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« SCS vs. CRT: Another politically motivated reasoning steel cage match! | Main | Science curiosity vs. politically motivated reasoning: An experimental steel cage match! »
Thursday
Aug042016

Cultural cognition of weather: a cool (or warm) guest post!

And now for something completely different-- a guest post from someone who knows what he's talking about! (And is this just my politics speaking or was July really friggin hot?!)

Cultural Cognition of Weather
by Larry Hamilton
Carsey School of Public Policy, Univ. New Hampshire

December of 2015 was the warmest ever recorded in New Hampshire, by far. Indeed, in temperature anomaly terms (degrees above or below average) it was the warmest of any month for at least 121 years. January, February and March of 2016 were less extreme but each still ranked among the top 15, making winter 2015–2016 overall the state’s warmest on record — eclipsing previous records set successively in 1998, 2002 and 2012 (Figure 1).

Seeing in this record a research opportunity, colleagues and I added a question to a statewide telephone survey conducted in February 2016, to ask whether respondents thought that temperatures in the recent December had been warmer, cooler, or about average for the state. Two months later (April), we asked a similar question about the past winter as a whole. Physical signs of the warm winter had been unmistakable, including mostly bare ground, little shoveling or plowing needed, poor skiing, spring-like temperatures on Christmas day, and early blooming in a state where winters often are snowy and springs late. Not surprisingly, a majority of respondents correctly recalled the warm season. Their accuracy displayed mild but statistically significant political differences, however. Tea Party supporters, and people who do not think that humans are changing the climate, less often recalled recent warmth (Hamilton & Lemcke-Stampone 2016). Although percentage differences were not large, these patterns echoed greater differences seen in studies that asked about longer-term changes. Our February and April surveys had found counterparts on a much more immediate, tangible scale.

Fig. 1

Although the February and April 2016 results fit with broader patterns, they were not overwhelming by themselves. Believing in the value of replication, we asked the question one more time on a July 2016 survey, with winter several months behind. Most people still recalled the unseasonable warmth. Our July wording and results are as follows:

Thinking back to earlier this year, would you say that THIS PAST WINTER, the weather where you live was generally colder, warmer, or about average for winter in your area? ROTATE 1–3

1          Colder than average winter for your area (4%)
2          Warmer than average winter for your area
(74%)
3          About average winter for your area
(18%)
98        DK/NA (4%)

Political and climate-belief gaps now appeared wider than they had been earlier in the year. Figure 2 shows one striking example: a 21-point gap between supporters of Clinton and Trump (this was, after all, primarily a political poll).

Fig. 2Figure 3 breaks down the percentage of “warmer” responses on the July survey by other respondent characteristics, including their beliefs about climate change. P-values summarize tests from probability-weighted logit regression.

Fig. 3One notable pattern in Figure 3 involves political identification; we see a 17-point gradient from Tea Party supporters to Democrats in recollections about the winter they had all just experienced. Climate-change beliefs produce wider differences: respondents who don’t believe that climate is changing, or that climate is changing but for natural reasons, were much less likely to recall the warm winter.

Figure 4 places this July poll in context with political gradients (using the same 4-party scheme) from five previous surveys that asked longer-term climate/weather questions. Panels (a) and (b) involve atmospheric CO2 levels and Arctic sea ice (Hamilton 2012, 2015). Panels (c) and (d) depict results from two Northeast Oregon surveys that asked whether summers there had become warmer in the past two decades (Hamilton et al. 2016). Panel (e) charts responses to a question about whether flooding in New Hampshire had increased over the past decade (Hamilton et al. in press). Panel (f) repeats the unpublished July survey results described earlier, on whether New Hampshire’s recent winter had been warm.

Fig. 4What underlies this replicable pattern? Atmospheric CO2 levels and Arctic sea ice are not directly experienced by most people. They are measured and communicated mainly by scientists, so public resistance to these well-observed realities might be conceived as a problem of science communication, highlighting the need for ideologically-tailored methods. But science communication on these topics already involves many different organizations, research teams, and individual scientists taking diverse and ofttimes innovative approaches. An alternative hypothesis is that the partisan gradients reflect not shortcomings of science communication but the efficacy of counter-science communication, convincing ideologically receptive audiences that undisputed facts are false. The sociological literature about such counter-messaging has recently been summarized by Dunlap and McCright (2015).

Science communication seems distant, moreover, from panels c–f, which involve phenomena that can be directly experienced. Warmer, dryer summers in Northeast Oregon have exacerbated insect and disease threats to forests, both directly and indirectly contributing to the frequency of large wildfires. Such changes are visible, and in isolation seem equally compatible with individual beliefs that climate is change is happening either for natural or anthropogenic reasons — which together comprise 85% of the respondents in both Oregon surveys. Nevertheless, we find steep political gradients. Similar observations apply to flooding in New Hampshire, which has caused significant damage, and is most salient not through scientific reports but through news coverage if not personal experience. Again, most news coverage made no explicit connections with climate change, and most people (89% on these surveys) agreed anyway that climate is changing, whether from human or natural causes.

Although wildfires and floods might not impact everyone, or impress them with decadal change, the snowiness or un-snowiness of a winter affects daily life for just about everyone living in New Hampshire. Panel f depicts ideology-influenced perceptions at the mundane scale of recent weather.

References

Dunlap, R.E. & A.M. McCright. 2015. “Challenging climate change: The denial countermovement.” Pp. 300–332 in R.E. Dunlap & R.J. Brulle (eds), Climate Change and Society: Sociological Perspectives. New York: Oxford University Press.

Hamilton, L.C. 2012. “Did the Arctic ice recover? Demographics of true and false climate facts.” Weather, Climate, and Society 4(4):236–249. doi: 10.1175/WCAS-D-12-00008.1

Hamilton, L.C. 2015. “Polar facts in the age of polarization.” Polar Geography 38(2):89–106. doi: 10.1080/1088937X.2015.1051158

Hamilton, L.C., J. Hartter, B.D. Keim, A.E. Boag, M.W. Palace, F.R. Stevens & M.J. Ducey. 2016. “Wildfire, climate, and perceptions in northeast Oregon.” Regional Environmental Change doi: 10.1007/s10113-015-0914-y

Hamilton, L.C. & M. Lemcke-Stampone. 2016. “Was December warm? Family, politics, and recollections of weather.” Durham, NH: Carsey School of Public Policy. http://scholars.unh.edu/carsey/276/

Hamilton, L.C., C.P. Wake, J. Hartter, T.G. Safford & A. Puchlopek. in press. “Flood realities, perceptions, and the depth of divisions on climate.” Sociology doi: 10.1177/0038038516648547

 

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Reader Comments (59)

Larry -

Interesting post.

==> Science communication seems distant, moreover, from panels c–f, which involve phenomena that can be directly experienced.==>

This jibes with my own view, which is that the impact of scientific messaging - which indeed may exacerbate preexisting cleavages that are associated with ideological orientation - are of a limited impact, and not particularly causal in explaining polarization. (In contrast to what I see to be Dan's viewpoint).

Indeed, it seems to me that there are factors that are more explanatory, and personal experience and ideological orientation are among those (along with others such the tendencies in how people process risk, psychological and pattern-recognition cognitive attributes, etc.) and that science communication is more likely to be a tool that is filtered and used to reinforce preexisting polarization than to drive polarization...

A question..

It seems that your current report differs somewhat from something interesting I've seen you show previously - in that at least on some of the items, mainstream Republicans were not reporting beliefs that were closer to Democrats than to Tea Partiers, but the opposite (they were reporting beliefs that were closer to Republicans than to Dems). Of course, those differences look may well be within the margin of error...but I'm wondering if you have any thoughts about that.

August 4, 2016 | Unregistered CommenterJoshua

Joshua, in our first paper testing the 4-party approach (Hamilton & Saito 2014), we found that across a range of science or environment issues, the views of non-Tea Party Republicans often are closer to those of Independents than to Tea Party supporters.
https://www.academia.edu/9642476/A_four-party_view_of_US_environmental_concern
(See graphic illustrations in Fig 1 & 2 of that paper, and formal tests in Table 2.)

Further examples can be seen in the first four panels of Fig 4 in this blog post.

That personal experience (e.g., of adverse climate/weather) could override ideological predispositions has been a motivating hypothesis in much of this work. Unfortunately our data so far don't offer much support. Instead, it looks more like ideology overrides recollections. Amazing to see that happening not just with distant realities like Arctic sea ice, but things as tangible and mundane as recent weather.

More discussion and tests around specific examples in our Oregon wildfire paper,
https://www.academia.edu/21771087/Wildfire_Climate_and_Perceptions_in_Northeast_Oregon
and a New Hampshire flooding paper that's in press.

Perhaps truly disastrous personal experience would move the dial farther, but if we're facing irreversible changes, that's a gloomy thought.

August 4, 2016 | Unregistered CommenterL Hamilton

Larry -

==> , the views of non-Tea Party Republicans often are closer to those of Independents than to Tea Party supporters. ==>

Thanks. Looks like I "mis-remembered."

August 4, 2016 | Unregistered CommenterJoshua

I think this is a very fascinating evaluation of the conflation of weather and climate! I am especially interested in the data from the paper Larry Hamilton cites in the comment above, on a 4 party view: http://www.academia.edu/9642476/A_four-party_view_of_US_environmental_concern. I think this ought to be linked in with Dan's discussions of SCS, CRT and what he is labeling as "Science Curiosity". I suspect that the scientifically curious are a polar opposite to the Tea Party. A cross cutting collection of some Republicans and Independents as well as quite a few Democrats who are inclined to accept as credible the science establishment information that Tea Party members would be predisposed to reject.

I'd tie that to a recent article by George Lakoff on Trump voters and authoritarianism: http://blogs.berkeley.edu/2016/08/01/understanding-the-allure-of-trump/.

Which in my mind links back to a particular white subculture as described here 50 years ago: http://www.kentucky.com/news/special-reports/fifty-years-of-night/. Some of these people are the ones who emigrated after serving as the Confederate cannon fodder in the Civil War to places in the west, of which NE Oregon is just one example. Later, they also became an important part of the blue collar working class in places like Indiana or Ohio.

I think that in our current times of rapid technological change it is important to consider who benefits and is harmed by advancements enabled by science discoveries. http://www.nature.com/news/donald-trump-s-appeal-should-be-a-call-to-arms-1.20356?WT.mc_id=TWT_NatureNews

This gets to the conflation about what we know about science, and what science based technologies we choose to implement. In addition to sub-cultural differences in egalitarian or authoritarian points of view, we also have a societal split between those that subscribe to a preservationist, first do no harm outlook, and an exploitation, fix any harms later one. With key financial drivers for the latter, and a lot of hypocrisy between what people may espouse and the manner in which they actually live there lives.

August 5, 2016 | Unregistered CommenterGaythia Weis

so what we're talking about unscientifically is a 3 degree warming trend over the course of 120 years, and the ability for society to make a relativistic observation of such. it really can't be done by the average human being. ask a person in new hampshire if there is much of a difference between five straight days with a high temp of 35 degrees, or five straight days with the high of 38 degrees and they will respond, 'what difference?'

August 5, 2016 | Unregistered CommenterDR. CDouglas

Gaythia, you might also be interested in research where we asked people "Do you trust scientists for information about X?" where X ranged from climate change to nuclear power, GMOs and vaccines. The last 3 were chosen because some commentators had suggested that on those particular items, the liberal-to-conservative gradient (well known regarding climate change) would slant in the opposite direction. But no, it did not. For each of these topics, liberals were most likely and conservatives least likely to say they trust scientists for information. A good visualization of that finding is Figure 4 in “Conservative and Liberal Views of Science: Does Trust Depend of the Topic?”
https://carsey.unh.edu/publication/views-of-science

August 5, 2016 | Unregistered CommenterL Hamilton

Gsythia -

==> . I suspect that the scientifically curious are a polar opposite to the Tea Party.

That seems a bit strong to me...although you might find this as evidence for your suspicion.

https://tamino.files.wordpress.com/2011/10/q74.jpg

Tea partiers seem relatively uninterested in testing their opinions about climate change....which is interesting since it's safe to assume (per Dan's evidence) that not many in the general public (including tea partiers) are terribly well-informed about clinate change.

August 5, 2016 | Unregistered CommenterJoshua

Dr. D:
"ask a person in new hampshire if there is much of a difference between five straight days with a high temp of 35 degrees, or five straight days with the high of 38 degrees and they will respond, 'what difference?'"

Probably, but we wouldn't ask that. If an entire winter season in snow country averaged 3 degrees warmer, however, people reasonably might notice things like less snow in their yard and driveway, shorter ski season, earlier plants blooming, ice skating less safe etc. Perhaps that would make a better question.

But the winter of 2015-16, which we did ask about, set historical records by being 8 degrees F above the 20th-century average; December alone was 14 degrees above average, and Christmas day (often white here) it hit 60 F in many parts of the state. Deviations that great, with impacts throughout daily life, certainly ought to be noticeable. Which the survey confirmed -- 74% said the winter had been warmer than average.

