10% tax system.

In either analysis method the desirability of a dimension can be skewed by what defines the desirability bounds.  Given this, we must answer the question, “should the actual extremes determine what we perceive as best and worst?”  I say they should not.


Ok, it's waaaay past my bedtime...  but one more thing.

The pre-conditions state the the measurements must be quantitative.  This helps elucidate that there is a forced coupling in the current "Geography" measurement.  Properly decoupled, it should be broken down into "Miles of Coastline" and "Border with Canada." Each of these has a separate quantifiable range of possible values (the latter being boolean), neither of which depends on the other.  

Argh, I'm falling asleep.  I look forward to your responses.
Title: Re:Re-Examination of the Spreadsheet
Post by: phylinidaho on January 10, 2003, 07:26:40 am
Thanks Justin,
I have had a nagging discomfort with the spreadsheet from the beginning, but was unable to articulate my misgivings. Although I don't thoroughly understand your explanation (it has been too long since I studied statistics - given that age was already a factor at that time), I think that you are on the right track.

Phyllis  :)
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 10, 2003, 12:52:58 pm

1) Group rows according to category.

Good idea.

Quote
2) Order states alphabetically (note, when new data rows are added they are most often arranged alphabetically, so it eases entry).

Well, I have them grouped by their order on the State Data page - in the past, I've usually entered new data rows according to their arrangement on the State Data page, so that's easiest for me anyway... This arrangement is by voting population.

Quote
3) We still need a row for number of voting-age residents, a better indicator for the size of our task than the population or number of voters in the 2000 election (actually the latter is not bad if we don't stir up too much opposition, but voting-age population is if we do stir it up).

Yeah, maybe.  Total population includes both potential voters (voting-age population) and future voters (children).  So if we added voting population, we'd want to replace total population with non-voting population.

Quote
4) I'm a bit worried about the taxes row. There is some variation about what are called taxes. Oregon rates low in some measures of taxes because they hide their revenue-generation behind different terminology, and have a lot of "user fees". I can dig some more info up on this if you want.

Sure, do that.  The data I have are from the Tax Foundation & include fees.  However, they also tag Permanent Fund payments in Alaska as tax credits, so Alaska looks really low on taxes.  So I know there are some potential flaws there.

Quote
5) I still don't like the fact I can't control "optimum value" as in my spreadsheet, because I don't agree (for example) that "UrbanClus" are bad, or that there is no such thing as a variable with a best value not at the extremes. For this reason alone I will keep using my spreadsheet, although I might mine yours for rows!   :)

Well, for UrbanClus you can give a negative weighting.  Maybe in the Really Big, Sophisticated Spreadsheet that we might create there can be a column for picking an optimum value.  I just think that's asking too much of most people, who aren't knee-deep in this stuff.

Quote
6) Each row needs a reference to where the data was found.

Do you mean the source for the raw data?

Quote
7) The variable names in the sheet and on the state data page should be the same. I understand this causes problems as you are length-limited...

The variable names in the spreadsheet are longer & more descriptive than the State Data page, where we're seriously cramped for space; I supposed this wouldn't cause a problem, but maybe it does.

Quote
8 ) Your definition (cell comment) of urban clusters and urban areas needs more info (pop limits, etc) in spreadsheet, and also in state data page.

OK.

Quote
9) You could use the @RANK function underneath the ratings row; I've done this in mine.

Good idea.

Quote
10) If we are going to have a row for household income, we probably ought to have one for cost of living too, since low income states often correlate with low cost of living...

That's true.  I think the median household income figures do try to control for that, but I'll look into it.

Quote
11) For that NEA row, I don't think you should use percentage of population (since they are not significant that way - that is, in throwing the vote due only to their portion of the vote), but number of NEA members (since they are activists we will be fighting).

I thought you might say that. ;)  I wanted to distinguish between states that have lots of NEA members because they're pro-union and states that have lots of NEA members because they have high population.  If the latter, then you should be weighting the population variable more heavily.  It's arbitrary which way you do it, really.

Quote
12) You have some columns and rows bolded, I wonder why?

They are?  I believe I just have the total points row and the Weight column bolded.  Makes sense to me, as that's where the attention is drawn for the user.

Quote
In my sheet I got WY as strong winner followed by SD and ND. Now I'm happy.   :D

Before, I had DE in first place; now it's in 9th. Amazing what the addition of a few rows can do, ha ha. Makes me wonder if there aren't more rows we ought to have...

heh heh  Well, the rows we had left out were things that to date had not been considered very important.  However, they do systematically favor the West, since the interpretations are that more federal land & more private land are both good.  If you put heavy weights on these hitherto ignored variables, it's natural that your rankings would change dramatically.  If we can identify other variables that can legitimately be considered very important (& not "dependent" on existing variables), we should include them.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 10, 2003, 01:09:53 pm
Justin - you're right that in theory what we want is a range of acceptable values for each variable.  That's why we eliminated states over 1.5 million population: they were just beyond the pale.  However, relying on actual extremes for the variables in the spreadsheet is, I believe, desirable for several reasons:

1) Objectivity.  You can't argue with the data as given.  Acceptability ranges you can argue about, and there's not necessarily a right answer.  This makes it easy for people to manipulate the spreadsheet so that the state they already favored comes out on top.  The spreadsheet is designed to avoid this: to make the best states float to the top, even if they're counterintuitive.  Even now, though, some people trying to twist & manipulate the weightings in very odd ways to make the spreadsheet say what they want it to say.  Allowing people to specify acceptability ranges would exacerbate the problem severely.

2) Focus.  We're getting close to the period when we will need to vote on the best state.  Thus, it is becoming more and more desirable to focus our attention both on the most important variables & a single way in which to aggregate them.  Opening up more parameters disperses our focus and reduces the chance that we can agree on even a common way to approach the issue of selecting a single state.  It increases the chances of confusion reigning when it comes time to choose the state.

3) Parsimony.  The Principle of Parsimony is that when there are a complex and a simple method to reach an equally good result, you should use the simple method.  In this case, the Principle of Parsimony militates against using acceptability ranges, since of the variables left in the dataset, almost all the existing ranges are acceptable.  In other words, there is no crime rate that would be too high to be acceptable, of the crime rates in the dataset.  There is no tax rate that is too high to be acceptable.  Being high on these measures is bad, but these failings are ones that can be overcome.  Voting population & jobs are perhaps variables where some states may fall outside the range of acceptability - and some would say geography as well.  But these variables are few enough that you can take them into account by eyeballing the raw data.  "I think that state is just too large to be workable; I would eliminate it."

4) Difficulty.  For most people specifying weightings is good enough.  Asking them to specify optimum values, acceptability ranges, and so on is beyond their expertise or interest.  Maybe a Very Big & Complex Spreadsheet would be desirable, allowing people who are mathematically confident & very interested in the state research to manipulate parameters at will.  I am not opposed to creating such a spreadsheet at all.  But I think we also need to keep a simpler spreadsheet that everyone can use.
Title: Re:Re-Examination of the Spreadsheet
Post by: Justin on January 10, 2003, 03:19:41 pm
Quote
1) Objectivity.  You can't argue with the data as given.
True, but since we are attempting to extrapolate subjective meaning from the data, correctly identifying the subjective variables is paramount.


Quote
[Use of] Acceptability ranges ... makes it easy for people to manipulate the spreadsheet so that the state they already favored comes out on top.  ... Even now, though, some people trying to twist & manipulate the weightings in very odd ways to make the spreadsheet say what they want it to say.  Allowing people to specify acceptability ranges would exacerbate the problem severely.

I agree that complexity may increase (more on that later), but I also believe that the “odd ways” the weights are being used is directly due to the fact that is the only instrument being used to adjust value.  The problem here is there are two values, one for the desirability of something, and the other being how one thing compares to another.


Quote
Opening up more parameters disperses our focus and reduces the chance that we can agree on even a common way to approach the issue of selecting a single state.  

The alternative method does not open up more parameters, it just puts the value of those parameters in our hands.


Quote
The Principle of Parsimony is that when there are a complex and a simple method to reach an equally good result, you should use the simple method.

This requires an a priori judgment, since the “complex” method has not been proven to reach an equally good result.


