Yes, let's set the record straight.
When one takes Tol (2009) and fixes the missing negative signs, out of the 14 estimates for the aggregate economic impact of climate change, the only one which shows a statistically significant positive effect was another paper Tol wrote (one other shows a net benefit of 0.1%). And that paper showed a net benefit of 2.3% of GDP; larger than the harm shown by 10 of the 13 other estimates in the paper.
Which contrasts starkly with his claim in Tol (2009) that, and I quote:
Given that the studies in Table 1 use different methods, it is striking that the estimates are in broad agreement on a number of points—indeed, the uncertainty analysis displayed in Figure 1 reveals that no estimate is an obvious outlier.
So when he writes in this article,
In fact, the original and corrected data are not materially different. There is no statistically significant difference between the trends fitted to the original data and to the corrected data.
Remember that the shape of the graph is substantially determined from one estimate... which Tol was the author of. Remove that 1 study (and use his corrections from Tol (2014)), and the graph would show a reduction in GDP for all values of warming, rather than a net increase up to about 2 C.
And in the 2014 correction to that paper - which only corrected some of the errors - he expanded that to 21 estimates, and every single estimate added showed a net harm. Including these estimates, the net effect according to Figures 1 and 2 of the corrected correction - yes, the correction had to be corrected - went from "warming is likely beneficial up to about 2.25 C" to "warming is always detrimental". And worse, his x-axis form his original figure went from "temperature change relative to today" to "temperature change relative to preindustrial times"... but for some reason, this change isn't discussed anywhere in the correction, and one can plainly compare the two and see that he didn't adjust data for the different baseline.
As for his claim that:
Since 2009, however, more estimates of the economic impact of climate change have been published. These new results do affect the fitted trend, but not in the way suggested by Mr Ward. The new trend shows positive impacts for warming up to about two degrees global warming, just like the old trend did. The new trend, however, shows markedly less negative impacts for more profound warming than did the old trend. In other words, in the last five years, we have become less pessimistic about the impacts of climate change.
This is bullshit, pure and simple. This is simply a characteristic of the fact that he's modeling it using a quadratic equation. It's not a result of new work showing less negative impacts at larger amounts of warming, it's a function of his adjusting the prior vertex downwards. Say I have a dataset with 3 points: (-2,0), (0,2), and (2,0), and I use them to create a quadratic model, y = -0.5x2 +2. Now, say it turns out that - whoops! - "gremlins" got into my model and the vertex should be (0,1). In order to preserve a quadratic curve, my leading coefficient will have to halve, resulting in my new model, y = -0.25x2 + 1. If you then look at my model outside the range of my data, say at x = 4, you're going to find that my revised model is "less pessimistic" than my prior model, not because my data was any less pessimistic, but because that's how quadratic functions work.
Is Tol merely completely incompetent, or is Tol knowingly lying?