What's interesting here is that among the 26% who did not notice the record-breaking warm winter, we see not just recall errors but evidence of cultural cognition -- following patterns observed with different questions on other surveys as well.

August 5, 2016 | Unregistered CommenterL Hamilton

In my opinion, both the links from Larry Hamilton and Joshua above have the same cultural cognition issue. People are answering with regards to their tribal affiliations, and it is still unknown as to how that segues with actual actions. And actions speak louder than words. In the modern era, social media like Facebook are probably positioned to know a lot more about us, or at least images that we'd like to project, than an polling method would be likely to get participants to have the patience to answer.

First we'd have to establish what we mean by science. Peter Dear spits this between doing and knowing. https://carsey.unh.edu/publication/views-of-science One can desire to know more about the meaning of the universe by exploring nuclear physics, without succumbing to the urge to build and use an atomic bomb. A culture like Taos Pueblo can use it's understanding of nature to successfully live in the same place sustainably for 1000 years. Or, science informed technologies can be utilized in manners that allow the world can be conquered.

Another book I've read recently approaches science from the anthropological perspective of how different cultures express their understanding of nature through how they devise taxonomic classification systems. And how those different ways of knowing affect ability to make decisions. https://mitpress.mit.edu/books/native-mind-and-cultural-construction-nature. This has a passage in which one of the authors is rather disparaging of the knowledge of undergraduates at his institution relative to Mayan 4 year olds in the indigenous groups studied.
Professor: Tell me all of the trees you know.
Student: Oak, pine, spruce, cherry...(giggle) evergreen....Christmas tree is that a kind of tree?
Professor: Tell me some plants.
Student: I can't think of any plants that aren't trees....I know a lot about angiosperms, gymnosperms, gametophytes, sporophytes, but that is biology. It's not really about plants and trees.

A third take in this survey of books I've read recently (biased by their purchase from a used bookstore in Ithaca, NY) is https://thehumanevolutionblog.com/2015/09/14/book-review-population-wars-by-greg-graffin/. This is about how framing science advancement as a "War on X" affects outlook on policies, which in the author's opinion would be better implemented from a more holistic, evolutionary and ecosystem point of view.

Back to the link from Larry: As an analytical chemist I would have no problem with answering that my opinions were informed by science. But I think that takes understanding that the array of possible policy decisions based on the best available science doesn't dictate any particular solution as "best" without a cultural context. And that there are considerable efforts to distort the interpretation of science for gain. Exxon and climate, for example.

Or Monsanto and GMOs. http://www.tandfonline.com/doi/abs/10.1080/17524032.2016.1198823
"Findings show that for nearly two decades, Monsanto consistently employed discursive resources that concealed details about actors and action, reflected trends among experts in global sustainability discourse, and reshaped narratives to promote itself, products, and biotechnology in general."

Monsanto was originally the manufacturer of PCBs, something for which they have been able to avoid responsibility for decades by having successfully divested that unit, and subsequently acting as if the matter had nothing at all to do with them. http://www.chemicalindustryarchives.org/dirtysecrets/annistonindepth/toxicity.asp. Only just recently are lawsuits succeeding in connecting today's Monsanto with what they refer to as "the former Monsanto" (I should probably point out that I was in the past employed by GE, which has spent years mired in lawsuits related to pollution related to its use of PCBs, although I never had any connection to that, and merely used it as an example when pushing for environmentally sound practices, as in we don't want that again, right?).

My point in this discussion is that Monsanto really does employ many excellent scientists. But as a corporation they promote a specific view when it comes to GMOs, that they can be trusted without additional regulation, that they are making good choices when implementing technologies based on the science of genomics, and overall, anyone pushing back against them must be anti-science. In my opinion, it is to Monsanto's benefit to amplify the voices of fringe extremists who advocate that specific now in use GMOs are dangerously unhealthy, and to simultaneously keep more robust discussions of overall sustainability, and appropriate regulation out of the public media. Upcoming expansions of implementations using genomics, such as CRISPR, ought to be recieving much more public attention.


To Joshua's link, I'd note that elections demonstrate that many Republicans will vote all the way to the bottom of the ballot while Democrats tend to drop off. Democrats when asked, generally express some pride in the idea that they will not vote for a candidate that they do not know anything about except that the person is the Democratic candidate while for Republicans, the R is enough. Tea Party members may be the ones that actively express an ideology of acting on belief not informed by other information, but in practice they may not be the only players.

I'd also note that for a scientist, having to testify or give evidence for legal matters can be an awful experience. Lawyers tend to ask questions like "Is it true beyond the shadow of a reasonably doubt?" and scientist answer with some statement about the "preponderance of the evidence" which can sound like mumbo jumbo to those into more authoritarian sounding answers.

August 6, 2016 | Unregistered CommenterGaythia Weis

"December of 2015 was the warmest ever recorded in New Hampshire [...] Seeing in this record a research opportunity, colleagues and I added a question..."

I note from your NOAA graph that the previous two data points were unusually low, compared to the average. Did it occur to you to try asking the same question about the unusually cold years previously, to test whether Democrats were similarly forgetful or dismissive of evidence contrary to their expectations?

My expectation would be that climate change believers would declare that trying to deduce anything from a single year in one small geographic area was statistical fraud, when scientists report that climate change may only be detected in decadal/continental scale records. 'Climate' is defined as a 30-year average. One cold winter says nothing. And therefore we ought to have no strong expectations about the last two winters being particularly warm or particularly cold. That's certainly what they said when there was that snowy winter where the sceptics told jokes about having to shovel all the global warming off their drives...

So far as I know, the scientific consensus position is that a single warm winter for one year in one US state isn't evidence of anything, nor does it noticeably confirm/refute the global warming hypothesis. (One prominent sceptic used to amuse himself by posting long-term temperature records where the local long-term trend was downwards. About 1/3rd of places go down, 2/3rds go up. The global average is up, but you can't possibly tell that from a single coin flip.) Your evidence suggests that this message hasn't got out to everyone yet, and that left-leaning global warming believers are especially likely to have missed it - as they are still looking at local weather patterns for evidence of global changes. (And indeed, expecting that other people ought to interpret a warm winter that way.) Is this a problem of science communication, highlighting the need for ideologically-tailored methods?

"What underlies this replicable pattern? Atmospheric CO2 levels and Arctic sea ice are not directly experienced by most people. They are measured and communicated mainly by scientists, so public resistance to these well-observed realities might be conceived as a problem of science communication, highlighting the need for ideologically-tailored methods."

What public resistance? I know there is public resistance to statements about the *significance* of the CO2 rise, or the *causes* of the Arctic sea ice decline, but I've not heard that there was any significant resistance to the actual numbers.

"Do you trust scientists for information about X?"

It's an interesting question. Should they?

Feynman said that science is the belief in the ignorance of experts. Galileo said in questions of science, the authority of a thousand is not worth the humble reasoning of a single individual. Locke said that argumentum ad verecundiam was one of the ways in which human reasoning fails us. The founders of the Royal Society (men of far higher principle than the current lot!) said 'Nullius in Verba' - take nobody's word for it.

The position of scientific philosophy is that you shouldn't trust scientists for information about anything (although as we've noted the general public mostly do and arguably must). You should instead insist that it is independently checked, by people motivated to find any flaws in the reasoning or evidence. (i.e. you don't trust the people, you trust the process.) It appears you're evidence suggests conservatives are more likely than liberals to take a properly scientifically sceptical stance. That surprises me. I'd have expected it to be about equal.
:-)

August 10, 2016 | Unregistered CommenterNiV

NiV:
"I note from your NOAA graph that the previous two data points were unusually low, compared to the average. Did it occur to you to try asking the same question about the unusually cold years previously, to test whether Democrats were similarly forgetful or dismissive of evidence contrary to their expectations?"

Retrospectively, that's an intriguing suggestion, and if I'd known in 2015 (a cold winter) that 2016 would be record warm, I might have tried it. I suspect the overwhelming majority of residents then too would have called the weather correctly, as the snowiness was impressive. Whether there's an opposite political bias in recollections would be a good research question.

It would not be an equal-but-opposite test in terms of weather, though. 2016 was the warmest winter in at least 121 years, 8F above 20th-century average, and following previous warm records set in 2012, 2002 and 1998. 2014 on the other hand was not quite 3F below average, and nowhere close to a record. The last cold record in this state was set in 1917.

We provide some background about "Weather and Climate" in that section of our brief http://scholars.unh.edu/carsey/276/ , starting with:

"As average temperatures rise, the frequency of unusually warm conditions rises and the frequency of unusually cold conditions declines. During the era of steeper warming since 1975, only eleven New Hampshire winters (December through March) were below the twentieth-century average, whereas thirty-one were above it. The rising proportion of warm winters is another sign that New Hampshire climate is changing along with global climate."

There's more about that step-pause-step signature of 20th-century warming (followed twice as steeply by New Hampshire winters, as in Fig 1 above), and about the contribution of El Nino in 2016, in our brief. Without turning it into a climate paper, we tried to introduce some of the concepts.

August 10, 2016 | Unregistered CommenterL Hamilton

I have two questions, one of which is similar to NiV's. First, how do we know people had any recall problems? It seems quite possible to me a similar pattern might have been found if that winter was not a record-breaker. It may just be that people are more inclined to say certain things based on their preconceived views. If so, this may not reflect a recall problem at all. It may just be a problem of how you get people to answer the question you are wanting to ask as opposed to some other question.

The second question is this author refers to a study which finds liberals say they trust scientists on issues like GMOs at a similar rate as conservatives. This is offered to show the commonly perceived bias on such issues (where liberals are wrong) is wrong. However, again, how do we know that is what this means? An alternative answer would be liberals say they trust scientists on these issues because they believe scientists agree with them when in reality they do not. Of that were the case, liberals might believe they trust scientists even though their views are only supported by a (relatively) small number of scientists.

I don't know if these questions have been considered elsewhere, but given they didn't even get mentioned here, one could easily get the impression there is some confirmation bias at play. That wouldn't be surprising. It is often easy to come up with a theory then perform a test that gives results which match the theory and stop there, failing to check for alternative explanations.

August 10, 2016 | Unregistered CommenterBrandon Shollenberger

"Retrospectively, that's an intriguing suggestion, and if I'd known in 2015 (a cold winter) that 2016 would be record warm, I might have tried it."

Why? What difference would that have made? The same comparison applies to the previous year before those two cold ones, which also looks like a record.

"It would not be an equal-but-opposite test in terms of weather, though. 2016 was the warmest winter in at least 121 years, 8F above 20th-century average, and following previous warm records set in 2012, 2002 and 1998."

Again, I'm not sure I follow. I thought the question was whether the winter was warmer or colder than 'average'? You don't specify what you mean by 'average', but I would surmise most people would be thinking of a much shorter period than 121 years, particularly if your interest is in people's recollections of weather. People's own memory, 30 years, a decade. If you're asking about their own direct experiences and personal observations, rather than trusting what scientists report, it doesn't make sense to expect them to operate on a 121 year timescale. (And for that matter, why not longer? Why not back to the last ice age? Or over the Earth's entire history?)

The issue of "records" can be a tricky one. Even assuming independence, the probability of the current year being a 121year record is 1/121, and the probability of some state in the US experiencing such a record is 1-(1-1/121)^50 = 33%. About one year in three there would be such a record somewhere. And temperature in neighbouring US states over time is both strongly autocorrelated and cross-correlated, so the probability is far, far higher than the independence assumption would indicate.

That's a considerably more sophisticated analysis than most of the general public could do, I agree, but a lot of people I know are 'suspicious' of the number of records for this, that, and the other that the media routinely report on all subjects - not just weather. 100-year records turn up a lot more often than one every hundred years, and everyone has direct experience of it. (And that's even before we get into all the issues of the US temperature record being subject to "adjustments", urban heat islands, changes in instrumentation, etc., which has been widely reported on the sceptical side of the debate.)

So awareness of the weather will be a combination of two factors - direct experience, and media coverage. I expect the record warmth would have been reported locally in the media, so part of people's awareness of the warmth of the recent winter will be based on that, and differentially believed depending on political alignment. Only part of their awareness is down to experience. And the experience part will be based on a short-term record of people's memories, not the 100-year scientific record they only see via the media.

If you want to isolate the effect on people's memories of their own experiences, rather than the known differential effect due to selective acceptance of 'what scientists/the media say', the cold weather would (arguably) be less 'polluted' by politics/media than the warm weather, and would be equally distinct from the 'average' you're asking about in their personal experiences.

"As average temperatures rise, the frequency of unusually warm conditions rises and the frequency of unusually cold conditions declines."

Not necessarily. The spread of temperatures can change as well as the average.

The third graph shown here indicates that it does. A blue central band surrounded by red indicates a widening spread (e.g. 1860), red surrounded by blue means its narrowing (e.g. 1960). You can also see that in the full year's data, while the number of moderately above/below average days (+/- 4 C) does change frequency, changes in the extremes (+/- 4-10 C) is not so clear. You had to look for summer temperature extremes (fourth graph) to find a visible change.

