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On August 17 2014 03:17 IgnE wrote:
average is no more correct than median. it depends on what you are looking at. and if the cost of benefts rises faster than the cost of other goods in the bundle than benefits inflation should be calculated differently, while also explaining why "compensation" appearing to rise (through benefits) is an illusion. its very disingenuous of you to say that one way of calculating inflation (the ipd or pce way) is "more correct" while dismissing any arguments about the deficiency of said techniques in accurately measuring inflation in another economic sector. go ahead and explain in more detail why you think im wrong.
as for calling me a liar, maybe you didnt get the data from Heritage but that's where it originated and that's where you should have gotten it from
Where are you getting that Heritage is the source? The article I linked is from The Cleveland Fed, dated 02.03.2012. The Heritage article you linked is dated 07.17.2013. The Fed article is authored by Jacobson and Occhino, the Heritage article is authored by Sherk. Here's a similar article from the St. Louis Fed dated 09.07.2007.
Benefits inflation shouldn't be calculated differently because it is part of the bundle. The bundle already accounts for the difference, so you don't need to account for it a second time. The correct measure of inflation to use in this case is one tied to output, since that's consistent with the theory employed. If you use CPI on compensation, GDP deflator on productivity and import prices go up, than productivity and compensation should diverge. So picking the right thing and being consistent is important here.
In the context of the productivity-compensation link, average is correct. Yes you can use median if you want to use productivity-compensation in specific contexts, but you can't use it to show a de-linking between productivity and compensation. It seems odd to me to do that though. If you want to show inequality, use a measure of inequality. Why re-purpose the productivity-compensation link for something it isn't made for?
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On August 17 2014 03:10 WhiteDog wrote:Show nested quote +On August 17 2014 02:56 JonnyBNoHo wrote:On August 17 2014 02:15 WhiteDog wrote:On August 17 2014 02:07 JonnyBNoHo wrote:On August 17 2014 01:40 WhiteDog wrote:On August 16 2014 08:43 JonnyBNoHo wrote:On August 16 2014 08:17 WhiteDog wrote:On August 16 2014 08:11 JonnyBNoHo wrote:On August 16 2014 08:01 WhiteDog wrote:On August 16 2014 07:58 JonnyBNoHo wrote:
[quote]
?? I didn't deny a gap. You're either having a hard time reading my posts or you aren't reading them at all. I used the phrase "small" because the gap is much smaller than in your graphs. Subjectively, I think it is small anyways as it only represents a few percent of GDP.
Secondly, it is misleading to post productivity with non-supervisory median wages. The link between productivity and income is with total compensation for all workers, not wages for non-supervisory. Additionally, the link needs to use the same deflators for them to be correct. You remember that in the same post I also posted another graph with 4 curve and each different scenario, each showing a gap ? You just quoted the one that you wanted to criticise right ? And can you tell me what's a big gap for you ? 50 pts is "small", so what's big ? 100 ? How can you judge that the gap is small or big ? Both your graphs deserve criticism for the same reasons. As for calling the gap small, did you not notice where I said "subjectively"?? And it's not misleading because you can't evaluate the productivity of non supervisionary workers alone since productivity per group or per anything doesn't exist since production is a social activity you know. Your logic is completely backwards here. If you can't measure the productivity of non-supervisory workers alone than you shouldn't be posting their compensation along with a graph of productivity. edit: You can talk to no end about the statistics and everything else (because all statistical artifacts are rather rash picture of reality), and then there is the fact, there is a gap - bigger than anything since 1950 so I will use the term "huge" gap because I want to, just like you use to term "small" because you want to - and a stagnation of the bottom 25 % wages since 20 years. Bottom 25% of income has risen. I wouldn't call that stagnation, unless you want to look at simple gross wages. I don't think that's a particularly meaningful stat though. 1 - I subjectively consider that all men are pink. 2 - The logic is not backwards, it's just that there are no statistical artefact to specifically evaluate what we are talking about so we purposefully use a deficient one but better than all compensation of all workers. It's often the case in social science : using imperfect data. 3 - I specifically said wage. I consider it very meaningful for political reasons. 1 - You wrote: "How can you judge that the gap is small or big ?" Exactly. Calling it big or small is subjective, unless we can agree on some metric for determining the 'bigness' of the gap. 2 - Sure, using imperfect data can sometimes be OK but you should be upfront about it. Productivity and median non-supervisory wages aren't supposed to be linked. Posting a graph of them together as if they were supposed to be linked (as total productivity and total compensation are) seems misleading to me, if not downright wrong. 3 - Politically it is meaningful, especially when it comes to quick talking points, but from an economic standpoint not so much. Income matters much more than a subset of income. 1 - You put aside the fact that my assumption that the gap is "huge" is based in historical data, and not on my subjectivity alone : it is the biggest gap since WWII. 2 - Your data on compensation are also imperfect. It's "on average", in a broad and statistically homogeneous population, with no distinction between top and bottom income, and "real" value like inflation is an homogeneous phenomena that touch every income group in the same way. Yet I'm not nitpicking since I consider imperfect data as a norm in social science. 3 - It is even meaningful economically, since wage are supposed to be set at marginal productivity in economical theory. This theorical stand is not only an hypothesis, it is and has been the ground justification for capitalism for most economists : it is a question of merit since your wage is relative to your productivity. A gap, small, big or whatever, is yet another clue to point that the theory of the pure and perfect market is false. It's an economical, theorical, moral and political problem, and you're putting it aside for your own conveniance. 1 - You put aside the fact that my gap was small compared to your gap. This is a really petty discussion point. Put this one aside? 2 - It's not so imperfect in the context that it's used. Again, the link is between productivity and compensation and those are the two lines used. Really, that should be the end of the story here. If you want to bring up inequality there exists appropriate data for that. What you shouldn't do is improperly display a productivity-compensation chart just to make it easier to tell your story. 3- Again, you should be talking about compensation here, not just wages. Did you want to talk about why the gap exists, because we can do that! I can show you a breakdown of all the relevant components that contributed to gap. It's pretty benign. Two big ones (as I said a while back) are faster depreciation and imputed rent to homeowners. A third big one is an end to a secular decline in corporate profits around 1980 - which had to happen at some point since profits aren't sustainable at zero. 1 - It's smaller than mine, but not "small". 2 - It is imperfect. The link that we were discussing about is between productivity and compensation for the bottom "99 %". You're talking about you for the second part of your comment, right ? 3 - No. Just because you read a conservative piece of econ doesn't make it true. The core problem is that the distribution of income is a political matter, and not an economic one. The simple fact that you go from wage to compensation prove that in itself - because "compensations" are the result of policies right ? On August 17 2014 01:56 JonnyBNoHo wrote:On August 16 2014 14:37 IgnE wrote:On August 16 2014 08:55 JonnyBNoHo wrote:On August 16 2014 07:51 GreenHorizons wrote:On August 16 2014 07:42 WhiteDog wrote:On August 16 2014 07:29 JonnyBNoHo wrote:On August 16 2014 07:00 WhiteDog wrote:[quote] And you think you're graph prove that what we were talking about is wrong ? lol + Show Spoiler +![[image loading]](http://graphics8.nytimes.com/images/2012/04/28/opinion/042812krugman2/042812krugman2-blog480.jpg) You don't see the gap ? http://krugman.blogs.nytimes.com/2012/04/28/where-the-productivity-went/?_php=true&_type=blogs&_r=0A key to understanding this growth of income inequality—and the disappointing increases in workers’ wages and compensation and middle-class incomes—is understanding the divergence of pay and productivity. Productivity growth has risen substantially over the last few decades but the hourly compensation of the typical worker has seen much more modest growth, especially in the last 10 years or so. The gap between productivity and the compensation growth for the typical worker has been larger in the “lost decade” since the early 2000s than at any point in the post-World War II period. In contrast, productivity and the compensation of the typical worker grew in tandem over the early postwar period until the 1970s. ![[image loading]](http://s3.epi.org/files/2012/ib330-figureA.png.538) http://www.epi.org/publication/ib330-productivity-vs-compensation You wrote that the bottom 99% have had their income stagnate since 1980. I think the chart I posted refuted that rather well. As for the productivity-compensation gap, much of it is error from using different price deflators for productivity and income or ignoring benefits. The correct chart looks this: ![[image loading]](http://1.bp.blogspot.com/-Duoho7jmo9k/TzWMRTCWB6I/AAAAAAAAAmM/pWO4IEKqDdE/s1600/labor+income+2.JPG) Linkstill a gap, but it isn't huge. Also, some of the gap is due to higher depreciation rates and 'imputed' income to homeowners. LOL You're taking a graph that goes back to 1947 to make it seem like the gap is "not huge". Awesome. That's like 50 pts gap (at least) with 1947 at base 100. I think the graphs do a good job of showing the underlying theme regardless of the severity. The majority of people are working harder/being more productive and getting compensated less for their efforts/production, while the top 'earners' are gathering a growing share of the wealth generated by the increased productivity. That's exactly the misinterpretation that I'm trying to prevent. The chart shows that the economy as a whole is more productive and that people are, again as a whole, being compensated more. It also shows that the compensation isn't 100% commensurate with the productivity gain (which may be OK, or not). What the chart does not show is that any subset of the economy is being unfairly compensated in relation to their productivity. That does not mean all subgroups are fairly compensated in relation to their productivity, only that if that is happening, the graph doesn't show it. Instead of quoting that lame Cleveland Fed website you should quote the real source of your massaged data, the Heritage Foundation, so that WhiteDog can respond properly. http://www.heritage.org/research/reports/2013/07/productivity-and-compensation-growing-togetherSo the differences in the graph include things like benefits and "paid leave" that weren't figured into the more popularly used wages vs productivity graph. It's unclear what paid leave means and why it wouldn't be included in wages, since you still get wages, you just happen to not show up at work. My inclination is to say that the massaging Heritage does by including benefits ignores overall increased spending on healthcare that is canceled out by increased benefits, factoring in bonuses somehow, despite the fact that the overwhelming majority of the workforce has no access to appreciable bonuses, and favorable inflation measures that diminish the apparent difference but ignore the differences in inflation's effects on those with less income and wealth. Like instead of including benefits as just a lump sum form of "compensation" why are they not indexed and compared to the cost of benefits in the 70s? It seems like benefits are just being included flatly as "compensation" without being adjusted for "benefit inflation." The Lawrence Mishel paper seems more correct ( http://www.csls.ca/ipm/23/IPM-23-Mishel-Gee.pdf). It seems odd to argue, as Heritage does, that workers in healthcare are stuck in a "low productivity" sector and dragging down their own compensation because they lack skills to move into "higher productivity" fields, without taking into account what might be "benefits inflation" in that very field. + Show Spoiler +![[image loading]](http://www.heritage.org/~/media/images/reports/2013/07/bg%202825/bgproductivityandcompensationchart6825.ashx) I also find it odd that Heritage thinks this is a compelling argument: Even this remaining 23 percent gap is exaggerated, for two reasons. The government productivity is mismeasured and overstated, because BLS is doing an incomplete job accounting for the prices of imported goods that have been used in production. Consider a widget factory that starts using cheaper inputs from China. The BLS does not capture the full cost-savings to employers. It appears to BLS that factories are producing more widgets at lower cost. This looks like increased productivity. However, the gains are coming from trade and the lower price foreign goods, not worker productivity. This may account for about half of the remaining 23 point gap you see in Figure 12. It's as if being able to pay Chinese workers far less than American workers does not impact worker productivity. Yes, the productivity is not American productivity, but to pretend that this isn't a problem in itself, and to pretend that it doesn't specifically affect American workers, seems like economic accounting sleight of hand. The Heritage Foundation's paper: Conclusion
Many pundits and politicians contend that employees’ pay has not kept up with their productivity and that this phenomenon pre-dates the recent deep recession and sluggish recovery. They argue that workers are more productive than ever before, but that employers systematically underpay them. Fortunately, these claims are false. They rest on mistaken comparisons of economic data. Looking at total compensation data—including benefits—from the same source as the productivity figures and using consistent measures of inflation eliminate over three-quarters of the apparent gap between pay and productivity. Factors artificially inflating productivity—like greater depreciation and measurement errors—account for most of the remaining difference. Workers’ compensation has closely tracked their productivity over the past generation. Policymakers should not worry about closing this nonexistent gap. Instead they should look for ways to improve the skills of less-productive workers. We can compare this to the Economic Policy Institute's response, which includes this footnote: Just as one example, Heritage assumes that the gap between compensation and productivity caused by difference in the price deflators used to calculate productivity of firms and used to calculate inflation-adjusted compensation should be seen simply as evidence that consumer price inflation is overstated. There’s an equally compelling interpretation (pdf) that this is instead evidence that we’re overstating the productivity of firms that can be translated into consumption growth, and hence that the last generation has been characterized not just by growing inequality, but by even worse overall economic performance than is commonly thought. and which generally criticizes the Heritage report for using average rather than median compensation figures. ![[image loading]](http://s1.epi.org/files/2013//wp-figure-2.jpg) http://www.epi.org/blog/compensationproductivity-link-broken-vast/#_note1 Average is correct, median is incorrect. Compensation is correct, wages is incorrect. You don't need a special price index for benefits when you use a price index for the economy as a whole. Sorry, but everything you posted here is wrong. If you want me to break down every part here, ask and I will. And why would average is correct and not median ? Because it suits you better ? 1 - ignoring. 2 - The link is between productivity for all workers and compensation for all workers, not a subset of workers. If you want to use a subset of workers, you need both a subset of productivity as well as a subset of compensation. 3 - I use compensation because it's the correct measure. What conservative piece of econ? IgnE claims I got my information from the Heritage Foundation. I didn't, he's an liar.And again, average is correct because it is consistent with the theory that we're using. If productivity increases that creates a limited pool of new resources to be distributed. Part of that pool of resources will be distributed to workers in the form of compensation (wages + benefits). What the theory does not say, is that those new resources will be evenly distributed to all workers or that wages will remain a constant fraction of total compensation. Edit: why don't you want to talk about what caused the gap? 1 - Because I'm right. 2 - Subset productivity can't be evaluated, so we use something else ... That's social science. 3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ? What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland. By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway.
1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best?
2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me.
3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits.
By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but.
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On August 17 2014 04:06 JonnyBNoHo wrote:Show nested quote +On August 17 2014 03:10 WhiteDog wrote:On August 17 2014 02:56 JonnyBNoHo wrote:On August 17 2014 02:15 WhiteDog wrote:On August 17 2014 02:07 JonnyBNoHo wrote:On August 17 2014 01:40 WhiteDog wrote:On August 16 2014 08:43 JonnyBNoHo wrote:On August 16 2014 08:17 WhiteDog wrote:On August 16 2014 08:11 JonnyBNoHo wrote:On August 16 2014 08:01 WhiteDog wrote:
[quote]
You remember that in the same post I also posted another graph with 4 curve and each different scenario, each showing a gap ? You just quoted the one that you wanted to criticise right ?
