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Minimum Wage Study - MW Does Not Kill Jobs

Meanwhile, those at the top of the heap take the lions share, leave the scraps, call it 'trickle down economics' and slap each other on the backs in good fellowship.
 

Normal data standards say that you report the precision you have. We see one digit past the decimal place--that's all they have and it's not perfectly solid as evidenced by how often it's revised later.
Educate yourself - How is unemployment data collected? - because you are unsuprisingly misinformed.

Your obsession with significant digits is fascinating because it misses the point - the actual of number of unemployed is estimated. It is accepted as the one of the best labor force estimates on the planet in terms of methodology.
Foot, meet bullet. From your own source they figure the estimate has a 90% chance of being within 300,000 of the correct value. That translates to somewhere between 2% and 4% error. In other words, between one and two digits of precision which is exactly what I have been saying.

Since minimum wage workers are about 1% of the population it should be apparent that unemployment of minimum wage workers has a fraction of a digit of negative precision--in other words, it's meaningless.
 

Normal data standards say that you report the precision you have. We see one digit past the decimal place--that's all they have and it's not perfectly solid as evidenced by how often it's revised later.
Educate yourself - How is unemployment data collected? - because you are unsuprisingly misinformed.

Your obsession with significant digits is fascinating because it misses the point - the actual of number of unemployed is estimated. It is accepted as the one of the best labor force estimates on the planet in terms of methodology.
Foot, meet bullet. From your own source they figure the estimate has a 90% chance of being within 300,000 of the correct value. That translates to somewhere between 2% and 4% error. In other words, between one and two digits of precision which is exactly what I have been saying.

Since minimum wage workers are about 1% of the population it should be apparent that unemployment of minimum wage workers has a fraction of a digit of negative precision--in other words, it's meaningless.
Your reasoning is based on a misunderstanding of statistics and poor readoning The 90% confidence interval does not mean there is any necessary error or imprecision in measurement. It means that the sample my estimate may differ from a complete census.

Moreover, the notion that changes in unemployment would not necessarily be captured is ludicrous.

BTW, the estimates for workers earning the federal minimum wage or below is closer to 2%. Since some states have minimum wages above the federal minimum, it is possible the number is even higher.

Finally, the point you persistently avoid is there are studies based on a complete census if s region .
 
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Normal data standards say that you report the precision you have. We see one digit past the decimal place--that's all they have and it's not perfectly solid as evidenced by how often it's revised later.
Educate yourself - How is unemployment data collected? - because you are unsuprisingly misinformed.

Your obsession with significant digits is fascinating because it misses the point - the actual of number of unemployed is estimated. It is accepted as the one of the best labor force estimates on the planet in terms of methodology.
Foot, meet bullet. From your own source they figure the estimate has a 90% chance of being within 300,000 of the correct value. That translates to somewhere between 2% and 4% error. In other words, between one and two digits of precision which is exactly what I have been saying.

Since minimum wage workers are about 1% of the population it should be apparent that unemployment of minimum wage workers has a fraction of a digit of negative precision--in other words, it's meaningless.
Your reasoning is based on a misunderstanding of statistics and poor readoning The 90% confidence interval does not mean there is any necessary error or imprecision in measurement. It means that the sample my estimate may differ from a complete census.
Reality 101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?

Moreover, the notion that changes in unemployment would not necessarily be captured is ludicrous.
A change that was within the confidence interval would not be seen.

BTW, the estimates for workers earning the federal minimum wage or below is closer to 2%. Since some states have minimum wages above the federal minimum, it is possible the number is even higher.

Finally, the point you persistently avoid is there are studies based on a complete census if s region .
No--that's a common error of the advocates of raising the minimum wage. It's actually the value for at or below the minimum wage. The only way a normal employee can be below minimum wage is if they are tipped. And tipped workers typically end up above minimum wage, often well above it. The demographics of the "or below" group also is very different than for the "at" group.
 
