Daniel Hannan on the selfishness of running a deficit and post-truth realities

In the latest Ici Londres production Dan Hannan looks at the morality of deficits.

Daniel Hannan starts by quoting Matthew 7:9-10

If the son shall ask bread of any of you that is a father, will you give him a stone? Or if he asks for a fish will you give him a serpent?

The passage goes onto to say the if you are evil, understand how to give good gifts to your children. By implication, to act for good, we must also understand how to act for the good, not just have the moral injunction.

Hannan goes onto say we do not run up large debts to bequeath to our children. Yet many impose a very different standard as voters, convincing themselves that they are being unselfish. By asking for more money from the State, whether to pay for care in old age or for a pay rise in the public sector, or remission of tuition fees, it might be a very good claim, but it is not an intrinsically unselfish claim, as they are asking for everybody else to chip in and pay for their cause. Conversely those who try to impose some fiscal discipline are deemed selfish. They are standing up for future generations. Austerity is not a random preference but a simple reality.

This is all pretty obvious stuff to anyone who understands basic morality and the slightest notion of finance. It is certainly within the understanding of anybody who has been brought up in a traditional British public school education. But I would suggest it is totally alien to the vast majority of the British public. This reason is described by a new word that entered the Oxford English Dictionary last month.


Relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief.

The General Election campaign is a clear illustration of the domination of post-truthers in public life. There is no understanding of public finances, just mass beliefs that are not based on any moral tradition. The spread of the beliefs is on social media, driven by those who most forcefully and repeatedly express their ideas. People are wrong because they disagree with the mass beliefs and shouted down (or trolled in the electronic version) because of it.

In a post last month – General Election 2017 is a victory for the Alpha Trolls over Serving One’s Country – I concluded

It is on the issue of policy to combat climate change that there is greatest cross-party consensus, and the greatest concentration of alpha trolls. It is also where there is the clearest illustration of policy that is objectively useless and harmful to the people of this country.

Like with public finances, climate change is an where post-truthers dominate. Two examples to illustrate.

Consensus messaging

There is no clear evidence of an emerging large human-caused problem with climate and there is no prospect of action to reduce greenhouse has emissions to near zero. Instead we have a dodgy survey that claimed 97% of academic papers on an internet search matching the topics ‘global climate change’ or ‘global warming’ expressed support (belief / assumptions) in the broadest, most banal, form of the global warming hypothesis. This was converted by Senator Bernie Sanders, in questioning Scott Pruitt, into the following:-

As you may know, some 97% of scientists who have written articles for peer-reviewed journals have concluded that climate change is real, it is caused by human activity, and it is already causing devastating problems in the US and around the world.


While you are not certain, the vast majority of scientists are telling us that if we do not get our act together and transform out energy system away from fossil fuel there is a real question as to the quality of the planet that we are going to be leaving our children and our grandchildren. 

The conversion from banal belief to these sweeping statements is not the fault of the Senator, though he (or his speech-writers) should have checked. Rather it is of lead author John Cook and his then PhD supervisor Cognitive Psychology Professor Stephan Lewandowsky. Post-truthers will not recognize the glaring difference between the dodgy survey and the Senator’s statements, as it is appeals to emotion and belief that are primary in evaluating political realities.

Mitigating Climate Change

Dangerous climate change is allegedly caused by human greenhouse emissions. The proposed solution is to reduce those emissions (mostly CO2 emissions from the burning of fossil fuels) to near zero. The key for policy is that emissions are global, yet most countries, covering over 80% of the global population have no primary obligation under the 1992 Rio Declaration to reduce their emissions. These developing “non-Annex” countries have accounted for all the in emissions since 1990, as shown in this graph.

The problem can be expressed in my First Law of Climate Mitigation

To reduce global greenhouse gas emissions, the aggregate reduction in countries that reduce their emissions must be greater than aggregate increase in emissions in all other countries.

All the ranting about supporting the Paris Agreement ignores this truism. As a result, countries like the UK who pursue climate mitigation will increase their energy costs and make life harder for the people, whilst not achieving the policy aims. It is the poorest in those policy countries who will bear the biggest burden and create comparative disadvantages compared to the non-policy countries. For the developing countries (shown in purple in the graph) to reduce their emissions would destroy their economic growth, thus preventing the slow climb out of extreme poverty still endured by the majority of people on this planet. In so doing we ignore the moral tradition from our Christian heritage that the primary moral concern of public policy should be the help the poor, the disadvantaged and the marginalized. Ignoring the truism and pursuing bequeaths a worse future for our children and our grandchildren. This is the same for climate change as for public finances. But in both cases it is the post-truth “reality” that prevent this recognition of basic logic and wider morality.