"We provide some background about "Weather and Climate" in that section of our brief"

It's not too bad, and I applaud the fact you made the effort, but detection/attribution of climate change is a complicated subject with a lot of subtle statistical issues that I agree you can't hope to cover in a brief section of a non-specialist non-climate-science paper.

To determine whether there is a statistically significant change in climate, you first have to know the expected distribution of temperature histories under the natural background null hypothesis. In particular, you need to know how often you would expect to see consistent multi-decadal rises and falls if there was in fact no global warming. And it's entirely possible to see such apparent trends even when there is no underlying trend in the distribution.

If you want to know more, I'll be happy to explain at length (like in the comments thread here), or you could check the stuff in Box and Jenkins' textbook on Time Series Analysis. Recent global climate data appears to fit a trendless ARIMA(3,1,0) model best, according to Box/Jenkins standard methods, but that doesn't mean that's how the physics really works.

However, to summarise briefly, the biggest problem in detection/attribution is that nobody had a validated statistical model of the background "normal" climate to compare against, and so a scientifically valid comparison is impossible. Climate scientists do the best they can, but ultimately it's down to "expert judgement" (i.e. their opinion) rather than being a quantified scientific demonstration.

Although we don't have global records going back more than about a century, we do have longer local records. The longest is the Central England Temperature series (HadCET), which goes back to 1659. There are several instances of long-term rises in it, the longest being 1680-1733 (actually bigger and longer than the late 20th century change!), so we do know that long-term trends can happen naturally. We don't have enough data to say how often.

This observation also implies that anthropogenic rises of this sort of magnitude can't be statistically detected in local data. If you can't distinguish the entirely natural 1733 peak from the abnormal(?) 1998 peak in England just by looking at the data, how do you expect to be able to do so with New Hampshire?

It's complicated. On physical grounds, some anthropogenic warming is to be expected, but the pure greenhouse warming that results from the reasonably well-understood bit (about 1 C per doubling of CO2) is multiplied by an unknown number related to "climate feedbacks" which can't be accurately modeled yet. Recent empirical evidence suggests it's significantly lower than the mainstream climate models predict, but of course this is still scientifically controversial. Simple yes/no statements can't cover the subtleties of the real competing scientific positions.

August 10, 2016 | Unregistered CommenterNiV

Brandon:
"First, how do we know people had any recall problems?"

Actually, that was my point, the errors show a political pattern that probably reflects something like cultural cognition, not random memory error. Using "recall" was shorthand, but assuming people believe what they reported about the weather, it seems at least some people's recollections about the past winter were shaped by their politics.

"The second question is this author refers to a study which finds liberals say they trust scientists on issues like GMOs at a similar rate as conservatives. This is offered to show the commonly perceived bias on such issues (where liberals are wrong) is wrong. However, again, how do we know that is what this means?"

Well, survey researchers don't know what goes on inside people's heads, they just observe a behavior (response to the question). In the absence of data, I think many people would have guessed that liberals would be more likely to answer that they trust scientists on evolution and climate, but less likely on nuclear power safety, GMOs or vaccines. So we asked the questions and collected the data, but found that hypothesis not supported.

"It is often easy to come up with a theory then perform a test that gives results which match the theory and stop there, failing to check for alternative explanations."

But here we found results opposite to our hypothesis, and duly reported them. That happens to me often.

August 10, 2016 | Unregistered CommenterL Hamilton

NiV:
“If you're asking about their own direct experiences and personal observations, rather than trusting what scientists report, it doesn't make sense to expect them to operate on a 121 year timescale.”

No, and we didn’t expect something so un-sensible. However, as a historical record, last winter was above average even if someone’s timescale is only two years.

“Even assuming independence, the probability of the current year being a 121year record is 1/121, and the probability of some state in the US experiencing such a record is 1-(1-1/121)^50 = 33%. About one year in three there would be such a record somewhere.”

This too seems borrowed from a different conversation, perhaps on blogs? Of course they’re not independent, and we made no causal argument from one record, or about other states. We did point out that last winter’s record in New Hampshire is part of a rising trend.

“(And that's even before we get into all the issues of the US temperature record being subject to "adjustments", urban heat islands, changes in instrumentation, etc., which has been widely reported on the sceptical side of the debate.)”

But widely debunked on the science side. We read different literatures.

“The spread of temperatures can change as well as the average.”

Mathematically yes. My description of extremes rising with the mean is accurate for the New Hampshire winters we’re looking at (Fig. 1), and also globally.

“If you want to know more, I'll be happy to explain at length (like in the comments thread here), or you could check the stuff in Box and Jenkins' textbook on Time Series Analysis. Recent global climate data appears to fit a trendless ARIMA(3,1,0) model best, according to Box/Jenkins standard methods, but that doesn't mean that's how the physics really works.”

First differencing (as in ARIMA(3,1,0)) removes a trend, and has sometimes been used to hide the incline in global temperatures. But trends are central to the issue of climate change. We need to characterize and understand them, not hide them. For the undifferenced New Hampshire winter series ARIMA(3,0,0) does not fit at all, while ARIMA(1,0,1) does well. But as you say, that’s unphysical. Better to put some physics back in, for example by representing global temperatures (makes less sense for local) as a function of lagged values of CO2, multivariate El Nino, total solar irradiance, and atmospheric optical depth. One way to do this is by ARMAX modeling with ARIMA(1,0,1) disturbances. In my experience such models track observed temperatures pretty well, with interpretable parameters and white-noise residuals.

“If you can't distinguish the entirely natural 1733 peak from the abnormal(?) 1998 peak in England just by looking at the data, how do you expect to be able to do so with New Hampshire?”

Again, not clear what you’re arguing against that we said.

August 10, 2016 | Unregistered CommenterL Hamilton

"No, and we didn’t expect something so un-sensible. However, as a historical record, last winter was above average even if someone’s timescale is only two years."

And the previous winters were below average, whether someones's timescales are two years or twenty. Why object to the comparison on the grounds that the warm winter is a 121-year record and the cold winter is not, if the longer timescale is not relevant to your argument?

"This too seems borrowed from a different conversation, perhaps on blogs? Of course they’re not independent, and we made no causal argument from one record, or about other states. We did point out that last winter’s record in New Hampshire is part of a rising trend."

But you also seemed to be making a big deal out of the point that the warm winter was a "record". In judging whether it is above or below average, that's not relevant, nor would it be apparent to an observer on the ground, relying on their own recollections.

"But widely debunked on the science side. We read different literatures."

I suspect we read substantially the *same* literature, but interpret it differently! That's how Dan's motivated reasoning works.

Each side is firmly convinced that the arguments of the other side have been debunked. Given this symmetry, why would anyone suppose that the mechanisms in play are any different? We're all human. Our brains are wired the same way.

"Mathematically yes. My description of extremes rising with the mean is accurate for the New Hampshire winters we’re looking at (Fig. 1), and also globally."

I just demonstrated that it's not true globally (the red/blue plots). Around 1950-1980 the distribution narrowed and the extremes declined.

"First differencing (as in ARIMA(3,1,0)) removes a trend, and has sometimes been used to hide the incline in global temperatures."

There's no first differencing in ARIMA(3,1,0). You're confusing the model itself with the transformation commonly applied to it to turn it into a more tractable stationary series.

It's entirely possible to have a ARIMA(3,1,0)+trend model, which is distinct from ARIMA(3,1,0) alone. First differencing turns that into ARIMA(3,0,0)+offset, which is detectable with sufficient data.

"But trends are central to the issue of climate change."

When we're studying the detection/attribution task, the question is whether there *is* a trend. If you simply assume there is one, you will of course 'find' one but then you're begging the question. The task of detection/attribution is to compare the no-trend models against the with-trend models to determine which fits the data better. Since you're trying to prove there *is* a trend, your null hypothesis (the one you're trying to disprove) therefore has to have no trend.

Strictly, since both sides accept that there will be a trend and the competing hypotheses are actually how big it is, the comparison ought to be small-trend versus big-trend, but if the tests fail to reject the no-trend case, they'll necessarily fail on the small-trend null as well.

"Better to put some physics back in, for example by representing global temperatures (makes less sense for local) as a function of lagged values of CO2, multivariate El Nino, total solar irradiance, and atmospheric optical depth."

If you throw a sufficient number of basis functions into the mix, you can curve-fit anything. "With four parameters I can fit an elephant, and with five I can make him wiggle his trunk."

To put some physics in (which I agree is what is needed), you need a validated physical model, meaning one that has been demonstrated to be able to make predictions of the distribution of temperature history sufficiently accurately to distinguish hypotheses. I'm pretty sure that if the AOGCMs have so far failed to do so, that a trivial 'epicycle-type' model with a handful of linearly combined forcing parameters isn't going to do so.

"Again, not clear what you’re arguing against that we said."

You presented the rising trends in the New Hampshire data, and say things like: "The rising proportion of warm winters is another sign that New Hampshire climate is changing along with global climate" and " Both curves exhibit the pattern of early twentieth-century warming, mid-century pause, and post-1975 takeoff, which is a signature of global change" and "New Hampshire’s gradual warming is not the only thing that made December 2015 so extreme". You're connecting the local climate record to the global rise in temperatures (which in today's political context is going to be interpreted as a reference to anthropogenic climate change) and emphasise this connection by calling it "extreme" with "broad consequences for everything from winter recreation to forest ecosystems and insects", suggesting it's not natural or normal.

But given that the 1733 peak (which I assume you would agree has to be completely natural/normal) also showed a rising trend of warmer winters, and a rise-pause-rise pattern, would also pass your test, how can that be valid?

On re-reading and parsing your words more carefully, I accept that what you write doesn't make any explicit connection between the observed rise and anthropogenic change. I'm guilty of doing what I complain of in others:- interpreting phrases like "global rise in temperatures" and "climate change" and "consequences for ecosystems" in the modern political context in which such phrases are inextricably linked with the AGW hypothesis. My apologies for the misinterpretation. However, I'm pretty sure that most other people are going to interpret it the same way, and I strongly suspect that was intentional (not in any nefarious way - just that that's what you were thinking of, and expecting readers to think of, too). My argument is with the implicit implication.

August 11, 2016 | Unregistered CommenterNiV

L Hamilton:

Actually, that was my point, the errors show a political pattern that probably reflects something like cultural cognition, not random memory error. Using "recall" was shorthand, but assuming people believe what they reported about the weather, it seems at least some people's recollections about the past winter were shaped by their politics.

I apologize for misunderstanding you then, but when people discuss the results of scientific studies, I expect a certain degree of precision. I do not expect a person making multiple remarks like, "Most people still recalled the unseasonable warmth" would mean they aren't meaning to claim there were actually errors in recollection.

Similarly, while "assuming people believe what they reported about the weather" may allow us to argue there are errors in recollection, that assumption is by no means a given. And even if we make that assumption, we cannot conclude with certainty any errors in recollection are due to memories of the previous winter. An alternative possibility is people remembered the most recent winter perfectly fine but misremembered previous ones.

Well, survey researchers don't know what goes on inside people's heads, they just observe a behavior (response to the question). In the absence of data, I think many people would have guessed that liberals would be more likely to answer that they trust scientists on evolution and climate, but less likely on nuclear power safety, GMOs or vaccines. So we asked the questions and collected the data, but found that hypothesis not supported.

And you described that as:

As expected, liberals were most likely and conservatives least likely to say that they trust scientists for information about climate change or evolution. Contrary to the topic-bias hypothesis, however, liberals also were most likely and conservatives least likely to trust scientists for information about vaccines, nuclear power safety, and GMOs.

Notice the change in these two sentences. The first sentence accurately describes what people reported. The second sentence stops discussing what people reported and instead referred to what people actually do/believe. These are not the same thing. Even if a person genuinely believes they trust scientists regarding a given topic, they may well misunderstand what scientists as a whole have to say on that topic.

This subtle change in topic of discussion runs throughout the entire paper you link to as it constantly refers to "trust in scientists" as opposed to "reported trust in scientists," never once offering a caveat about how people's claimed levels of trust in scientists may not actually reflect their real levels of trust in scientists.

But here we found results opposite to our hypothesis, and duly reported them. That happens to me often.

In one case. In the other case not. In neither case have you described any steps taken to confirm the interpretations you came up with were the correct ones as opposed to other interpretations which might also fit your results. The conclusions you reached may be correct, but they involve logical leaps that are not based in any data or analysis you've provided.

As far as I can tell, these are simply cases of over-interpreting the data. The data may fit certain interpretations, but without analysis to confirm no other interpretations are equally valid, we cannot know those interpretations are correct. It is fine to offer the interpretations as ones you believe. It is even fine to offer them as ones you argue are most likely. It's just not okay when even a casual reader reading your analysis can easily ask, "How do you know X, Y or Z isn't the cause?" without you having a meaningful answer.

August 12, 2016 | Unregistered CommenterBrandon Shollenberger

Brief recap, “The cultural cognition of weather”

- Winter of 2015-2016 was New Hampshire’s warmest in at least 120 years.
- A survey several months later unsurprisingly found that three-quarters of the respondents recalled winter temperatures as having been “above average.”
- However, there was a 21-point difference between the recollections of Clinton and Trump supporters, or 17 points between Democrats and Tea Partiers.
- These temperature-recollection/political-identity associations appear qualitatively robust, in that similar (significant but smaller) differences appeared on two previous New Hampshire surveys asking about the same winter; as well as significant and larger differences with the same pattern on other surveys asking different climate-observation questions.
- Conservative rejection of anthropogenic climate change, a dominant feature of US surveys, provides an obvious explanation for the common political pattern affecting responses to these questions, from basic science to local weather.