101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
Nope, never “took” any statistics or higher math. But I was given to understand confidence intervals as limits to the range of possible error, not an assurance that such error must exist. So if there is a value of 20 put forth for “x” with a 95% confidence interval, the actual value of “x”COULD be 19 or 21, but it’s not
22 or higher, nor is it 18 or lower.
In my admittedly low level understanding, this does not render the evaluation useless - it gives a reliable range of possible values for “x”. But you are saying that the effect you seek to isolate must necessarily lie entirely within the error bar, correct?
Yet you blithely put forth blue sky projections pulled out of … ??
tipped workers typically end up above minimum wage
How “typically”? I hear lots of them saying that for every shift that nets them $50/hr, there are thirty shifts that net them $4/hr or similar. But since you object to stats that contain confidence intervals, you must surely be able to evidence your assertion with unassailable facts sans any error bars or confidence intervals, right?

I’m open to being entirely wrong about all of the above, but only if it can be shown where I have gone astray by expecting a degree of accuracy from you that you demand of others …
 

Normal data standards say that you report the precision you have. We see one digit past the decimal place--that's all they have and it's not perfectly solid as evidenced by how often it's revised later.
Educate yourself - How is unemployment data collected? - because you are unsuprisingly misinformed.

Your obsession with significant digits is fascinating because it misses the point - the actual of number of unemployed is estimated. It is accepted as the one of the best labor force estimates on the planet in terms of methodology.
Foot, meet bullet. From your own source they figure the estimate has a 90% chance of being within 300,000 of the correct value. That translates to somewhere between 2% and 4% error. In other words, between one and two digits of precision which is exactly what I have been saying.

Since minimum wage workers are about 1% of the population it should be apparent that unemployment of minimum wage workers has a fraction of a digit of negative precision--in other words, it's meaningless.
Your reasoning is based on a misunderstanding of statistics and poor readoning The 90% confidence interval does not mean there is any necessary error or imprecision in measurement. It means that the sample my estimate may differ from a complete census.
Reality 101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
. i teach it. You are wrong. A confidence interval has nothing to do with the precision of measurement. The point estimate is precise and an unbiased estimate of the underlying population parameter.
Loren Pechtel said:
Moreover, the notion that changes in unemployment would not necessarily be captured is ludicrous.
A change that was within the confidence interval would not be seen.
. Utter nonsense. A properly taken new sample would very likely show it.
Loren Pechtel said:
BTW, the estimates for workers earning the federal minimum wage or below is closer to 2%. Since some states have minimum wages above the federal minimum, it is possible the number is even higher.

Finally, the point you persistently avoid is there are studies based on a complete census if s region .
No--that's a common error of the advocates of raising the minimum wage. It's actually the value for at or below the minimum wage. The only way a normal employee can be below minimum wage is if they are tipped. And tipped workers typically end up above minimum wage, often well above it. The demographics of the "or below" group also is very different than for the "at" group.
You are wrong. There are exceptions to minimum wages that go beyond tipped workers.

And, of course, you missed the point that there are more minimum wage workers than you claim .

At this point, given your lack of relevant information and knowledge, along with your contradictory position that the effects of an increase in the minimum wage on employment are an unmeasurable empirical question it must be negative, indicate to this poster you that entire position is based on ignorance, illogic and belief.
 
101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
Nope, never “took” any statistics or higher math. But I was given to understand confidence intervals as limits to the range of possible error, not an assurance that such error must exist. So if there is a value of 20 put forth for “x” with a 95% confidence interval, the actual value of “x”COULD be 19 or 21, but it’s not
22 or higher, nor is it 18 or lower.
In my admittedly low level understanding, this does not render the evaluation useless - it gives a reliable range of possible values for “x”. But you are saying that the effect you seek to isolate must necessarily lie entirely within the error bar, correct?
Yet you blithely put forth blue sky projections pulled out of … ??
1) You're being a bit simple about it. A 95% confidence interval (also reported as p=.05) means that it's 95% likely that the value is within that range. It is not a certainty.

2) The existence of an error range inherently says you are not certain of the exact value.