Quote
In this case, the Principle of Parsimony militates against using acceptability ranges, since of the variables left in the dataset, almost all the existing ranges are acceptable.  In other words, there is no crime rate that would be too high to be acceptable, of the crime rates in the dataset.

The issue comes not when saying if something is “too” extreme, but rather when the acceptable range is sufficiently larger than the range of the observed data.  If you do not take into account the best and worst case (as opposed to min and max), then for a narrow oberved range, small variations can have large influences on the final result.


Quote
4) Difficulty.  For most people specifying weightings is good enough.

Given the issues with “odd” weightings I would disagree.  Even I, when confronted with only weights to indicate my preferences, found it the current method...stifling.


Quote
Maybe a Very Big & Complex Spreadsheet would be desirable, allowing people who are mathematically confident & very interested in the state research to manipulate parameters at will.

I think this puts an unnecessarily complex spin on it.  The net change of the method I propose would be to go to the “Best” and “Worst” column on the Raw Data page and enter in values you think are best and worst.  That’s it.

One slight issue with just changing values in the current spreadsheet is that the directionality of Best and Worst is predefined.  For instance, if I felt large coastlines were bad, I would want to put a small value for Best.  In this case, just negating the weight (without changing it’s magnitude) will effect the change.  The magnitude will still indicate the importance of this measurement over others.


Quote
I am not opposed to creating such a spreadsheet at all.  But I think we also need to keep a simpler spreadsheet that everyone can use.
Cool.  I agree we need to keep both, and I would be happy to work on this for/with you.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 10, 2003, 04:14:28 pm
Justin - How do you recommend coming up with Best and Worst values, apart from using observed min and max?  If there is a standard way of doing so, I'd be in favor of creating a new spreadsheet that allows you to do that.  The problem I foresee is that while disputes about "which state?" now hinge on weightings only, if we open up the ranges to unlimited tampering, then disputes about "which state?" will hinge on both weightings and range parameters, making it nearly hopeless to achieve consensus.
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 10, 2003, 04:19:39 pm
Jason, I believe you are correct, that we ought to keep things simple. It's just that personally, once I get into playing with spreadsheets, I can't stop!   :P

Another thing we should be doing (you said it more or less) is focussing on relatively few, important (and it's hoped, independent) variables. That is, instead of getting in big - and fruitless - arguments about the desireability of certain states, we should be arguing about what variables are important and what weight they should have. The state then falls out as a result.

This should tone down the subjective nature of the discussion, and eliminate at least some extraneous variables that are not really germane.

It's hard to argue weight because everyone has a different total weight (summed over all variables). That is one of the reasons I suggested having a total weight of 100; if we all had this baseline I could then argue that population should get a 15 or 20, and everyone would be understanding I mean it should get 15% or 20% of the total weight. It's like going into a candy store with 100 pennies - what are you going to buy with them?   ???

Quote
6) Each row needs a reference to where the data was found.
 

Do you mean the source for the raw data?


Yes. I added a wide column at the end of my raw data for the URL for the data. It's just a credibility matter. It's like footnotes in books, doubtful types like me need them...

Quote
Quote:
11) For that NEA row, I don't think you should use percentage of population (since they are not significant that way - that is, in throwing the vote due only to their portion of the vote), but number of NEA members (since they are activists we will be fighting).
 

I thought you might say that.   I wanted to distinguish between states that have lots of NEA members because they're pro-union and states that have lots of NEA members because they have high population.  If the latter, then you should be weighting the population variable more heavily.  It's arbitrary which way you do it, really.

I've mentioned this issue with you on some other variable, guess I'm getting predictable.

The way I am dealing with it is making two rows (in this case, NEA membership). One of them is percentage of population, the other is number of members. Then I take the weight I was going to apply to that variable and split it between the two rows. If I thought (as in this case), the actual number was more important than the percentage, I'd give the number row more weight. The point being, there are states with 1) high percentage and high number, 2) high percentage but low number (due to low overall population) 3) low percentage but high number, and 4) low percentage and low number. If a state is unfairly penalized by having a high percentage in a low overall population, the other row based on number will compensate.

I don't know if this is a good way to handle these variables, but it's how I handle them...

On the bolded columns and stuff, it might be the translation is funny. I am using Lotus 1-2-3.

On that UrbanClus and UrbanArea thing, if you are saying both of these are bad (i.e., less is better), then you are saying rural states are the best. Do we really think this? It would make campaigning hard, as some have mentioned, and drive our campaign efforts into high-expense paths like TV. Maybe it's too much to say Urban Clusters (which go only to 50,000 population after all) are bad. Perhaps it would make sense to keep the UrbanArea row (less is better), add a Rural row (<2500 population, and default it to "more is better"), and then just eliminate the Urban Clusters row altogether, thus treating it as more neutral. I think this would be understandable and salable to the members, and they wouldn't have to compensate by fiddling other weights (you know how much I don't like that - we want to keep things simple, after all...)

Welcome aboard, Justin!
Title: Re:Re-Examination of the Spreadsheet
Post by: Justin on January 10, 2003, 05:57:18 pm
Quote
How do you recommend coming up with Best and Worst values, apart from using observed min and max?  If there is a standard way of doing so, I'd be in favor of creating a new spreadsheet that allows you to do that.
Unfortunately, given its subjective nature, the method can be no more “standard” than the method that determined the 1.5M max population requirement. Yes, numerical analysis can help you make a decision, but it is still your decision to make.

In simplified terms, the acceptability range just indicates how forgiving you are about a particular dimension.  While one can attempt to use weights to accomplish this, they will also skew the dimension comparison, thus causing both to be erroneous.

Currently you are pre-populating the weights.  Weights inherently bring the state battle to the forefront.  Perhaps we should pre-populate the acceptability ranges instead, this way we can put the blinders on and focus on one dimension at a time, allowing us to be more dispassionate.

In effect we already do this with population, where Worst is 1.5M.  A good question here would be, “What is the population Best?”  It’s probably not zero.


Quote
The problem I foresee is that ... disputes about "which state?" will hinge on both weightings and range parameters, making it nearly hopeless to achieve consensus.
I agree, but I wasn’t aware that we were trying to reach a consensus.  I thought we were providing raw information, and a framework in which to apply one’s own value judgments.  We should not expect to reach a consensus, but rather encourage individuals to play with the numbers, and make up their own minds.  The state decision should be the product of a vote, not of our actuarial prowess.

Title: Re:Re-Examination of the Spreadsheet
Post by: Justin on January 10, 2003, 06:16:53 pm
Quote
Welcome aboard, Justin!
Thanks Zxcv.  It is a rare thing that will keep me up until 4am formulating a proposal.  It feels good.


On another note...

I understand that many people may feel uncomfortable with an unwieldy spreadsheet.  I can build a more user-friendly application that can guide them through the process, allowing them to input their priorities, without overwhelming them.  I would just need as much raw data as possible. For example, breaking down Gun control issues, rather than stating some state has a Gun control value of 8.9, which doesn’t have much empirical value.

If this is worthwhile, let me know and I can get started Monday.
Title: Re:Re-Examination of the Spreadsheet
Post by: holy instant on January 10, 2003, 06:29:30 pm
As much as I love the concept of the FSP and the willingness of so many to participate, I would like to point out that we have a name for all this spreadsheet analysis: MENTAL MASTURBATION.

Mental masturbation happens when one doesn't have any idea what is really important but looks at surface appearances and then goes round and round intellectually trying to figure things out using a hopelessly limited viewpoint.  

If the pioneers heading west in the 1830s and 1840s had considered things like jobs waiting for them and borders with countries and a few of these other spreadsheet items, there would have been no westward migration.

Incidently I talked to a leading architect the other day who happens to be a liberal environmentalist Ayn Rand hater.  I told him about the FSP goals and he said, "If they are smart they will choose Wyoming!"

Sometimes your enemies can see more clearly than your friends, wouldn't you say?
Title: Re:Re-Examination of the Spreadsheet
Post by: TedApelt on January 10, 2003, 07:22:47 pm
Quote
True, most of my background is in astronomy, engineering, and physics.