And can you tell me what's a big gap for you ? 50 pts is "small", so what's big ? 100 ? How can you judge that the gap is small or big ? Both your graphs deserve criticism for the same reasons. As for calling the gap small, did you not notice where I said "subjectively"?? And it's not misleading because you can't evaluate the productivity of non supervisionary workers alone since productivity per group or per anything doesn't exist since production is a social activity you know. Your logic is completely backwards here. If you can't measure the productivity of non-supervisory workers alone than you shouldn't be posting their compensation along with a graph of productivity. edit: You can talk to no end about the statistics and everything else (because all statistical artifacts are rather rash picture of reality), and then there is the fact, there is a gap - bigger than anything since 1950 so I will use the term "huge" gap because I want to, just like you use to term "small" because you want to - and a stagnation of the bottom 25 % wages since 20 years. Bottom 25% of income has risen. I wouldn't call that stagnation, unless you want to look at simple gross wages. I don't think that's a particularly meaningful stat though. 1 - I subjectively consider that all men are pink. 2 - The logic is not backwards, it's just that there are no statistical artefact to specifically evaluate what we are talking about so we purposefully use a deficient one but better than all compensation of all workers. It's often the case in social science : using imperfect data. 3 - I specifically said wage. I consider it very meaningful for political reasons. 1 - You wrote: "How can you judge that the gap is small or big ?" Exactly. Calling it big or small is subjective, unless we can agree on some metric for determining the 'bigness' of the gap. 2 - Sure, using imperfect data can sometimes be OK but you should be upfront about it. Productivity and median non-supervisory wages aren't supposed to be linked. Posting a graph of them together as if they were supposed to be linked (as total productivity and total compensation are) seems misleading to me, if not downright wrong. 3 - Politically it is meaningful, especially when it comes to quick talking points, but from an economic standpoint not so much. Income matters much more than a subset of income. 1 - You put aside the fact that my assumption that the gap is "huge" is based in historical data, and not on my subjectivity alone : it is the biggest gap since WWII. 2 - Your data on compensation are also imperfect. It's "on average", in a broad and statistically homogeneous population, with no distinction between top and bottom income, and "real" value like inflation is an homogeneous phenomena that touch every income group in the same way. Yet I'm not nitpicking since I consider imperfect data as a norm in social science. 3 - It is even meaningful economically, since wage are supposed to be set at marginal productivity in economical theory. This theorical stand is not only an hypothesis, it is and has been the ground justification for capitalism for most economists : it is a question of merit since your wage is relative to your productivity. A gap, small, big or whatever, is yet another clue to point that the theory of the pure and perfect market is false. It's an economical, theorical, moral and political problem, and you're putting it aside for your own conveniance. 1 - You put aside the fact that my gap was small compared to your gap. This is a really petty discussion point. Put this one aside? 2 - It's not so imperfect in the context that it's used. Again, the link is between productivity and compensation and those are the two lines used. Really, that should be the end of the story here. If you want to bring up inequality there exists appropriate data for that. What you shouldn't do is improperly display a productivity-compensation chart just to make it easier to tell your story. 3- Again, you should be talking about compensation here, not just wages. Did you want to talk about why the gap exists, because we can do that! I can show you a breakdown of all the relevant components that contributed to gap. It's pretty benign. Two big ones (as I said a while back) are faster depreciation and imputed rent to homeowners. A third big one is an end to a secular decline in corporate profits around 1980 - which had to happen at some point since profits aren't sustainable at zero. 1 - It's smaller than mine, but not "small". 2 - It is imperfect. The link that we were discussing about is between productivity and compensation for the bottom "99 %". You're talking about you for the second part of your comment, right ? 3 - No. Just because you read a conservative piece of econ doesn't make it true. The core problem is that the distribution of income is a political matter, and not an economic one. The simple fact that you go from wage to compensation prove that in itself - because "compensations" are the result of policies right ? On August 17 2014 01:56 JonnyBNoHo wrote:On August 16 2014 14:37 IgnE wrote:On August 16 2014 08:55 JonnyBNoHo wrote:On August 16 2014 07:51 GreenHorizons wrote:On August 16 2014 07:42 WhiteDog wrote:On August 16 2014 07:29 JonnyBNoHo wrote:[quote] You wrote that the bottom 99% have had their income stagnate since 1980. I think the chart I posted refuted that rather well. As for the productivity-compensation gap, much of it is error from using different price deflators for productivity and income or ignoring benefits. The correct chart looks this: Linkstill a gap, but it isn't huge. Also, some of the gap is due to higher depreciation rates and 'imputed' income to homeowners. LOL You're taking a graph that goes back to 1947 to make it seem like the gap is "not huge". Awesome. That's like 50 pts gap (at least) with 1947 at base 100. I think the graphs do a good job of showing the underlying theme regardless of the severity. The majority of people are working harder/being more productive and getting compensated less for their efforts/production, while the top 'earners' are gathering a growing share of the wealth generated by the increased productivity. That's exactly the misinterpretation that I'm trying to prevent. The chart shows that the economy as a whole is more productive and that people are, again as a whole, being compensated more. It also shows that the compensation isn't 100% commensurate with the productivity gain (which may be OK, or not). What the chart does not show is that any subset of the economy is being unfairly compensated in relation to their productivity. That does not mean all subgroups are fairly compensated in relation to their productivity, only that if that is happening, the graph doesn't show it. Instead of quoting that lame Cleveland Fed website you should quote the real source of your massaged data, the Heritage Foundation, so that WhiteDog can respond properly. http://www.heritage.org/research/reports/2013/07/productivity-and-compensation-growing-togetherSo the differences in the graph include things like benefits and "paid leave" that weren't figured into the more popularly used wages vs productivity graph. It's unclear what paid leave means and why it wouldn't be included in wages, since you still get wages, you just happen to not show up at work. My inclination is to say that the massaging Heritage does by including benefits ignores overall increased spending on healthcare that is canceled out by increased benefits, factoring in bonuses somehow, despite the fact that the overwhelming majority of the workforce has no access to appreciable bonuses, and favorable inflation measures that diminish the apparent difference but ignore the differences in inflation's effects on those with less income and wealth. Like instead of including benefits as just a lump sum form of "compensation" why are they not indexed and compared to the cost of benefits in the 70s? It seems like benefits are just being included flatly as "compensation" without being adjusted for "benefit inflation." The Lawrence Mishel paper seems more correct ( http://www.csls.ca/ipm/23/IPM-23-Mishel-Gee.pdf). It seems odd to argue, as Heritage does, that workers in healthcare are stuck in a "low productivity" sector and dragging down their own compensation because they lack skills to move into "higher productivity" fields, without taking into account what might be "benefits inflation" in that very field. + Show Spoiler +I also find it odd that Heritage thinks this is a compelling argument: Even this remaining 23 percent gap is exaggerated, for two reasons. The government productivity is mismeasured and overstated, because BLS is doing an incomplete job accounting for the prices of imported goods that have been used in production. Consider a widget factory that starts using cheaper inputs from China. The BLS does not capture the full cost-savings to employers. It appears to BLS that factories are producing more widgets at lower cost. This looks like increased productivity. However, the gains are coming from trade and the lower price foreign goods, not worker productivity. This may account for about half of the remaining 23 point gap you see in Figure 12. It's as if being able to pay Chinese workers far less than American workers does not impact worker productivity. Yes, the productivity is not American productivity, but to pretend that this isn't a problem in itself, and to pretend that it doesn't specifically affect American workers, seems like economic accounting sleight of hand. The Heritage Foundation's paper: Conclusion
Many pundits and politicians contend that employees’ pay has not kept up with their productivity and that this phenomenon pre-dates the recent deep recession and sluggish recovery. They argue that workers are more productive than ever before, but that employers systematically underpay them. Fortunately, these claims are false. They rest on mistaken comparisons of economic data. Looking at total compensation data—including benefits—from the same source as the productivity figures and using consistent measures of inflation eliminate over three-quarters of the apparent gap between pay and productivity. Factors artificially inflating productivity—like greater depreciation and measurement errors—account for most of the remaining difference. Workers’ compensation has closely tracked their productivity over the past generation. Policymakers should not worry about closing this nonexistent gap. Instead they should look for ways to improve the skills of less-productive workers. We can compare this to the Economic Policy Institute's response, which includes this footnote: Just as one example, Heritage assumes that the gap between compensation and productivity caused by difference in the price deflators used to calculate productivity of firms and used to calculate inflation-adjusted compensation should be seen simply as evidence that consumer price inflation is overstated. There’s an equally compelling interpretation (pdf) that this is instead evidence that we’re overstating the productivity of firms that can be translated into consumption growth, and hence that the last generation has been characterized not just by growing inequality, but by even worse overall economic performance than is commonly thought. and which generally criticizes the Heritage report for using average rather than median compensation figures. http://www.epi.org/blog/compensationproductivity-link-broken-vast/#_note1 Average is correct, median is incorrect. Compensation is correct, wages is incorrect. You don't need a special price index for benefits when you use a price index for the economy as a whole. Sorry, but everything you posted here is wrong. If you want me to break down every part here, ask and I will. And why would average is correct and not median ? Because it suits you better ? 1 - ignoring. 2 - The link is between productivity for all workers and compensation for all workers, not a subset of workers. If you want to use a subset of workers, you need both a subset of productivity as well as a subset of compensation. 3 - I use compensation because it's the correct measure. What conservative piece of econ? IgnE claims I got my information from the Heritage Foundation. I didn't, he's an liar.And again, average is correct because it is consistent with the theory that we're using. If productivity increases that creates a limited pool of new resources to be distributed. Part of that pool of resources will be distributed to workers in the form of compensation (wages + benefits). What the theory does not say, is that those new resources will be evenly distributed to all workers or that wages will remain a constant fraction of total compensation. Edit: why don't you want to talk about what caused the gap? 1 - Because I'm right. 2 - Subset productivity can't be evaluated, so we use something else ... That's social science. 3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ? What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland. By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway. 1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best? 2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me. 3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits. By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but.
And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough.
The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income...
The regulation part was sarcastic.
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On August 17 2014 04:27 WhiteDog wrote:Show nested quote +On August 17 2014 04:06 JonnyBNoHo wrote:On August 17 2014 03:10 WhiteDog wrote:On August 17 2014 02:56 JonnyBNoHo wrote:On August 17 2014 02:15 WhiteDog wrote:On August 17 2014 02:07 JonnyBNoHo wrote:On August 17 2014 01:40 WhiteDog wrote:On August 16 2014 08:43 JonnyBNoHo wrote:On August 16 2014 08:17 WhiteDog wrote:On August 16 2014 08:11 JonnyBNoHo wrote:
[quote]
Both your graphs deserve criticism for the same reasons. As for calling the gap small, did you not notice where I said "subjectively"??
[quote]
Your logic is completely backwards here. If you can't measure the productivity of non-supervisory workers alone than you shouldn't be posting their compensation along with a graph of productivity.
edit: [quote]Bottom 25% of income has risen. I wouldn't call that stagnation, unless you want to look at simple gross wages. I don't think that's a particularly meaningful stat though. 1 - I subjectively consider that all men are pink. 2 - The logic is not backwards, it's just that there are no statistical artefact to specifically evaluate what we are talking about so we purposefully use a deficient one but better than all compensation of all workers. It's often the case in social science : using imperfect data. 3 - I specifically said wage. I consider it very meaningful for political reasons. 1 - You wrote: "How can you judge that the gap is small or big ?" Exactly. Calling it big or small is subjective, unless we can agree on some metric for determining the 'bigness' of the gap. 2 - Sure, using imperfect data can sometimes be OK but you should be upfront about it. Productivity and median non-supervisory wages aren't supposed to be linked. Posting a graph of them together as if they were supposed to be linked (as total productivity and total compensation are) seems misleading to me, if not downright wrong. 3 - Politically it is meaningful, especially when it comes to quick talking points, but from an economic standpoint not so much. Income matters much more than a subset of income. 1 - You put aside the fact that my assumption that the gap is "huge" is based in historical data, and not on my subjectivity alone : it is the biggest gap since WWII. 2 - Your data on compensation are also imperfect. It's "on average", in a broad and statistically homogeneous population, with no distinction between top and bottom income, and "real" value like inflation is an homogeneous phenomena that touch every income group in the same way. Yet I'm not nitpicking since I consider imperfect data as a norm in social science. 3 - It is even meaningful economically, since wage are supposed to be set at marginal productivity in economical theory. This theorical stand is not only an hypothesis, it is and has been the ground justification for capitalism for most economists : it is a question of merit since your wage is relative to your productivity. A gap, small, big or whatever, is yet another clue to point that the theory of the pure and perfect market is false. It's an economical, theorical, moral and political problem, and you're putting it aside for your own conveniance. 1 - You put aside the fact that my gap was small compared to your gap. This is a really petty discussion point. Put this one aside? 2 - It's not so imperfect in the context that it's used. Again, the link is between productivity and compensation and those are the two lines used. Really, that should be the end of the story here. If you want to bring up inequality there exists appropriate data for that. What you shouldn't do is improperly display a productivity-compensation chart just to make it easier to tell your story. 3- Again, you should be talking about compensation here, not just wages. Did you want to talk about why the gap exists, because we can do that! I can show you a breakdown of all the relevant components that contributed to gap. It's pretty benign. Two big ones (as I said a while back) are faster depreciation and imputed rent to homeowners. A third big one is an end to a secular decline in corporate profits around 1980 - which had to happen at some point since profits aren't sustainable at zero. 1 - It's smaller than mine, but not "small". 2 - It is imperfect. The link that we were discussing about is between productivity and compensation for the bottom "99 %". You're talking about you for the second part of your comment, right ? 3 - No. Just because you read a conservative piece of econ doesn't make it true. The core problem is that the distribution of income is a political matter, and not an economic one. The simple fact that you go from wage to compensation prove that in itself - because "compensations" are the result of policies right ? On August 17 2014 01:56 JonnyBNoHo wrote:On August 16 2014 14:37 IgnE wrote:On August 16 2014 08:55 JonnyBNoHo wrote:On August 16 2014 07:51 GreenHorizons wrote:On August 16 2014 07:42 WhiteDog wrote:
[quote]
LOL You're taking a graph that goes back to 1947 to make it seem like the gap is "not huge". Awesome. That's like 50 pts gap (at least) with 1947 at base 100. I think the graphs do a good job of showing the underlying theme regardless of the severity. The majority of people are working harder/being more productive and getting compensated less for their efforts/production, while the top 'earners' are gathering a growing share of the wealth generated by the increased productivity. That's exactly the misinterpretation that I'm trying to prevent. The chart shows that the economy as a whole is more productive and that people are, again as a whole, being compensated more. It also shows that the compensation isn't 100% commensurate with the productivity gain (which may be OK, or not). What the chart does not show is that any subset of the economy is being unfairly compensated in relation to their productivity. That does not mean all subgroups are fairly compensated in relation to their productivity, only that if that is happening, the graph doesn't show it. Instead of quoting that lame Cleveland Fed website you should quote the real source of your massaged data, the Heritage Foundation, so that WhiteDog can respond properly. http://www.heritage.org/research/reports/2013/07/productivity-and-compensation-growing-togetherSo the differences in the graph include things like benefits and "paid leave" that weren't figured into the more popularly used wages vs productivity graph. It's unclear what paid leave means and why it wouldn't be included in wages, since you still get wages, you just happen to not show up at work. My inclination is to say that the massaging Heritage does by including benefits ignores overall increased spending on healthcare that is canceled out by increased benefits, factoring in bonuses somehow, despite the fact that the overwhelming majority of the workforce has no access to appreciable bonuses, and favorable inflation measures that diminish the apparent difference but ignore the differences in inflation's effects on those with less income and wealth. Like instead of including benefits as just a lump sum form of "compensation" why are they not indexed and compared to the cost of benefits in the 70s? It seems like benefits are just being included flatly as "compensation" without being adjusted for "benefit inflation." The Lawrence Mishel paper seems more correct ( http://www.csls.ca/ipm/23/IPM-23-Mishel-Gee.pdf). It seems odd to argue, as Heritage does, that workers in healthcare are stuck in a "low productivity" sector and dragging down their own compensation because they lack skills to move into "higher productivity" fields, without taking into account what might be "benefits inflation" in that very field. + Show Spoiler +I also find it odd that Heritage thinks this is a compelling argument: Even this remaining 23 percent gap is exaggerated, for two reasons. The government productivity is mismeasured and overstated, because BLS is doing an incomplete job accounting for the prices of imported goods that have been used in production. Consider a widget factory that starts using cheaper inputs from China. The BLS does not capture the full cost-savings to employers. It appears to BLS that factories are producing more widgets at lower cost. This looks like increased productivity. However, the gains are coming from trade and the lower price foreign goods, not worker productivity. This may account for about half of the remaining 23 point gap you see in Figure 12. It's as if being able to pay Chinese workers far less than American workers does not impact worker productivity. Yes, the productivity is not American productivity, but to pretend that this isn't a problem in itself, and to pretend that it doesn't specifically affect American workers, seems like economic accounting sleight of hand. The Heritage Foundation's paper: Conclusion
Many pundits and politicians contend that employees’ pay has not kept up with their productivity and that this phenomenon pre-dates the recent deep recession and sluggish recovery. They argue that workers are more productive than ever before, but that employers systematically underpay them. Fortunately, these claims are false. They rest on mistaken comparisons of economic data. Looking at total compensation data—including benefits—from the same source as the productivity figures and using consistent measures of inflation eliminate over three-quarters of the apparent gap between pay and productivity. Factors artificially inflating productivity—like greater depreciation and measurement errors—account for most of the remaining difference. Workers’ compensation has closely tracked their productivity over the past generation. Policymakers should not worry about closing this nonexistent gap. Instead they should look for ways to improve the skills of less-productive workers. We can compare this to the Economic Policy Institute's response, which includes this footnote: Just as one example, Heritage assumes that the gap between compensation and productivity caused by difference in the price deflators used to calculate productivity of firms and used to calculate inflation-adjusted compensation should be seen simply as evidence that consumer price inflation is overstated. There’s an equally compelling interpretation (pdf) that this is instead evidence that we’re overstating the productivity of firms that can be translated into consumption growth, and hence that the last generation has been characterized not just by growing inequality, but by even worse overall economic performance than is commonly thought. and which generally criticizes the Heritage report for using average rather than median compensation figures. http://www.epi.org/blog/compensationproductivity-link-broken-vast/#_note1 Average is correct, median is incorrect. Compensation is correct, wages is incorrect. You don't need a special price index for benefits when you use a price index for the economy as a whole. Sorry, but everything you posted here is wrong. If you want me to break down every part here, ask and I will. And why would average is correct and not median ? Because it suits you better ? 1 - ignoring. 2 - The link is between productivity for all workers and compensation for all workers, not a subset of workers. If you want to use a subset of workers, you need both a subset of productivity as well as a subset of compensation. 3 - I use compensation because it's the correct measure. What conservative piece of econ? IgnE claims I got my information from the Heritage Foundation. I didn't, he's an liar.And again, average is correct because it is consistent with the theory that we're using. If productivity increases that creates a limited pool of new resources to be distributed. Part of that pool of resources will be distributed to workers in the form of compensation (wages + benefits). What the theory does not say, is that those new resources will be evenly distributed to all workers or that wages will remain a constant fraction of total compensation. Edit: why don't you want to talk about what caused the gap? 1 - Because I'm right. 2 - Subset productivity can't be evaluated, so we use something else ... That's social science. 3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ? What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland. By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway. 1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best? 2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me. 3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits. By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but. And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough. The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income... The regulation part was sarcastic.