Brandon disagrees about the interpretation of a different survey, which found conservatives less likely to say they trust scientists, even on topics selected to test hypotheses this pattern would be reversed. He offers alternative explanations:

“Even if a person genuinely believes they trust scientists regarding a given topic, they may well misunderstand what scientists as a whole have to say on that topic....
... never once offering a caveat about how people's claimed levels of trust in scientists may not actually reflect their real levels of trust in scientists.”

No doubt such phenomenon exists, but with what net effects? A consilience of evidence supports the simpler inference that conservatives really are less inclined to trust science, across a number of major topics. To pick some prominent examples: Conclusions of most scientists with relevant expertise regarding climate change, evolution, age of the Earth, or the value of vaccinations are well known, and richly supported by evidence across scores of disciplines. At the same time we know equally well, whether from surveys or political leaders, which ideological factions among the US public are more likely to reject mainstream scientific conclusions on these topics, and dismiss supporting evidence as a hoax.

NiV suggests we should have done the “winter” survey a year earlier, after the below-average winter of 2014-15, and in retrospect I agree. We did not think of it at the time because that winter had been cold but not historically way below average, and the winter before it had been cold as well. People with either short (2-year) or long (generational) time horizons could reasonably have said 2014-15 was about average. December of 2015, in contrast, really stood out -- not only the warmest December, but in anomaly terms the warmest month by far, in the state’s recorded history. And this following the previous two cold winters. Who could not notice? Wondering about social construction of extreme weather is what kicked off this particular study.

Other criticisms by NiV focus on the reality of anthropogenic climate change, which I did not explicitly address here. But he/she correctly infers that I agree with most active scientists on this point -- ACC is happening now, and likely to have adverse effects. I won’t hijack Dan’s blog for that argument, which is better addressed elsewhere.

August 14, 2016 | Unregistered CommenterL Hamilton

"Other criticisms by NiV focus on the reality of anthropogenic climate change, which I did not explicitly address here."

Not quite. The main point I was addressing was whether warm/cold single years, or longer-term local temperature records from a relatively small geographical region, constituted evidence of global warming. The mainstream scientific consensus on this is (rightly) that they're not. And yet, not surprisingly given the political division of opinions, and the competing uses of warm and cold local weather events in the media to try to persuade the public, a lot of people are firmly convinced that you can, and moreover, they equally firmly believe scientists have said so.

And the paper *does* address this, claiming that the rise-pause-rise is a "signature" of global warming; that the local rise is causally linked to the global one, and is evidence for it. (Where I erred is in thinking you were also using it to support the case for the warming being anthropogenic, which is equally unsupported scientifically, even in a mainstream reading, but which I read in from how your vocabulary would be interpreted in the political context. I agree we don't need to go there.)

As I said above (and you can see in figure 4 here,) even the mainstream analysis says that even in the United States, roughly 1/3rd of places have negative trends.

The reason, despite this point, that local weather events and records have become a point of political division is that advocates have tried to connect the rather remote and abstract scientific reports of fractions of a degree change in the global average with the general public's personal experiences of dramatic and inconvenient, uncomfortable, or even disastrous weather events right where they live. The idea is to connect people emotionally and personally to the issue. From a political persuasive point of view, it's an excellent tactic. From a scientific point of view, it stinks.

And so on this particular point, the conservatives are far closer to the consensus scientific position than the liberals. I doubt, though, that that is because the communication of science succeeded better with conservatives. I think it is simply that what people believe about science has nothing to do with what the scientific evidence actually says; it's all about what they read (and believe) in the media.

--

From the point of view of providing another data point on the relationship of politics to beliefs about the weather, the paper makes a valuable contribution. The issue is the interpretation. The paper appears to assume that people ought to connect their personal experiences of a dramatic warm winter with global warming, and that AGW non-believers are selectively forgetting or ignoring it because it conflicts with their beliefs. I propose that from a scientific point of view, people should not connect local events with global averages, should be as forgetful of weather as they are of most everyday background events, and it is the AGW believers who are only showing a higher awareness because they are more likely to have seen/absorbed the media coverage of the "record hottest winter".

My point is that the previous unusually cold winters are not just an additional line of evidence for the same thing - only weaker because it was not as significant a record-breaker. They're actually a better test of experiential recollections, because they'll be less polluted by memories of media coverage. The hundred-year record is not relevant to memories of personal experiences, and the information would only be accessible to most people via the media, and so the warm winter is actually a worse, not better example to pick for this reason.

I'm hoping that this exchange may be valuable to you, because I believe science relies on people with a diversity of perspectives are needed for us to see past our respective blindspots. Even though we may disagree on the evidence for AGW, we can still help one another. We have different preconceptions, and make different assumptions, and so can each see possibilities that the other would miss. That's where much of the value is in doing what you've just done with this guest blog post - putting your ideas out there and inviting those who disagree to poke holes in them, and then hanging around to poke holes in their attempts right back. Please don't be put off from debating it by the fact that I'm taking an opposing position. I *want* you to argue with me (for me to test the strength my own arguments and reasons for believing as I do against an intelligent opponent), and I truly appreciate the fact that you have taken the time to debate with us. Too many scientists don't. Thank you.

August 15, 2016 | Unregistered CommenterNiV

NiV:
“The main point I was addressing was whether warm/cold single years, or longer-term local temperature records from a relatively small geographical region, constituted evidence of global warming.”

Yes, I understood that was your point, but it’s different from mine. Global warming refers to the rising global average; of course some places are warming faster, slower or not at all. New Hampshire winters have warmed at double the average rate, and with similar timing, which tells us that New Hampshire is changing along with the globe, only faster. It is not by itself evidence of global warming, any more than sea surface temperatures in the “cool spot” S of Greenland are evidence of global cooling. On the other hand, that New Hampshire’s recent winter fits with the longer-term trend in that state, and the globe, is important context for “so what?” parts of the paper. (Those sea surface temperatures are important too, but for different reasons; they reflect ocean circulation changes linked to meltwater from the Greenland Ice Sheet.)

“The mainstream scientific consensus on this is (rightly) that they're not.”

Lots of researchers are testing whether the frequency of extreme events is changing in directional ways, e.g. setting more hot records than cold. Our brief illustrates that concept with the humble case of New Hampshire winters. More technical analysis in the growing literature on attribution seeks estimates of conditional probabilities, but I haven’t ventured there.

“And the paper *does* address this, claiming that the rise-pause-rise is a "signature" of global warming; that the local rise is causally linked to the global one, and is evidence for it.”

Causally linked, but with arrows going the other way. New Hampshire is not evidence for global warming, just one local manifestation.

“The paper appears to assume that people ought to connect their personal experiences of a dramatic warm winter with global warming.”

We nowhere assume people ought to make this connection, but find evidence that some of them do: AGW non-believers are less accurate in recalling recent warmth.

“They're actually a better test of experiential recollections, because they'll be less polluted by memories of media coverage.”

As I said, in retrospect if would be interesting to have asked a similar question in 2015. Interpretation would not be clear-cut because whether 2014-15 was exceptional depends on whether you take a medium (instead of short or long) time frame, whereas 2015-16 was exceptional either way. As for a cold winter “less polluted” by media -- having lived through it I think the opposite is more likely. Big storms bring weathercasters to life, they’re out there in their parkas telling you to stay off the streets, reporting on roof collapses and towns that have already spent their snow budgets, etc. My impression is the cold winter got far more media attention than the warm. That would be testable from archives. In terms of daily experience too, winter storms and unmelting snow (several feet deep in our yard for most of the winter) are very much in your face. So comparing these two winters would not be a clean test for ideological symmetry, as critics could point out no matter what we found.

August 16, 2016 | Unregistered CommenterL Hamilton

"Causally linked, but with arrows going the other way. New Hampshire is not evidence for global warming, just one local manifestation."

There's no evidence for that, either.

What you're talking about here is 'attribution'. ‘Attribution’ of causes of climate change is the process of establishing the most likely causes for the detected change with some defined level of confidence (which you should note is not the same thing in the IPCC's lexicon as 'likelihood'). Unequivocal attribution would require controlled experimentation with the climate system. Since that is not possible, in practice attribution of anthropogenic climate change is understood to mean demonstration that a detected change is ‘consistent with the estimated responses to the given combination of anthropogenic and natural forcing’ and ‘not consistent with alternative, physically plausible explanations of recent climate change that exclude important elements of the given combination of forcings’. In particular, you would have to demonstrate that the warming of New Hampshire was inconsistent with local natural variability before being able to ascribe it to global change. You haven't done that, and neither has anybody else. And given near identical-looking observations of natural variability like the peak in 1733 England, it doesn't seem likely that you could.

Detection of anthropogenic influence is not yet possible for all climate variables for a variety of reasons. The approaches used in detection and attribution research cannot fully account for all uncertainties, and thus ultimately "expert judgement" is required to give a calibrated assessment of whether a specific cause is responsible for a given climate change. That is to say, it's ultimately based on the opinions of authority, not quantified empirical evidence.

Climate model experiments (if you're prepared to put any weight an unvalidated model) have indicated that multi-decadal internal variability could be responsible for some of the rapid warming seen in the central USA between 1901 and 1940 and rapid cooling between 1940 and 1979. Also, regional temperature is more strongly influenced by variability and changes in climate dynamics, such as temperature changes associated with the NAO, which may itself show an anthropogenic influence, or the Atlantic Multi-decadal Oscillation (AMO), which could in some regions and seasons be poorly simulated by models and could be confounded with the expected temperature response to external forcings.

The extent to which temperature changes at sub-continental scales can be attributed to anthropogenic forcings, and the extent to which it is possible to estimate the contribution of greenhouse gas forcing to regional temperature trends, remains a topic for further research. According to mainstream climate science opinion, surface temperature changes are detectable mainly at large spatial scales of the order of several thousand kilometres. Robust detection and attribution are inhibited at the grid box scales because it becomes difficult to separate the effects of the relatively well understood large-scale external influences on climate, such as greenhouse gas, aerosols, solar and volcanic forcing, from each other and from local influences that may not be related to these large-scale forcings. This occurs because the contribution from internal climate variability increases at smaller scales, because the spatial details that can help to distinguish between different forcings at large scales are not available or unreliable at smaller scales, and because forcings that could be important at small spatial scales, such as land use change or black carbon aerosols, are uncertain and may not have been included in the models used for detection.

That's all a very wordy way of saying you can't do it. Local climate has many contributory causes, many of them nothing to do with global events, and you cannot say for any individual event which of those contributors actually caused it. It might easily have been one of the others, and given the number of such alternatives, probably was. You certainly don't know that it wasn't.

That's what the mainstream science says, anyway. Believe it or not, as you choose.

But I think I've said everything I need to say on the subject. If you're still not convinced, so be it. :-)

"As for a cold winter “less polluted” by media -- having lived through it I think the opposite is more likely. Big storms bring weathercasters to life, they’re out there in their parkas telling you to stay off the streets, reporting on roof collapses and towns that have already spent their snow budgets, etc. My impression is the cold winter got far more media attention than the warm."

I accept that's a plausible possibility; one that didn't occur to me! My thanks!
:-)

Now, is there any objective evidence that it did?

August 16, 2016 | Unregistered CommenterNiV

"Now, is there any objective evidence that it did?"

Well, as I wrote, that should be testable from archives. It's your hypothesis, I'm skeptical, but have at if you think it's worthwhile.

August 17, 2016 | Unregistered CommenterL Hamilton

NiV:
“Local climate has many contributory causes, many of them nothing to do with global events, and you cannot say for any individual event which of those contributors actually caused it.”

Attribution of individual events has become a hot research topic lately, being something that many people would like to know. Here are two papers (not paywalled) on the state of the art:

http://www.nature.com/nclimate/journal/v5/n8/full/nclimate2657.html

http://onlinelibrary.wiley.com/doi/10.1002/wcc.380/pdf

But we weren’t trying to do that. We note that decadal to century-scale change in New Hampshire winters resemble the pattern of global warming, so attribution of a common cause seems straightforward -- it is not contested in any recent study of this region’s climate that I know of. Last winter (not an “event” as that term is used in recent literature; we’re looking at a four-month average) was consistent with longer-term trends, whether such trends are expressed as (1) significant rise in average temperatures, (2) more frequent above-average winters, or (3) warm records successively broken, while the cold record is a century old.