Ted, if you are an astronomer, you should really like Wyoming. The state is half-way up through the pea soup, due to altitude, and there's not much light pollution either! Not much astronomy going on in Delaware, I bet.   ;)

True.  One of the things I like best about the West is astronomy.  However, in choosing a state, I am thinking of how easy or hard campaigning would be there, and dark skies don't help with that.
Title: Re:Re-Examination of the Spreadsheet
Post by: TedApelt on January 10, 2003, 07:30:29 pm
the inclusion of federal land % as a good thing

WHAT??? ???

How could federal land be anything but trouble for us?  Maybe it won't be much of a problem, maybe the feds won't use it against us (I suspect they will!), but how could it possibly be good for us?
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 10, 2003, 09:34:03 pm
holy, the settlers for the Oregon Territory did use the best information they had available to them, to decide where to go. Unfortunately when they got there they found the information was extremely unreliable, and all the fertile land was already owned by earlier settlers. Many of them ended up with crap land up in the hills and could barely survive the first few winters. We can be sure if they had access to better information they would have used it. And spreadsheets are just a means of automating simple numerical computations; they probably played this stuff out in their heads when choosing where to go.

Ted, go ahead and read this:
http://www.lasvegassun.com/sunbin/stories/nevada/2000/jul/04/510464612.html

Easterners apparently have no idea how mad people out here get about these transgressions by the federal government. If we are ever going to try to push the feds back into some semblance of constitutional governance, for our state anyway, we will need people so motivated. Are there issues back east that provide the same sort of motivation? I heard about the Maine lobster fisheries, but that is pretty small stuff compared to what happens out here.

I'm still not sure why you think campaigning will be difficult out here (outside statewide races, which I admit are difficult). How about an example? Look at Sweetwater County in Wyoming. A couple of big towns (Green River and Rock Springs) 20 miles apart, and a lot of empty land. The state reps are based in a county, so running for state rep in this county you'd hit these two towns and do mailings to the ranches and farms. Make one or two swings through the little towns. What's so tough?

It's funny, with my expanded spreadsheet I've now tried several different weight vectors, both simple ones and others using almost every row, and I always end up with Wyoming on top! The other positions move around some. I'd actually like to see a vector that puts another state on top; I know it is possible but I bet it will be hard to justify. Any takers, guys?

Justin, you might do what I did and modify (for your own use) Jason's sheet, in your case using different acceptability ranges, and seeing what you get. As to other applications, we need something for people who don't have spreadsheet applications like Excel or 1-2-3. I never could get the Java thing to work, although I didn't try hard.

There is the Excel Viewer, free from Microsoft. Maybe we could have a collection of fixed spreadsheets with different weight vectors (simple ones), that people can go through, to find the one that comes closest to matching their preferences.

Personally I don't think we need to break down the rows much more. Things like gun control we can fix once we get there. More than breaking down things like gun control, we need to look at our 5 or 6 major measures, and make sure the data is reliable. It sure wouldn't hurt to get corroboration from other sources.
Title: Re:Re-Examination of the Spreadsheet
Post by: Justin on January 10, 2003, 11:04:35 pm
Quote
I never could get the Java thing to work, although I didn't try hard.

Well, good thing I'm a Java software engineer.  ;D

I'll work on the design on Monday (have to work on a project this weekend).  I'll set it up so that we can readily change the sets of data, but the basic formulae will be consistent.

One question, what format whould be preferable, applet or web-based (like JSP/ASP/PHP stuff)?  Applets can get a bit fancier with the UI, but web-based doesn't require the user to have the Java plug-in on their machine.
Title: Re:Re-Examination of the Spreadsheet
Post by: stpeter on January 10, 2003, 11:22:01 pm
Incidently I talked to a leading architect the other day who happens to be a liberal environmentalist Ayn Rand hater.  I told him about the FSP goals and he said, "If they are smart they will choose Wyoming!"
A classic quote from someone who sounds like the anti-Roark. :) I agree that Wyoming is the best choice and I'm not sure what all the arguing is about at this point, but I'm trying to stay patient...
Title: Re:Re-Examination of the Spreadsheet
Post by: TedApelt on January 11, 2003, 02:14:32 am
Ted asked:
Quote
How could federal land be anything but trouble for us?  Maybe it won't be much of a problem, maybe the feds won't use it against us (I suspect they will!), but how could it possibly be good for us?
Ted, I live in a county and state (Lake County, Colorado) with a very large percentage of federal land and lakes. I answered the above question in the following discussion thread.
http://forum.freestateproject.org/index.php?board=5;action=display;threadid=686

In that thread, you said that it was not a problem.  You did not say that it was somehow good for us.

You might be right that it is harmless, but I still have my suspicions that for environmental or other reasons restrictions will be placed on industrial, agricultural, or other uses of private land that is near the federal land.  This is already happening in Florida with the Everglades.

These restrictions could be quite reasonable, and might be the same as if a large company owned the land, but they could also be an excuse for the feds to handicap our efforts.  I am not sure, but I do have a very uneasy feeling about it.

There is also a lot of talk about using the threat of succession as some kind of bargaining chip.  If a lot of federal land was involved when we tried to do that, it would seriously weaken that option.  And, even if we decided to never use that option, we could still be painted as extremists that are plotting to seize and sell off national parks or something like that, even if it was absolute nonsense.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 11, 2003, 11:08:39 am
Justin - Web-based is definitely better than applet, if you can do it that way.
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 12, 2003, 02:12:09 am
Jason, here's a document that explains the distinctions about taxes and other forms of revenue.

http://www.oregontaxes.org/yt11-01.pdf

Besides that explanation, it also has several tables that illustrates what is going on; these tables have all the states so our candidates are in there.

I don't know if you have taken this into consideration already - if so, then there's nothing to worry about.

The Alaska spending is astounding. Wyoming doesn't look so hot either. I know Alaska is spending oil money; is Wyoming spending money from minerals?
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 12, 2003, 01:16:46 pm
Wyoming does get a lot of revenue from natural resources - not as much as Alaska, but it is a major issue in the state.  Another thing to remember about western states is that their state governments spend a lot of money on highways because of their large land areas.  So large spending totals don't necessarily indicate a statist political culture there; that's 1 reason I favor including all kinds of different variables for getting at political culture.  Spending is probably a better measure for size of government than taxation, though, since it includes what the government spends from borrowing & non-tax revenue, both of which are also (in general) Bad Things from a libertarian perspective.
Title: Re:Re-Examination of the Spreadsheet
Post by: freedomroad on January 12, 2003, 07:03:54 pm
Spending is probably a better measure for size of government than taxation, though...

I am not sure what size of government in this respect matters.  What matters is how free the people are.  What matters is what tax rates are.

Also, in AKs defense, everything is a lot more expensive in AK
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 12, 2003, 07:36:47 pm
Spending is probably a better measure for size of government than taxation, though...

I am not sure what size of government in this respect matters.  What matters is how free the people are.  What matters is what tax rates are.


Are you any freer if government charges you "fees" instead of "taxes," or backloads taxes onto future generations through borrowing?  Size of government, measured by spending, directly correlates with individual freedom.
Title: Re:Re-Examination of the Spreadsheet
Post by: freedomroad on January 13, 2003, 12:06:37 am
Quote
I am not sure what size of government in this respect matters.  What matters is how free the people are.  What matters is what tax rates are.

from Keith (FreedomRoad)
Quote
Are you any freer if government charges you "fees" instead of "taxes," or backloads taxes onto future generations through borrowing?  Size of government, measured by spending, directly correlates with individual freedom.
from JasonPSorens

I think user fees are much better.  Also, you have to remember federal government dependence.  The Western states, overall, get much more help from the federal gov. than the Eastern states.  However, states like ND and SD get a lot more help than WY does.

I am in favor of the government replacing many of its taxes with user fees in the short term.  This is a libertarian method.  I am not the first libertarian to speak of this.  This is basic libertarian step-by-step freedom.