3) I'm not putting forth blue sky projections. Rather, I'm showing that for a huge range of actual values the confidence interval will include zero. I put a piece of paper on a scale--reads 0. Obviously paper is weightless! I can put quite a bit of paper on it (I'm thinking of the scale we weigh suitcases with) and it will still say zero. Thus you can't conclude that because the scale says zero that I have no paper.

tipped workers typically end up above minimum wage
How “typically”? I hear lots of them saying that for every shift that nets them $50/hr, there are thirty shifts that net them $4/hr or similar. But since you object to stats that contain confidence intervals, you must surely be able to evidence your assertion with unassailable facts sans any error bars or confidence intervals, right?

I’m open to being entirely wrong about all of the above, but only if it can be shown where I have gone astray by expecting a degree of accuracy from you that you demand of others …
If they really were only getting $4/hr for thirty of the thirty-one shifts the employer would be in trouble with the labor department.
 
Reality 101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
. i teach it. You are wrong. A confidence interval has nothing to do with the precision of measurement. The point estimate is precise and an unbiased estimate of the underlying population parameter.
Estimate. Just because the value is precise doesn't mean the underlying value is exactly what the estimate says.

It sounds like you're applying it to a spherical cow rather than looking at what it means in the real world.

Loren Pechtel said:
Moreover, the notion that changes in unemployment would not necessarily be captured is ludicrous.
A change that was within the confidence interval would not be seen.
. Utter nonsense. A properly taken new sample would very likely show it.
Once again, showing that you don't actually understand. (And, why the class has that nickname--too many teachers of it don't actually understand.)

Loren Pechtel said:
BTW, the estimates for workers earning the federal minimum wage or below is closer to 2%. Since some states have minimum wages above the federal minimum, it is possible the number is even higher.

Finally, the point you persistently avoid is there are studies based on a complete census if s region .
No--that's a common error of the advocates of raising the minimum wage. It's actually the value for at or below the minimum wage. The only way a normal employee can be below minimum wage is if they are tipped. And tipped workers typically end up above minimum wage, often well above it. The demographics of the "or below" group also is very different than for the "at" group.
You are wrong. There are exceptions to minimum wages that go beyond tipped workers.
Note that I said "normal employee". I realize there are exceptions, I'm excluding them from the sample because they're small and have no bearing on the effect of raising the minimum wage anyway.

And, of course, you missed the point that there are more minimum wage workers than you claim .
No--I pointed out the 2% figure is counting the wrong thing.

At this point, given your lack of relevant information and knowledge, along with your contradictory position that the effects of an increase in the minimum wage on employment are an unmeasurable empirical question it must be negative, indicate to this poster you that entire position is based on ignorance, illogic and belief.
You twist everything I say and then claim contradictions that were not there.
 
Rather, I'm showing that for a huge range of actual values the confidence interval will include zero.
Yeah, that’s how it is with undetectable effects.
101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
Nope, never “took” any statistics or higher math. But I was given to understand confidence intervals as limits to the range of possible error, not an assurance that such error must exist. So if there is a value of 20 put forth for “x” with a 95% confidence interval, the actual value of “x”COULD be 19 or 21, but it’s not
22 or higher, nor is it 18 or lower.
In my admittedly low level understanding, this does not render the evaluation useless - it gives a reliable range of possible values for “x”. But you are saying that the effect you seek to isolate must necessarily lie entirely within the error bar, correct?
Yet you blithely put forth blue sky projections pulled out of … ??
1) You're being a bit simple about it. A 95% confidence interval (also reported as p=.05) means that it's 95% likely that the value is within that range. It is not a certainty.

2) The existence of an error range inherently says you are not certain of the exact value.

3) I'm not putting forth blue sky projections. Rather, I'm showing that for a huge range of actual values the confidence interval will include zero. I put a piece of paper on a scale--reads 0. Obviously paper is weightless! I can put quite a bit of paper on it (I'm thinking of the scale we weigh suitcases with) and it will still say zero. Thus you can't conclude that because the scale says zero that I have no paper.

tipped workers typically end up above minimum wage
How “typically”? I hear lots of them saying that for every shift that nets them $50/hr, there are thirty shifts that net them $4/hr or similar. But since you object to stats that contain confidence intervals, you must surely be able to evidence your assertion with unassailable facts sans any error bars or confidence intervals, right?

