A Bureaucratic Boondoggle Exposed – Watts Up With That?

Ross McKitrick’s Latest Study Shows SCC Manipulation for Political Ends

The Biden administration put in a lot hard at work inflating the Social Cost of Carbon (SCC), using exaggerated agricultural damage estimates to justify sweeping climate policies. But in a new study, economist Ross McKitrick—one of the sharpest minds in climate policy skepticism—has taken apart the foundations of these inflated numbers, revealing what happens when climate alarmism meets real data.

The Biden Administration raised its Social Cost of Carbon (SCC) estimate about fivefold based in part on global crop yield decline projections estimated on a meta-analysis data base first published in 2014. The data set contains 1722 records but half were missing at least one variable (usually the change in CO₂) so only 862 were available for multivariate regression modeling. By re-examining the underlying sources I was able to recover 360 records and increase the sample size to 1222. Reanalysis on the larger data set yields very different results. While the original smaller data set implies yield declines of all crop types even at low levels of warming, on the full data set global average yield changes are zero or positive even out to 5 °C warming.

https://www.nature.com/articles/s41598-025-90254-2

Of course, the entire concept of the Social Cost of Carbon is a bureaucratic fantasy—a number conjured up by modelers who can tweak discount rates, speculative damage functions, and climate projections until they get the politically convenient answer. It’s an arbitrary metric, designed less to quantify real-world economic impacts and more to justify sweeping government interventions. That said, even within this rigged framework, McKitrick’s study exposes how the game is played: if you follow their own rules but use the full dataset, the SCC comes out far lower than the Biden administration’s sky-high estimate. In other words, if SCC were a legitimate measure (it isn’t), this paper shows they’re still doing it wrong.

McKitrick’s study, Extended Crop Yield Meta-Analysis Data Do Not Support Upward SCC Revision, exposes how bureaucrats have distorted agricultural yield projections to push for higher SCC estimates. His findings? The supposed climate-related crop damage is wildly overstated. In reality, global crop yields appear to remain stable—or even increase—under warming scenarios up to 5°C. This fundamentally undermines one of the key justifications for the massive SCC hikes driving Biden’s climate policies.

Let’s break this down.

How the SCC Got a Makeover

The SCC is supposed to measure the economic damage per ton of carbon dioxide emissions. Under the Biden administration, the Environmental Protection Agency (EPA) boosted this estimate to an eye-popping $220 per ton—a nearly fivefold increase from the first Trump administration’s EPA’s previous $51 per ton. A big chunk of this increase comes from projected agricultural losses, derived from the GIVE damage model. Nearly half of the SCC estimate ($103 per ton) is based on assumed losses in global food production due to warming.

But as McKitrick demonstrates, these assumptions are built on a foundation of bad data and flawed modeling.

The Data Problem: When Missing Numbers Become Policy Drivers

The SCC estimates for agriculture rely on two studies:

• Challinor et al. (2014) (C14): A meta-analysis of crop yield simulations under climate change.
• Moore et al. (2017) (M17): A re-analysis of C14, but with a much more pessimistic outlook.

C14 actually suggested that warming associated with CO2 increases could produce a moderate net benefit for crop yields. M17, using the same dataset but modifying the statistical approach, suddenly found widespread yield declines. Conveniently, this study became a primary input for the EPA’s justification of its SCC hike.

But here’s the kicker: The dataset used for these calculations was incomplete. C14 initially contained 1,722 data points, but nearly half were missing at least one crucial variable—often the change in CO2 levels. This left only 862 data points for regression modeling.

McKitrick painstakingly reconstructed the missing data, increasing the sample size by 40% to 1,222 records. The result? The apocalyptic yield declines of M17 evaporate. With the fuller dataset, global crop yields actually show zero to positive changes even with warming up to 5°C.

CO2: The Forgotten Fertilizer

One of the biggest sleights of hand in climate agriculture modeling is the tendency to ignore the well-documented benefits of CO2 fertilization. Plants need CO2 to grow, and numerous studies show that increasing CO2 enhances photosynthesis, improves water efficiency, and boosts crop yields.

M17 downplayed this by imposing a concave function on CO2 fertilization effects—essentially assuming that its benefits diminish sharply at higher levels. This assumption is questionable at best, especially when real-world evidence suggests that CO2 enrichment remains beneficial even at much higher concentrations.

McKitrick’s findings show that once CO2 fertilization is properly accounted for, the supposed catastrophic losses in food production disappear.

Bureaucratic SCC Manipulation: A Policy-Driven Fiction

The SCC is supposed to be based on objective economic analysis. Instead, it has become a politically weaponized tool, rigged to produce the “right” answer for those advocating aggressive climate policies.

The Biden EPA’s decision to increase the SCC by a factor of five wasn’t based on new empirical evidence of damage—it was driven by selective use of studies that inflated the cost of carbon while ignoring counterbalancing benefits.

McKitrick’s study reveals that when the full dataset is used, the SCC—at least in terms of agricultural impacts—should be much lower. If agricultural productivity is stable or improving, the massive projected damages vanish, bringing SCC estimates crashing down.

The Bottom Line: SCC Overestimation Means Bad Policy

Ross McKitrick’s study is a devastating blow to the bureaucratic inflation of the SCC. It demonstrates that:

1. The Biden administration’s SCC hike was based on flawed and incomplete agricultural damage models.
2. CO2-induced warming does not lead to catastrophic yield declines; in fact, crop yields remain stable or increase even at 5°C warming.
3. The manipulated SCC figures are being used to justify extreme climate policies that hurt economic growth and energy security.

If we’re going to make rational policy decisions, we need an SCC that reflects reality—not one inflated to serve a political agenda. McKitrick’s work is a reminder that bad data leads to bad policy, and bad policy leads to unnecessary economic pain.

The next time you hear a bureaucrat justify draconian climate policies by citing the “high cost of carbon,” remember this: It’s all built on a foundation of smoke and mirrors.

McKitrick’s full paper can be found here.

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