Also, look at the federal gov.  The fed. gov. will spend all of the money it gets and then some.  This happens if a R or D is in power.  The debt will keep going up like it did the entire time Clinton was prez.  If the gov. will spend the money and just make the gov. bigger and more expensive....  Taxes have to be cut.  Continue to cut taxes.  People need their money.  People know how to spend money much more practial than the gov.  The gov. will continue to grow.  We might be able to change this.  However, this is the way things work as we know them.  Lots of us used this arguement in TN when the R and D combined together and tried to give us an income tax on wages.  We fought them for years.  The managed to give TN the largest tax increase in its history but we still do NOT TAX wages in TN.  Thank you, God.
Title: Re:Re-Examination of the Spreadsheet
Post by: JasonPSorens on January 13, 2003, 09:05:39 am
Well, user fees would be fine if the government were doing only what it is supposed to be doing.  But if the government monopolizes a service and then charges an exorbitant user fee, which you have to pay because it is a monopoly, then that is a real detriment to freedom.
Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on January 13, 2003, 01:48:59 pm
Here is a quote from that document:
Quote
Examples of non-tax revenues include fees and charges, which increased dramatically during the 1990's at all levels of government. System Development Charges (SDC's) for instance, which are an effort to compensate local governments for expected future costs of development and the demands it places on infrastructure, were relatively rare 10 years ago but are now a very prevalent means of raising money. The City of West Linn, for example, now charges more than $12,000 in SDC's on construction of a single-family dwelling.

User fees do make a certain amount of sense - which is why governments love them so much. They are an easy sell to citizens. But for some strange reason when costs are moved off the broadbased taxes onto fees, the broadbased taxes never go down at all. Hmmm, I wonder why?  ::)

Not only that, but there has been a lot of lobbying to throw school costs onto SDC's (I live in a high growth area so schools are crowded). Well, if they take school money out of property taxes, or income taxes, or SDC's, it doesn't matter, because I'm screwed either way. SDC's are supposed to cover infrastructure that you use when you move here, but homeschoolers don't use the damn government child warehousing facilities, so what kind of "user" fees are they?

The other reason governments like fees is that it allows them to nickel and dime us to death. Governments hate being limited to a single tax because people can see the whole thing in one lump. It raises less ire when they can nibble us here and there.

You can expect every state to move in the direction of "user fees", still keeping state monopolies as Jason notes. But we won't see broad-based taxes going down. That's one of the things we'll have to deal with in our chosen state. Not sure how to address it, but some think tank or other must have put some thought into it.
Title: Re:Re-Examination of the Spreadsheet
Post by: Hank on August 22, 2003, 11:53:55 am
We LIKE having these federal lands IF the government would just leave 'em alone and let us manage 'em. That's what Wyoming has managed to get the feds to agree to with the Bighorn National Forest.  They could even let more private outfits manage grazing land like it was there own.  Ownership is not the question. It is who manages of the ranges and forests. Us or them?
Title: Re:Re-Examination of the Spreadsheet
Post by: Kelton on August 22, 2003, 12:44:09 pm
Relevant to the topic at hand:
From http://groups.yahoo.com/group/wyfsp/message/486 (http://groups.yahoo.com/group/wyfsp/message/486)

From:   Jason P Sorens <jason.sorens@y...>
Date:  Thu Jul 3, 2003  12:06 pm
Subject:  Re: state sheets due MONDAY!

I've had a couple questions about what "weighting array" means: it just means that you'll need to include a typical series of variable weights in the state comparisons spreadsheet
(http://www.freestateproject.org/files/statecomparisons.xls) that put your state in first. I've whipped up some typical weightings for each state, for those of you who want to use them. I've labelled each state as "not difficult," "slightly difficult," "difficult," or "very difficult" depending on how strange the weights need to be to get the state into first. Of course, spreadsheet rankings are not at all the only criteria for making a state choice, but they are among the criteria. Putting these labels next to each state is also intended to stimulate a close look at the spreadsheet and encourage people to send me any important new variables or data that should go into the spreadsheet before the ballot mailings go out.
AK - not difficult

SIZE Voters 18.6
SIZE Finance 6.5
SIZE Population 2.2
SIZE Area 0.5
VIABILITY Coast 6.7
VIABILITY Border 1.6
VIABILITY Dependence 9.1
VIABILITY FedLand 5.6
CULTURE Spending 3.9
CULTURE Taxes 2.1
CULTURE Prez 0.6
CULTURE Gun Control 3.1
CULTURE Homeschooling 1.6
CULTURE Natives 1.9
CULTURE UrbanAreas 2.1
CULTURE UrbanClus 0.6
CULTURE NEA 2.1
CULTURE Ideology 2
CULTURE GovEmp 2.4
CULTURE EFI 1.1
CULTURE LandPlanning 1.2
CULTURE SBSI 1.1
CULTURE CPS 0.9
CULTURE Smoking 1.4
CULTURE SeatBelts 1.4
CULTURE Marijuana 3
QUALITY Livability 1
QUALITY Crime 2.5
QUALITY Income 1
QUALITY Jobs 8.7
QUALITY PrivLand 3
QUALITY JanTemp 0.5



DE - slightly difficult

Category Variable WEIGHT
SIZE Voters 17
SIZE Finance 7
SIZE Population 2
SIZE Area 6
VIABILITY Coast 7
VIABILITY Border 3
VIABILITY Dependence 11.5
VIABILITY FedLand 1.5
CULTURE Spending 2.7
CULTURE Taxes 1.7
CULTURE Prez 0.5
CULTURE Gun Control 2.1
CULTURE Homeschooling 1.4
CULTURE Natives 0.9
CULTURE UrbanAreas 2.8
CULTURE UrbanClus 1.4
CULTURE NEA 1.4
CULTURE Ideology 1.4
CULTURE GovEmp 2.7
CULTURE EFI 0.9
CULTURE LandPlanning 2.5
CULTURE SBSI 0.9
CULTURE CPS 0.9
CULTURE Smoking 1.1
CULTURE SeatBelts 0.9
CULTURE Marijuana 1.2
QUALITY Livability 1
QUALITY Crime 2
QUALITY Income 1.2
QUALITY Jobs 9.1
QUALITY PrivLand 3.2
QUALITY JanTemp 1.1



ID - slightly difficult

Category Variable WEIGHT
SIZE Voters 17
SIZE Finance 5
SIZE Population 1.5
SIZE Area 3
VIABILITY Coast 4
VIABILITY Border 2
VIABILITY Dependence 10
VIABILITY FedLand 6
CULTURE Spending 3.5
CULTURE Taxes 1.2
CULTURE Prez 0.7
CULTURE Gun Control 2.5
CULTURE Homeschooling 3
CULTURE Natives 1
CULTURE UrbanAreas 1
CULTURE UrbanClus 0.3
CULTURE NEA 3.5
CULTURE Ideology 2.5
CULTURE GovEmp 2.9
CULTURE EFI 1.2
CULTURE LandPlanning 1.2
CULTURE SBSI 1.2
CULTURE CPS 1.2
CULTURE Smoking 1.2
CULTURE SeatBelts 1.2
CULTURE Marijuana 1.7
QUALITY Livability 0.4
QUALITY Crime 2.4
QUALITY Income 0.5
QUALITY Jobs 11.6
QUALITY PrivLand 2.6
QUALITY JanTemp 3



ME - very difficult

Category Variable WEIGHT
SIZE Voters 14.9
SIZE Finance 1.9
SIZE Population 0.9
SIZE Area 3.9
VIABILITY Coast 15.5
VIABILITY Border 5.5
VIABILITY Dependence 6.5
VIABILITY FedLand 0
CULTURE Spending 1.5
CULTURE Taxes 0.5
CULTURE Prez 0.1
CULTURE Gun Control 1.5
CULTURE Homeschooling 0.4
CULTURE Natives 0.4
CULTURE UrbanAreas 9.5
CULTURE UrbanClus 4.5
CULTURE NEA 0.5
CULTURE Ideology 0.5
CULTURE GovEmp 7.9
CULTURE EFI 0.2
CULTURE LandPlanning 0.2
CULTURE SBSI 0.2
CULTURE CPS 1.5
CULTURE Smoking 0.7
CULTURE SeatBelts 0.2
CULTURE Marijuana 2.9
QUALITY Livability 3
QUALITY Crime 4.5
QUALITY Income 1
QUALITY Jobs 5
QUALITY PrivLand 4
QUALITY JanTemp 0.2



