Latest posts by H. Sterling Burnett (see all)
- Misguided Youth Protesters Have It Wrong — the World Is Actually Getting Better and Better - January 14, 2020
- Climate-Change Alarmists Are Getting More Delusional In Their Predictions - January 9, 2020
- Climate Nags are Trying to Ruin Christmas - December 27, 2019
President Trump vowed to increase transparency concerning how federal agencies operate and impose rules.
Regulations should be based on the best-available scientific and economic analyses of any problem being addressed and the likely outcomes of rules proposed to solve it. And good government requires an informed citizenry. This means taxpayers, who foot the bill for much of the research used to justify regulations and fund the agencies charged with ensuring the public health and environmental quality, should have access to the information used to make regulatory decisions.
Good government and sound scientific practice benefit from the transparent sharing of relevant information and data. This ensures claims made by researchers are accurate, which is best assured by retesting. Moreover, this gives the public confidence those who propose regulations and the regulators are not making deals behind closed doors that benefit themselves at the expense of the public good.
Although environmental lobbyists and deep-state bureaucrats, who are wedded to the power ever larger government delivers to them, decry the Trump administration’s regulatory reform efforts, falsely claiming they threaten public health and the environment, the truth is Trump’s team is improving the science used by regulatory agencies.
Under Trump, the Environmental Protection Agency changed how it runs its scientific advisory panels, which are tasked with ensuring the research the agency uses to develop and justify regulations is rigorous, has integrity and is based on the best-available science. EPA ceased automatically renewing the terms of board members on various panels. EPA is now filling its scientific panels and boards on a competitive basis as each member’s term expires. This is improving the science EPA uses to inform its decisions, by expanding diversity — diversity of interests, diversity of scientific disciplines and diversity of backgrounds — thus bringing in a wider array of viewpoints to EPA decision-making.
In addition, to reduce opportunities for corruption, EPA ceased allowing members of its federal advisory committees to apply for EPA research grants and instituted policies to ensure advisory panel members and grant recipients have no other conflicts of interest. It was always a foolish practice to allow those recommending and often determining who gets EPA grants to also be in the running for those grants. However, this was business as usual at EPA, where grant-makers awarded themselves and their friends billions of taxpayer dollars over the years while lobbying for increased budgets for the regulatory agencies who delivered their grants.
In addition, EPA has taken steps to end the use of secret science, implementing rules requiring the data underlying scientific studies used by EPA to craft regulations be available for public inspection, criticism and independent verification. For years, EPA bureaucrats have imposed regulations justified on the basis of the results of studies by authors who refused to disclose the data underlying their research, effectively preventing others from retesting their work for confirmation or falsification. Unless the reviewers can examine the underlying data and assumptions and attempt to replicate the results, it’s difficult to determine whether regulations based upon that research is justified.
Most recently, the administration has required EPA and other agencies to adjust their approach to making predictions about the direction and effects of climate change, requiring them to limit climate model projections to the year 2040 — 20 years in the future.
Climate models have routinely overestimated future warming and other climate changes, and the further one looks into the future, the less reliable models’ projections are, which is true not just for climate models but of all econometric models.
Climate models, like models used by every other discipline, are beset by basic problems, including inadequate or missing information, poorly understood parameters, and assumptions filling in for nonexistent data. The result is projections about the future being tentative in the extreme. Small initial errors are magnified exponentially over time. In other words, the further out projections are from the starting point the less reliable they are.
As climate models have proven unable to accurately project changes that have occurred over the past two decades, there is no reason to believe the alarming forecasts they’ve made about the year 2100 should be trusted to inform public policies that could limit people’s freedom of choice and impose trillions of dollars in costs on the economy.
To paraphrase American hero Neil Armstrong, the Trump administration’s actions have been “small steps for regulatory agencies, but giant leaps for scientific integrity.”