Kevin Marshall


How strong is the Consensus Evidence for human-caused global warming?

You cannot prove a vague theory wrong. If the guess that you make is poorly expressed and the method you have for computing the consequences is a little vague then ….. you see that the theory is good as it can’t be proved wrong. If the process of computing the consequences is indefinite, then with a little skill any experimental result can be made to look like an expected consequence.

Richard Feynman – 1964 Lecture on the Scientific Method

It’s self-evident that democratic societies should base their decisions on accurate information. On many issues, however, misinformation can become entrenched in parts of the community, particularly when vested interests are involved. Reducing the influence of misinformation is a difficult and complex challenge.

The Debunking Handbook 2011 – John Cook and Stephan Lewandowsky

My previous post looked at the attacks on David Rose for daring to suggest that the rapid fall in global land temperatures at the El Nino event were strong evidence that the record highs in global temperatures were not due to human greenhouse gas emissions. The technique used was to look at long-term linear trends. The main problems with this argument were
(a) according to AGW theory warming rates from CO2 alone should be accelerating and at a higher rate than the estimated linear warming rates from HADCRUT4.
(b) HADCRUT4 shows warming stopped from 2002 to 2014, yet in theory the warming from CO2 should have accelerated.

Now there are at least two ways to view my arguments. First is to look at Feynman’s approach. The climatologists and associated academics attacking journalist David Rose chose to do so from a perspective of a very blurred specification of AGW theory. That is human emissions will cause greenhouse gas levels to rise, which will cause global average temperatures to rise. Global average temperature clearly have risen from all long-term (>40 year) data sets, so theory is confirmed. On a rising trend, with large variations due to natural variability, then any new records will be primarily “human-caused”. But making the theory and data slightly less vague reveals an opposite conclusion. Around the turn of the century the annual percentage increase in CO2 emissions went from 0.4% to 0.5% a year (figure 1), which should have lead to an acceleration in the rate of warming. In reality warming stalled.

The reaction was to come up with a load of ad hoc excuses. Hockey Schtick blog reached 66 separate excuses for the “pause” by November 2014, from the peer-reviewed to a comment in the UK Parliament.  This could be because climate is highly complex, with many variables, the presence of each contributing can only be guessed at, let alone the magnitude of each factor and the interrelationships with all factors. So how do you tell which statements are valid information and which are misinformation? I agree with Cook and Lewandowsky that misinformation is pernicious, and difficult to get rid of once it becomes entrenched. So how does one evaluate distinguish between the good information and the bad, misleading or even pernicious?

The Lewandowsky / Cook answer is to follow the consensus of opinion. But what is the consensus of opinion? In climate one variation is to follow a small subset of academics in the area who answer in the affirmative to

1. When compared with pre-1800s levels, do you think that mean global temperatures have generally risen, fallen, or remained relatively constant?

2. Do you think human activity is a significant contributing factor in changing mean global temperatures?

Problem is that the first question is just reading a graph and the second could be is a belief statement will no precision. Anthropogenic global warming has been a hot topic for over 25 years now. Yet these two very vague empirically-based questions, forming the foundations of the subject, should be able to be formulated more precisely. On the second it is a case of having pretty clear and unambiguous estimates as to the percentage of warming, so far, that is human caused. On that the consensus of leading experts are unable to say whether it is 50% or 200% of the warming so far. (There are meant to be time lags and factors like aerosols that might suppress the warming). This from the 2013 UNIPCC AR5 WG1 SPM section D3:-

It is extremely likely that more than half of the observed increase in global average surface temperature from 1951 to 2010 was caused by the anthropogenic increase in greenhouse gas concentrations and other anthropogenic forcings together.

The IPCC, encapsulating the state-of-the-art knowledge, cannot provide firm evidence in the form of a percentage, or even a fairly broad range even with over 60 years of data to work on..  It is even worse than it appears. The extremely likely phrase is a Bayesian probability statement. Ron Clutz’s simple definition from earlier this year was:-

Here’s the most dumbed-down description: Initial belief plus new evidence = new and improved belief.

For the IPCC claim that their statement was extremely likely, at the fifth attempt, they should be able to show some sort of progress in updating their beliefs to new evidence. That would mean narrowing the estimate of the magnitude of impact of a doubling of CO2 on global average temperatures. As Clive Best documented in a cliscep comment in October, the IPCC reports, from 1990 to 2013 failed to change the estimate range of 1.5°C to 4.5°C. Looking up Climate Sensitivity in Wikipedia we get the origin of the range estimate.