MT - very difficult

Category Variable WEIGHT
SIZE Voters 14
SIZE Finance 4
SIZE Population 1.8
SIZE Area 1
VIABILITY Coast 8
VIABILITY Border 5
VIABILITY Dependence 6
VIABILITY FedLand 0.1
CULTURE Spending 1
CULTURE Taxes 1
CULTURE Prez 1
CULTURE Gun Control 1.4
CULTURE Homeschooling 1.5
CULTURE Natives 0.2
CULTURE UrbanAreas 8
CULTURE UrbanClus 2.2
CULTURE NEA 2
CULTURE Ideology 1.5
CULTURE GovEmp 4
CULTURE EFI 0.5
CULTURE LandPlanning 8
CULTURE SBSI 0.5
CULTURE CPS 0.1
CULTURE Smoking 0.5
CULTURE SeatBelts 1.8
CULTURE Marijuana 0.7
QUALITY Livability 2
QUALITY Crime 0.2
QUALITY Income 0
QUALITY Jobs 11
QUALITY PrivLand 11
QUALITY JanTemp 0



ND - difficult

Category Variable WEIGHT
SIZE Voters 15
SIZE Finance 7.1
SIZE Population 2
SIZE Area 6
VIABILITY Coast 5
VIABILITY Border 4
VIABILITY Dependence 5.4
VIABILITY FedLand 0
CULTURE Spending 4.5
CULTURE Taxes 2
CULTURE Prez 0.1
CULTURE Gun Control 2.5
CULTURE Homeschooling 1
CULTURE Natives 0
CULTURE UrbanAreas 8
CULTURE UrbanClus 5
CULTURE NEA 1
CULTURE Ideology 1
CULTURE GovEmp 3.5
CULTURE EFI 0.5
CULTURE LandPlanning 6
CULTURE SBSI 0.5
CULTURE CPS 1.7
CULTURE Smoking 1
CULTURE SeatBelts 1.7
CULTURE Marijuana 0.5
QUALITY Livability 1
QUALITY Crime 5
QUALITY Income 0
QUALITY Jobs 3
QUALITY PrivLand 6
QUALITY JanTemp 0



NH - slightly difficult

Category Variable WEIGHT
SIZE Voters 17.6
SIZE Finance 7
SIZE Population 1.9
SIZE Area 2.5
VIABILITY Coast 8
VIABILITY Border 3
VIABILITY Dependence 14.5
VIABILITY FedLand 0.8
CULTURE Spending 4.5
CULTURE Taxes 2.2
CULTURE Prez 0.5
CULTURE Gun Control 2.5
CULTURE Homeschooling 1
CULTURE Natives 1.8
CULTURE UrbanAreas 1.5
CULTURE UrbanClus 0.6
CULTURE NEA 2.3
CULTURE Ideology 1.4
CULTURE GovEmp 2.7
CULTURE EFI 0.9
CULTURE LandPlanning 0.7
CULTURE SBSI 0.7
CULTURE CPS 1.1
CULTURE Smoking 1
CULTURE SeatBelts 1.1
CULTURE Marijuana 1.7
QUALITY Livability 1.5
QUALITY Crime 3.5
QUALITY Income 1
QUALITY Jobs 9
QUALITY PrivLand 1
QUALITY JanTemp 0.5



SD - difficult

SIZE Voters 17
SIZE Finance 3
SIZE Population 1.3
SIZE Area 6
VIABILITY Coast 2
VIABILITY Border 1
VIABILITY Dependence 6
VIABILITY FedLand 0
CULTURE Spending 4.4
CULTURE Taxes 2.8
CULTURE Prez 0.7
CULTURE Gun Control 2
CULTURE Homeschooling 1.3
CULTURE Natives 0.7
CULTURE UrbanAreas 4.7
CULTURE UrbanClus 2.1
CULTURE NEA 1.7
CULTURE Ideology 1
CULTURE GovEmp 4
CULTURE EFI 1.8
CULTURE LandPlanning 3.5
CULTURE SBSI 1.8
CULTURE CPS 1.1
CULTURE Smoking 1
CULTURE SeatBelts 1
CULTURE Marijuana 0.8
QUALITY Livability 2.7
QUALITY Crime 4.2
QUALITY Income 0
QUALITY Jobs 11.4
QUALITY PrivLand 9
QUALITY JanTemp 0



VT - slightly difficult

Category Variable WEIGHT
SIZE Voters 18
SIZE Finance 8
SIZE Population 2.2
SIZE Area 6
VIABILITY Coast 4.5
VIABILITY Border 2.5
VIABILITY Dependence 9.5
VIABILITY FedLand 1.5
CULTURE Spending 2.5
CULTURE Taxes 1.5
CULTURE Prez 0.5
CULTURE Gun Control 2.9
CULTURE Homeschooling 1.5
CULTURE Natives 1.5
CULTURE UrbanAreas 6
CULTURE UrbanClus 3
CULTURE NEA 1
CULTURE Ideology 0.5
CULTURE GovEmp 3.1
CULTURE EFI 0.6
CULTURE LandPlanning 1.9
CULTURE SBSI 0.6
CULTURE CPS 1.8
CULTURE Smoking 1.1
CULTURE SeatBelts 1.7
CULTURE Marijuana 1.2
QUALITY Livability 2
QUALITY Crime 2.9
QUALITY Income 1
QUALITY Jobs 6
QUALITY PrivLand 2
QUALITY JanTemp 1



WY - not difficult

SIZE Voters 18.1
SIZE Finance 8.5
SIZE Population 2
SIZE Area 2.5
VIABILITY Coast 4.6
VIABILITY Border 1
VIABILITY Dependence 13.5
VIABILITY FedLand 4.9
CULTURE Spending 3.8
CULTURE Taxes 1.6
CULTURE Prez 0.7
CULTURE Gun Control 2.2
CULTURE Homeschooling 1.1
CULTURE Natives 1.5
CULTURE UrbanAreas 1.8
CULTURE UrbanClus 0.4
CULTURE NEA 2
CULTURE Ideology 1.9
CULTURE GovEmp 2.1
CULTURE EFI 1
CULTURE LandPlanning 1
CULTURE SBSI 0.9
CULTURE CPS 0.9
CULTURE Smoking 1.4
CULTURE SeatBelts 1.1
CULTURE Marijuana 2.1
QUALITY Livability 1.2
QUALITY Crime 2.9
QUALITY Income 0.5
QUALITY Jobs 8.5
QUALITY PrivLand 3.2
QUALITY JanTemp 1.1



----
Title: Re:Re-Examination of the Spreadsheet
Post by: Kelton on September 02, 2003, 01:26:08 pm
Here is an interesting criticism of the Small Business Survival Index, or SBSI that is used in the spreadsheet:



“Small Business Survival Index” Severely Flawed
Study of little value as a comparative analysis of business tax climate in U.S. (http://www.mncn.org/bp/special6.pdf)

Here is the document cached on Google, in case you can't use Adobe Acrobat:
http://ms101.mysearch.com/jsp/GGcres.jsp?id=37feue_BRqoJ&u=http://www.mncn.org/bp/special6.pdf (http://ms101.mysearch.com/jsp/GGcres.jsp?id=37feue_BRqoJ&u=http://www.mncn.org/bp/special6.pdf)
From the article:

"  The small business survival index simply consists of adding up various tax rates and non-rate tax measurements plus the crime rate within each state. The tax rates are combined together without any attempt to weight the rates based upon their impact upon business survival.  "

. . .
" In short, even if the measures that the small business survival index  examined were comprehensive, the haphazard manner in which the index is constructed is sufficient to disqualify it as a serious measure of business survival. "




Incidentally, anybody looking for a current, up-to-date ranking that takes into account actual business survival rates by examining start-up rates, failure rates, sales, etc.?