I’m open to being entirely wrong about all of the above, but only if it can be shown where I have gone astray by expecting a degree of accuracy from you that you demand of others …

If they really were only getting $4/hr for thirty of the thirty-one shifts the employer would be in trouble with the labor department.

Sorry, I was a bit hyperbolic with the $4. But that doesn’t feed the donkey. “Trouble with the labor department” doesn’t assure that any tipped worker is making more than MW. And if you talk to some tipped workers who are not in high dollar restaurants etc, you can discover for yourself that lots don’t make double digit dollars per hour.
See, Loren, that’s the beauty of it all. You can keep people suppressed and willing to work for a pittance. I believe your fears are based in the notion that businesses relying on slave wages will no longer be viable. At the edges, I agree. And good riddance.
 
Reality 101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
. i teach it. You are wrong. A confidence interval has nothing to do with the precision of measurement. The point estimate is precise and an unbiased estimate of the underlying population parameter.
Estimate. Just because the value is precise doesn't mean the underlying value is exactly what the estimate says.

It sounds like you're applying it to a spherical cow rather than looking at what it means in the real world.

Loren Pechtel said:
Moreover, the notion that changes in unemployment would not necessarily be captured is ludicrous.
A change that was within the confidence interval would not be seen.
. Utter nonsense. A properly taken new sample would very likely show it.
Once again, showing that you don't actually understand. (And, why the class has that nickname--too many teachers of it don't actually understand.)
You are mistaken. A new estimate occurs every month with a new sample. A new sample means new data. It is ludicrous to think that a new sample with new data would not show a change in all cases if there was a change.
Loren Pechtel said:
BTW, the estimates for workers earning the federal minimum wage or below is closer to 2%. Since some states have minimum wages above the federal minimum, it is possible the number is even higher.

Finally, the point you persistently avoid is there are studies based on a complete census if s region .
No--that's a common error of the advocates of raising the minimum wage. It's actually the value for at or below the minimum wage. The only way a normal employee can be below minimum wage is if they are tipped. And tipped workers typically end up above minimum wage, often well above it. The demographics of the "or below" group also is very different than for the "at" group.
You are wrong. There are exceptions to minimum wages that go beyond tipped workers.
Note that I said "normal employee". I realize there are exceptions, I'm excluding them from the sample because they're small and have no bearing on the effect of raising the minimum wage anyway.
Ah, the special pleading case.
And, of course, you missed the point that there are more minimum wage workers than you claim .
No--I pointed out the 2% figure is counting the wrong thing.
First, you ignored the salient point that in a number of states there are workers earning the state minimum wage which EXCEEDS the federal minimum wage. Those workers are excluded from that 2%. Second, you provided absolutely no evidence to indicate that the 1% is the correct estimate for the federal min. wage earners.
At this point, given your lack of relevant information and knowledge, along with your contradictory position that the effects of an increase in the minimum wage on employment are an unmeasurable empirical question it must be negative, indicate to this poster you that entire position is based on ignorance, illogic and belief.
You twist everything I say and then claim contradictions that were not there.
A handwaved complaint. Please point out what you believe is a twisted interpretation of your position.
 
there are workers earning the state minimum wage which EXCEEDS the federal minimum wage. Those workers are excluded from that 2%
That's pretty significant since thirty (30) States' MW exceed the federal MW.
 
We have the proof
that MW did precisely the harm it's not supposed to do.

We have one data point that shows the extreme case causes harm
No!

This has been shown repeatedly not to be the case.

You do not get to keep using it; It's gone, exploded, no longer a thing.

We have ZERO data points that show any harm at all.

You don't get to cite American Samoa as data, for the same reason that in a discussion of combustion, you don't get to cite Phlogiston in support of your position.

Continuing to use falsehoods as though they hadn't been soundly refuted, is the hallmark of religion and propaganda. Phlogiston doesn't explain fire; Russia didn't defeat Ukraine in 2022; American Samoa is not an example the effects of minimum wage increases.