Although temperature shows wide short-term fluctuations, its longer-term trends tend to be clearer and analytically more tractable compared with changes in precipitation. But precipitation is important as well. Here’s how we framed the complex, uncertain but not information-free question of attribution for a forthcoming paper on flooding:

“Analysing long-term flow records for New England watersheds with minimal human influence, Collins (2009) concludes that flood magnitudes in New Hampshire and across New England have increased since 1970. Armstrong et al. (2012, 2014) show that the magnitude and frequency of floods across New England are increasing, again on rivers with minimal human impact. Other analyses confirm increases in both precipitation and extreme precipitation events in New England (Douglas and Fairbanks, 2011; Hayhoe et al., 2007; Hodgkins and Dudley, 2011; Melillo et al., 2014; Spierre and Wake, 2010). The causes of rising flood damage in New Hampshire include both an increase in impervious cover (i.e., buildings and pavement) associated with urban development (Nowak and Greenfield, 2012) that serves to increase runoff; and the increase in extreme precipitation events, especially in the southern half of the state (Wake et al., 2011a, 2011b).
Attribution is difficult for individual weather events, but theory and trends point toward global change. For example, overall precipitation across the US has increased, as have the frequency and magnitude of the heaviest rainfall events (Walsh et al., 2014). Warmer air can contain more water vapour compared to cooler air, and the amount of atmospheric water vapour has increased over land and oceans (Santer et al., 2007). More water vapour in the atmosphere means there is more water that can fall as rain. Dynamical aspects of the atmosphere change, influencing weather patterns and storms. In mid-latitudes such as New England, there has been an increase in extreme precipitation events associated with fronts (Kunkel et al., 2013). Projections of future climate suggest that the recent trend towards increased heavy precipitation events will continue in the northeastern US (Hayhoe et al., 2007) and across the country (Wuebbles et al., 2013).”

Being skeptical ourselves, in the paper we test previous reports of increased regional precipitation, extreme events, and flooding by conducting our own analyses, using original or more recent data.

August 17, 2016 | Unregistered CommenterL Hamilton

Well, logic takes a beating when it comes to politics.

The reason conservatives want to pollute is that paying workers to reduce or stop pollution requires paying workers a lot of money that increases costs and prices, and the claim is, paying workers kills jobs. And reduces gdp. As if workers take their pay and burn it. Depriving consumed of the free money they would get if workers were not paid.

Another part of the politics is that if New Hampshire is warm in January, then you can grow June crops in NH in January because the daylight will be 14-16 hours. The temperature determines the seasons, not the height of the sun in the sky.

I wonder what the answer would be to the question, "if climate change increases temperatures in winter to the normal for summer, would the hours of daylight be longer?"

August 19, 2016 | Unregistered Commentermulp

"We note that decadal to century-scale change in New Hampshire winters resemble the pattern of global warming, so attribution of a common cause seems straightforward -- it is not contested in any recent study of this region’s climate that I know of."

Are you arguing that "correlation implies causation"? And that "absence of evidence is evidence of absence"?

"Warmer air can contain more water vapour compared to cooler air, and the amount of atmospheric water vapour has increased over land and oceans (Santer et al., 2007). More water vapour in the atmosphere means there is more water that can fall as rain."

I've never really understood the logic of this. It is true that warmer air can hold more water - but that would therefore imply that warmer air is less able to drop it in the form of rain. Rain happens when air cools to the point where the water can no longer all be held. If it's warmer to start with, this takes longer. And if the residual air after the rain has fallen is warmer, there will be more water vapour retained unfallen. It's not immediately obvious to me which effect dominates.

I suspect the real physics is rather more sophisticated than the rather trite line of reasoning would suggest. But it's plausible-sounding enough to convince a lot of the general public.

---
"The reason conservatives want to pollute is that paying workers to reduce or stop pollution requires paying workers a lot of money that increases costs and prices, ..."

No, conservatives want to stop pollution, too. The issue is one of priorities.

We have lots of problems to solve - creating all the food, fresh water, medicines, heating, lighting, air conditioning, washing machines, refrigerators, cars, lorries, trains, planes, tools, factories, shops, clothes; all the goods and services people need to live, to be comfortable and happy - and we have only limited skilled manpower with which to do it. Reducing pollution is one of the things we want, but only one, and if you have more of that, you will inevitably have less of something else. People - not just conservatives - have a choice. And what people choose is what the market delivers.

There is, in fact a very easy free-market solution available. One that requires no new legislation, government backing, subsidies, taxes, regulations, or coercion. It is incredibly simple.

Everybody who believes that global warming is a threat (about half the population according to some surveys) simply takes a pledge today to use no more fossil fuels, or any goods made using them, or transported using them. Period. The demand for fossil fuels would drop through the floor, the price would drop with it, and all the profit in oil, gas, and coal would vanish. Every fossil fuel company would get out of the business as fast as they could, since it would be costing them far more to extract than they can sell it for. And conversely, the price of renewables would skyrocket, the profits available would do likewise, leading all the energy companies to jump on the bandwagon. The massive influx of new money and competition would then fund the R&D needed to develop the technology and make it cheaper.

The same method was used by the vegetarians. They didn't get the government to ban meat, they simply stopped eating it themselves. And now there is a significant industry of vegetarian restaurants and suppliers to cater for them - often at a price premium - because businesses don't care about the issues and principles, they just supply what people want to buy. And if there were enough people wanted to go vegetarian, the entire food industry would rapidly follow them, with no arguments or complaints. It's very democratic.

The market provides what the people want. Not what the elites think they ought to want, or what people tell pollsters that they think they want to hear, or that sounds suitably 'caring', but what they actually want, revealed in the purchases they make. It is the collective priorities and preferences of the population as a whole that make these decisions, not businesses or governments. And the people, near universally, have decided that they would prefer to keep buying the products made with fossil fuels and to put up with the pollution. Nobody is willing to pay the costs of reducing it further. Liberals just as much as conservatives.

Hence the spectacle of climate campaigners boarding planes to fly around the world to places like Bali, to discuss how they're going to stop everyone else using fossil fuels. It would be funny, if it wasn't so serious.

"... and the claim is, paying workers kills jobs."

It is a general principle of economics - with very few exceptions - that if you raise the price of some good or service, fewer people buy it; and if you lower the price of goods/services, more people buy it. A job is just a contract to sell your labour to others, and wages are just the price you charge for the sale. So what happens to the amount of labour you can sell if you raise the price?

A business can only make a certain amount of money selling the product of its employees' labour. It will try to maximise the amount it makes, so once it reaches that maximum there's no more to be had. If an hour of your labour only makes the business $5, after paying all the other bills and expenses, then it simply cannot pay you more than $5/hour. There's nowhere for the additional money to come from. So if the government comes along and insists that they have to be paid $10/hour, then either they'll have to raise their own prices, losing trade, or cut working conditions to bring the cost of employment down enough to be able to afford it, or they'll have to stop providing that service, and fire the low-paid employees.

Neither the employers nor the employees want that, which is why over in my country they've been finding ways to jointly circumvent the minimum wage laws. One that's been causing controversy is the 'zero-hours contract', which means you get paid the $10/hour when work is available, but when it's not you get nothing. Intermittent and unpredictable work can therefore legally pay less than the minimum wage, and so keep a lot of needy people employed.

The same people who brought in the minimum wage laws in the first place now denounce this scheme as evil and want to ban it.

The trouble is, nobody actually has to sign up to a zero-hours contract. They only do so because the alternatives are all even worse. So if you ban it, they'll all be forced back into those worse alternatives.

The people trying to ban stuff never seem to realise that the right way to deal with abusive businesses is to use competition. Simply set up your own business in competition with the original, offering decent pay and conditions (if you can). All the low-paid staff at these places can jump ship and come and work for you, and the low pay problem is solved! If they want any workers, the other businesses will have to raise their own pay and conditions to match.

I think the possibility genuinely never occurs to them - it's not the way they've been brought up to think. But even if it did, they would likely soon discover that the reason they can't do it is that the other businesses are already paying people as much as their work is worth. (Because businesses already compete.) If you tried to employ them on higher pay, you couldn't make enough money from their work to pay them.

At the end of the day, businesses have no more control over what people get paid than the employees do. It's determined by the market. People with rare skills that are in higher demand than there are people able to supply them can charge higher wages. Every single job that pays more than minimum wage is evidence of a shortage of workers; of unfulfilled employment opportunities. The high wages are designed to attract more workers into that area, who can give up their minimum wage job, and undercut the current incumbent in the high-paid job. Low paid workers get paid more. High paid workers get paid less, and businesses find labour cheaper, and therefore buy more of it. The money saved by reducing the wages of the higher paid pays the wages of more employees as the business expands, which it does because costs are lower and so the business can sell its goods cheaper, increasing sales.

The problem is that there are other barriers stopping the low-paid gaining the skills and experience needed to be able to do the high-paid jobs. It's frustrating! The poor want higher-paid jobs, and the businesses want more of them to be able to get them, because they're currently being forced to pay over the odds because of the rarity. But there are barriers that prevent it - poor education, working culture, regulation, bureaucracy, inefficiency, protectionism, and the ever-rising complexity of modern technology. It is these barriers that need to be torn down.

Both liberals and conservatives want the poor to get better paid jobs, but the conservatives want to do it by giving them the skills to earn it, and the liberals want to do it by forcing businesses to pay them more than they can earn. It is only the latter that kills jobs.

August 19, 2016 | Unregistered CommenterNiV

Incidentally, the answer to the question:

"if climate change increases temperatures in winter to the normal for summer, would the hours of daylight be longer?"

... is the same as the answer to the question:

"If you simulated the impact of the greenhouse effect on crop growth by growing crops in a greenhouse - with higher temperatures, higher 'rainfall', and higher levels of artificially generated CO2 in the atmosphere - would it kill all the crops as the climate scientists claim?"
:-)

August 19, 2016 | Unregistered CommenterNiV

==> ....but the conservatives want to do it by giving them the skills to earn it, and the liberals want to do it by forcing businesses to pay them more than they can earn. It is only the latter that kills jobs. ==>

There is a long history of liberals advocating for job training programs and employment-related educational programs, sometimes against widespread resistance from conservatives.

It can be hard to make accurate observations, categorical descriptions, and "explanations" of complicated social phenomena if you are susceptible to grossly inaccurate caricatures.

And your description of "pat them more than what they <I>can earn" conflates subjective with factual. Consider executives who earn hundreds of times the base salaries of typical employees even as companies decline as the result of the poor executive deviations they've made.

August 20, 2016 | Unregistered CommenterJoshua

==> At the end of the day, businesses have no more control over what people get paid than the employees do. It's determined by the market. ==>

Wow.

August 20, 2016 | Unregistered CommenterJoshua

"There is a long history of liberals advocating for job training programs and employment-related educational programs, sometimes against widespread resistance from conservatives."

I don't know. That may be an American thing. Over here, I've not seen any of that.

I do sometimes see complaints here about expensive training schemes that don't actually work - either teaching the wrong skills, or the teaching proving ineffective. Some of them have been no more than thinly disguised welfare: with no prospect of anyone being able to get jobs out of it, but being forced to attend to keep getting their benefits. But I don't understand how resistance to the principle of the policy of training the low-paid and unemployed would fit into a conservative philosophy. Perhaps you can enlighten me. How do these conservatives justify their opposition?

"It can be hard to make accurate observations, categorical descriptions, and "explanations" of complicated social phenomena if you are susceptible to grossly inaccurate caricatures."

Mmm. Yes? And the reason conservatives "want to pollute" is...?

"Consider executives who earn hundreds of times the base salaries of typical employees even as companies decline as the result of the poor executive deviations they've made."

Why do star footballers earn massive salaries even as the clubs they belong to drop down the league?

Because they can still do the job massively better than most people could. Even a mediocre player from a team at the bottom of a professional league could still play any amateur side off the field. Top players have skills in massively greater demand than there is a supply, but they're up against equally skilled opposition. Sometimes they make mistakes. Sometimes external circumstances conspire against them. Sometimes they lose. They just do so less often than you would.

If football teams could sign star players on tiny salaries, and keep them, they would. More profit for them.
Businesses likewise.

"Wow."

I do like the succinct way you express your disbelief with such a complete lack of any counter-argument!
:-)

I presume there's a reason for that lack?

August 20, 2016 | Unregistered CommenterNiV

NiV -

We could go back and forth about the effectiveness of and return from various job training programs, but the fact would remain that your generalization would be grossly inaccurate.

I was trained as a carpenter in a jobs program that to a great degree only existed because of a large-scale initiative that was created by liberals with overriding opposition from conservatives. It was a program that largely relied on federal funding (CETA) and run by trade unions whereby minorities (I was an exception as an enrolee) were given trade-related education and skills training to enable well-paying employment. Economically needy homeowners got their homes worked on at a discount while the trainees acquired marketable skills.

It was a program that worked very well. It didn't remotely reassemble your caricature of "disguised welfare" in the least. I wouldn't assume anything (without a thorough look st the research) about federal job-training on the whole, but no doubt it was the only one that worked and would have been one of the programs that were attacked by conservatives as "big government" and government interference in the market. Indeed, perhaps the most iconic liberal government initiative ever, the WPA, and the predominating ideological split between conservatives and liberals over that program shows how facile and bias-confirming your caricature was.

As for your idealized "explanation" of market and wage economics. Yes, sometimes I am surprised that summertime so skilled in sophisticated analysis will reduce complex issues to such simplistic caricatures in service to ideology.