Well, ask no more, here it is:
http://www.bizminer.com/2003_May_profiles/samples/BestPlaces.htm (http://www.bizminer.com/2003_May_profiles/samples/BestPlaces.htm)
Title: Re:Re-Examination of the Spreadsheet
Post by: Kelton on September 02, 2003, 06:17:47 pm
Ranking the states using the spreadsheet factors (Culture)

Spending    NH>DE>SD>ND>WY>ID>VT=AK>ME>MT
Taxes       AK>NH>DE>WY=SD>MT>ND>VT>ID>ME
Prez        WY>ID>ND>SD>AK>MT>NH>ME>DE>VT
Gun-Control AK>VT>NH>WY=ID=ME=MT>ND>SD>DE
Homeschool  AK>ID>WY=MT>VT=SD=DE=NH>ME
Natives     AK>WY>NH>ID>DE>VT>MT>ME>SD>ND
Urban       VT>ME>WY>SD>MT>ND>AK>NH>ID>DE
UrbanClus   DE>NH>ME>ID>ND>VT>AK>SD>MT>WY
NEA         ID>SD>NH>WY>DE>ND>ME>VT>MT>AK
Ideology    ID>AK>WY>NH>MT>SD>DE>ND>ME>VT
GovEmp      NH>DE>VT>ME>SD>ID>MT>ND>AK>WY
EFI         ID>WY>SD>NH>DE>ND>MT>VT>AK>ME
Landplan    WY=AK=ND=SD=MT>ID>NH=ME>VT=DE
SBSI        SD>WY>NH>AK>ND>ID>DE>MT>VT>ME
EFNA        DE>SD>NH>WY>VT>ID>ME=ND>AK
CPS         ID>VT>NH>ND>DE>WY>ME>SD>AK>MT
Smoking     WY>ID>ND>NH=AK>VT=SD=ME>DE0
SeatBelts   NH>VT=ID>AK=ND=MT=SD=DE>WY>ME
Helmets     NH>WY=AK=ND=SD=DE=MT=ID=ME>VT
AutoIns     NH>ND>DE>ID=VT>WY>MT>AK>SD>ME
HCMand      ID>ND>WY=SD>AK>VT>MT=NH>DE>ME
Liquor      ND>AK>WY>SD>NH=DE>MT>ID>VT=ME
RLCper      WY>ID>AK>NH>MT>SD>ME>VT>DE>ND
RLCec       WY>NH>ID>AK>MT>DE>SD>ME>VT>ND



Same thing again, 0-10 linear interpolation score included:



Spending    NH10>DE8.48>SD5.43>ND3.70>WY3.04>ID2.83>VT=AK2.39>ME2.17>MT0
Taxes       AK10>NH8.36>DE7.31>WY=SD5.52>MT4.63>ND3.58>VT3.13>ID2.99>ME0
Prez        WY10>ID9.40>ND6.88>SD6.81>AK6.46>MT6.21>NH2.53>ME1.09>DE0.28>VT0
Gun-Control AK10>VT8.75>NH7.50>WY=ID=ME=MT6.75>ND4.25>SD1.25>DE0
Homeschool  AK10>ID9.00>WY=MT7.00>VT=SD=DE=NH3.00>ME2.0
Natives     AK10>WY8.72>NH8.49>ID7.35>DE7.03>VT5.29>MT4.77>ME1.51>SD1.28>ND0
Urban       VT10>ME8.55>WY8.38>SD8.32>MT8.30>ND6.34>AK4.65>NH4.59>ID4.18>DE0
UrbanClus   DE10>NH9.13>ME8.77>ID7.28>ND7.17>VT6.85>AK6.67>SD4.93>MT4.24>WY0
NEA         ID10>SD9.85>NH9.26>WY7.6>DE7.57>ND5.65>ME5.58>VT5.25>MT4.43>AK0
Ideology    ID10>AK8.58>WY8.41>NH7.91>MT6.49>SD5.72>DE4.61>ND4.07>ME2.03>VT0
GovEmp      NH10>DE9.88>VT8.93>ME8.57>SD5.36>ID4.76>MT4.52>ND3.57>AK0.83>WY0
EFI         ID10>WY7.87>SD7.61>NH7.26>DE7.22>ND5.30>MT4.43>VT2.74>AK0.91>ME0
Landplan    WY=AK=ND=SD=MT10>ID6.7>NH=ME3.30>VT=DE0
SBSI        SD10>WY8.60>NH7.13>AK5.47>ND3.86>ID3.78>DE3.30>MT1.85>VT0.94>ME0
EFNA        DE10>SD8.70>NH8.26>WY5.22>VT3.04>ID2.61>ME=ND0.87>AK0
CPS         ID10>VT9.96>NH9.93>ND9.22>DE8.67>WY8.66>ME8.61>SD7.57>AK5.23>MT0
Smoking     WY10>ID5.30>ND4.00>NH=AK3.30>VT=SD=ME2.0>DE0
SeatBelts   NH10>VT=ID4.44>AK=ND=MT=SD=DE3.33>WY2.22>ME0
Helmets     NH10>WY=AK=ND=SD=DE=MT=ID=ME>VT0
AutoIns     NH10>ND2.00>DE1.00>ID=VT0.80>WY0.60>MT0.40>AK0.30>SD0.20>ME0
HCMand      ID10>ND8.46>WY=SD7.69>AK6.15>VT4.62>MT=NH3.08>DE1.54>ME0
Liquor      ND10>AK7.27>WY5.45>SD4.55>NH=DE3.64>MT2.73>ID0.91>VT=ME0
RLCper      WY10>ID9.42>AK8.91>NH8.17>MT6.66>SD3.70>ME3.60>VT1.83>DE0.96>ND0
RLCec       WY10>NH9.14>ID8.68>AK7.66>MT4.87>DE4.69>SD4.41>ME3.52>VT1.09>ND0




Title: Re:Re-Examination of the Spreadsheet
Post by: johnadams on September 03, 2003, 12:52:56 am
Incidentally, anybody looking for a current, up-to-date ranking that takes into account actual business survival rates by examining start-up rates, failure rates, sales, etc.?

Well, ask no more, here it is:
http://www.bizminer.com/2003_May_profiles/samples/BestPlaces.htm

....
Based on that report you cited, Kelton, here is how the FSP states rank on their overall index:

Overall Index Rank
Best Places for Business Profile: Small Business Version
http://www.bizminer.com/2003_May_profiles/samples/BestPlaces.htm

02   Idaho
11   Alaska
12   Vermont
15   Delaware
19   New Hampshire
33   Montana
34   North Dakota
40   Maine
45   Wyoming
50   South Dakota

Most of these state rankings are not particularly suprising (Idaho seems to rank highly on many business and economic rankings, for example), though Vermont fares better than I would have expected and South Dakota worse. If these data are meaningful, that would provide a sober reminder not to let the recent victories of statists in Vermont let one forget that there are still many good capitalists in that state and it would give me some more positive hope for the future of the state of my birth. Do you have any idea of what the reputation of Bizminer is?

Of course, everything depends on what is important to each individual Porcupine who votes, and business and economic factors may not be that important to many of them in making their selection, we just don't know.
Title: Re:Re-Examination of the Spreadsheet
Post by: Kelton on September 03, 2003, 02:06:19 am
Every index has some of our states wildly all over the place.  For instance, on the SBSI says South Dakota is the theoretically best place for businesses to survive, yet in actual practice, the measurements provided by bizminer (a marketing research company that has people willingly paying thousands of dollars for their reports), show a somewhat different story.

I would ignore this overall factor a bit until you have first examined the components on that Bizminer page. Here is what I think is the central component of that overall index that relates to business survival:

Small Business and Startup Failure Rates
Failure Index

VT 0.51  
DE 0.53
ID 1.00
SD 1.20
ND 1.32
WY 1.44
AK 1.76
MT 1.92
NH 1.92
ME 2.08


Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on September 03, 2003, 09:47:11 am
exitus, this bizminer index is like the cognetics index that we rejected earlier, because it directly measures survival rates and entrepreneurial activity, rather than regulatory burden. It is possible for high activity to exist in states with high regulatory burdens. One can do well in such states; it just takes someone who can stomach a lot of bureaucratic oversight and interference, and even perhaps bribery. But what does that have to do with freedom?

This index and the cognetics one might make sense being placed in the "QUALITY" category, but not "CULTURE". It is a poor measure of freedom. The state with the highest number in the "failure rates" section of the index is Connecticut, and Maine is next. These two states are not very free.