View attachment 44842

You cannot rewrite the facts of history or pretend they don't matter. All the facts matter:

The Minimum Wage was increased in American Samoa, and as a result the economy there suffered severely, due to businesses closing/cutting back which could not pay those higher wages. This is confirmed by the fact that

the proponents of this MW increase later admitted that it did more harm than good, by destroying businesses and jobs,
and they rescinded that MW increase.


Why did they reverse themselves if that MW increase did not do the damage of eliminating jobs and businesses? That's the "data" -- i.e., the PROOF!

bilby: "We have ZERO data points that show any harm at all."
Wrong! We have irrefutable proof, from the MW ADVOCATES themselves, which is the best kind of proof. I.e., proof that harm was done. The True Believers in MW themselves had to reverse themselves and retract their own MW increase.

When the proponents of MW admit that it caused harm, and they reverse their earlier decision, then we have irrefutable proof that it did cause net harm.

Why did the major proponents of it reverse themselves
if it did not do net harm?

Why did President Obama (who had voted for the increase earlier) then sign the bill to rescind that wage increase?

How can any honest person deny that this MW increase resulted in job losses and harm to the economy?

To this day they still have not restored that original wage increase, even though it's been more than 10 years, which should be long enough. If the only need was for it to be more gradual, it should have been possible to restore the original wage increase they passed in 2007, but phase it in more gradually, over a few years.

Explain why this wage increase was followed by job losses and business closures if it's not true that MW increase harmed businesses and reduced employment.

(summary: MW was increased, net harm resulted, this damage is widely recognized by those who enacted it, so they rescinded it and reduced the increase to phase it in more gradually over many years.)

The truth is obvious: The MW in Samoa will eventually be increased to finally be equal to the MW in the 50 states ("convergence"). But not until about 2036. Why not earlier? Why the delay? Because it's too obvious that it will do more harm than good. Everyone, including MW advocates, admit that it will do more harm than good, because the damage is too obvious. They all can see it so easily so that no one can seriously deny it. BUT, if they drag it out long enough, gradually, they can obscure the damage done so that it cannot be noticed so easily when it's finally phased in completely.

So, the damage is there -- there's no evidence or explanation to show that it's not there in 2030 or 2033 or 2036 just as in 2025 and in 2010 -- which everyone acknowledges because back then they rescinded that wage increase = proof that it did harm. Rather, the evidence is that the resulting net damage can be more easily hidden from easy detection and measurement (maybe after 2030). But there are no facts or science to show that somehow the damage magically disappears sometime in 2030-36. Obviously there is no such data or science or evidence to precisely measure it and prove what the permissible threshold is, or that there is any permissible threshold.

The postponement of the date for converging Samoan MW with the 50 States MW might continue even further, into the 2040s -- the date for the 2 to converge has already been postponed more than once. All we know for sure is that they all see clearly (even the labor unions recognize it), unmistakably, that the damage right now would be too noticeable. They can't fully put the increase into place until the damage from it becomes less obvious, less plain to see. At lower increments of MW the benefit also diminishes, so the % of net damage stays the same no matter how gradually the increases are phased in. All that's accomplished by phasing it in slowly is that the net damage done becomes less noticeable. There's absolutely no evidence that somehow the damage becomes low enough relative to the benefit -- only that it becomes less noticeable. The only net benefit is the employer-bashing glee experienced by the MW fanatics who attach themselves to the symbolism of the higher number (even if 99% of workers get no immediate increase at all).

The reason they won't put the whole increase in place now is the same reason why they won't increase the 50 States MW to $15 right now. Or to $20. The damage would be too obvious, in lost jobs and business cutbacks. No new "data" can refute this, unless the earlier reported facts (like the harm everyone witnessed after the Samoan MW increase) are found to be false. You can't prove with your calculations that anything else caused it.

All your data can prove is how noticeable the damage will be -- the damage that is sure to happen as a result. You can prove that $25/hour would do enough damage to be noticeable to all and impossible to cover up. Whereas somewhere at $15 or below there are ways to more easily hide the damage being done, to make it less noticeable.

