Also, I forgot to mention that the analysis accompanying Figure 1 does briefly discuss the absolute figures.
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Also, I forgot to mention that the analysis accompanying Figure 1 does briefly discuss the absolute figures.
Let me ask you, what do you believe "researchers as a share of total workforce" means? Why do you think it's an important statistic? Does it represent a nation's overall R&D potential or output? Or perhaps does it represent a nation's R&D efficiency?
Why does "researchers as a share of total workforce" matter as a statistic?
I'll give you my answer -- it is important because it is a reflection of the structure of a nation's overall workforce and thus it's overall economy. For example, a nation with 20% of its workforce working in R&D will likely be a "more advanced" economy than a nation with 1% of its workforce working in R&D, regardless of the absolute size of the workforce of each of the two nations.
However, that article is not comparing "how advanced" China's economy is versus the US economy. It is not comparing the structure of the Chinese economy vs the US economy.
It is trying to compare China's R&D output and potential and advancement with that of the US.
For that purpose, looking at "researchers as a share of total workforce" is entirely inappropriate. Instead, the most logical number is instead the absolute number of people working in R&D in each nation, along with various other variables such as the absolute expenditure on R&D.
You're trying to justify two statistics ("researchers as a share of total workforce" and "R&D expenditure as a share of GDP") which are entirely useless and inappropriate for the outcome that you're trying to measure.
They've created unnecessary statistics that are useless for the outcome that they are trying to measure. Instead, they should have stuck with the absolute numbers of China's absolute R&D expenditure vs US absolute R&D expenditure, and the absolute no. of China's R&D workforce vs the absolute no. of US R&D workforce.
It doesn't matter to me whether it's a "win" or not for Chinese higher education or potential research output.
What matters to me is whether it's a useful statistic for measuring the outcome we're interested in.
Based on that article and based on what you've written, we are interested in measuring the change of China's research potential over time, relative to that of the US.
For that, we are interested in China's absolute number of researchers over time vs the US's absolute number of researchers over time.
We are not interested in what proportion of their total workforce the researchers make up in each nation, because that doesn't tell us anything about each nation's research potential over time, it only tells us about how the job market and economic structure of each nation is changing over time.
I don't mind using the US as a barometer and a comparison. I think it's useless, but at least it isn't flawed.
However, I am saying that comparisons with the US (or comparisons with anyone!) that include "as a share of total workforce" or "as a share of total GDP" are misleading and flawed.
Yes it was mentioned, but not for the relevant part where it wanted to compare R&D expenditure and R&D workforce of China and the US.
We don't disagree here.
No, the article pretty clearly mentions that the question is about whether China is becoming more "innovative." This can be interpreted in two ways: 1. There is/will be more innovation coming out of China & 2. The Chinese population is qualitatively becoming more innovative.
Both outcomes interest me, and both should be analyzed.
I find it disappointing that the Scandinavians, other East Asian countries, and the US all have a populace that is much more involved in research and which is much more highly educated. Metrics measuring educational achievement for the Chinese population are much worse than for all other middle-income economies, even though China's R&D spending as a proportion of GDP is much higher than all other middle-income economies.
It does tell us something about how "innovative" the population is (obviously, there is more to the picture here, which the other indicators attempt to cover as well.) If you don't think it's important to see the myth of Chinese being uncreative dispelled, I don't know what to tell you. The article discusses this as well. I, for one, do not think this is an area in which China should proportionally lag so much - unlike, say, the size of the PLA, or per capita GDP.
They're not flawed if you understand that this comparison was never intended to be the end-all-be-all for the hypothesis you're seeking.
Good.
For both outcomes, the article is still using the wrong variables.
Yes, they are interesting outcomes to measure, however they whether there will be "more" innovation or R&D emerging out of China and whether the Chinese population is becoming qualitatively more innovative would be reflected in absolute measures of Chinese R&D expenditure and absolute numbers of people involved in R&D in China over time.
"Researchers as a share of total workforce" and "R&D expenditure as a share of GDP" are useful for measuring the overall per capita R&D that occurs in a country as well as the overall structure of the nation's economy.
However it tells us nothing about the absolute amount or the absolute change in a nation's R&D output.
(continued below)
Yes, those variables tells us about the "innovation per capita" or "R&D per capita" if you want to use that term.
However the article never talks about "per capita" R&D or "per capita" innovation nor did it significantly talk about the "structure" of each nation's economy. Rather, it talks about China's overall R&D potential and overall R&D output and overall innovative potential -- therefore, they are entirely incorrect for them to use "researchers as a share of total workforce" and "R&D expenditure as a share of GDP".
If you are interested in a nation's "overall" output in a particular metric then you want to look at the absolute numbers rather than the per capita numbers.
The article writes on page 11 as their goal:
"The goal of using these indicators is not to come up with a definitive measure of how innovative the Chinese economy is relative to the U.S. economy, but rather to explore Chinese progress relative to U.S. progress on a host of innovation indicators."
For the purpose of comparing Chinese progress relative to US progress for innovation indicators, the indicators have to be absolute in nature rather than per capita in nature.
If they had written "the goal is to compare the per capita make up of the Chinese work force engaged in R&D as a reflection of the overall structure of the Chinese economy" then I would 100% agree that "tesearchers as a share of total workforce" and "R&D expenditure as a share of GDP" are appropriate and logical variables to use.
It is flawed because the article is using their variables to measure the wrong outcome. They portrayed it as if they were comparing the overall potential R&D output and innovation.
If they were trying to measure the overall "R&D per capita" between China and the US or if they were comparing the overall structure of China and US economy then that would be logical and I would have no issue with such a claim.
I don't get your insistence on providing absolute numbers all the time. The OECD has the absolute numbers, and it is clear that these statistics came from the OECD. But I tried to entertain your request for per capita figures anyway (even though the statistics I previously provided, and what the article provides, are functionally the same).