But as an index of small business success, it is kind of interesting to note that DE and VT do terribly on it. This supports my notion that DE's business-friendly reputation has more to do with big out-of-state corporations, more than anything else.

Of course, bizrate then puts this caveat on it:
"When reviewing failure rates, it is important to note that low failure rates can be a sign of stability, but also of a sluggish economy with limited new vitality. Conversely, high failure rates indicate higher risk, but may also suggest high levels of new competition which may result from higher opportunity levels."

I'd also take that critique of SBSI with a grain of salt, written as it is by a group (a government organization, at that!) in a state that places 44th in the index. It is a lot easier to throw rocks than to construct a better index. Maybe SBSC missed a few small things with Minnesota, but they probably missed a few things with other states, too. Does that missed information (in Minnesota's case) mean they would have ended up much higher in the index? This group does not tell us, so it's doubtful. Minnesota needs to look at government items that make it appear poorly in the index, and it seems they are not interested in doing that.
Title: Re:Re-Examination of the Spreadsheet
Post by: bIlluminati on September 03, 2003, 10:50:49 am
Going back to basics: the purpose of the Free State Project is to magnify our influence by increasing the number of small government believers in a specific state.

One argument against Wyoming is that it doesn't have enough jobs. Well, if Wyoming has the same percentage of jobs as, say, Delaware but still doesn't have enough jobs, then we can't move 20,000 people into Wyoming, and we can't move the same ratio of people into Delaware, either. In this case, the problem reduces to finding the most libertarian state(s) already existing. Note that we could still rule out North Dakota, because of its shrinking job market. And we move to New Hampshire and Wyoming, which is what I believe will happen anyway, given our ornery nature.

If, however, we can move 20,000 activists into Wyoming, and I think we can, then the population formulas are relevant. However, the spreadsheet is set up as a linear regression, and I believe that non-linear factors dominate. Example: Montana - about half the people vote R and half D. Sounds ideal for a swing vote, until you look at the details. Baucus won 200,000 to 100,000, and the R rep also won 200,000 to 100,000. That means we would have to bring 100,000 voters to swing the election. That seems beyond our capabilities.

South Dakota, on the other hand, gets a statist rating, but only at the national level. And the Democrat won his Senate seat by 500 votes in Indian reservations. New Hampshire, while stuck in the northeast, has a large block of voters who live there because there is no income tax. A conservative libertarian coulld hate Vermont; a liberal libertarian could hate Idaho. So it is legitimate for there to be multiple ways, and non-linear ways, of rating the situation.

A lot of good non-linear thinking has gone into the discussion. Some of that can be quantified. It just takes some guessing on appropriate numerical factos, a la neural net. I would have sunk mine into it, if there were enough appropriate data. In five years, there will be enough data. Right now, I can say, WY is top three and ME is tenth any reasonable way to look at it. After that, the votes/jobs analysis dominates. And there is no unique way to analyze that.



Title: Re:Re-Examination of the Spreadsheet
Post by: Zxcv on September 03, 2003, 10:59:53 am
There was some talk that when we get to our state, we should have a think tank. One of the jobs of the think tank would be to improve and refine our spreadsheet into a real, usable, reliable measure of the freedom quotient in all 50 states. That would give everyone in this country, who is interested in freedom, a powerful tool to help decide where they can find it. Which would increase the tendency to "move toward freedom", which is what FSP is all about, in a way. (Creating more freedom via concentration of freedom-lovers.) I really like this idea, and hope to be involved with it.
Title: Re:Re-Examination of the Spreadsheet
Post by: Kelton on September 03, 2003, 03:55:38 pm
Zxcv, I agree that this Bizminer index should be put in the same class as the Cognetics survey, since it measures actual results more than potential.

But it is still useful to note that while South Dakota came in first for small-business survivability in 2002 by the SBSI , the actual results show that real-life survivability is statistically difficult in South Dakota, resulting in South Dakota coming-in dead last on the Bizminer survey.

Surely there are other factors for business survivability than a composite of tax rates and crime rates for something like this to happen.
I also think that the Minnesota group that criticized the SBSI did have a few legitimate grieviances.  For one thing,  "the tax rates are combined together without any attempt to weight the rates based upon their impact upon business survival."  The example was the death tax and how that does not have nearly as much impact, as say, a sales tax; yet the SBSI weighted them equally.  Another problem is that the SBSI did not take into account a lot of different unique features of how states tax differently, as the example given about property taxes for small businesses.

One excellent point brought-out by Varrin is that people should remember that each economic index in the spreadsheet also accounts for taxes.  Realize that when weighting the one tax measure highly, and the indices highly, you are actually giving a double and a triple weighting to the tax factor, only do that if you mean to do that.


All in all, I have no problem with any of the indices, so long as they are compared critically, such as here.  I really like the idea of the Free State think-tank and creating a comprehensive freedom quotient, one more bulletproof than our novice attempts so far.
Title: Re:Re-Examination of the Spreadsheet
Post by: johnadams on September 04, 2003, 12:20:01 pm
....I would ignore this overall factor a bit until you have first examined the components on that Bizminer page. Here is what I think is the central component of that overall index that relates to business survival:
....
It's interesting that the only state which ranks in the top five FSP states in both Overall Index score and Failure Index score is NH. However, my guess is that a study which measures actual results will be influenced by short-term economic variables like the recent national economic slowdown. So it is of course important to look at other factors, including those which are difficult to represent with numeric scores.

Overall Index Rank

02   Idaho
11   Alaska
12   Vermont
15   Delaware
19   New Hampshire

33   Montana
34   North Dakota
40   Maine
45   Wyoming
50   South Dakota


Small business and startup failure rates
Failure Index (Higher Score is Better)

ME   2.08
NH   1.92
MT   1.92
AK   1.76
WY   1.44

ND   1.32
SD   1.20
ID   1.00
DE   0.53
VT   0.51
Title: Re:Re-Examination of the Spreadsheet
Post by: johnadams on September 04, 2003, 12:42:54 pm
....This supports my notion that DE's business-friendly reputation has more to do with big out-of-state corporations, more than anything else.
....
Yes, I believe you are right on that. DE's business-friendly reputation has more to do with a single law than anything: the Financial Center Development Act of 1981. This law "lowered the state income taxes that banks must pay and eliminated the limit on how much interest and fees credit card companies could charge to customers nationwide." (Source: 1981 Banking Act: How one law transformed Delaware (http://www.delawareonline.com/newsjournal/business/2001/01/28fdca1.html)). This law made Delaware very popular with credit card companies: eight of the top 10 credit card companies have operations in Delaware. But it has not exactly made DE into a hotbed of entrepreneurial activity.

Also, the fact that so much of Delaware's business success depends on a single law and a single narrow industry means that it is in a precarious position. If DE voters should ever rescind that law or if other states should match or surpass it, then DE will lose its advantage in the credit card sector.
Title: Re:Re-Examination of the Spreadsheet
Post by: Kelton on September 04, 2003, 01:00:01 pm
....This supports my notion that DE's business-friendly reputation has more to do with big out-of-state corporations, more than anything else.
....
Yes, I believe you are right on that. DE's business-friendly reputation has more to do with a single law than anything: the Financial Center Development Act of 1981.

. . .the fact that so much of Delaware's business success depends on a single law and a single narrow industry means that it is in a precarious position. If DE voters should ever rescind that law or if other states should match or surpass it, then DE will lose its advantage in the credit card sector.
The strong Reagan-inspired movement that brought-in the very libertarian-leaning conservative, Pete DuPont and massive sweeping changes in the early 1980's has largely vanished.  Delaware's Credit Card industry is also being regulated to death within Delaware, making some companies move operations to different locations, now Largely to Nevada, some to South Dakota and even Utah, with American Express.
The advantages to incorporating in Delaware have also largely been vanquished in the courts, where Delaware's legislation against piercing the 'corporate veil' was virtually nullified, yet remains in Nevada this link provides more on that :
http://www.nvinc.com/piercecorp.htm (http://www.nvinc.com/piercecorp.htm)


It all goes back to the idea that some states have a certain heritage of freedom which current political movements no longer support and it may be noted that most of the factors that harmed Delaware in the spreadsheet were the result of recent legislation.
Title: Re:Re-Examination of the Spreadsheet
Post by: johnadams on September 04, 2003, 01:18:25 pm
....the spreadsheet is set up as a linear regression, and I believe that non-linear factors dominate. Example: Montana - about half the people vote R and half D. Sounds ideal for a swing vote, until you look at the details. Baucus won 200,000 to 100,000, and the R rep also won 200,000 to 100,000. That means we would have to bring 100,000 voters to swing the election. That seems beyond our capabilities.