Everyone knows that the damage to business and production happens as a result, and there's plenty of evidence for this. We don't need "data" to prove it in any "study" published by official experts by scientifically calculating the damage caused by each increased dollar of MW. This is not how we empirically know economic outcomes. There's no empirical "data" to calculate and prove the particular damage done by each increase in MW, even though it's proved that damage does happen, and no "data" to prove that damage doesn't happen at certain low increments of MW but does happen at other higher increments.

It's proved that the net damage is done, but it's not proved what is the amount of damage from each additional increment of MW or that certain lower increments cause no net damage. There's no evidence that the damage vs. benefit % improves at certain levels over other levels. All that's proved is that at certain high levels the % damage is always too high, whereas at certain low levels we can't measure the damage as easily as the benefit to a select few and the net result (damage) is less noticeable and easier to disregard.

The Samoan case demonstrates this such that no one can deny it. Many other cases also demonstrate it, but the Samoan case is unique because in this one case the MW proponents themselves proved that MW increase did the harm which all of them swear again and again cannot happen: MW causes job losses and net harm.

In contrast, no one has ever proved similarly that MW does net benefit. The opponents of MW have never had to rescind their opposition to MW because of recognized empirical results proving that MW works as intended by proponents.

But MW proponents did rescind their MW increase in this case, proving that MW did cause the opposite of their intended results. That's the proof. The MW crusaders themselves this time proved the case for the other side, by their own decision.


All they've ever proved is that the net harm MW causes is not as great as some had predicted = MW does not work, ever, but the damage it does can hopefully be made low enough so as to not be noticed in particular cases ("the sky does not fall").

The nutty claims in the OP to this topic are not any proved empirical results acknowledged by anyone other than MW crusader fanatics. Such as the damage done by MW increase has been acknowledged by those who enacted it and who then had to undo the damage from it.
 
higher MW = higher labor cost = higher cost of production =
Higher Prices for all, rich and poor
That discounts the workers replaced by automation and that discounts the businesses that close because they're no longer economic.
It also discounts the economic growth due to poor people having more money to spend.
No, the only ones with more money to spend are those getting the artificial wage increase. Most of the poor have LESS real income because of the higher prices they must pay due to the higher labor cost resulting from higher MW.
 
Above screed notwithstanding,
American Samoa is NOT the USA.

What happens when you raise the MW in American Samoa is not a predictor of what happens in the USA.
Most of the poor have LESS real income because of the higher prices they must pay due to the higher labor cost resulting from higher MW.
^ Someone is terminally confused.
“Most of the poor” DON’T HAVE EMPLOYEES.
They would be the RECIPIENTS of that higher labor money, not the payees. The higher prices caused by their higher wages would be a tiny fraction; the vast bulk of it would be paid by those who do the vast bulk of consuming, not the poor.
 
Pizza Hut will lay off delivery drivers;

[quotes] Multiple Pizza Hut franchises in California are planning to lay off delivery drivers as the restaurant chain braces for an increase in the minimum wage for fast food workers next year. Several Pizza Hut operators filed notices to comply with the Worker Adjustment and Retraining Notification Act saying they were discontinuing their delivery services. "PacPizza, LLC, operating as Pizza Hut, has made a business decision to eliminate first-party delivery services and, as a result, the elimination of all delivery driver positions," a federal WARN Act notice filed by the fast-food operator with the state's Employment Development Department said, Business Insider reported.
Another operator, Southern California Pizza Co. also announced layoffs of around 841 drivers across the state. The moves impact Pizza Hut locations in Los Angeles, Orange, San Bernardino, Riverside and Ventura counties. [/quote]

News

One Pizza Hut delivery driver told Business Insider that he was offered a $400 severance if he stuck around through his February 5 layoff date.
"The money they are giving us as severance pay is a slap on the face," he told Insider. "It comes to $3 a month for nine-plus years of service."


WTF, nine years as a pizza delivery driver?!
 
WTF, nine years as a pizza delivery driver?!
Shame how those dummokratz are eliminizing all them career puzzishins, huh?

How the hell are the hoi polloi s’posed to get their pizza in Santa Monica?
 
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