A committee on anthropogenic global warming convened in 1979 by the National Academy of Sciences and chaired by Jule Charney estimated climate sensitivity to be 3 °C, plus or minus 1.5 °C. Only two sets of models were available; one, due to Syukuro Manabe, exhibited a climate sensitivity of 2 °C, the other, due to James E. Hansen, exhibited a climate sensitivity of 4 °C. “According to Manabe, Charney chose 0.5 °C as a not-unreasonable margin of error, subtracted it from Manabe’s number, and added it to Hansen’s. Thus was born the 1.5 °C-to-4.5 °C range of likely climate sensitivity that has appeared in every greenhouse assessment since…

It is revealing that quote is under the subheading Consensus Estimates. The climate community have collectively failed to update the original beliefs, based on a very rough estimate. The emphasis on referring to consensus beliefs about the world, rather than looking outward for evidence in the real world, I would suggest is the primary reason for this failure. Yet such community-based beliefs completely undermines the integrity of the Bayesian estimates, making its use in statements about climate clear misinformation in Cook and Lewandowsky’s use of the term. What is more, those in the climate community who look primarily to these consensus beliefs rather than the data of the real world will endeavour to dismiss the evidence, or make up ad hoc excuses, or smear those who try to disagree. A caricature of these perspectives with respect to global average temperature anomalies is available in the form of a flickering widget at John Cooks’ skepticalscience website. This purports to show the difference between “realist” consensus and “contrarian” non-consensus views. Figure 2 is a screenshot of the consensus views, interpreting warming as a linear trend. Figure 3 is a screenshot of the non-consensus or contrarian views. They is supposed to interpret warming as a series of short, disconnected,  periods of no warming. Over time, each period just happens to be at a higher level than the previous. There are a number of things that this indicates.

(a) The “realist” view is of a linear trend throughout any data series. Yet the period from around 1940 to 1975 has no warming or slight cooling depending on the data set. Therefore any linear trend line derived for a longer period than 1970 to 1975 and ending in 2015 will show a lower rate of warming. This would be consistent the rate of CO2 increasing over time, as shown in figure 1. But for shorten the period, again ending in 2015, and once the period becomes less than 30 years, the warming trend will also decrease. This contracts the theory, unless ad hoc excuses are used, as shown in my previous post using the HADCRUT4 data set.

(b) Those who agree with the consensus are called “Realist”, despite looking inwards towards common beliefs. Those who disagree with warming are labelled “Contrarian”. This is not inaccurate when there is a dogmatic consensus. But it utterly false to lump all those who disagree with the same views, especially when no examples are provided of those who hold such views.

(c) The linear trend appears as a more plausible fit than the series of “contrarian” lines. By implication, those who disagree with the consensus are viewed as as having a distinctly more blinkered and distorted perspective than those who follow the consensus. Yet even using gistemp data set (which is gives greatest support to the consensus views) there is a clear break in the linear trend. The less partisan HADCRUT4 data shows an even greater break.

Those who spot the obvious – that around the turn of the century warming stopped or slowed down, when in theory it should have accelerated – are given a clear choice. They can conform to the scientific consensus, denying the discrepancy between theory and data. Or they can act as scientists, denying the false and empirically empty scientific consensus, receiving the full weight of all the false and career-damaging opprobrium that accompanies it.





Kevin Marshall


Beliefs and Uncertainty: A Bayesian Primer

Ron Clutz’s introduction, based on a Scientific American article by John Horgan on January 4, 2016, starts to grapple with the issues involved.

The take home quote from Horgan is on the subject of false positives.

Here is my more general statement of that principle: The plausibility of your belief depends on the degree to which your belief–and only your belief–explains the evidence for it. The more alternative explanations there are for the evidence, the less plausible your belief is. That, to me, is the essence of Bayes’ theorem.

“Alternative explanations” can encompass many things. Your evidence might be erroneous, skewed by a malfunctioning instrument, faulty analysis, confirmation bias, even fraud. Your evidence might be sound but explicable by many beliefs, or hypotheses, other than yours.