South Dakota, on the other hand, gets a statist rating, but only at the national level. And the Democrat won his Senate seat by 500 votes in Indian reservations. New Hampshire, while stuck in the northeast, has a large block of voters who live there because there is no income tax. A conservative libertarian coulld hate Vermont; a liberal libertarian could hate Idaho. So it is legitimate for there to be multiple ways, and non-linear ways, of rating the situation.
....
I think you've hit on some key points here, bIlluminati. Many issues are more complex than a simple linear analysis can show. I think the ideal voting situation would be a state in which the two major parties are both competitive and there is a significant libertarian culture, history and voting block as well. The ideal state would be welcoming of the FSP and the two major parties would have incentive to compete for the votes of the incoming Porcupines. In the ideal situation, both the Republicans and Democrats would claim to be more libertarian than the other party and many voters would also be attracted to the real libertarians: the Porcupines and the state libertarian party. No state matches this ideal perfectly, but NH seems to come the closest.

Some have argued that a state which is largely Republican and has a state Republican party and congressional delegation that is libertarian-oriented provides the best opportunity for the FSP. I am not convinced of this. My estimation is that in such a state the dominant Republicans will have little incentive to compete for Porcupine and libertarian votes, because they are generally beating the Democrats easily anyway. And when the libertarian party tries to attract new members and convert Republicans they will just say, "Why don't you just become a Republican?" There would be much pressure to sell out on the left-libertarian issues in such a state.
Title: Re:Re-Examination of the Spreadsheet
Post by: Kelton on September 04, 2003, 01:19:16 pm
Small business and startup failure rates
Failure Index (Higher Score is Better)


Ah, yes, thanks for pointing that out, I was going by the earlier mention of a different idea and ended-up getting confused.
 
The Bizminer survey does say this:
"A state that performs on a par with the US average will score a 1.00 in that index. A state that scores a 1.10 on an index outperforms the national average by 10%. Conversely, a score of 0.90 is ten points below the national average. Higher failure rates result in a lower index. For all other measures, higher values result in higher index scores."

Economists also point-out that where there is a high amount of job 'churning' the economy is also healthy and more lively: so if there are a high amount of failure rates, that is not a problem, so long as there is also a larger amount of start-ups.  I guess this is why Idaho can have a somewhat high failure rate and yet soar to the top of the rankings while Maine fails least and sinks near the bottom.

As to what to do with all of these thoughts, (assuming anybody still even cares about the spreadsheet anymore), I thought what that Mr. Harper did by combining the Cognetics survey with the SBSI was a great way to balance theoretical with practical.  Likewise, if we could combine our SBSI spreadsheet data and compare it to the Bizminer data, that would be more insightful, I think.
Title: Re:Re-Examination of the Spreadsheet
Post by: Kelton on September 04, 2003, 01:27:36 pm
Some have argued that a state which is largely Republican and has a state Republican party and congressional delegation that is libertarian-oriented provides the best opportunity for the FSP. I am not convinced of this. My estimation is that in such a state the dominant Republicans will have little incentive to compete for Porcupine and libertarian votes, because they are generally beating the Democrats easily anyway. And when the libertarian party tries to attract new members and convert Republicans they will just say, "Why don't you just become a Republican?" There would be much pressure to sell out on the left-libertarian issues in such a state.

This is starting to go off-topic, but I'll respond this once,

I'm one of those who have advocated this.  My argument is based around the 'wasted-vote' syndrome'.  If you try to push a 3rd party where the D's and R's are already neck-and neck, this is going to be a strong factor, whether you like it or not.

The nice thing about my theory is that it is readily provable with current voting statistics, but your theory is just mere speculation.  
Title: Re:Re-Examination of the Spreadsheet
Post by: johnadams on September 04, 2003, 01:38:03 pm
There was some talk that when we get to our state, we should have a think tank. One of the jobs of the think tank would be to improve and refine our spreadsheet into a real, usable, reliable measure of the freedom quotient in all 50 states. That would give everyone in this country, who is interested in freedom, a powerful tool to help decide where they can find it. Which would increase the tendency to "move toward freedom", which is what FSP is all about, in a way. (Creating more freedom via concentration of freedom-lovers.) I really like this idea, and hope to be involved with it.
Yes, I also think that is an excellent idea.

I think that developing a libertarian "school"/institute in a fine private university in the Free State would be a good base for such a think tank. This academic school would be a source of future Porcupine think tank members and would attract other great libertarian thinkers to the free state. Some relatively successful libertarian think tanks that Porcupines might look to for ideas on how to develop a Free State Institute:

Ludwig Von Mises Institute, Auburn University
The Objectivist Center, Poughkeepsie, NY
Pioneer Institute, Boston
Society for the Development of Austrian Economics, St. Lawrence University

Perhaps Professor Walter Williams, who has already signed on to the FSP, could help start the Free State Institute (maybe he even already has that in mind?).

The development of a libertarian infrastructure is essential to any Free State Project. A libertarian society must create a host of libertarian social structures in addition to a libertarian think tank.

My notes on Wendy McElroy's Institutionalizing Idealism (http://www.zetetics.com/mac/articles/ideals.html)

It can be done:
"If institutions can be sculpted to embody corruption, then they can be designed in order to maximize libertarian ideals. They can be designed with a tendency toward freedom rather than tyranny."

Libertarian leaders and institutions must be aligned with libertarian principles--hypocrisy must be avoided:
"Libertarian professors at state universities pocket tax money, while insisting 'taxation is theft.'"
A system of libertarian institutional analysis must be developed:
Title: Re:Re-Examination of the Spreadsheet
Post by: johnadams on September 04, 2003, 02:12:52 pm
....The nice thing about my theory is that it is readily provable with current voting statistics, but your theory is just mere speculation.  
Yes, speculation, though based on the nature and results of certain political campaigns--but they could be exceptions. I vaguely recall reading something about the voting statistics you are referring to. Could you point me to them again so I can refresh my memory and perhaps correct my misperception? Thanks Kelton.
Title: Re:Re-Examination of the Spreadsheet
Post by: Kelton on September 05, 2003, 12:57:48 pm
Spending is probably a better measure for size of government than taxation, though...

I am not sure what size of government in this respect matters.  What matters is how free the people are.  What matters is what tax rates are.

Also, in AKs defense, everything is a lot more expensive in AK

"What matters is what tax rates are."

Whose tax rates?  The average voter who doesn't pay a sales tax or income tax but votes for more and more government expenditures, paid for by a handful of capitalist oil company owners and workers who are forced to sacrifice their lives for the good of the state, so that the population can enjoy not having to pay their share of the state burden?

Title: Re:Re-Examination of the Spreadsheet
Post by: ida dawn on September 17, 2003, 04:27:54 pm


Overall Index Rank
Best Places for Business Profile: Small Business Version
http://www.bizminer.com/2003_May_profiles/samples/BestPlaces.htm

02   Idaho
11   Alaska
12   Vermont
15   Delaware
19   New Hampshire
33   Montana
34   North Dakota
40   Maine
45   Wyoming
50   South Dakota



Don't know whether anyone is following this discussion anymore, but feel compelled to comment on this Bizminer study. Please note that I have absolutely no background in statistics.

A. I am amazed to see SD at the bottom, given that there is a trail of dust behind the small businesses that are moving out of MN into Sioux Falls....so I can't help wondering how the Bizminer study was structured.

B. The critique from MN on the SBSI is, probably, a result of the movement referred to in A.  The big spenders/taxers in Hennepin and Ramsey counties of MN are getting very nervous about the exodus.        ;D