Consider the following:

http://money.cnn.com/2015/04/14/news/companies/ceo-pay-cuts-pay-increases/

Or
http://www.forbes.com/sites/timworstall/2014/09/01/we-cant-reduce-inequality-by-forcing-walmart-to-pay-like-costco/#6e0285647224


Just the first examples, from simple Google searches of where it wasn't "the market" that determined wages, but a mix of "the market" and corporate/executive/business decision-making and priorities - as is certainly almost always the case. Executives always have the option to adjust salary structure so as to realize any particular configuration of priorities - even if we go with the simplistic banality of the argument that their only goal is return to maximize return to shareholders.

August 20, 2016 | Unregistered CommenterJoshua

'Are you arguing that "correlation implies causation"? And that "absence of evidence is evidence of absence"?'

Dude, you're flailing.

August 20, 2016 | Unregistered CommenterL Hamilton

"attacked by conservatives as "big government" and government interference in the market"

Was it? OK, then I disagree with them and think they were wrong. I've not previously seen that, myself.

"Consider the following:"

The first looked more like a PR stunt. Advertising enough to shift the needle on public approval of a company costs a lot of money - a lot more than a million a year. It's a clever idea.

But the justification he offers is based on market arguments. He's buying better (happier) workers by paying more.

The second seems to be saying that if you offer a different service, you have to charge a different price. That doesn't contradict the market having control.

"Just the first examples, from simple Google searches of where it wasn't "the market" that determined wages, but a mix of "the market" and corporate/executive/business decision-making and priorities - as is certainly almost always the case."

They're the same thing.

The market is a combination of executive decision-making - how much do we have to pay to get the quality of workers we want/need? - and worker decision-making - how hard am I willing to work to get the pay I want/need? The supply curve rises with price, because the higher the wage the more workers are willing/able to work for it. The demand curve drops as price rises, because the higher the wage the fewer employers there are willing/able to pay it. The two lines cross at a certain point, called the market equilibrium, where the number of workers willing to work for the pay equals the number of employers willing to pay for the work.

If the price is set anywhere else, then either a glut or shortage results, and one side or the other can individually make more money by shifting their own personal price towards the equilibrium. To the extent that most people like making more money, that's what happens.

The market equilibrium is, of course, partly a result of executives deciding how to structure the business. It's their task to find the arrangement that maximises returns, subject to the constraints imposed by the rest of the world. That's what the demand curve is measuring. But it's just as much determined by the availability of workers and their decision-making, as measured by the supply curve. If a company offers too little, they'll not be able to recruit anyone (shortage). If they offer too much, they'll be inundated with applications from other workers willing to undercut the one's they've got (glut), as well as having higher costs than the competition, making it more difficult to compete.

It's the same as when a worker either demands too much (nobody will employ them) or too little (they'll be able to profit by moving). Either way, they benefit by moving their price towards the market equilibrium. They can influence things by their decisions about what skills to acquire and offer, in the same sort of way as company executives do, but ultimately they have no more (or less) influence over collective prices than the executives.

---

"We note that decadal to century-scale change in New Hampshire winters resemble the pattern of global warming, so attribution of a common cause seems straightforward"

That's "correlation implies causation".

"it is not contested in any recent study of this region’s climate that I know of"

That's absence of evidence being used to imply evidence of absence.

Who's flailing?

August 21, 2016 | Unregistered CommenterNiV

NiV -

==> . The two lines cross at **a** certain point, ==>

I remember a favorite cartoon I saw a while back: two economists speaking in front of a blackboard covered with neatly written equations. One says to the other..."These would predict the economy perfectly if we could just remove the humans."

Your "explanation" of wage economics is so 20th century. As you must know, nowadays, economists work much harder to account for the non-mathematically derived quirks of human behavior, information asymmetry, market failure, moral hazards, etc. when they explore why utility maximization returns all variety of equilibria in the real world.

==> , partly a result of executives deciding how to structure the business. ==>

Yes, that was my point.

For example, when Donald Trump decides to have his casino company, that is losing money hand-over-fist, pay another company THAT HE OWNS for the use of equipment (without putting it out for competitive bids), or for the use of his name (at the price he personally sets as appropriate) it can directly affect the decision-making of other executives in his company about the wages that to pay employees. Another executive may choose to make difference decisions that impact expenditures and wages because he or she is more interested in long-term sustainability than making a quick buck, who is more concerned about the welfare of the welfare of the employees, or feels that a business has a responsibility to the larger community. Or another executive may simply decide to sacrifice some measure of profitability in order to manufacture hats in the United States rather than having them manufactured in China and then imported for sales here. So I guess you might call that the market making the decisions but I would call it people making decisions based on individual interpretation of some mixture of market economics and personal priorities.

Obviously, the same sort of critique would apply to your idealized and theoretical explanation of executive salary. In the real world the determination of what you might call an equilibrium includes the influence of the greed of executives who are looking to raise share values so they can cash it out quickly regardless of the impact on employees or the long-term viability of the business. And of course, board members who are looking for short-term returns are more than willing to compensate handsomely, executives who find that particular point of "equilibrium" which most aligns with such a goal.

August 21, 2016 | Unregistered CommenterJoshua

"I remember a favorite cartoon I saw a while back: two economists speaking in front of a blackboard covered with neatly written equations. One says to the other..."These would predict the economy perfectly if we could just remove the humans.""


two climate scientists speaking in front of a blackboard covered with neatly written equations. One says to the other..."These would predict the weather perfectly if only we could just remove the atmosphere."
:-)

The law of supply and demand has been the "consensus" in mainstream economics for more than a century. But you feel quite undisturbed to be sceptical of it. How about that, eh? :-)

"Another executive may choose to make difference decisions that impact expenditures and wages because he or she is more interested in long-term sustainability than making a quick buck, who is more concerned about the welfare of the welfare of the employees, or feels that a business has a responsibility to the larger community."

There are two issues there.

One is the question of whether economics measures the value of things besides money/cash. It does. The more general concept is called 'utility', and if somebody is given a warm-and-fuzzy feeling from giving their own money to charity, that feeling counts as part of their payment.

The other question to ask is whose money is it? If the executive making the decision owns the company, that's fine. If the articles of association of the company declare charity to the community to be one of the company's purposes, and the owners are fine with that, then that's also perfectly OK. If it's good PR, that works too.

But it becomes a bit dodgy when you start giving yourself that warm-and-fuzzy by stealing somebody else's money and giving it away to people you like. I'm all in favour of voluntary charity, but there's no virtue in doing it with somebody else's money. That's plain theft.

"In the real world the determination of what you might call an equilibrium includes the influence of the greed of executives who are looking to raise share values so they can cash it out quickly regardless of the impact on employees or the long-term viability of the business."

The share value is the market's best estimate of the time-discounted long-term return from the business. Anything that impacts long-term viability impacts share value. If you're going to cash out quickly, you have to convert capital assets to cash, instead. (And that's deliberately made pretty difficult, given that the executives normally own lots of shares themselves, and don't have direct access to the company's cash. Owners are not stupid.)

Unless you're talking about executives who mislead the shareholders about long-term value for their own profit? Yes, that can happen. As can staff pilfering from the petty cash, or customers shoplifting. But that's generally counted as one of the costs of doing business. If it makes a significant difference, you're doing something wrong.

The other thing to note is that the long-term viability of a business is not the only consideration. If the short-term return from shutting the business down is higher than the (discounted) long-term value, then the right thing to do is to shut the business down, and reallocate the resources to something more productive. Businesses normally continue operating because they're generally a lot more valuable as a long-term going concern than they are as a pile of assets to be sold off.

August 21, 2016 | Unregistered CommenterNiV

NiV -

==> The law of supply and demand has been the "consensus" in mainstream economics for more than a century. But you feel quite undisturbed to be sceptical of it. ==>

Skeptical of the law of supply and demand? As an abstract model, not at all. As a universal and blanket explanation for all economic interactions between all actors, however, I think its usefulness is limited to some degree. I'm not one for fetishizing the "free market" due to ideological orientation.

Over the course of my life, I have found that "law" to be less than 100% explanatory for how wages are set. Greed, generosity, irrationality, fraud, habit, short-term thinking, complacency, entitlement, nepotism, favoritism, discrimination, exploitation, etc., may all come into play to varying degrees, in various circumstances, in my experience. I guess you've been fortunate to live in a more perfect and less variable world than I, apparently one where human behavior follows theoretical models completely.

==> The share value is the market's best estimate of the time-discounted long-term return from the business. ==>

There are often times where good arguments can be made as to why the share value is not commensurate with the best estimate of the time-discounted long-term return from the businesses. You know what they say, prediction is hard, especially about the future. The perception of such discrepancies is why the stock market exists and thrives. Over the long term, it wouldn't argue that there is a pattern of mismatch, but in the short term, there most certainly is in many cases, in both directions (I suggest watching The Big Short for an entertaining depiction). And the financial engineering industry is devoted to creating and leveraging those mismatches. There is little doubt, IMO, that there are many executives who are more than happy to focus on the short-term gains that can be made to share value, whether or not it comes at the expense of long-term value. I think that there are many, many, many examples of such. There is much discussion of that phenomenon among market researchers. For example, just look at the vast analysis of the effect of stock options for execs on their decision-making processes. Or have a look at something like this:

--snip--
We find evidence that industry and size adjusted CEO pay is negatively related to future shareholder wealth changes for periods up to five years after sorting on pay. For example, firms that pay their CEOs in the top ten percent of pay earn negative abnormal returns over the next five years of approximately -13%. The effect is stronger for CEOs who receive higher incentive pay relative to their peers. Our results are consistent with high-pay induced CEO overconfidence and investor overreaction towards firms with high paid CEOs.
--snip--

http://online.wsj.com/public/resources/documents/CEOperformance122509.pdf

So what we have there is an interesting scenario in that it suggests that as the compensation gets further out of the mainstream, there is long-term economic pressure to reign in the excessiveness. But on the other hand, it also strongly suggests that within the bounds of that larger pattern, there is a lot of "violation" of the laws you like to consider explanatory.

If you're so much enamored with the "market" process so as to think those "violations" don't happen (often), and that the only thing that determines share value are "laws" such as that of demand/supply, I suppose there isn't much that I can do to change your mind.

But for myself, something like this seems like a more likely picture of reality:

--snip--
This paper surveys the recent literature on CEO compensation.  The rapid rise in CEO pay over the last 30 years has sparked an intense debate about the nature of the pay‐setting process.  Many view the high level of CEO compensation as the result of powerful managers setting their own pay.   Others interpret high pay as the result of optimal contracting in a competitive market for managerial talent.  We describe and discuss the empirical evidence on the evolution of CEO pay and on the relationship between pay and firm performance since the 1930s.  Our review suggests that both managerial power and competitive market forces are important determinants of CEO pay, but that neither approach is fully consistent with the available evidence.  We briefly discuss promising directions for future research.
--snip--

http://web.mit.edu/frydman/www/COMP%20SURVEY%2008-02-10.pdf

August 22, 2016 | Unregistered CommenterJoshua

NiV:
'That's "correlation implies causation".
That's absence of evidence being used to imply evidence of absence.
Who's flailing?'"

I've actually read those studies. If you had too, you'd know they don't rest on correlation, and do present evidence. Instead you choose to fling memes, as if to illustrate for this thread the concepts of "motivated disbelief" (Campbell & Kay 2014) and "hyperskepticism" (Kraft 2015).

Rewinding to some earlier remarks about time series:

There's no first differencing in ARIMA(3,1,0).
Yes, there is. The d in ARIMA(p,d,q) refers to the order of differencing.

When we're studying the detection/attribution task, the question is whether there *is* a trend.
Yes, so I routinely test for that.

If you simply assume there is one, you will of course 'find' one but then you're begging the question.
Assuming there's a trend without testing is opposite to what I do. What's your trick to find one by assumption?

If you throw a sufficient number of basis functions into the mix, you can curve-fit anything. "With four parameters I can fit an elephant, and with five I can make him wiggle his trunk."
It's a cute meme but less relevant here, as the ARMAX model I described is not curve-fitting. 7 parameters include well-established physical effects on surface temperatures from ENSO, solar irradiance, aerosols & CO2. Climate is complicated, with a lot more variables and relationships than these. Even so the simple model yields a visually striking fit, p<.00005, to a ragged time series with 371 data points. Results from this ARMAX analysis, which anyone can replicate, agree with somewhat-to-much more sophisticated work by many other teams -- yet another sign the broad conclusions in this literature are robust.

a trivial 'epicycle-type' model
There are no cycles, epi or otherwise, in this model.

We could go on, I guess. Meanwhile the original post seems to have stood up pretty well.

August 22, 2016 | Unregistered CommenterL Hamilton

"I've actually read those studies. If you had too, you'd know they don't rest on correlation, and do present evidence."

I was referring to your statements, not the studies. Your stated argument was: "We note that decadal to century-scale change in New Hampshire winters resemble the pattern of global warming, so attribution of a common cause seems straightforward". That's a use of "correlation implies causation". If you've got a better argument, feel free to describe/explain it.