There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS.
The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing.
Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers.
As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view.
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Plotting median wages against mean productivity seems like a strange thing to do, since we know nothing about the distribution of productivity. Even in an extreme case where we might find that median wages have declined, who is to say that the same can't be said about productivity?
There is no doubt that income and wealth inequality is on the increase in many place, but in the specific context of this study it does not seem very fruitful to consider this.
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On August 17 2014 03:52 JonnyBNoHo wrote:Show nested quote +On August 17 2014 03:17 IgnE wrote:
average is no more correct than median. it depends on what you are looking at. and if the cost of benefts rises faster than the cost of other goods in the bundle than benefits inflation should be calculated differently, while also explaining why "compensation" appearing to rise (through benefits) is an illusion. its very disingenuous of you to say that one way of calculating inflation (the ipd or pce way) is "more correct" while dismissing any arguments about the deficiency of said techniques in accurately measuring inflation in another economic sector. go ahead and explain in more detail why you think im wrong.
as for calling me a liar, maybe you didnt get the data from Heritage but that's where it originated and that's where you should have gotten it from
Where are you getting that Heritage is the source? The article I linked is from The Cleveland Fed, dated 02.03.2012. The Heritage article you linked is dated 07.17.2013. The Fed article is authored by Jacobson and Occhino, the Heritage article is authored by Sherk. Here's a similar article from the St. Louis Fed dated 09.07.2007. Benefits inflation shouldn't be calculated differently because it is part of the bundle. The bundle already accounts for the difference, so you don't need to account for it a second time. The correct measure of inflation to use in this case is one tied to output, since that's consistent with the theory employed. If you use CPI on compensation, GDP deflator on productivity and import prices go up, than productivity and compensation should diverge. So picking the right thing and being consistent is important here. In the context of the productivity-compensation link, average is correct. Yes you can use median if you want to use productivity-compensation in specific contexts, but you can't use it to show a de-linking between productivity and compensation. It seems odd to me to do that though. If you want to show inequality, use a measure of inequality. Why re-purpose the productivity-compensation link for something it isn't made for?
ok maybe the fed graph you linked isn't sourced from the heritage report. my bad. im on a phone and cant double check as easily.
just saying that healthcare is factored into the inflation price indexes doesnt seem to really address the concern here. the indexes choose a somewhat arbitrary weighting for various categories and the hypothesis at issue here is that healthcare costs arent being weighted appropriately. if the only compensation that has gone up is healthcarw benefits that doesnt necessarily mean that we should consider that compensation as equivalent to wages, since healthcarw might be considered a relatively stable good over time. seems like you would have to argue that health outcomes have improved at a similar rate to the imputed healthcare compensation increases over the last 30 years, despite the US lagging behind its peers in life expectancy gains. the cpi vs pce indexes for example factor healthcare costs into their index very differently
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On August 17 2014 04:55 JonnyBNoHo wrote:Show nested quote +On August 17 2014 04:27 WhiteDog wrote:On August 17 2014 04:06 JonnyBNoHo wrote:On August 17 2014 03:10 WhiteDog wrote:On August 17 2014 02:56 JonnyBNoHo wrote:On August 17 2014 02:15 WhiteDog wrote:On August 17 2014 02:07 JonnyBNoHo wrote:On August 17 2014 01:40 WhiteDog wrote:On August 16 2014 08:43 JonnyBNoHo wrote:On August 16 2014 08:17 WhiteDog wrote:
[quote]
1 - I subjectively consider that all men are pink.
2 - The logic is not backwards, it's just that there are no statistical artefact to specifically evaluate what we are talking about so we purposefully use a deficient one but better than all compensation of all workers. It's often the case in social science : using imperfect data.
3 - I specifically said wage. I consider it very meaningful for political reasons. 1 - You wrote: "How can you judge that the gap is small or big ?" Exactly. Calling it big or small is subjective, unless we can agree on some metric for determining the 'bigness' of the gap. 2 - Sure, using imperfect data can sometimes be OK but you should be upfront about it. Productivity and median non-supervisory wages aren't supposed to be linked. Posting a graph of them together as if they were supposed to be linked (as total productivity and total compensation are) seems misleading to me, if not downright wrong. 3 - Politically it is meaningful, especially when it comes to quick talking points, but from an economic standpoint not so much. Income matters much more than a subset of income. 1 - You put aside the fact that my assumption that the gap is "huge" is based in historical data, and not on my subjectivity alone : it is the biggest gap since WWII. 2 - Your data on compensation are also imperfect. It's "on average", in a broad and statistically homogeneous population, with no distinction between top and bottom income, and "real" value like inflation is an homogeneous phenomena that touch every income group in the same way. Yet I'm not nitpicking since I consider imperfect data as a norm in social science. 3 - It is even meaningful economically, since wage are supposed to be set at marginal productivity in economical theory. This theorical stand is not only an hypothesis, it is and has been the ground justification for capitalism for most economists : it is a question of merit since your wage is relative to your productivity. A gap, small, big or whatever, is yet another clue to point that the theory of the pure and perfect market is false. It's an economical, theorical, moral and political problem, and you're putting it aside for your own conveniance. 1 - You put aside the fact that my gap was small compared to your gap. This is a really petty discussion point. Put this one aside? 2 - It's not so imperfect in the context that it's used. Again, the link is between productivity and compensation and those are the two lines used. Really, that should be the end of the story here. If you want to bring up inequality there exists appropriate data for that. What you shouldn't do is improperly display a productivity-compensation chart just to make it easier to tell your story. 3- Again, you should be talking about compensation here, not just wages. Did you want to talk about why the gap exists, because we can do that! I can show you a breakdown of all the relevant components that contributed to gap. It's pretty benign. Two big ones (as I said a while back) are faster depreciation and imputed rent to homeowners. A third big one is an end to a secular decline in corporate profits around 1980 - which had to happen at some point since profits aren't sustainable at zero. 1 - It's smaller than mine, but not "small". 2 - It is imperfect. The link that we were discussing about is between productivity and compensation for the bottom "99 %". You're talking about you for the second part of your comment, right ? 3 - No. Just because you read a conservative piece of econ doesn't make it true. The core problem is that the distribution of income is a political matter, and not an economic one. The simple fact that you go from wage to compensation prove that in itself - because "compensations" are the result of policies right ? On August 17 2014 01:56 JonnyBNoHo wrote:On August 16 2014 14:37 IgnE wrote:On August 16 2014 08:55 JonnyBNoHo wrote:On August 16 2014 07:51 GreenHorizons wrote:
[quote]
I think the graphs do a good job of showing the underlying theme regardless of the severity.
The majority of people are working harder/being more productive and getting compensated less for their efforts/production, while the top 'earners' are gathering a growing share of the wealth generated by the increased productivity. That's exactly the misinterpretation that I'm trying to prevent. The chart shows that the economy as a whole is more productive and that people are, again as a whole, being compensated more. It also shows that the compensation isn't 100% commensurate with the productivity gain (which may be OK, or not). What the chart does not show is that any subset of the economy is being unfairly compensated in relation to their productivity. That does not mean all subgroups are fairly compensated in relation to their productivity, only that if that is happening, the graph doesn't show it. Instead of quoting that lame Cleveland Fed website you should quote the real source of your massaged data, the Heritage Foundation, so that WhiteDog can respond properly. http://www.heritage.org/research/reports/2013/07/productivity-and-compensation-growing-togetherSo the differences in the graph include things like benefits and "paid leave" that weren't figured into the more popularly used wages vs productivity graph. It's unclear what paid leave means and why it wouldn't be included in wages, since you still get wages, you just happen to not show up at work. My inclination is to say that the massaging Heritage does by including benefits ignores overall increased spending on healthcare that is canceled out by increased benefits, factoring in bonuses somehow, despite the fact that the overwhelming majority of the workforce has no access to appreciable bonuses, and favorable inflation measures that diminish the apparent difference but ignore the differences in inflation's effects on those with less income and wealth. Like instead of including benefits as just a lump sum form of "compensation" why are they not indexed and compared to the cost of benefits in the 70s? It seems like benefits are just being included flatly as "compensation" without being adjusted for "benefit inflation." The Lawrence Mishel paper seems more correct ( http://www.csls.ca/ipm/23/IPM-23-Mishel-Gee.pdf). It seems odd to argue, as Heritage does, that workers in healthcare are stuck in a "low productivity" sector and dragging down their own compensation because they lack skills to move into "higher productivity" fields, without taking into account what might be "benefits inflation" in that very field. + Show Spoiler +I also find it odd that Heritage thinks this is a compelling argument: Even this remaining 23 percent gap is exaggerated, for two reasons. The government productivity is mismeasured and overstated, because BLS is doing an incomplete job accounting for the prices of imported goods that have been used in production. Consider a widget factory that starts using cheaper inputs from China. The BLS does not capture the full cost-savings to employers. It appears to BLS that factories are producing more widgets at lower cost. This looks like increased productivity. However, the gains are coming from trade and the lower price foreign goods, not worker productivity. This may account for about half of the remaining 23 point gap you see in Figure 12. It's as if being able to pay Chinese workers far less than American workers does not impact worker productivity. Yes, the productivity is not American productivity, but to pretend that this isn't a problem in itself, and to pretend that it doesn't specifically affect American workers, seems like economic accounting sleight of hand. The Heritage Foundation's paper: Conclusion
Many pundits and politicians contend that employees’ pay has not kept up with their productivity and that this phenomenon pre-dates the recent deep recession and sluggish recovery. They argue that workers are more productive than ever before, but that employers systematically underpay them. Fortunately, these claims are false. They rest on mistaken comparisons of economic data. Looking at total compensation data—including benefits—from the same source as the productivity figures and using consistent measures of inflation eliminate over three-quarters of the apparent gap between pay and productivity. Factors artificially inflating productivity—like greater depreciation and measurement errors—account for most of the remaining difference. Workers’ compensation has closely tracked their productivity over the past generation. Policymakers should not worry about closing this nonexistent gap. Instead they should look for ways to improve the skills of less-productive workers. We can compare this to the Economic Policy Institute's response, which includes this footnote: Just as one example, Heritage assumes that the gap between compensation and productivity caused by difference in the price deflators used to calculate productivity of firms and used to calculate inflation-adjusted compensation should be seen simply as evidence that consumer price inflation is overstated. There’s an equally compelling interpretation (pdf) that this is instead evidence that we’re overstating the productivity of firms that can be translated into consumption growth, and hence that the last generation has been characterized not just by growing inequality, but by even worse overall economic performance than is commonly thought. and which generally criticizes the Heritage report for using average rather than median compensation figures. http://www.epi.org/blog/compensationproductivity-link-broken-vast/#_note1 Average is correct, median is incorrect. Compensation is correct, wages is incorrect. You don't need a special price index for benefits when you use a price index for the economy as a whole. Sorry, but everything you posted here is wrong. If you want me to break down every part here, ask and I will. And why would average is correct and not median ? Because it suits you better ? 1 - ignoring. 2 - The link is between productivity for all workers and compensation for all workers, not a subset of workers. If you want to use a subset of workers, you need both a subset of productivity as well as a subset of compensation. 3 - I use compensation because it's the correct measure. What conservative piece of econ? IgnE claims I got my information from the Heritage Foundation. I didn't, he's an liar.And again, average is correct because it is consistent with the theory that we're using. If productivity increases that creates a limited pool of new resources to be distributed. Part of that pool of resources will be distributed to workers in the form of compensation (wages + benefits). What the theory does not say, is that those new resources will be evenly distributed to all workers or that wages will remain a constant fraction of total compensation. Edit: why don't you want to talk about what caused the gap? 1 - Because I'm right. 2 - Subset productivity can't be evaluated, so we use something else ... That's social science. 3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ? What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland. By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway. 1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best? 2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me. 3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits. By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but. And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough. The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income... The regulation part was sarcastic. There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS. The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing. Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers. As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view.
Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall.
Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. We make such assumption evrytime we evaluate anything relates to productivity - the reason why it is called "apparent productivity". This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ?
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OK, so let's assume the compensation/productivity gains gap is 23% and growing from Johnny's source, I would be willing to debate policy measures to bring it back into lockstep. I certainly won't argue along ideological lines that increases in productivity shouldn't be passed along in the from of total compensation. What is the best way to go about recoupling the two metrics?
A raise in the federal minimum wage from 7.25 to 9.42? (seems fair to me)
an across the board 23% raise to everybody? (economic suicide imo)
I wouldn't mind legislating transparency on productivity gains to be sent out with W2's. (the average employee will probably be too stupid to utilize this info without collective bargaining)
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On August 17 2014 06:01 WhiteDog wrote:Show nested quote +On August 17 2014 04:55 JonnyBNoHo wrote:On August 17 2014 04:27 WhiteDog wrote:On August 17 2014 04:06 JonnyBNoHo wrote:On August 17 2014 03:10 WhiteDog wrote:On August 17 2014 02:56 JonnyBNoHo wrote:On August 17 2014 02:15 WhiteDog wrote:On August 17 2014 02:07 JonnyBNoHo wrote:On August 17 2014 01:40 WhiteDog wrote:On August 16 2014 08:43 JonnyBNoHo wrote:
[quote]
1 - You wrote: "How can you judge that the gap is small or big ?" Exactly. Calling it big or small is subjective, unless we can agree on some metric for determining the 'bigness' of the gap.
2 - Sure, using imperfect data can sometimes be OK but you should be upfront about it. Productivity and median non-supervisory wages aren't supposed to be linked. Posting a graph of them together as if they were supposed to be linked (as total productivity and total compensation are) seems misleading to me, if not downright wrong.
3 - Politically it is meaningful, especially when it comes to quick talking points, but from an economic standpoint not so much. Income matters much more than a subset of income. 1 - You put aside the fact that my assumption that the gap is "huge" is based in historical data, and not on my subjectivity alone : it is the biggest gap since WWII. 2 - Your data on compensation are also imperfect. It's "on average", in a broad and statistically homogeneous population, with no distinction between top and bottom income, and "real" value like inflation is an homogeneous phenomena that touch every income group in the same way. Yet I'm not nitpicking since I consider imperfect data as a norm in social science. 3 - It is even meaningful economically, since wage are supposed to be set at marginal productivity in economical theory. This theorical stand is not only an hypothesis, it is and has been the ground justification for capitalism for most economists : it is a question of merit since your wage is relative to your productivity. A gap, small, big or whatever, is yet another clue to point that the theory of the pure and perfect market is false. It's an economical, theorical, moral and political problem, and you're putting it aside for your own conveniance. 1 - You put aside the fact that my gap was small compared to your gap. This is a really petty discussion point. Put this one aside? 2 - It's not so imperfect in the context that it's used. Again, the link is between productivity and compensation and those are the two lines used. Really, that should be the end of the story here. If you want to bring up inequality there exists appropriate data for that. What you shouldn't do is improperly display a productivity-compensation chart just to make it easier to tell your story. 3- Again, you should be talking about compensation here, not just wages. Did you want to talk about why the gap exists, because we can do that! I can show you a breakdown of all the relevant components that contributed to gap. It's pretty benign. Two big ones (as I said a while back) are faster depreciation and imputed rent to homeowners. A third big one is an end to a secular decline in corporate profits around 1980 - which had to happen at some point since profits aren't sustainable at zero. 1 - It's smaller than mine, but not "small". 2 - It is imperfect. The link that we were discussing about is between productivity and compensation for the bottom "99 %". You're talking about you for the second part of your comment, right ? 3 - No. Just because you read a conservative piece of econ doesn't make it true. The core problem is that the distribution of income is a political matter, and not an economic one. The simple fact that you go from wage to compensation prove that in itself - because "compensations" are the result of policies right ? On August 17 2014 01:56 JonnyBNoHo wrote:On August 16 2014 14:37 IgnE wrote:On August 16 2014 08:55 JonnyBNoHo wrote:
[quote]
That's exactly the misinterpretation that I'm trying to prevent. The chart shows that the economy as a whole is more productive and that people are, again as a whole, being compensated more. It also shows that the compensation isn't 100% commensurate with the productivity gain (which may be OK, or not).
What the chart does not show is that any subset of the economy is being unfairly compensated in relation to their productivity. That does not mean all subgroups are fairly compensated in relation to their productivity, only that if that is happening, the graph doesn't show it. Instead of quoting that lame Cleveland Fed website you should quote the real source of your massaged data, the Heritage Foundation, so that WhiteDog can respond properly. http://www.heritage.org/research/reports/2013/07/productivity-and-compensation-growing-togetherSo the differences in the graph include things like benefits and "paid leave" that weren't figured into the more popularly used wages vs productivity graph. It's unclear what paid leave means and why it wouldn't be included in wages, since you still get wages, you just happen to not show up at work. My inclination is to say that the massaging Heritage does by including benefits ignores overall increased spending on healthcare that is canceled out by increased benefits, factoring in bonuses somehow, despite the fact that the overwhelming majority of the workforce has no access to appreciable bonuses, and favorable inflation measures that diminish the apparent difference but ignore the differences in inflation's effects on those with less income and wealth. Like instead of including benefits as just a lump sum form of "compensation" why are they not indexed and compared to the cost of benefits in the 70s? It seems like benefits are just being included flatly as "compensation" without being adjusted for "benefit inflation." The Lawrence Mishel paper seems more correct ( http://www.csls.ca/ipm/23/IPM-23-Mishel-Gee.pdf). It seems odd to argue, as Heritage does, that workers in healthcare are stuck in a "low productivity" sector and dragging down their own compensation because they lack skills to move into "higher productivity" fields, without taking into account what might be "benefits inflation" in that very field. + Show Spoiler +I also find it odd that Heritage thinks this is a compelling argument: Even this remaining 23 percent gap is exaggerated, for two reasons. The government productivity is mismeasured and overstated, because BLS is doing an incomplete job accounting for the prices of imported goods that have been used in production. Consider a widget factory that starts using cheaper inputs from China. The BLS does not capture the full cost-savings to employers. It appears to BLS that factories are producing more widgets at lower cost. This looks like increased productivity. However, the gains are coming from trade and the lower price foreign goods, not worker productivity. This may account for about half of the remaining 23 point gap you see in Figure 12. It's as if being able to pay Chinese workers far less than American workers does not impact worker productivity. Yes, the productivity is not American productivity, but to pretend that this isn't a problem in itself, and to pretend that it doesn't specifically affect American workers, seems like economic accounting sleight of hand. The Heritage Foundation's paper: Conclusion
Many pundits and politicians contend that employees’ pay has not kept up with their productivity and that this phenomenon pre-dates the recent deep recession and sluggish recovery. They argue that workers are more productive than ever before, but that employers systematically underpay them. Fortunately, these claims are false. They rest on mistaken comparisons of economic data. Looking at total compensation data—including benefits—from the same source as the productivity figures and using consistent measures of inflation eliminate over three-quarters of the apparent gap between pay and productivity. Factors artificially inflating productivity—like greater depreciation and measurement errors—account for most of the remaining difference. Workers’ compensation has closely tracked their productivity over the past generation. Policymakers should not worry about closing this nonexistent gap. Instead they should look for ways to improve the skills of less-productive workers. We can compare this to the Economic Policy Institute's response, which includes this footnote: Just as one example, Heritage assumes that the gap between compensation and productivity caused by difference in the price deflators used to calculate productivity of firms and used to calculate inflation-adjusted compensation should be seen simply as evidence that consumer price inflation is overstated. There’s an equally compelling interpretation (pdf) that this is instead evidence that we’re overstating the productivity of firms that can be translated into consumption growth, and hence that the last generation has been characterized not just by growing inequality, but by even worse overall economic performance than is commonly thought. and which generally criticizes the Heritage report for using average rather than median compensation figures. http://www.epi.org/blog/compensationproductivity-link-broken-vast/#_note1 Average is correct, median is incorrect. Compensation is correct, wages is incorrect. You don't need a special price index for benefits when you use a price index for the economy as a whole. Sorry, but everything you posted here is wrong. If you want me to break down every part here, ask and I will. And why would average is correct and not median ? Because it suits you better ? 1 - ignoring. 2 - The link is between productivity for all workers and compensation for all workers, not a subset of workers. If you want to use a subset of workers, you need both a subset of productivity as well as a subset of compensation. 3 - I use compensation because it's the correct measure. What conservative piece of econ? IgnE claims I got my information from the Heritage Foundation. I didn't, he's an liar.And again, average is correct because it is consistent with the theory that we're using. If productivity increases that creates a limited pool of new resources to be distributed. Part of that pool of resources will be distributed to workers in the form of compensation (wages + benefits). What the theory does not say, is that those new resources will be evenly distributed to all workers or that wages will remain a constant fraction of total compensation. Edit: why don't you want to talk about what caused the gap? 1 - Because I'm right. 2 - Subset productivity can't be evaluated, so we use something else ... That's social science. 3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ? What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland. By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway. 1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best? 2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me. 3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits. By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but. And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough. The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income... The regulation part was sarcastic. There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS. The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing. Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers. As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view. Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall. Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ? And this has nothing to do with inequalities it s about income distribution...
We do not know anything about the distribution of productivity since an individuals productivity cannot be observed directly. We only have mean productivity (simply GDP/hours worked), we do not have median productivity because that is obviously impossible. Given this, why would you want to compare mean productivity growth with median wage growth? It would tell you absolutely nothing about the relationship between productivity and wages, since the distribution of productivity growth is unknown. It is not necessary to assume a flat distribution to use a mean, that whole comment is just gobbledygook.
To put it more simply: Why compare the guy in the middle's wage to average productivity? Lets say you find that guy in the middle isn't earning more, even though on average people have gotten more productive, does that then mean people are getting screwed? No, maybe the guys on the bottom and the top have gotten much more productive while the guy in the middle has stayed about the same, and is actually being compensated fairly. Since you can't actually know the guy in the middle's productivity why are you even interested in comparing his specific wage to productivity? It is just a very strange thing to do, the mean vs mean plot even shows a sizeable gap so there isn't even a need to do any hack statistics.
(My opinion on the gap is that it is obviously problematic, hard to understand, and even harder to do anyting about).
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On August 17 2014 06:17 Crushinator wrote:Show nested quote +On August 17 2014 06:01 WhiteDog wrote:On August 17 2014 04:55 JonnyBNoHo wrote:On August 17 2014 04:27 WhiteDog wrote:On August 17 2014 04:06 JonnyBNoHo wrote:On August 17 2014 03:10 WhiteDog wrote:On August 17 2014 02:56 JonnyBNoHo wrote:On August 17 2014 02:15 WhiteDog wrote:On August 17 2014 02:07 JonnyBNoHo wrote:On August 17 2014 01:40 WhiteDog wrote:
[quote]
1 - You put aside the fact that my assumption that the gap is "huge" is based in historical data, and not on my subjectivity alone : it is the biggest gap since WWII.
2 - Your data on compensation are also imperfect. It's "on average", in a broad and statistically homogeneous population, with no distinction between top and bottom income, and "real" value like inflation is an homogeneous phenomena that touch every income group in the same way. Yet I'm not nitpicking since I consider imperfect data as a norm in social science.