In other words, there’s nothing magical about Bayes’ theorem. It boils down to the truism that your belief is only as valid as its evidence. If you have good evidence, Bayes’ theorem can yield good results. If your evidence is flimsy, Bayes’ theorem won’t be of much use. Garbage in, garbage out.
With respect to the question of whether global warming is human caused, there is basically a combination of three elements – (i) Human caused (ii) Naturally caused (iii) Random chaotic variation. There may be a number of sub-elements and an infinite number of combinations including some elements counteracting others, such as El Nino events counteracting underlying warming. Evaluation of new evidence is in the context of explanations being arrived at within a community of climatologists with strong shared beliefs that at least 100% of recent warming is due to human GHG emissions. It is that same community who also decide the measurement techniques for assessing the temperature data; the relevant time frames; and the categorization of the new data. With complex decisions the only clear decision criteria is conformity to the existing consensus conclusions. As a result, the original Bayesian estimates become virtually impervious to new perspectives or evidence that contradicts those original estimates.

Science Matters

Those who follow discussions regarding Global Warming and Climate Change have heard from time to time about the Bayes Theorem. And Bayes is quite topical in many aspects of modern society:

Bayesian statistics “are rippling through everything from physics to cancer research, ecology to psychology,” The New York Times reports. Physicists have proposed Bayesian interpretations of quantum mechanics and Bayesian defenses of string and multiverse theories. Philosophers assert that science as a whole can be viewed as a Bayesian process, and that Bayes can distinguish science from pseudoscience more precisely than falsification, the method popularized by Karl Popper.

Named after its inventor, the 18th-century Presbyterian minister Thomas Bayes, Bayes’ theorem is a method for calculating the validity of beliefs (hypotheses, claims, propositions) based on the best available evidence (observations, data, information). Here’s the most dumbed-down description: Initial belief plus new evidence = new and improved belief.   (A fuller and…

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James Ross Island warming of past 100 years not unusual

At Wattsupwiththat there is a post by Sebastian Lüning The Medieval Warm Period in Antarctica: How two one-data-point studies missed the target.

Lüning has the following quote and graphic from Mulvaney et al. 2012, published in Nature.

But the late Bob Carter frequently went on about the recent warming being nothing unusual. Using mainstream thinking, would you trust a single climate denialist against proper climate scientists?

There is a simple test. Will similar lines fit to data of the last two thousand years? It took me a few minutes to produce the following.

Bob Carter is right and nine leading experts, plus their peer reviewers are wrong. From the temperature reconstruction there were at least five times in the last 2000 years when there were similar or greater jumps in average temperature. There are also about seven temperature peaks similar to the most recent.

It is yet another example about how to look at the basic data rather than the statements of the experts. It is akin to a court preferring the actual evidence rather than hearsay.

Kevin Marshall

Abused Women and Claims of Climate Consensus

Steven Goddard, in explaining why women consistently show stronger support for President Obama than men, comments.

Many people with feminine personalities fall into co-dependency, and are satisfied by ridiculous lies in a thoroughly abusive relationship.

That is a bit strong. In modern terminology, women tend to network more than men. In older terminology, they like to gossip and form opinions on the basis on their social interactions. Such characteristics help hold social units together, but do make women more prone to being won over by emotive arguments that males.

But women in abusive relationships have very low self-esteem being continually told that they are inferior. The men in their lives tell them that their opinion does not count. Any signs of questioning are rebutted verbally, emotionally and physically. The greatest abusers tend to be the biggest liars and the most emotionally inadequate. In more traditional, male-dominated communities such abusers claim legitimacy from that society for practices (such as adultery) that it would not condone. Unfortunately the traditional male-dominated churches have used alleged biblical authority to support the male-abusers in marriage, and even to excuse or down-play paedophilia.

In terms of climatology, claims of superiority of climate scientists have some parallels with these abusing and hate-filled men. Supporters of climate consensus claim that deniers are psychologically inferior and totally incapable of understanding the world around them. They stamp down on any dissent with spurious reasons, such as alleged funding by big oil, yet do not admit to their own funding, nor (and far more dangerously) their own very dogmatic belief systems. They claim the authority of science, but never define what science is, nor how their dogma fits into the best traditions of science.

There are increasing exceptions to the feminine submissiveness. The late Margaret Thatcher is the most extreme. She had a strong sense of values and phenomenal determination to pursue those values. But Thatcher also considered and vigorously questioned any briefings before making decisions. If a case could be made she would change her mind. This may in part be due to a traditional training in science. It is part also due to a feminine side of empathy with opposing points of view.

This feminine trait of talking to other people and listening to different views might explain why although all sides of the climate argument are dominated by men, the most prominent climate bloggers women are sceptical. This includes Joanne Nova, Donna Laframboise, Judith Curry and Lucia. Before someone points out some women alarmists blogs, their respective Alexa rankings are currently 149873, 883955, 393802 and 619501.