I had assumed when you said "But we weren’t trying to do that" that the references were just general background on attempts at attribution applied to local weather events (thanks, but I'm already well aware of it) and not part of your argument regarding New Hampshire. You hadn't claimed they supported your New Hampshire attribution specifically. I therefore wasn't commenting on or criticising those studies.

For what it's worth, neither study overcomes the issues I've already mentioned. The first study is paywalled, but the abstract indicates that they're not even attempting to carry out local weather attribution, but instead arguing that local weather is affected by continental/global changes, and referring elsewhere for attribution of those global changes to AGW. That's a shaky chain of reasoning, based partially on a causal version of confirming the consequent. (A causes B and B causes C, therefore - so they say - A caused C. If low air pressure causes rain and rain causes wet pavements, then low pressure caused the wet pavement. The man I can see washing his car with a hosepipe had nothing at all to do with it.)

The second study explains that attribution is mostly done by using climate models to model the distribution of local weather events with/without AGW, and arguing that their higher probability under the AGW hypothesis counts as evidence: giving an over-unity likelihood ratio. That would indeed be a valid line of reasoning if the models had been validated to correctly predict the distributions of weather events sufficiently reliably - which of course they haven't. There are a lot of weather variable distributions they are known to predict wrongly, and to just pick the particular variables they happen to get more-or-less right is to commit the Texas Sharpshooter fallacy. There is also a discussion of an 'empirical' method, but this appears to simply measure an increase in the number of extreme events and then use "confirming the consequent" to argue attribution. That *is* somewhat similar to the method you use, but I'd argue has the same flaw, and gives no reasoning to explain why it isn't a mistake.

"Yes, there is. The d in ARIMA(p,d,q) refers to the order of differencing."

No, there isn't. It's the order of integration (the 'I' in 'ARIMA'). The definition basically defines an integral by specifying how many times you have to differentiate it to get a stationary series. But the model itself is integrated, not differentiated.

Consider a simple physical model of the climate. We suppose that the temperature is proportional to the total heat content of the Earth, that the total heat content this year is equal to the total heat content last year plus the net heat absorbed/radiated, and that the net heat absorbed/radiated is proportional to total cloud cover, which is a random variable with a constant Gaussian distribution centred on zero. The cloud cover, and hence heat input/output is like a sequence of coin tosses. The total heat content, and hence temperature, is a random walk - at least approximately, over short time intervals.

(Obviously the cloudiness distribution has to shift away from zero eventually in order to keep temperature within finite bounds. What this model is saying is that any such feedback effect is too small to detect on these timescales, and so can legitimately be neglected in making an approximation; not that it doesn't exist. That it can be considered negligible is demonstrated in practice using a unit-root test, like Augmented Dickey-Fuller.)

We have not "differenced" anything to get the temperature. We've actually integrated (or summed) something else to obtain it. Because integrated series have some rather awkward mathematical properties (like infinite mean and undefined variance), it is often convenient to transform it into a more tractable sort of variable by differencing - i.e. to study cloudiness instead of temperature - but that's a completely different physical quantity, with a different distribution model. Cloudiness is stationary and obtained by differencing. Temperature - the ARIMA(p,d,q) model with non-zero d - is not.

And nor does it hide trends. A non-zero trend in temperature corresponds to a non-zero mean of net heat transfer due to cloudiness etc. The only thing the differencing of total heat content "hides" is the absolute level of the heat content (for example, it ignores the heat content of the Earth's molten core). But that's irrelevant to the physics of climate change, and unknown anyway.

So it is totally incorrect to say: "First differencing (as in ARIMA(3,1,0)) removes a trend, and has sometimes been used to hide the incline in global temperatures." There's no first-differencing in ARIMA(3,1,0), it doesn't hide a trend, and it can't be used to hide an incline in global temperatures. What it does is not to hide it, but offer an alternative explanation for it.

As my simplified accumulation-of-heat model demonstrates, integrated models can represent a perfectly legitimate and plausible physical mechanism, and are a perfectly valid type of behaviour in themselves. To reject them simply because you don't like the alternative conclusions they make possible is invalid reasoning.

"Yes, so I routinely test for that."

Against what null hypothesis?

"It's a cute meme but less relevant here, as the ARMAX model I described is not curve-fitting. 7 parameters include well-established physical effects on surface temperatures from ENSO, solar irradiance, aerosols & CO2."

In what way is that not curve-fitting? It looks like a classic curve-fitting approach to me.

"Even so the simple model yields a visually striking fit, p<.00005,"

p-values? Under what distribution assumption?

(A lot of people use statistical software as a substitute for understanding, and rely on the p-value the software outputs, which is commonly based on assuming Gaussian IID. That's wrong.)

And you need to ask Dan here about p-values. He's done quite a number of posts on the subject! :-)

"7 parameters include well-established physical effects on surface temperatures from ENSO, solar irradiance, aerosols & CO2."

Aerosols are not currently measurable (globally) to sufficient accuracy to do that. It's regarded as being more accurate to back-calculate it from the climate models. They determine what aerosol profile causes the model to follow the observed temperature history, and use that as your aerosol estimate. It's arguably a legitimate way to measure aerosols (apart from the models being unvalidated, that is) since you are in effect simply using temperature observations as a proxy measurement for it. But it does mean you can't then use the fit to temperature so obtained as evidence of the accuracy of your model.

The same goes for clouds, and their effect on surface solar irradiance / albedo.

"There are no cycles, epi or otherwise, in this model."

Sorry - that was an allusion to the Ptolemaic model of the solar system which is commonly used to explain why curve-fitting is invalid reasoning. I assumed you would be familiar with the educational meme - but evidently it's not taught everywhere. Ptolemy modeled the solar system as a set of wheels attached to wheels (called epicycles) to explain the detailed motion of the planets. The problem is that it is effectively fitting a sum of sine waves to an observed function, which is always possible to do to arbitrary accuracy just by adding enough extra sinusoids. The quality of the fit doesn't prove anything, because a good fit is an unavoidable consequence of the method. If it hadn't fitted, you would just add more epicycles until it did.

Climate sceptics used to have a line in fitting linear models very like this to temperature using sets of variables that *didn't* include anthropogenic influences. Their favourites were to use various combinations of AMO and PDO - natural multi-decadal cycles in global-scale temperature that have been going on for centuries at least, and probably millennia. The fits they got were equally visually striking. The reasoning is equally invalid.

August 22, 2016 | Unregistered CommenterNiV

NiV ,

Here you go. Quite apropos and timely, I thoughtk

http://www.cnn.com/2016/08/22/politics/donald-trump-activist-investor/index.html

So,

Greenmailong = law of supply and demand?

Maybe so

"Corporate ransoming" = law of supply and demand?

Maybe so.

Driving up share value beyond a reasonable time-discounted long-term best estimate, for the purpose of cashing in on short term gain at the expense of long-term viability?

You betcha.

Does that, also, conform to the jaw of supply and demand?

Maybe so. Funny, though, that they made that manifestation of the law of supply and demand illegal.

Oh well, I guess that should just be chalked up to government overreach, mucking up the market, and authoritarian limitation of freedoms.

August 22, 2016 | Unregistered CommenterJoshua

NiV:
I assumed you would be familiar with the educational meme - but evidently it's not taught everywhere.
Ooooh, snark. I recognized your analogy, and also why it doesn’t work here.

p-values? Under what distribution assumption?
(A lot of people use statistical software as a substitute for understanding, and rely on the p-value the software outputs, which is commonly based on assuming Gaussian IID. That's wrong.)

More snark, and off target yet again. The residuals in this case actually do pass tests for Gaussian white noise. I check that routinely, and also try other methods without those assumptions. In the ARMAX example we get p<.00005 whether using a robust variance-covariance matrix (Huber-White sandwich) or outer product of the gradient vectors. Either way this ARMAX model yields white-noise residuals according to portmanteau Q tests over 1 to 30-month lags, and a reasonably Gaussian distribution according to skewness-kurtosis tests. Stepping away from time series methods, we can get similar p values without Gaussian and/or iid errors assumptions using robust (biweight) regression, or with either quantile regression or OLS using robust, bootstrap or jackknife standard errors. Each method has limitations but together they illustrate how hard you’d have to work to make the CO2 result go away. (First differencing, though, that’s the trick!)

All these methods broadly agree because, as I said, the basic fit is very good. In a stripped-down OLS model, ENSO and CO2 alone (1-month lags) explain two-thirds of the variance in monthly global temperature since 1980 (that’s 3 parameters fitting 438 data points). Adding solar irradiance and aerosol optical depth makes physical sense, and their effects are significant, but weak. Physical relevance, rather than statistical fit, is the best argument for including the latter two parameters.

If you include AMO and PDO as additional predictors, then (1) model fit does not improve much further; (2) PDO effect is not different from zero; and (3) AMO effect appears non-zero but it’s physically circular, you’re now using temperature to explain temperature. Take CO2 out of the equation, and the overall fit drops despite now having 8 other terms.

August 23, 2016 | Unregistered CommenterL Hamilton

"Greenmailing = law of supply and demand?"

So far as I can see, yes.

A takeover is only worth doing if the shares are undervalued. If the price being offered is fair or more than fair (as judged by the current owners), which it has to be for a takeover to work, the current owners would just sell. The only reason they wouldn't be happy with that is if the price on the ticket was actually lower than the true value.

When an offer is made to buy an asset, and the board don't want to lose control, they can effectively raise their price to outbid the putative buyer. To do so, all they have to do is pay the difference in value (as judged by the buyer).

For example, suppose most people in the market value the company at $10m (it's listed price), the bidder values it at $13m, and the company board value it at $15m. (That people value an entity differently is the whole basis of trade - it's how both participants can gain from trading.) The bidder indicates an intention to buy it at $12m. That's $1m profit. The board don't want to sell a $15m asset for $12m (that'd be a $3m loss from their point of view), so they raise their price and outbid. The bidder will go away in exchange for anything more than $1m.

One reason why the parties might value the asset differently from the market is that they're being unusually inefficient. For example, they may be using $13m of capital assets to operate a business in a way so that returns are only worth $10m to the shareholders, but benefits them personally as employees or business beneficiaries to the tune of $15m (or the beneficial equivalent thereof). For example, the company might pay salaries above the market rate, and the takeover bidder plans to raise the company's value by reducing them, and using the money thereby saved to employ more people and expand the business.

If there's only one bidder able/willing to make the attempt, it's possible to buy back their initial share to effectively outbid their price. If there are lots of bidders, they can't buy them all off, their only choice is to change the way they do business to raise its stock market value above the bid, or be taken over and have the change imposed upon them.

It's the market's way of eliminating inefficiency, and ensuring resources are allocated to their most profitable use.

"Does that, also, conform to the jaw of supply and demand?"

Yes.

The attempt to buy the company certainly does - demand exceeds supply, so the price rises. The attempt to buy the bidder off by buying back the shares could be argued to be an attempt to buck the market - keeping the price artificially low. But really all it means is that the shares representing control of the company have a higher value to the board than other people which is simply a part of the demand for those shares, so that can be regarded as a manifestation of supply and demand as well. The higher price they pay for the shares simply reflects their own higher demand for the control they represent.

"Maybe so. Funny, though, that they made that manifestation of the law of supply and demand illegal."

That's what protectionism is all about.

"Oh well, I guess that should just be chalked up to government overreach, mucking up the market, and authoritarian limitation of freedoms."

Something like that, yes.
:-)

August 23, 2016 | Unregistered CommenterNiV

Oy,, more economistsplaining.

==> A takeover is only worth doing if the shares are undervalued.==>

Remarkable!

Did you read the article that explains what greenmailing is? It wasn't that the shares were undervalued.

It was that Trump was able to use his money to leverage the share price so as to extort the company so as to overpay, beyond a reasonable long-term discounted evaluation of the long-term value as determined by the market. He forced their hand to overpay.

Of course, the company had the option to not overpay or to call Trump's bluff and let him take over - with the problem being the loss of many jobs and shareholder value. In the end, many of those companies endured that fate anyway, of course.

NiV - really, all this "splaining" gets tedious. If you don't want to engage at a meaningful level of exchange, just say so.

==> It's the market's way of eliminating inefficiency, and ensuring resources are allocated to their most profitable use. ==>

Again, quite remarkable. So basically any form of greed, generosity, irrationality, fraud, habit, short-term thinking, complacency, entitlement, nepotism, favoritism, discrimination, exploitation, etc., even slavery, get "splained" away as a "market efficiency. " Hey, I guess that works for you. Me, not so much. They all exist on their own as factors in play, and using a euphemism to describe those influences is just useless, IMO. In reality, it explains nothing. It adds no insight, and merely satisfies a fetish. And in the end, it disables any real discussion of where, on top of moral and ethical considerations, those influences actually increase inefficiency. A blanket assumption that any other factors can simply be explained as a process of efficiency nets zero insight.

==> Something like that, yes. ==>

Yeah, I figured. How else can the tautology and self-sealing circular reasoning return the desired result?