3 - It is even meaningful economically, since wage are supposed to be set at marginal productivity in economical theory. This theorical stand is not only an hypothesis, it is and has been the ground justification for capitalism for most economists : it is a question of merit since your wage is relative to your productivity. A gap, small, big or whatever, is yet another clue to point that the theory of the pure and perfect market is false. It's an economical, theorical, moral and political problem, and you're putting it aside for your own conveniance. 1 - You put aside the fact that my gap was small compared to your gap. This is a really petty discussion point. Put this one aside? 2 - It's not so imperfect in the context that it's used. Again, the link is between productivity and compensation and those are the two lines used. Really, that should be the end of the story here. If you want to bring up inequality there exists appropriate data for that. What you shouldn't do is improperly display a productivity-compensation chart just to make it easier to tell your story. 3- Again, you should be talking about compensation here, not just wages. Did you want to talk about why the gap exists, because we can do that! I can show you a breakdown of all the relevant components that contributed to gap. It's pretty benign. Two big ones (as I said a while back) are faster depreciation and imputed rent to homeowners. A third big one is an end to a secular decline in corporate profits around 1980 - which had to happen at some point since profits aren't sustainable at zero. 1 - It's smaller than mine, but not "small". 2 - It is imperfect. The link that we were discussing about is between productivity and compensation for the bottom "99 %". You're talking about you for the second part of your comment, right ? 3 - No. Just because you read a conservative piece of econ doesn't make it true. The core problem is that the distribution of income is a political matter, and not an economic one. The simple fact that you go from wage to compensation prove that in itself - because "compensations" are the result of policies right ? On August 17 2014 01:56 JonnyBNoHo wrote:On August 16 2014 14:37 IgnE wrote:[quote] Instead of quoting that lame Cleveland Fed website you should quote the real source of your massaged data, the Heritage Foundation, so that WhiteDog can respond properly. http://www.heritage.org/research/reports/2013/07/productivity-and-compensation-growing-togetherSo the differences in the graph include things like benefits and "paid leave" that weren't figured into the more popularly used wages vs productivity graph. It's unclear what paid leave means and why it wouldn't be included in wages, since you still get wages, you just happen to not show up at work. My inclination is to say that the massaging Heritage does by including benefits ignores overall increased spending on healthcare that is canceled out by increased benefits, factoring in bonuses somehow, despite the fact that the overwhelming majority of the workforce has no access to appreciable bonuses, and favorable inflation measures that diminish the apparent difference but ignore the differences in inflation's effects on those with less income and wealth. Like instead of including benefits as just a lump sum form of "compensation" why are they not indexed and compared to the cost of benefits in the 70s? It seems like benefits are just being included flatly as "compensation" without being adjusted for "benefit inflation." The Lawrence Mishel paper seems more correct ( http://www.csls.ca/ipm/23/IPM-23-Mishel-Gee.pdf). It seems odd to argue, as Heritage does, that workers in healthcare are stuck in a "low productivity" sector and dragging down their own compensation because they lack skills to move into "higher productivity" fields, without taking into account what might be "benefits inflation" in that very field. + Show Spoiler +I also find it odd that Heritage thinks this is a compelling argument: Even this remaining 23 percent gap is exaggerated, for two reasons. The government productivity is mismeasured and overstated, because BLS is doing an incomplete job accounting for the prices of imported goods that have been used in production. Consider a widget factory that starts using cheaper inputs from China. The BLS does not capture the full cost-savings to employers. It appears to BLS that factories are producing more widgets at lower cost. This looks like increased productivity. However, the gains are coming from trade and the lower price foreign goods, not worker productivity. This may account for about half of the remaining 23 point gap you see in Figure 12. It's as if being able to pay Chinese workers far less than American workers does not impact worker productivity. Yes, the productivity is not American productivity, but to pretend that this isn't a problem in itself, and to pretend that it doesn't specifically affect American workers, seems like economic accounting sleight of hand. The Heritage Foundation's paper: Conclusion
Many pundits and politicians contend that employees’ pay has not kept up with their productivity and that this phenomenon pre-dates the recent deep recession and sluggish recovery. They argue that workers are more productive than ever before, but that employers systematically underpay them. Fortunately, these claims are false. They rest on mistaken comparisons of economic data. Looking at total compensation data—including benefits—from the same source as the productivity figures and using consistent measures of inflation eliminate over three-quarters of the apparent gap between pay and productivity. Factors artificially inflating productivity—like greater depreciation and measurement errors—account for most of the remaining difference. Workers’ compensation has closely tracked their productivity over the past generation. Policymakers should not worry about closing this nonexistent gap. Instead they should look for ways to improve the skills of less-productive workers. We can compare this to the Economic Policy Institute's response, which includes this footnote: Just as one example, Heritage assumes that the gap between compensation and productivity caused by difference in the price deflators used to calculate productivity of firms and used to calculate inflation-adjusted compensation should be seen simply as evidence that consumer price inflation is overstated. There’s an equally compelling interpretation (pdf) that this is instead evidence that we’re overstating the productivity of firms that can be translated into consumption growth, and hence that the last generation has been characterized not just by growing inequality, but by even worse overall economic performance than is commonly thought. and which generally criticizes the Heritage report for using average rather than median compensation figures. http://www.epi.org/blog/compensationproductivity-link-broken-vast/#_note1 Average is correct, median is incorrect. Compensation is correct, wages is incorrect. You don't need a special price index for benefits when you use a price index for the economy as a whole. Sorry, but everything you posted here is wrong. If you want me to break down every part here, ask and I will. And why would average is correct and not median ? Because it suits you better ? 1 - ignoring. 2 - The link is between productivity for all workers and compensation for all workers, not a subset of workers. If you want to use a subset of workers, you need both a subset of productivity as well as a subset of compensation. 3 - I use compensation because it's the correct measure. What conservative piece of econ? IgnE claims I got my information from the Heritage Foundation. I didn't, he's an liar.And again, average is correct because it is consistent with the theory that we're using. If productivity increases that creates a limited pool of new resources to be distributed. Part of that pool of resources will be distributed to workers in the form of compensation (wages + benefits). What the theory does not say, is that those new resources will be evenly distributed to all workers or that wages will remain a constant fraction of total compensation. Edit: why don't you want to talk about what caused the gap? 1 - Because I'm right. 2 - Subset productivity can't be evaluated, so we use something else ... That's social science. 3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ? What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland. By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway. 1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best? 2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me. 3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits. By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but. And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough. The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income... The regulation part was sarcastic. There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS. The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing. Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers. As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view. Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall. Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ? And this has nothing to do with inequalities it s about income distribution... We do not know anything about the distribution of productivity since an individuals productivity cannot be observed directly. We only have mean productivity (simply GDP/hours worked), we do not have median productivity because that is obviously impossible. Given this, why would you want to compare mean productivity growth with median wage growth? It would tell you absolutely nothing about the relationship between productivity and wages, since the distribution of productivity growth is unknown. It is not necessary to assume a flat distribution to use a mean, that whole comment is just gobbledygook. To put it more simply: Why compare the guy in the middle's wage to average productivity? Lets say you find that guy in the middle isn't earning more, even though on average people have gotten more productive, does that then mean people are getting screwed? No, maybe the guys on the bottom and the top have gotten much more productive while the guy in the middle has stayed about the same, and is actually being compensated fairly. Since you can't actually know the guy in the middle's productivity why are you even interested in comparing his specific wage to productivity? It is just a very strange thing to do, the mean vs mean plot even shows a sizeable gap so there isn't even a need to do any hack statistics. (My opinion on the gap is that it is obviously problematic, hard to understand, and even harder to do anyting about).
You do this because as you point out, there's no other way to get to the data more directly so we have to create an estimate. Sure, the estimate makes lots of assumptions that might not be true, but it's better than nothing, assuming the writers are open and honest that they're making an estimate based on assumptions rather than calling it Truth.
A lot of economics and finance is based on estimates created from tautological arguments and mathematical identities. Most professionals understand that this is often the best we can do with time and cost-benefit constraints. The same goes for things like BMI, F = ma, and the caloric content of food. They're estimates making lots of assumptions, but if you're trying to get a number quickly and can live with a ballpark figure rather than six significant figure precision, they're close enough.
Your criticisms are fair that the number may not be a good reflection of reality, but it's only relevant if people are taking it a little too seriously. On this particular forum, usually the opposite is true...
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On August 17 2014 07:05 coverpunch wrote:Show nested quote +On August 17 2014 06:17 Crushinator wrote:On August 17 2014 06:01 WhiteDog wrote:On August 17 2014 04:55 JonnyBNoHo wrote:On August 17 2014 04:27 WhiteDog wrote:On August 17 2014 04:06 JonnyBNoHo wrote:On August 17 2014 03:10 WhiteDog wrote:On August 17 2014 02:56 JonnyBNoHo wrote:On August 17 2014 02:15 WhiteDog wrote:On August 17 2014 02:07 JonnyBNoHo wrote:
[quote]
1 - You put aside the fact that my gap was small compared to your gap. This is a really petty discussion point. Put this one aside?
2 - It's not so imperfect in the context that it's used. Again, the link is between productivity and compensation and those are the two lines used. Really, that should be the end of the story here. If you want to bring up inequality there exists appropriate data for that. What you shouldn't do is improperly display a productivity-compensation chart just to make it easier to tell your story.
3- Again, you should be talking about compensation here, not just wages. Did you want to talk about why the gap exists, because we can do that! I can show you a breakdown of all the relevant components that contributed to gap. It's pretty benign. Two big ones (as I said a while back) are faster depreciation and imputed rent to homeowners. A third big one is an end to a secular decline in corporate profits around 1980 - which had to happen at some point since profits aren't sustainable at zero. 1 - It's smaller than mine, but not "small". 2 - It is imperfect. The link that we were discussing about is between productivity and compensation for the bottom "99 %". You're talking about you for the second part of your comment, right ? 3 - No. Just because you read a conservative piece of econ doesn't make it true. The core problem is that the distribution of income is a political matter, and not an economic one. The simple fact that you go from wage to compensation prove that in itself - because "compensations" are the result of policies right ? On August 17 2014 01:56 JonnyBNoHo wrote:
[quote]
Average is correct, median is incorrect. Compensation is correct, wages is incorrect. You don't need a special price index for benefits when you use a price index for the economy as a whole. Sorry, but everything you posted here is wrong.
If you want me to break down every part here, ask and I will. And why would average is correct and not median ? Because it suits you better ? 1 - ignoring. 2 - The link is between productivity for all workers and compensation for all workers, not a subset of workers. If you want to use a subset of workers, you need both a subset of productivity as well as a subset of compensation. 3 - I use compensation because it's the correct measure. What conservative piece of econ? IgnE claims I got my information from the Heritage Foundation. I didn't, he's an liar.And again, average is correct because it is consistent with the theory that we're using. If productivity increases that creates a limited pool of new resources to be distributed. Part of that pool of resources will be distributed to workers in the form of compensation (wages + benefits). What the theory does not say, is that those new resources will be evenly distributed to all workers or that wages will remain a constant fraction of total compensation. Edit: why don't you want to talk about what caused the gap? 1 - Because I'm right. 2 - Subset productivity can't be evaluated, so we use something else ... That's social science. 3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ? What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland. By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway. 1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best? 2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me. 3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits. By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but. And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough. The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income... The regulation part was sarcastic. There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS. The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing. Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers. As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view. Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall. Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ? And this has nothing to do with inequalities it s about income distribution... We do not know anything about the distribution of productivity since an individuals productivity cannot be observed directly. We only have mean productivity (simply GDP/hours worked), we do not have median productivity because that is obviously impossible. Given this, why would you want to compare mean productivity growth with median wage growth? It would tell you absolutely nothing about the relationship between productivity and wages, since the distribution of productivity growth is unknown. It is not necessary to assume a flat distribution to use a mean, that whole comment is just gobbledygook. To put it more simply: Why compare the guy in the middle's wage to average productivity? Lets say you find that guy in the middle isn't earning more, even though on average people have gotten more productive, does that then mean people are getting screwed? No, maybe the guys on the bottom and the top have gotten much more productive while the guy in the middle has stayed about the same, and is actually being compensated fairly. Since you can't actually know the guy in the middle's productivity why are you even interested in comparing his specific wage to productivity? It is just a very strange thing to do, the mean vs mean plot even shows a sizeable gap so there isn't even a need to do any hack statistics. (My opinion on the gap is that it is obviously problematic, hard to understand, and even harder to do anyting about). You do this because as you point out, there's no other way to get to the data more directly so we have to create an estimate. Sure, the estimate makes lots of assumptions that might not be true, but it's better than nothing, assuming the writers are open and honest that they're making an estimate based on assumptions rather than calling it Truth. A lot of economics and finance is based on estimates created from tautological arguments and mathematical identities. Most professionals understand that this is often the best we can do with time and cost-benefit constraints. The same goes for things like BMI, F = ma, and the caloric content of food. They're estimates making lots of assumptions, but if you're trying to get a number quickly and can live with a ballpark figure rather than six significant figure precision, they're close enough. Your criticisms are fair that the number may not be a good reflection of reality, but it's only relevant if people are taking it a little too seriously. On this particular forum, usually the opposite is true...
I am responding to the whole median vs mean thing because it is clearly bullshit, mean is obviously superior if one were to pick a single metric to represent wages. There is nothing being estimated here though, it is just straight up measurements so I don't know where you are coming from with that. You have mean productivity and not median, then you must have a pretty damn good reason to make the comparison using median wages instead of mean. In this case the assumption is completely baseless as far as I know: the assumption is that the distributions of wages and productivity MUST be meaningfully dissimilar. If I am wrong and there actually is a reason beyond potentially getting graphs that SEEM more scary then I will gladly stand corrected.
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On August 17 2014 07:34 Crushinator wrote:Show nested quote +On August 17 2014 07:05 coverpunch wrote:On August 17 2014 06:17 Crushinator wrote:On August 17 2014 06:01 WhiteDog wrote:On August 17 2014 04:55 JonnyBNoHo wrote:On August 17 2014 04:27 WhiteDog wrote:On August 17 2014 04:06 JonnyBNoHo wrote:On August 17 2014 03:10 WhiteDog wrote:On August 17 2014 02:56 JonnyBNoHo wrote:On August 17 2014 02:15 WhiteDog wrote:
[quote]
1 - It's smaller than mine, but not "small".
2 - It is imperfect. The link that we were discussing about is between productivity and compensation for the bottom "99 %". You're talking about you for the second part of your comment, right ?
3 - No. Just because you read a conservative piece of econ doesn't make it true. The core problem is that the distribution of income is a political matter, and not an economic one. The simple fact that you go from wage to compensation prove that in itself - because "compensations" are the result of policies right ?
[quote]
And why would average is correct and not median ? Because it suits you better ? 1 - ignoring. 2 - The link is between productivity for all workers and compensation for all workers, not a subset of workers. If you want to use a subset of workers, you need both a subset of productivity as well as a subset of compensation. 3 - I use compensation because it's the correct measure. What conservative piece of econ? IgnE claims I got my information from the Heritage Foundation. I didn't, he's an liar.And again, average is correct because it is consistent with the theory that we're using. If productivity increases that creates a limited pool of new resources to be distributed. Part of that pool of resources will be distributed to workers in the form of compensation (wages + benefits). What the theory does not say, is that those new resources will be evenly distributed to all workers or that wages will remain a constant fraction of total compensation. Edit: why don't you want to talk about what caused the gap? 1 - Because I'm right. 2 - Subset productivity can't be evaluated, so we use something else ... That's social science. 3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ? What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland. By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway. 1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best? 2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me. 3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits. By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but. And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough. The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income... The regulation part was sarcastic. There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS. The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing. Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers. As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view. Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall. Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ? And this has nothing to do with inequalities it s about income distribution... We do not know anything about the distribution of productivity since an individuals productivity cannot be observed directly. We only have mean productivity (simply GDP/hours worked), we do not have median productivity because that is obviously impossible. Given this, why would you want to compare mean productivity growth with median wage growth? It would tell you absolutely nothing about the relationship between productivity and wages, since the distribution of productivity growth is unknown. It is not necessary to assume a flat distribution to use a mean, that whole comment is just gobbledygook. To put it more simply: Why compare the guy in the middle's wage to average productivity? Lets say you find that guy in the middle isn't earning more, even though on average people have gotten more productive, does that then mean people are getting screwed? No, maybe the guys on the bottom and the top have gotten much more productive while the guy in the middle has stayed about the same, and is actually being compensated fairly. Since you can't actually know the guy in the middle's productivity why are you even interested in comparing his specific wage to productivity? It is just a very strange thing to do, the mean vs mean plot even shows a sizeable gap so there isn't even a need to do any hack statistics. (My opinion on the gap is that it is obviously problematic, hard to understand, and even harder to do anyting about). You do this because as you point out, there's no other way to get to the data more directly so we have to create an estimate. Sure, the estimate makes lots of assumptions that might not be true, but it's better than nothing, assuming the writers are open and honest that they're making an estimate based on assumptions rather than calling it Truth. A lot of economics and finance is based on estimates created from tautological arguments and mathematical identities. Most professionals understand that this is often the best we can do with time and cost-benefit constraints. The same goes for things like BMI, F = ma, and the caloric content of food. They're estimates making lots of assumptions, but if you're trying to get a number quickly and can live with a ballpark figure rather than six significant figure precision, they're close enough. Your criticisms are fair that the number may not be a good reflection of reality, but it's only relevant if people are taking it a little too seriously. On this particular forum, usually the opposite is true... I am responding to the whole median vs mean thing because it is clearly bullshit, mean is obviously superior if one were to pick a single metric to represent wages. There is nothing being estimated here though, it is just straight up measurements so I don't know where you are coming from with that. You have mean productivity and not median, then you must have a pretty damn good reason to make the comparison using median wages instead of mean. In this case the assumption is completely baseless as far as I know: the assumption is that the distributions of wages and productivity MUST be meaningfully dissimilar. If I am wrong and there actually is a reason beyond potentially getting graphs that SEEM more scary then I will gladly stand corrected.