Citation 53 refers to the proportional statistics.
On the same site, I can obtain the total headcount of researchers by changing the MSTI variable under "Science and Technology Indicators." However, this data only exists for up to 2012 for the PRC. Another problem is that there is no headcount for the US in this dataset.
So even the OECD doesn't have the complete absolute figures you demand. Yet, for the MSTI variable used in the article [Total Researchers per Thousand Labor Force], the OECD does have data for up to 2016 and for the US. Blame for OECD for not having these figures, making it impossible to calculate per capita.
Because absolute numbers are relevant for the outcome that the article is trying to measure, whereas "R&D expenditure as share of GDP" and "R&D workers as share of overall workforce" are irrelevant to the outcome they're trying to measure.
Let me repeat --
"It is flawed because the article is using their variables to measure the wrong outcome. They portrayed it as if they were comparing the overall potential R&D output and innovation.
If they were trying to measure the overall "R&D per capita" between China and the US or if they were comparing the overall structure of China and US economy then that would be logical and I would have no issue with such a claim."
The reason I insist on absolute numbers is because the article itself said they were wanting to compare China's overall R&D and innovation progress vs the US. For such a comparison, absolute numbers are appropriate, whereas using "per capita" numbers are inappropriate.
Basically, that is a mistake on the article's part. That's what I am saying.
That is fine, then simply don't calculate per capita.
Better to not create any statistics than create statistics that are irrelevant and misleading.
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Also, I don't understand why you are only selectively quoting parts of my replies. Please read my full replies so that you can comprehend my arguments, and I would appreciate it if you could also quote them with your own response if you agree or disagree.
Not quoting them and not responding to them makes it feel like you're either ignoring them or you don't understand them, when they are actually rather important parts of my argument.
This is an utterly pedantic distinction. "Progress" can absolutely be measured in per capita terms, and I am not willing to debate this based on the overwhelming evidence that exists in the term's common usage.
It can't specifically mention the per capita statistics, because they don't exist/are not presently calculable with the data available. On the contrary, you'd have to be extremely obtuse to ignore that the article aims to examine qualitative aspects of Chinese innovation.
You can still advance an argument based on proportions without expressly using per capita terms.
Disagree. Our subjective interpretations shall have to differ here.
No it certainly is not pedantic.
For every output there is a difference between per capita vs absolute, and distinguishing between the two is very important because it massively changes the argument one is trying to make.
If I described China as the largest absolute greenhouse gas emitter relative to other nations in the world in absolute terms it is very different to if I described China's greenhouse gas emissions ranking in the world in per capita terms. That is just one example. There are many others one can come up with.
The same principle applies for R&D and innovation.
There is nothing in the article which talked about comparing "per capita" R&D and innovation.
Instead, it only talked about R&D and innovation in China at a national, overall manner.
The article attempts to use indicators to measure the overall progress and overall potential of Chinese R&D and innovation.
Some of the indicators it uses are logical and correct.
However, some of them are wrong, namely "researchers as a share of total workforce" and "R&D expenditure as a share of GDP" -- because those indicators only tell us about the per capita and structural nature of China's R&D and innovation, but they do not tell us anything about overall progress or overall potential.
The problem is that they never made an argument about comparing the US and China on per capita terms!
Using proportions makes sense if you're comparing per capita or structural differences, but the article never sought to compare those domains of R&D or innovation in a per capita or structural way.
There is nothing subjective at all.
The article doesn't mention anything about comparing per capita R&D or per capita innovation or structural differences between China and the US, yet you are forcing yourself to interpret their incorrect variables in a way to make it seem like it is the case.
Given all of the above, doesn't it make more sense to conclude that the article's authors have simply made a few mistakes, instead of trying to shoehorn variables that are incompatible with the outcome they are trying to measure?
It's purely irrelevant to you, and would not generally mislead the audience of the article, provided they are reasonably experienced with digesting economic reports. Even if the wording of the article was not exact in outlining its goals and outcomes (which I still disagree with, but I am entertaining your interpretation regardless), the reader should still appreciate and understand the notability of the wide proportional difference between R&D expenditure and share of researchers in the workforce, relative to the US (and other countries that I mentioned, for that matter). It's still relevant to the topic of innovation in China, which the audience is undoubtedly universally interested in.
I respond to claims according to a subjective order of priority, choosing to address what I see as the most egregious ones first.
It is entirely because I am interested in China and its development in terms of R&D and innovation that I am being so pedantic about calling out the mistakes of this article.
Don't misunderstand me -- I fully think that comparing China's per capita R&D and per capita innovation and economic structure with that of the US or other nations is a very legitimate and sensible comparison to do and an interesting one at that.
If the article was interested in comparing those outcomes, then using the variables "researchers as a share of total workforce" and "R&D expenditure as a share of GDP" would make sense.
The problem is the article never mentioned comparing those outcomes (i.e.
er capita R&D, per capita innovation, economic structure), but only talks about measuring China's overall R&D and innovation output or potential, which needs absolute variables. The article has made mistakes in its variables and outcomes. Plain and simple.
It either should have specified that it was interested in comparing per capita outcomes to suit the per capita variables that they described, or it should have used absolute variables for the absolute measures that they described.
Instead, they messed up and mismatched per capita variables ("researchers as a share of total workforce" and "R&D expenditure as a share of GDP") for an absolute outcome (overall Chinese R&D).
Funnily enough it seems like you never reply to the actual meat of my arguments.
Please take note of the bolded sentences in my reply to you. They are the essential cruxes of my argument. If you choose to ignore those then my only conclusion is that you are choosing to not engage me in discussion despite the fact that I've done you the favour of quoting and replying to your replies in full.