August 23, 2016 | Unregistered CommenterJoshua

BTW -

It's interesting that in the UK, there are restrictions placed against anti-takeover defenses, so as to protect shareholders (theoretically) by preventing defensive maneuvers made without shareholder input, or transfer of shares to a favored bidder.

August 23, 2016 | Unregistered CommenterJoshua

NiV -

Since you're a Mill fan...

Came across this Mill quote while watching Jonathan Haidt talking about polarization (and the authoritarianism among Trump supporters) - which I thought summed up pretty well the difference between my perspective and yours about the law of supply and demand (see the MIT abstract I posted above).

In almost every one of the leading controversies. . . both sides were in the right in what they affirmed, though in the wrong in what they denied; and that if either could have been made to take the others’ views in addition to its own, little more would have been needed to make its doctrine correct..</>

August 24, 2016 | Unregistered CommenterJoshua

"In a stripped-down OLS model, ENSO and CO2 alone (1-month lags) explain two-thirds of the variance in monthly global temperature since 1980 (that’s 3 parameters fitting 438 data points)."

In a stripped down OLS model, smoothed AMO and PDO alone explain 85% of the variance in USHCN between 1905 and 2007. (Figure 18 here.) That's two parameters fitting 102 data points.

This one does AMO, PDO, and trend, and finds that the best fit trend component varies between 0.5 and 1.3 C/century, while the AMO+PDO component constitutes between 42% and 86% of the rise - and almost everywhere over 50%. Correlations with the oscillatory component range from about 0.7 in the north west to about 0.95 in the south east, so variance explained ranges from 50% to 90%. That's 3 parameters fitting about 720 points.

So what? Curve-fitting is easy.

It's no good starting with CO2 and ENSO, and then seeing if AMO/PDO changes the fit significantly. You have to start with PDO+AMO, and then see if adding CO2 changes things drastically. You're not trying to prove that CO2 gives a good fit - you're trying to prove that it's impossible to get a good fit without CO2! That means trying every combination of every other conceivable causal variable and showing that they're all worse!

---

Joshua,

"Did you read the article that explains what greenmailing is? It wasn't that the shares were undervalued."

Ye, I read it. I do know what greenmailing is. And contrary to the beliefs of famously left-wing CNN journalists, it doesn't work as a strategy unless the shares are undervalued, because yes, they'd just let the bidder buy the company at an inflated price, wait for things to go wrong and the price to crash, then buy them all back at the lower price. Share value then goes back up again. The net result would be nothing but a massive transfer of $billions in cash from the greenmailer to the current company owners. = PROFIT!!!

"NiV - really, all this "splaining" gets tedious. If you don't want to engage at a meaningful level of exchange, just say so."

I *am* engaging at a meaningful level. You're just rejecting any explanation that doesn't fit your preconceptions.

Supply-and-demand is really just a statement of the obvious. People value assets differently, for all sorts of reasons. The ones who value it most highly try to buy it from the others for the cheapest price they can find. Both parties benefit by moving the price towards the point where the number of people wanting to buy equals the number wanting to sell.

All you've done is give an example of somebody wanting to buy something, and being offered something better instead. What you're really complaining about is the fact that when shares in a company are on general sale, *anyone* can buy them, even people whose plans you don't like.

You're free not to like it, but there's nothing going on here to contradict supply-and-demand.

"Again, quite remarkable. So basically any form of greed, generosity, irrationality, fraud, habit, short-term thinking, complacency, entitlement, nepotism, favoritism, discrimination, exploitation, etc., even slavery, get "splained" away as a "market efficiency. ""

Greed, generosity, nepotism, favouritism, and discrimination are just varieties of utility, and yes, are included in the standard economic treatment. Irrationality, fraud, and slavery are excluded, as they're not instances of voluntary and mutually beneficial trade.

"And in the end, it disables any real discussion of where, on top of moral and ethical considerations, those influences actually increase inefficiency."

"Moral and ethical considerations" are like a vegetarian discussing the economics of a butcher's shop. The price of beef is still determined by supply and demand.

A vegetarian could offer to pay a meat-eater not to buy beef. They're buying the meat-eater's temporary vegetarianism - it's a trade like any other. But it means that any meat-eater able to afford the price of beef can get paid by the vegetarian not to buy it, which could prove expensive for the vegetarian. You might not *like* it that meat-eaters get paid for their immoral preferences, or that they can make vegetarians pay up by threatening to buy beef. But both the meat-eater and the vegetarian profit from the trade. The meat-eater prefers the money to the beef. The vegetarian prefers saving the lives of cows to the money. Both are happy with the trade. And the price the vegetarians pay moves towards the level where the number of meat-eaters willing not to eat meat for that price equals the number of vegetarians willing to pay them that much not to.

So you see, moral and ethical considerations don't change anything. Trade can be immoral (according to some particular moral system) but still obey the law of supply-and-demand.

August 24, 2016 | Unregistered CommenterNiV

In a stripped down OLS model, smoothed AMO and PDO alone explain 85% of the variance in USHCN between 1905 and 2007. (Figure 18 here.) That's two parameters fitting 102 data points

You forgot to mention, "With 22 point smoothing." This has got comical.

August 24, 2016 | Unregistered CommenterL Hamilton

"You forgot to mention, "With 22 point smoothing." This has got comical."

What's that orange line in your first graph, above? :-)

Figure 6 in your paper, where you show the comparison between New Hampshire and the global line - what's that word in parentheses after each label in the key? Hmm?

Deary me.

August 24, 2016 | Unregistered CommenterNiV

What's that orange line in your first graph, above? :-)
Figure 6 in your paper, where you show the comparison between New Hampshire and the global line - what's that word in parentheses after each label in the key? Hmm?

Yep, the smooth curve labeled "smoothed" has been smoothed. The jagged line labeled "winter temp" is winter temperature. The ARMAX analysis I've been describing involves monthly global temperatures, not smoothed (and for good reason). All these comments railing against it and you never had a clue what it was? You could have just asked.

Deary me

Yep,a mess. How many words have you posted here so far?

August 24, 2016 | Unregistered CommenterL Hamilton

NiV -

==> And contrary to the beliefs of famously left-wing CNN journalists,

That does a pretty good job of illustrating what I think its tedious. First, I don't think that they're particularly left-wing. For the most part, they're mainstream. That would obviously be a point of disagreement between us, which you could easily anticipate, but you don't even acknowledge that disagreement, let along the subjectivity or your assessment, but simply just state your opinion as fact, and even more importantly, don't even see the irrelevancy of your feelings about their political orientation as to the substance of our discussion re: the article. Whether or not the reporters are "left-wing" is irrelevant as a matter of whether or not greenmailing is what took place or what greenmailing is and how that relates to the issue of economic "laws", and it's laughable that you (apparently) think that I couldn't formulate my understanding independently of the political orientation of the reporters. It's just tedious to have to engage with someone who engages at such a superficial, banal, and typical internet-banter level.


Instead, you assume the posture of "explaining" elementary concepts of economics while ignoring everything that I say about the conditions, nuances, and circumstances that contextualize the discussion.

For example:

I do know what greenmailing is. And contrary to the beliefs of famously left-wing CNN journalists, it doesn't work as a strategy unless the shares are undervalued, because yes, they'd just let the bidder buy the company at an inflated price, wait for things to go wrong and the price to crash, then buy them all back at the lower price. Share value then goes back up again. The net result would be nothing but a massive transfer of $billions in cash from the greenmailer to the current company owners. = PROFIT!!! </>

Where you say that you know what greenmailing is, but then conflate greenmailing with practices like a hostile takeover. They are different, and whether you agree that what Trump did in that circumstance was greenmailing as opposed to a hostile takeover or not, the fact that you conflate the two makes any further discussion pointless, IMO. Not only can I not learn anything, we can't even exchange in meaningful discussion of differing points of view.

And as here:

Greed, generosity, nepotism, favouritism, and discrimination are just varieties of utility, and yes, are included in the standard economic treatment. Irrationality, fraud, and slavery are excluded, as they're not instances of voluntary and mutually beneficial trade.

Skipping over the absurdity that there's no meaningful distinction between, say, discrimination and "other varieties of utility," you just simply distinguish slavery and fraud by arbitrary criteria (involuntary and mutually beneficial) without even realizing that to have a meaningful discussion, you'd need to at least offer an argument in justification.

Another example is how you fail to even present an argument if the face of the articles I offered, that present evidence in direct contrast to your "econosplaining' about the "laws" of economic interaction t's a shame, because we could have a meaningful discussion. But it seems that pretty much inevitably, we reach this point in these discussions - where it seems to me that you're basically just "mailing it in."

I can well-imagine that you have a diametric view of the interaction. So it goes. But FWIW, if it matters to you, when you engage at the level that you've engaged in in this exchange, it doesn't stimulate me to challenge my beliefs or to consider alternative perspectives. You've stated that you believe that you're engaging at a meaningful level, but perhaps if you give it some thought, there might be a way that further discussion might have a greater mutual benefit. It's pretty much a guarantee that when you start with your condescending "explanations," particularly on fairly rudimentary topics where it's a matter of disagreement not a lack of knowledge on my part, it's a lost cause. Much better, if you're interested in exchanging in a way that I feel would be beneficial, would be if, instead, you would simply explain your perspectives and treat them as such rather than a matter of fact.

August 25, 2016 | Unregistered CommenterJoshua

Larry,

"All these comments railing against it and you never had a clue what it was? You could have just asked."

I didn't need to ask. I just found it comical that you would criticise a paper on the grounds it used smoothing. :-)

---

Joshua,

"That does a pretty good job of illustrating what I think its tedious. First, I don't think that they're particularly left-wing. For the most part, they're mainstream."

All American TV journalism is left wing apart from Fox News. Even I know that.
http://www.journalism.org/2014/10/21/political-polarization-media-habits/pj_2014-10-21_media-polarization-11/
http://www.journalism.org/2014/10/21/political-polarization-media-habits/

"Whether or not the reporters are "left-wing" is irrelevant as a matter of whether or not greenmailing is what took place or what greenmailing is and how that relates to the issue of economic "laws""

Agreed. The point was to explain why you shouldn't have expected me to accept a CNN article as an authority on what greenmailing is.

"Instead, you assume the posture of "explaining" elementary concepts of economics while ignoring everything that I say about the conditions, nuances, and circumstances that contextualize the discussion."

I only keep explaining elementary concepts because you continue to claim not to believe them, or accept them. Frankly, I find it shocking in this day and age that I'd have to explain the law of supply and demand to anyone, or that it determines prices in a market.

"Where you say that you know what greenmailing is, but then conflate greenmailing with practices like a hostile takeover. They are different,"

I agree they're different. Greenmailing is declaring the intention to carry out a hostile takeover, but expressing a willingness to drop it if the company pays you more than you expect to gain from such a takeover instead. A hostile takeover is what happens when the bidder doesn't make such an offer, or it's not accepted. Greenmailing is therefore a conditional hostile takeover.

However, I don't accept that I was conflating the two.

"Skipping over the absurdity that there's no meaningful distinction between, say, discrimination and "other varieties of utility,""

There's a distinction in a moral sense, but not in an economic one.

All trade is voluntary, and there is no requirement for people's motives and preferences to be restricted merely to the material gain in the items traded. If a person hates Israel, or opposes the fossil fuel industry, they're free to discriminate against them when deciding whether to buy oranges or invest in their shares. The pleasure/displeasure they gain from having supported or boycotted a group they dislike is counted as part of their payment. You can buy non-Israeli oranges, but you pay a small premium for the privilege because the supply is more constrained - that premium being the cash equivalent of the utility contributed by the discrimination. Same applies if you don't like trading with black people, homosexuals, right-wingers, women, Jews, Catholics, vegetarians, or whatever. Or if you don't buy right-wing papers, watch Fox News, or eat cabbage just because you 'don't like cabbage'. Economics treats it all the same way. It's just a preference.

"you just simply distinguish slavery and fraud by arbitrary criteria (involuntary and mutually beneficial) without even realizing that to have a meaningful discussion, you'd need to at least offer an argument in justification."

Again, this stuff is elementary. The whole basis of supply and demand is that it describes what happens when *both* parties make choices whether to trade or not trade based on whether they benefit. Only when both benefit will both of them agree to trade. Only if trade is voluntary does it matter whether they choose to engage. That's obvious.

"particularly on fairly rudimentary topics where it's a matter of disagreement not a lack of knowledge on my part"

I have some difficulty with that. Did you *know* that the standard economic treatment of supply and demand is based on assumptions of voluntary mutual benefit and simply disagreed with economists that it follows? Did you *know* that greenmailing is a conditional hostile takeover? Because what you say gives me the incredibly strong impression that you didn't.

*I* think it's rudimentary, but given the number of people who disagree with it, I'm forced to accept that most people think it isn't. Most people don't enjoy mathematics lessons, either. So what do I do? Assume you know what I'm talking about, or try to explain? Because I've tried both, and you've complained either way.

August 25, 2016 | Unregistered CommenterNiV

I didn't need to ask. I just found it comical that you would criticise a paper on the grounds it used smoothing. :-)
Now that I see you never got it, all those non-sequiters fall into place. Including this one.

August 25, 2016 | Unregistered CommenterL Hamilton

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