The Heritage paper Jonny posted directly addresses the issue:
Mean vs. Median Compensation. The fact that average productivity has risen with average compensation does not mean that employees face no economic challenges. Median compensation growth has not risen as quickly as average productivity—but this is not because employers have deprived workers of the fruits of their labor. Rather, in developed countries across the world high-skilled workers’ productivity has grown faster than that of less-skilled workers. Most economists attribute this phenomenon to “skill-biased technological change.”
In this case, they argue that using the median is misleading because workers might fall in different, discrete groups of income and are not normally distributed like you might see if income vs productivity were on a spectrum, i.e. linear. Unfortunately, proving such non-linear relationships is far out of the ken of most economists and commenters.
I think the argument for using the median instead of the mean is that there are too many forces at work for incomes that might pull the mean in misleading directions, Heritage goes into factors that could make incomes look lower than they are and pull the mean down:
Cash wages and salaries make up only part of total employee compensation. Employers also compensate their employees with non-cash benefits, such as health insurance, retirement benefits, and paid leave. These “fringe” benefits have become an increasingly large share of employee earnings, in large part because such benefits are typically tax exempt while wage income is taxable (demonstrating the power of tax policy to affect economic decisions). In 1973, non-wage benefits accounted for 13 percent of employee compensation. By 2012 that figure had risen by half—20 percent of employee earnings now come in benefits.
Economists expect workers’ total compensation to rise with their productivity, but that increase can come in the form of either wages or benefits. Employers care about the total cost of hiring a worker; they do not care about how their labor costs divide between wages and benefits. Employee benefits come out of the wages that employees would otherwise be paid. Examining wage data alone ignores the increasing role of benefits in compensation.
These might pull the median down too, but pulling the median is much harder since it would need to be practiced much more widely to have an effect.
Heritage attacks the methodology at all stages of the process and urges more caution in reading and analyzing the data, so you're not alone or unique in saying the existing measures are not accurate. Unfortunately they don't go into how big of a difference it makes to use mean vs median, but either way, I think the lack of variances in the discussion is pretty alarming. It's one thing to say one measure is better than another, but we should know how big a difference it makes.
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On August 17 2014 08:24 coverpunch wrote:Show nested quote +On August 17 2014 07:34 Crushinator wrote:On August 17 2014 07:05 coverpunch wrote:On August 17 2014 06:17 Crushinator wrote:On August 17 2014 06:01 WhiteDog wrote:On August 17 2014 04:55 JonnyBNoHo wrote:On August 17 2014 04:27 WhiteDog wrote:On August 17 2014 04:06 JonnyBNoHo wrote:On August 17 2014 03:10 WhiteDog wrote:On August 17 2014 02:56 JonnyBNoHo wrote:
[quote]
1 - ignoring.
2 - The link is between productivity for all workers and compensation for all workers, not a subset of workers. If you want to use a subset of workers, you need both a subset of productivity as well as a subset of compensation.
3 - I use compensation because it's the correct measure. What conservative piece of econ? IgnE claims I got my information from the Heritage Foundation. I didn't, he's an liar.
And again, average is correct because it is consistent with the theory that we're using. If productivity increases that creates a limited pool of new resources to be distributed. Part of that pool of resources will be distributed to workers in the form of compensation (wages + benefits). What the theory does not say, is that those new resources will be evenly distributed to all workers or that wages will remain a constant fraction of total compensation.
Edit: why don't you want to talk about what caused the gap? 1 - Because I'm right. 2 - Subset productivity can't be evaluated, so we use something else ... That's social science. 3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ? What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland. By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway. 1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best? 2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me. 3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits. By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but. And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough. The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income... The regulation part was sarcastic. There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS. The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing. Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers. As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view. Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall. Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ? And this has nothing to do with inequalities it s about income distribution... We do not know anything about the distribution of productivity since an individuals productivity cannot be observed directly. We only have mean productivity (simply GDP/hours worked), we do not have median productivity because that is obviously impossible. Given this, why would you want to compare mean productivity growth with median wage growth? It would tell you absolutely nothing about the relationship between productivity and wages, since the distribution of productivity growth is unknown. It is not necessary to assume a flat distribution to use a mean, that whole comment is just gobbledygook. To put it more simply: Why compare the guy in the middle's wage to average productivity? Lets say you find that guy in the middle isn't earning more, even though on average people have gotten more productive, does that then mean people are getting screwed? No, maybe the guys on the bottom and the top have gotten much more productive while the guy in the middle has stayed about the same, and is actually being compensated fairly. Since you can't actually know the guy in the middle's productivity why are you even interested in comparing his specific wage to productivity? It is just a very strange thing to do, the mean vs mean plot even shows a sizeable gap so there isn't even a need to do any hack statistics. (My opinion on the gap is that it is obviously problematic, hard to understand, and even harder to do anyting about). You do this because as you point out, there's no other way to get to the data more directly so we have to create an estimate. Sure, the estimate makes lots of assumptions that might not be true, but it's better than nothing, assuming the writers are open and honest that they're making an estimate based on assumptions rather than calling it Truth. A lot of economics and finance is based on estimates created from tautological arguments and mathematical identities. Most professionals understand that this is often the best we can do with time and cost-benefit constraints. The same goes for things like BMI, F = ma, and the caloric content of food. They're estimates making lots of assumptions, but if you're trying to get a number quickly and can live with a ballpark figure rather than six significant figure precision, they're close enough. Your criticisms are fair that the number may not be a good reflection of reality, but it's only relevant if people are taking it a little too seriously. On this particular forum, usually the opposite is true... I am responding to the whole median vs mean thing because it is clearly bullshit, mean is obviously superior if one were to pick a single metric to represent wages. There is nothing being estimated here though, it is just straight up measurements so I don't know where you are coming from with that. You have mean productivity and not median, then you must have a pretty damn good reason to make the comparison using median wages instead of mean. In this case the assumption is completely baseless as far as I know: the assumption is that the distributions of wages and productivity MUST be meaningfully dissimilar. If I am wrong and there actually is a reason beyond potentially getting graphs that SEEM more scary then I will gladly stand corrected. The Heritage paper Jonny posted directly addresses the issue: Show nested quote +Mean vs. Median Compensation. The fact that average productivity has risen with average compensation does not mean that employees face no economic challenges. Median compensation growth has not risen as quickly as average productivity—but this is not because employers have deprived workers of the fruits of their labor. Rather, in developed countries across the world high-skilled workers’ productivity has grown faster than that of less-skilled workers. Most economists attribute this phenomenon to “skill-biased technological change.” In this case, they argue that using the median is misleading because workers might fall in different, discrete groups of income and are not normally distributed like you might see if income vs productivity were on a spectrum, i.e. linear. Unfortunately, proving such non-linear relationships is far out of the ken of most economists and commenters. I think the argument for using the median instead of the mean is that there are too many forces at work for incomes that might pull the mean in misleading directions, Heritage goes into factors that could make incomes look lower than they are and pull the mean down: Show nested quote +Cash wages and salaries make up only part of total employee compensation. Employers also compensate their employees with non-cash benefits, such as health insurance, retirement benefits, and paid leave. These “fringe” benefits have become an increasingly large share of employee earnings, in large part because such benefits are typically tax exempt while wage income is taxable (demonstrating the power of tax policy to affect economic decisions). In 1973, non-wage benefits accounted for 13 percent of employee compensation. By 2012 that figure had risen by half—20 percent of employee earnings now come in benefits.
Economists expect workers’ total compensation to rise with their productivity, but that increase can come in the form of either wages or benefits. Employers care about the total cost of hiring a worker; they do not care about how their labor costs divide between wages and benefits. Employee benefits come out of the wages that employees would otherwise be paid. Examining wage data alone ignores the increasing role of benefits in compensation. These might pull the median down too, but pulling the median is much harder since it would need to be practiced much more widely to have an effect. Heritage attacks the methodology at all stages of the process and urges more caution in reading and analyzing the data, so you're not alone or unique in saying the existing measures are not accurate. Unfortunately they don't go into how big of a difference it makes to use mean vs median, but either way, I think the lack of variances in the discussion is pretty alarming. It's one thing to say one measure is better than another, but we should know how big a difference it makes.
Crushinator think we're talking about median productivity, which just doesn't exist, while we're talking about median compensation. The Heritage fundation argument is the same exact misleading argument that Crushinator and Jonny are doing : they discard the measure because reality is too "complex". It is a criticism that you can ALWAYS make towards any data in social sciences - because the "context" is both impossible to "assure" or "sature" (Derrida).
It's a fetichism of a statistical artifact that, in itself, is and never will be nothing but an incomplete picture of reality - mean or average compensation, or any other statistical artifact like "women" for exemple (you think all women make an homogeneous group ?) - that put aside a lot of things (I've poited some, like heterogeneous consumption practice, heterogeneous effect of the inflation on income hierarchy, both things that plays a role when you evaluate the purchasing power of a social group, etc.).
But what's Heritage proof that the poor showing of median compensation has nothing to do with workers being "deprived of the fruits of their labor" ? They consider that highly skilled workers productivity has grown faster, knowing that evaluating such productivity is misleading (for obvious reasons).
But take a second to reflect : you evaluate productivity by evaluating the end production in monetary term (the added value) compared to the means of production. If high skilled workers makes MORE MONEY with the same mean of production (labor and capital), they will mathematically have a higher PRODUCTIVITY, then you can argue that it is the productivity that explain the excess money. That is an AWESOME tautological argument : they make more money so they are more efficient, they make more money because they are more efficient.
The other argument for that kind of productivity bias is that technology today is made in a way that it favor highly productive workers - the O'Ring theory, the name of a piece responsible of the Challenger shuttle disaster, that enlight how important small details are in modern production / technological system, to a point where you have to pay highly skilled workers a lot because their "marginal productivity" is very high. That's a theory, not an all out fact that can totally explain the so called "productivity gap" between higly skilled workers and the rest, gap that would, according to them, explain the fall of median compensation. That's, for exemple, just putting aside the fact that a big part of the highly paid (skilled ? because that's a synonyme in their stupid world) workers that saw an increase in their "compensations" don't work in field heavy in "technological change" : lawyers, counselling, etc.
What an objective study would do is to use the number, comment them and then point out the limits - not discarding just simply median compensation because the productivity of another group, that you cannot evaluate truthfully, has grown faster. That's like basic academic honesty.
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On a separate note, with a day or so to contemplate on it, it's very interesting to see how people are coming out against Rick Perry's indictment.
For one, a lot of liberals are usually very unhappy with what they see as abusive DA tactics, and Perry punishing a DA with a drunk driving and unruly behavior rap by withholding funds seems like not just within his veto rights but good governance. The Texas legislature wrote in a line item veto for the governor precisely so he could punish offices like the Travis County DA without compromising the entire state budget. And beyond partisanship, a DA who gets arrested with a blood alcohol level triple the legal limit doesn't seem like the kind of person you want bringing cases or negotiating pleas on behalf of the state, in some cases deciding whether a suspect should spend the rest of his life in prison or be executed.
The whole thing is politics, which appear to be dirtier than ever. It was dumb of Perry to issue a naked threat and then act on it, which looks awfully like coercion at first glance. But it is within his rights to issue a veto for any reason he wants and he'll probably be able to argue the veto as an independent act rather than a prelude to making another, more credible threat (which would be coercive). I don't think the charges will stick and I don't think Texas Democrats are intending this to go through with any real punishment, except to tar Rick Perry with scandal that would deny him any real chance of winning the 2016 election. This seems to be part of the whole "paint Texas blue" thing.
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United States43611 Posts
On the one hand you want someone principled, on the other hand you want someone smart enough to have a clue how to apply those principles legally. The case didn't make me feel like he was vindictively persecuting an enemy, it made me feel like he was an idiot who both didn't know what he was empowered to do and didn't think to hire someone to tell him what he could do.
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On August 17 2014 18:50 WhiteDog wrote:Show nested quote +On August 17 2014 08:24 coverpunch wrote:On August 17 2014 07:34 Crushinator wrote:On August 17 2014 07:05 coverpunch wrote:On August 17 2014 06:17 Crushinator wrote:On August 17 2014 06:01 WhiteDog wrote:On August 17 2014 04:55 JonnyBNoHo wrote:On August 17 2014 04:27 WhiteDog wrote:On August 17 2014 04:06 JonnyBNoHo wrote:On August 17 2014 03:10 WhiteDog wrote:
[quote]
1 - Because I'm right.
2 - Subset productivity can't be evaluated, so we use something else ... That's social science.
3 - Well, IgnE being a liar or not (but I think he's not) you just expanded the calculation to a point where the gap is the smaller possible, with approximation and imperfect measurement - you didn't say anything about the fact that adjusted value are not necessarily a good measurement when talking about an heterogeneous group, nothing about the fact that AVERAGE is skewed because of a higher concentration in higher income, etc. And you didn't even argue on the fact that, even with your graph, there is still a 50 pts gap - that you cannot caracterize as "small". So who's fault is it for the 50 pts gap ? The state regulation ?
What's the theory that we are using ? It's not consistent, what's consistent is to put BOTH average and median, to see the average on one side, and how skewed the distribution is... That's why both median, average, and every possible measure are on the graph I posted, because it is a good and objective work, not a biased artifact made to comfort you in your own dreamland.
By the way, you did the EXACT same thing with the inequalities between men and women. Soon you'll show us that not so many people people are dying because of ebola in africa, because if you take into consideration the average life expectancy, chance to get any other deadly disease, chance to fall in a pit and chance to be crushed by a car, 80 % of the dead would have died anyway. 1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best? 2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me. 3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits. By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but. And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough. The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income... The regulation part was sarcastic. There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS. The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing. Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers. As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view. Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall. Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ? And this has nothing to do with inequalities it s about income distribution... We do not know anything about the distribution of productivity since an individuals productivity cannot be observed directly. We only have mean productivity (simply GDP/hours worked), we do not have median productivity because that is obviously impossible. Given this, why would you want to compare mean productivity growth with median wage growth? It would tell you absolutely nothing about the relationship between productivity and wages, since the distribution of productivity growth is unknown. It is not necessary to assume a flat distribution to use a mean, that whole comment is just gobbledygook. To put it more simply: Why compare the guy in the middle's wage to average productivity? Lets say you find that guy in the middle isn't earning more, even though on average people have gotten more productive, does that then mean people are getting screwed? No, maybe the guys on the bottom and the top have gotten much more productive while the guy in the middle has stayed about the same, and is actually being compensated fairly. Since you can't actually know the guy in the middle's productivity why are you even interested in comparing his specific wage to productivity? It is just a very strange thing to do, the mean vs mean plot even shows a sizeable gap so there isn't even a need to do any hack statistics. (My opinion on the gap is that it is obviously problematic, hard to understand, and even harder to do anyting about). You do this because as you point out, there's no other way to get to the data more directly so we have to create an estimate. Sure, the estimate makes lots of assumptions that might not be true, but it's better than nothing, assuming the writers are open and honest that they're making an estimate based on assumptions rather than calling it Truth. A lot of economics and finance is based on estimates created from tautological arguments and mathematical identities. Most professionals understand that this is often the best we can do with time and cost-benefit constraints. The same goes for things like BMI, F = ma, and the caloric content of food. They're estimates making lots of assumptions, but if you're trying to get a number quickly and can live with a ballpark figure rather than six significant figure precision, they're close enough. Your criticisms are fair that the number may not be a good reflection of reality, but it's only relevant if people are taking it a little too seriously. On this particular forum, usually the opposite is true... I am responding to the whole median vs mean thing because it is clearly bullshit, mean is obviously superior if one were to pick a single metric to represent wages. There is nothing being estimated here though, it is just straight up measurements so I don't know where you are coming from with that. You have mean productivity and not median, then you must have a pretty damn good reason to make the comparison using median wages instead of mean. In this case the assumption is completely baseless as far as I know: the assumption is that the distributions of wages and productivity MUST be meaningfully dissimilar. If I am wrong and there actually is a reason beyond potentially getting graphs that SEEM more scary then I will gladly stand corrected. The Heritage paper Jonny posted directly addresses the issue: Mean vs. Median Compensation. The fact that average productivity has risen with average compensation does not mean that employees face no economic challenges. Median compensation growth has not risen as quickly as average productivity—but this is not because employers have deprived workers of the fruits of their labor. Rather, in developed countries across the world high-skilled workers’ productivity has grown faster than that of less-skilled workers. Most economists attribute this phenomenon to “skill-biased technological change.” In this case, they argue that using the median is misleading because workers might fall in different, discrete groups of income and are not normally distributed like you might see if income vs productivity were on a spectrum, i.e. linear. Unfortunately, proving such non-linear relationships is far out of the ken of most economists and commenters. I think the argument for using the median instead of the mean is that there are too many forces at work for incomes that might pull the mean in misleading directions, Heritage goes into factors that could make incomes look lower than they are and pull the mean down: Cash wages and salaries make up only part of total employee compensation. Employers also compensate their employees with non-cash benefits, such as health insurance, retirement benefits, and paid leave. These “fringe” benefits have become an increasingly large share of employee earnings, in large part because such benefits are typically tax exempt while wage income is taxable (demonstrating the power of tax policy to affect economic decisions). In 1973, non-wage benefits accounted for 13 percent of employee compensation. By 2012 that figure had risen by half—20 percent of employee earnings now come in benefits.
Economists expect workers’ total compensation to rise with their productivity, but that increase can come in the form of either wages or benefits. Employers care about the total cost of hiring a worker; they do not care about how their labor costs divide between wages and benefits. Employee benefits come out of the wages that employees would otherwise be paid. Examining wage data alone ignores the increasing role of benefits in compensation. These might pull the median down too, but pulling the median is much harder since it would need to be practiced much more widely to have an effect. Heritage attacks the methodology at all stages of the process and urges more caution in reading and analyzing the data, so you're not alone or unique in saying the existing measures are not accurate. Unfortunately they don't go into how big of a difference it makes to use mean vs median, but either way, I think the lack of variances in the discussion is pretty alarming. It's one thing to say one measure is better than another, but we should know how big a difference it makes. Crushinator think we're talking about median productivity, which just doesn't exist, while we're talking about median compensation. The Heritage fundation argument is the same exact misleading argument that Crushinator and Jonny are doing : they discard the measure because reality is too "complex". It is a criticism that you can ALWAYS make towards any data in social sciences - because the "context" is both impossible to "assure" or "sature" (Derrida). It's a fetichism of a statistical artifact that, in itself, is and never will be nothing but an incomplete picture of reality - mean or average compensation, or any other statistical artifact like "women" for exemple (you think all women make an homogeneous group ?) - that put aside a lot of things (I've poited some, like heterogeneous consumption practice, heterogeneous effect of the inflation on income hierarchy, both things that plays a role when you evaluate the purchasing power of a social group, etc.).
We are talking about the relationship between productivity and compensation, not reviewing the merits of metrics of either of those variables in isolation. I do not dismiss the measure because reality is too complex to be able to understand anything about it, but because in my best understanding the measure does not inform us about our complex reality at all. Zero additional information about the relationship is transmitted by plotting median wages against mean productivity, no evidence for anything can possibly come from it.
Median would only be helpful if the distributions of productivity and wages are different. Then we might be able to say that some groups are succeeding more at converting productivity gains into compensation than others. If they are distributed similarly then median productivity gains would not change the picture. Since we do not have access to the distribution of productivity gains, it would not be informative, and potentially misleading.
Looking at median and modal wage growth is a good idea in general, but in the context of productivity-compensation it is not a helpful metric. We obviously should care about rising inequality.
I would also like to point out that your use of the term statistical artifact is completely nonsensical, so I can't really comment on anything related to it.
I do think it is a possibility that high-skill workers are better able to convert productivity gains into compensation, but plotting median wage vs mean wage vs mean productivity does not provide evidence for that hypothesis at all, regardless of outcome.
Maybe it isn't the best idea to argue econometrics here.
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On August 17 2014 20:38 Crushinator wrote:Show nested quote +On August 17 2014 18:50 WhiteDog wrote:On August 17 2014 08:24 coverpunch wrote:On August 17 2014 07:34 Crushinator wrote:On August 17 2014 07:05 coverpunch wrote:On August 17 2014 06:17 Crushinator wrote:On August 17 2014 06:01 WhiteDog wrote:On August 17 2014 04:55 JonnyBNoHo wrote:On August 17 2014 04:27 WhiteDog wrote:On August 17 2014 04:06 JonnyBNoHo wrote:
[quote]
1 - ?? lol, you think your subjective descriptor is more correct than my subjective descriptor. Would you also like to argue over which colors are best?
2 - You're presenting productivity and median compensation as if they were linked, because productivity and mean compensation are linked. Seems dishonest to me.
3 - It doesn't matter that average is skewed to higher income. The productivity-compensation link is agnostic towards inequality. When did I blame regulation? Lol, you're just blindly citing talking points now. I already stated the big causes, here's two - higher depreciation rates and a recovery in corporate profits.
By the way, I'm the one being honest with the data. I was honest with the gender gap data too. Don't try to frame this as anything but. And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough. The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income... The regulation part was sarcastic. There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS. The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing. Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers. As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view. Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall. Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ? And this has nothing to do with inequalities it s about income distribution... We do not know anything about the distribution of productivity since an individuals productivity cannot be observed directly. We only have mean productivity (simply GDP/hours worked), we do not have median productivity because that is obviously impossible. Given this, why would you want to compare mean productivity growth with median wage growth? It would tell you absolutely nothing about the relationship between productivity and wages, since the distribution of productivity growth is unknown. It is not necessary to assume a flat distribution to use a mean, that whole comment is just gobbledygook. To put it more simply: Why compare the guy in the middle's wage to average productivity? Lets say you find that guy in the middle isn't earning more, even though on average people have gotten more productive, does that then mean people are getting screwed? No, maybe the guys on the bottom and the top have gotten much more productive while the guy in the middle has stayed about the same, and is actually being compensated fairly. Since you can't actually know the guy in the middle's productivity why are you even interested in comparing his specific wage to productivity? It is just a very strange thing to do, the mean vs mean plot even shows a sizeable gap so there isn't even a need to do any hack statistics. (My opinion on the gap is that it is obviously problematic, hard to understand, and even harder to do anyting about). You do this because as you point out, there's no other way to get to the data more directly so we have to create an estimate. Sure, the estimate makes lots of assumptions that might not be true, but it's better than nothing, assuming the writers are open and honest that they're making an estimate based on assumptions rather than calling it Truth. A lot of economics and finance is based on estimates created from tautological arguments and mathematical identities. Most professionals understand that this is often the best we can do with time and cost-benefit constraints. The same goes for things like BMI, F = ma, and the caloric content of food. They're estimates making lots of assumptions, but if you're trying to get a number quickly and can live with a ballpark figure rather than six significant figure precision, they're close enough. Your criticisms are fair that the number may not be a good reflection of reality, but it's only relevant if people are taking it a little too seriously. On this particular forum, usually the opposite is true... I am responding to the whole median vs mean thing because it is clearly bullshit, mean is obviously superior if one were to pick a single metric to represent wages. There is nothing being estimated here though, it is just straight up measurements so I don't know where you are coming from with that. You have mean productivity and not median, then you must have a pretty damn good reason to make the comparison using median wages instead of mean. In this case the assumption is completely baseless as far as I know: the assumption is that the distributions of wages and productivity MUST be meaningfully dissimilar. If I am wrong and there actually is a reason beyond potentially getting graphs that SEEM more scary then I will gladly stand corrected. The Heritage paper Jonny posted directly addresses the issue: Mean vs. Median Compensation. The fact that average productivity has risen with average compensation does not mean that employees face no economic challenges. Median compensation growth has not risen as quickly as average productivity—but this is not because employers have deprived workers of the fruits of their labor. Rather, in developed countries across the world high-skilled workers’ productivity has grown faster than that of less-skilled workers. Most economists attribute this phenomenon to “skill-biased technological change.” In this case, they argue that using the median is misleading because workers might fall in different, discrete groups of income and are not normally distributed like you might see if income vs productivity were on a spectrum, i.e. linear. Unfortunately, proving such non-linear relationships is far out of the ken of most economists and commenters. I think the argument for using the median instead of the mean is that there are too many forces at work for incomes that might pull the mean in misleading directions, Heritage goes into factors that could make incomes look lower than they are and pull the mean down: Cash wages and salaries make up only part of total employee compensation. Employers also compensate their employees with non-cash benefits, such as health insurance, retirement benefits, and paid leave. These “fringe” benefits have become an increasingly large share of employee earnings, in large part because such benefits are typically tax exempt while wage income is taxable (demonstrating the power of tax policy to affect economic decisions). In 1973, non-wage benefits accounted for 13 percent of employee compensation. By 2012 that figure had risen by half—20 percent of employee earnings now come in benefits.
Economists expect workers’ total compensation to rise with their productivity, but that increase can come in the form of either wages or benefits. Employers care about the total cost of hiring a worker; they do not care about how their labor costs divide between wages and benefits. Employee benefits come out of the wages that employees would otherwise be paid. Examining wage data alone ignores the increasing role of benefits in compensation. These might pull the median down too, but pulling the median is much harder since it would need to be practiced much more widely to have an effect. Heritage attacks the methodology at all stages of the process and urges more caution in reading and analyzing the data, so you're not alone or unique in saying the existing measures are not accurate. Unfortunately they don't go into how big of a difference it makes to use mean vs median, but either way, I think the lack of variances in the discussion is pretty alarming. It's one thing to say one measure is better than another, but we should know how big a difference it makes. Crushinator think we're talking about median productivity, which just doesn't exist, while we're talking about median compensation. The Heritage fundation argument is the same exact misleading argument that Crushinator and Jonny are doing : they discard the measure because reality is too "complex". It is a criticism that you can ALWAYS make towards any data in social sciences - because the "context" is both impossible to "assure" or "sature" (Derrida). It's a fetichism of a statistical artifact that, in itself, is and never will be nothing but an incomplete picture of reality - mean or average compensation, or any other statistical artifact like "women" for exemple (you think all women make an homogeneous group ?) - that put aside a lot of things (I've poited some, like heterogeneous consumption practice, heterogeneous effect of the inflation on income hierarchy, both things that plays a role when you evaluate the purchasing power of a social group, etc.). We are talking about the relationship between productivity and compensation, not reviewing the merits of metrics of either of those variables in isolation. I do not dismiss the measure because reality is too complex to be able to understand anything about it, but because in my best understanding the measure does not inform us about our complex reality at all. Zero additional information about the relationship is transmitted by plotting median wages against mean productivity, no evidence for anything can possibly come from it. Median would only be helpful if the distributions of productivity and wages are different. Then we might be able to say that some groups are succeeding more at converting productivity gains into compensation than others. If they are distributed similarly then median productivity gains would not change the picture. Since we do not have access to the distribution of productivity gains, it would not be informative, and potentially misleading. Looking at median and modal wage growth is a good idea in general, but in the context of productivity-compensation it is not a helpful metric. We obviously should care about rising inequality. I would also like to point out that your use of the term statistical artifact is completely nonsensical, so I can't really comment on anything related to it. I do think it is a possibility that high-skill workers are better able to convert productivity gains into compensation, but plotting median wage vs mean wage vs mean productivity does not provide evidence for that hypothesis at all, regardless of outcome. Maybe it isn't the best idea to argue econometrics here.
And what about the information that while productivity raised, the result of the productivity is not evenly split in the worker population ? That's not an information to you ? It's not econometrics btw, every economists use median and average for obvious reasons. It's pettyfogging.
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On August 17 2014 20:58 WhiteDog wrote:Show nested quote +On August 17 2014 20:38 Crushinator wrote:On August 17 2014 18:50 WhiteDog wrote:On August 17 2014 08:24 coverpunch wrote:On August 17 2014 07:34 Crushinator wrote:On August 17 2014 07:05 coverpunch wrote:On August 17 2014 06:17 Crushinator wrote:On August 17 2014 06:01 WhiteDog wrote:On August 17 2014 04:55 JonnyBNoHo wrote:On August 17 2014 04:27 WhiteDog wrote:
[quote]
And how am I dishonest ? There is nothing subjective in saying it is the biggest gap since WW2. Nothing dishonest in saying that both average and median have value especially when we talk about an heterogeneous population. Nothing wrong in saying that you discard all data that go against your point of view with no good argumen.t expect "it's not the best". Nothing wrong in witnessing you putting aside all possible critics on the data that you use Nothing wrong in saying that a 50 pts gap (out of 400 with year 0 as base 100) is not sufficient enough.
The part about non supervisionary worker productivity is especially "dishonest", since you are basically asking me to show you data that can't be made. By doing that you're preventing us to talk, apprehend or just even imagine what we are talking about, which is that the lower income are not rewarded for productivity gain. Not to mention the part where everybody says that lowest income are stagnating since 20 years and you take data that goes back to 30 years or more to prove that there indeed has been an increase in income...
The regulation part was sarcastic. There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS. The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing. Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers. As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view. Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall. Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ? And this has nothing to do with inequalities it s about income distribution... We do not know anything about the distribution of productivity since an individuals productivity cannot be observed directly. We only have mean productivity (simply GDP/hours worked), we do not have median productivity because that is obviously impossible. Given this, why would you want to compare mean productivity growth with median wage growth? It would tell you absolutely nothing about the relationship between productivity and wages, since the distribution of productivity growth is unknown. It is not necessary to assume a flat distribution to use a mean, that whole comment is just gobbledygook. To put it more simply: Why compare the guy in the middle's wage to average productivity? Lets say you find that guy in the middle isn't earning more, even though on average people have gotten more productive, does that then mean people are getting screwed? No, maybe the guys on the bottom and the top have gotten much more productive while the guy in the middle has stayed about the same, and is actually being compensated fairly. Since you can't actually know the guy in the middle's productivity why are you even interested in comparing his specific wage to productivity? It is just a very strange thing to do, the mean vs mean plot even shows a sizeable gap so there isn't even a need to do any hack statistics. (My opinion on the gap is that it is obviously problematic, hard to understand, and even harder to do anyting about). You do this because as you point out, there's no other way to get to the data more directly so we have to create an estimate. Sure, the estimate makes lots of assumptions that might not be true, but it's better than nothing, assuming the writers are open and honest that they're making an estimate based on assumptions rather than calling it Truth. A lot of economics and finance is based on estimates created from tautological arguments and mathematical identities. Most professionals understand that this is often the best we can do with time and cost-benefit constraints. The same goes for things like BMI, F = ma, and the caloric content of food. They're estimates making lots of assumptions, but if you're trying to get a number quickly and can live with a ballpark figure rather than six significant figure precision, they're close enough. Your criticisms are fair that the number may not be a good reflection of reality, but it's only relevant if people are taking it a little too seriously. On this particular forum, usually the opposite is true... I am responding to the whole median vs mean thing because it is clearly bullshit, mean is obviously superior if one were to pick a single metric to represent wages. There is nothing being estimated here though, it is just straight up measurements so I don't know where you are coming from with that. You have mean productivity and not median, then you must have a pretty damn good reason to make the comparison using median wages instead of mean. In this case the assumption is completely baseless as far as I know: the assumption is that the distributions of wages and productivity MUST be meaningfully dissimilar. If I am wrong and there actually is a reason beyond potentially getting graphs that SEEM more scary then I will gladly stand corrected. The Heritage paper Jonny posted directly addresses the issue: Mean vs. Median Compensation. The fact that average productivity has risen with average compensation does not mean that employees face no economic challenges. Median compensation growth has not risen as quickly as average productivity—but this is not because employers have deprived workers of the fruits of their labor. Rather, in developed countries across the world high-skilled workers’ productivity has grown faster than that of less-skilled workers. Most economists attribute this phenomenon to “skill-biased technological change.” In this case, they argue that using the median is misleading because workers might fall in different, discrete groups of income and are not normally distributed like you might see if income vs productivity were on a spectrum, i.e. linear. Unfortunately, proving such non-linear relationships is far out of the ken of most economists and commenters. I think the argument for using the median instead of the mean is that there are too many forces at work for incomes that might pull the mean in misleading directions, Heritage goes into factors that could make incomes look lower than they are and pull the mean down: Cash wages and salaries make up only part of total employee compensation. Employers also compensate their employees with non-cash benefits, such as health insurance, retirement benefits, and paid leave. These “fringe” benefits have become an increasingly large share of employee earnings, in large part because such benefits are typically tax exempt while wage income is taxable (demonstrating the power of tax policy to affect economic decisions). In 1973, non-wage benefits accounted for 13 percent of employee compensation. By 2012 that figure had risen by half—20 percent of employee earnings now come in benefits.
Economists expect workers’ total compensation to rise with their productivity, but that increase can come in the form of either wages or benefits. Employers care about the total cost of hiring a worker; they do not care about how their labor costs divide between wages and benefits. Employee benefits come out of the wages that employees would otherwise be paid. Examining wage data alone ignores the increasing role of benefits in compensation. These might pull the median down too, but pulling the median is much harder since it would need to be practiced much more widely to have an effect. Heritage attacks the methodology at all stages of the process and urges more caution in reading and analyzing the data, so you're not alone or unique in saying the existing measures are not accurate. Unfortunately they don't go into how big of a difference it makes to use mean vs median, but either way, I think the lack of variances in the discussion is pretty alarming. It's one thing to say one measure is better than another, but we should know how big a difference it makes. Crushinator think we're talking about median productivity, which just doesn't exist, while we're talking about median compensation. The Heritage fundation argument is the same exact misleading argument that Crushinator and Jonny are doing : they discard the measure because reality is too "complex". It is a criticism that you can ALWAYS make towards any data in social sciences - because the "context" is both impossible to "assure" or "sature" (Derrida). It's a fetichism of a statistical artifact that, in itself, is and never will be nothing but an incomplete picture of reality - mean or average compensation, or any other statistical artifact like "women" for exemple (you think all women make an homogeneous group ?) - that put aside a lot of things (I've poited some, like heterogeneous consumption practice, heterogeneous effect of the inflation on income hierarchy, both things that plays a role when you evaluate the purchasing power of a social group, etc.). We are talking about the relationship between productivity and compensation, not reviewing the merits of metrics of either of those variables in isolation. I do not dismiss the measure because reality is too complex to be able to understand anything about it, but because in my best understanding the measure does not inform us about our complex reality at all. Zero additional information about the relationship is transmitted by plotting median wages against mean productivity, no evidence for anything can possibly come from it. Median would only be helpful if the distributions of productivity and wages are different. Then we might be able to say that some groups are succeeding more at converting productivity gains into compensation than others. If they are distributed similarly then median productivity gains would not change the picture. Since we do not have access to the distribution of productivity gains, it would not be informative, and potentially misleading. Looking at median and modal wage growth is a good idea in general, but in the context of productivity-compensation it is not a helpful metric. We obviously should care about rising inequality. I would also like to point out that your use of the term statistical artifact is completely nonsensical, so I can't really comment on anything related to it. I do think it is a possibility that high-skill workers are better able to convert productivity gains into compensation, but plotting median wage vs mean wage vs mean productivity does not provide evidence for that hypothesis at all, regardless of outcome. Maybe it isn't the best idea to argue econometrics here. And what about the information that while productivity raised, the result of the productivity is not evenly split in the worker population ? That's not an information to you ? It's not econometrics btw, every economists use median and average for obvious reasons. It's pettyfogging.
Econometrics: The use of statistical data for economic analysis.
Anyway I have already written too much about the importance of distributions. But I can go a little more before I peace out I geuss. If you would find that median wages have risen less than mean wages, that does not tell you anything meaningful about the productivity-compensation relationship it could very well be that median productivity has also risen less than mean productivity. So, no, I would not find such a finding meaningful in the context of wage-productivity relationship.
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On August 17 2014 21:17 Crushinator wrote:Show nested quote +On August 17 2014 20:58 WhiteDog wrote:On August 17 2014 20:38 Crushinator wrote:On August 17 2014 18:50 WhiteDog wrote:On August 17 2014 08:24 coverpunch wrote:On August 17 2014 07:34 Crushinator wrote:On August 17 2014 07:05 coverpunch wrote:On August 17 2014 06:17 Crushinator wrote:On August 17 2014 06:01 WhiteDog wrote:On August 17 2014 04:55 JonnyBNoHo wrote:
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There's also nothing subjective in saying the gap I showed in small in comparison to the gap that you showed. I mean, come on. Enough of your BS.
The dishonesty is in implying or stating that a relation exists when it does not. When you show a productivity-median wage graph you are implying that the two are related, when they are not. You're saying "you are more productive but you aren't getting compensated for it" when that isn't supported by the data you are showing.
Just read your own post: "which is that the lower income are not rewarded for productivity gain." But we don't know if that's true. Lower income workers aren't compensated for average productivity gains, but those productivity gains may not have anything to do with those lower income workers.
As for my chart on income, the post I replied to said bottom 99% since the 80's, not bottom 20% for last 20 years. My chart was entirely appropriate. Sorry if my data didn't comply with your view. Are you this dense ? You can t see the difference between something being smaller than something else and something being small ? 2m is smaller tha 2m20 but still rather tall. Crushinator what are you talking about ? Why would average be more fit than median since as we cannot evaluate individualsl productivity? When using average you consider that any productivity gain is evenly split in the distribution, an unfalsifiable assumption. This conversation is ridiculous. Even in Jonny's data there is a 50pts gap and it is not conclusive ? And this has nothing to do with inequalities it s about income distribution... We do not know anything about the distribution of productivity since an individuals productivity cannot be observed directly. We only have mean productivity (simply GDP/hours worked), we do not have median productivity because that is obviously impossible. Given this, why would you want to compare mean productivity growth with median wage growth? It would tell you absolutely nothing about the relationship between productivity and wages, since the distribution of productivity growth is unknown. It is not necessary to assume a flat distribution to use a mean, that whole comment is just gobbledygook. To put it more simply: Why compare the guy in the middle's wage to average productivity? Lets say you find that guy in the middle isn't earning more, even though on average people have gotten more productive, does that then mean people are getting screwed? No, maybe the guys on the bottom and the top have gotten much more productive while the guy in the middle has stayed about the same, and is actually being compensated fairly. Since you can't actually know the guy in the middle's productivity why are you even interested in comparing his specific wage to productivity? It is just a very strange thing to do, the mean vs mean plot even shows a sizeable gap so there isn't even a need to do any hack statistics. (My opinion on the gap is that it is obviously problematic, hard to understand, and even harder to do anyting about). You do this because as you point out, there's no other way to get to the data more directly so we have to create an estimate. Sure, the estimate makes lots of assumptions that might not be true, but it's better than nothing, assuming the writers are open and honest that they're making an estimate based on assumptions rather than calling it Truth. A lot of economics and finance is based on estimates created from tautological arguments and mathematical identities. Most professionals understand that this is often the best we can do with time and cost-benefit constraints. The same goes for things like BMI, F = ma, and the caloric content of food. They're estimates making lots of assumptions, but if you're trying to get a number quickly and can live with a ballpark figure rather than six significant figure precision, they're close enough. Your criticisms are fair that the number may not be a good reflection of reality, but it's only relevant if people are taking it a little too seriously. On this particular forum, usually the opposite is true... I am responding to the whole median vs mean thing because it is clearly bullshit, mean is obviously superior if one were to pick a single metric to represent wages. There is nothing being estimated here though, it is just straight up measurements so I don't know where you are coming from with that. You have mean productivity and not median, then you must have a pretty damn good reason to make the comparison using median wages instead of mean. In this case the assumption is completely baseless as far as I know: the assumption is that the distributions of wages and productivity MUST be meaningfully dissimilar. If I am wrong and there actually is a reason beyond potentially getting graphs that SEEM more scary then I will gladly stand corrected. The Heritage paper Jonny posted directly addresses the issue: Mean vs. Median Compensation. The fact that average productivity has risen with average compensation does not mean that employees face no economic challenges. Median compensation growth has not risen as quickly as average productivity—but this is not because employers have deprived workers of the fruits of their labor. Rather, in developed countries across the world high-skilled workers’ productivity has grown faster than that of less-skilled workers. Most economists attribute this phenomenon to “skill-biased technological change.” In this case, they argue that using the median is misleading because workers might fall in different, discrete groups of income and are not normally distributed like you might see if income vs productivity were on a spectrum, i.e. linear. Unfortunately, proving such non-linear relationships is far out of the ken of most economists and commenters. I think the argument for using the median instead of the mean is that there are too many forces at work for incomes that might pull the mean in misleading directions, Heritage goes into factors that could make incomes look lower than they are and pull the mean down: Cash wages and salaries make up only part of total employee compensation. Employers also compensate their employees with non-cash benefits, such as health insurance, retirement benefits, and paid leave. These “fringe” benefits have become an increasingly large share of employee earnings, in large part because such benefits are typically tax exempt while wage income is taxable (demonstrating the power of tax policy to affect economic decisions). In 1973, non-wage benefits accounted for 13 percent of employee compensation. By 2012 that figure had risen by half—20 percent of employee earnings now come in benefits.
Economists expect workers’ total compensation to rise with their productivity, but that increase can come in the form of either wages or benefits. Employers care about the total cost of hiring a worker; they do not care about how their labor costs divide between wages and benefits. Employee benefits come out of the wages that employees would otherwise be paid. Examining wage data alone ignores the increasing role of benefits in compensation. These might pull the median down too, but pulling the median is much harder since it would need to be practiced much more widely to have an effect. Heritage attacks the methodology at all stages of the process and urges more caution in reading and analyzing the data, so you're not alone or unique in saying the existing measures are not accurate. Unfortunately they don't go into how big of a difference it makes to use mean vs median, but either way, I think the lack of variances in the discussion is pretty alarming. It's one thing to say one measure is better than another, but we should know how big a difference it makes. Crushinator think we're talking about median productivity, which just doesn't exist, while we're talking about median compensation. The Heritage fundation argument is the same exact misleading argument that Crushinator and Jonny are doing : they discard the measure because reality is too "complex". It is a criticism that you can ALWAYS make towards any data in social sciences - because the "context" is both impossible to "assure" or "sature" (Derrida). It's a fetichism of a statistical artifact that, in itself, is and never will be nothing but an incomplete picture of reality - mean or average compensation, or any other statistical artifact like "women" for exemple (you think all women make an homogeneous group ?) - that put aside a lot of things (I've poited some, like heterogeneous consumption practice, heterogeneous effect of the inflation on income hierarchy, both things that plays a role when you evaluate the purchasing power of a social group, etc.). We are talking about the relationship between productivity and compensation, not reviewing the merits of metrics of either of those variables in isolation. I do not dismiss the measure because reality is too complex to be able to understand anything about it, but because in my best understanding the measure does not inform us about our complex reality at all. Zero additional information about the relationship is transmitted by plotting median wages against mean productivity, no evidence for anything can possibly come from it. Median would only be helpful if the distributions of productivity and wages are different. Then we might be able to say that some groups are succeeding more at converting productivity gains into compensation than others. If they are distributed similarly then median productivity gains would not change the picture. Since we do not have access to the distribution of productivity gains, it would not be informative, and potentially misleading. Looking at median and modal wage growth is a good idea in general, but in the context of productivity-compensation it is not a helpful metric. We obviously should care about rising inequality. I would also like to point out that your use of the term statistical artifact is completely nonsensical, so I can't really comment on anything related to it. I do think it is a possibility that high-skill workers are better able to convert productivity gains into compensation, but plotting median wage vs mean wage vs mean productivity does not provide evidence for that hypothesis at all, regardless of outcome. Maybe it isn't the best idea to argue econometrics here. And what about the information that while productivity raised, the result of the productivity is not evenly split in the worker population ? That's not an information to you ? It's not econometrics btw, every economists use median and average for obvious reasons. It's pettyfogging. Econometrics: The use of statistical data for economic analysis. Anyway I have already written too much about the importance of distributions. But I can go a little more before I peace out I geuss. If you would find that median wages have risen less than mean wages, that does not tell you anything meaningful about the productivity-compensation relationship it could very well be that median productivity has also risen less than mean productivity. So, no, I would not find such a finding meaningful in the context of wage-productivity relationship.
That average wage or compensation have risen in accordance or differently than productivity does not, in itself, tell anything about the relationship between productivity and average compensation either. There is a logical problem if you don't understand that the concomitant evolution of two variables (no matter the metric of the two variables !) does not say anything, in itself, about the relationship between the two. It is not relevant in the context of wage-productivity relationship in itself, what is relevant is the trend, that historically productivity and median wage used to evolve accordingly (in France median wage evolved even higher than average wage I believe), and that it is not the case anymore. This information is completly valid.
The relationship between the two cannot be explained without building a theorical ground to enlight the empirical data - the ground that most are using is that productivity and wage are linked, which is the basic economical theory (remuneration of the production factors at the marginal productivity). You, and most people, believe in that theorical framework, so you consider that the gap between median wage and productivity is meaningless - for you it might mean that median productivity (impossible to evaluate) has no risen like productivity - which is explicitly the reason why Heritage does not use median compensation !
I never believed in that cathechism in the sense that I believe the compensations, wage, income, etc. are determined by social factor. But that's another matter.
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EPT
