By: Guest Blogger Joe Indvik, ICF International
Policy design matters. But all too often, this notion is ignored by political pundits and belittled by policymakers in favor of flashy claims about the morality of a policy type. Like the latest sports car, a policy is usually touted as either a gem or a dud based on its superficial image, with only marginal public interest in looking at what’s actually under the hood. On the contrary, data-driven analysis of the inner workings of policy design will be the key to smart solutions on the road ahead for climate and energy policy the U.S.
The Waxman-Markey cap-and-trade bill of 2009 is a prime example. Claims about this former centerpiece of the American climate policy debate ran the gamut of dramatic generalization. They ranged from accusations of a job-killing socialist scheme that “would hurt families, business and farmers—basically anyone who drives a car and flips a light switch” to claims from hopeful environmentalists that any cap would be better than nothing. Discussion on the actual design of the bill was all but absent from the limelight. Energy policy discourse is often dominated by these combative back-and-forths, which focus on oversimplified notions of whether a policy would be good for the country while glossing over the practical nuances that make all the difference.
The Data Tells a Different Story
Some of my recent research provides ammunition for those who insist the devil is in the details. I recently teamed up with two colleagues from Harvard University and the German Institute for Economic Research to examine the effectiveness of feed-in tariffs (FIT), a policy widely adopted by European countries. A FIT is a type of renewable electricity subsidy that values renewable energy higher than fossil fuels, increasing the price received by energy producers when they sell electricity back to the grid. We wanted to know: Have feed-in tariffs actually increased renewable electricity generation in Europe, as intended? Armed with this simple premise and some statistical models, we set out to do the first rigorous analysis of whether this popular but controversial policy has really worked at the macro level. We emerged with some surprising insights that may prove crucial as the U.S. develops its climate and energy policy in the coming years.
Our first analysis revealed a startling conclusion. Countries with a FIT install more wind power each year, as expected, but countries with a FIT for solar photovoltaics do not appear to install more solar capacity at all. In other words, this result implies that European FIT policies for solar power have been an abject failure on the whole. But it occurred to us that there was a massive problem with this approach: It treats all FIT policies as equal. In reality, tariffs can (and do) have drastically different structures and operate in diverse markets. This creates very different incentives for renewable energy deployment in different times and places. Ultimately, it throws our first analysis out the window.
So we took a step back. Instead of looking at the issue from the pundit perspective, we put ourselves in the shoes of the real drivers of renewable energy deployment: investors. Investors are concerned with policy only to the extent that it improves the business case for renewables—i.e. increases their return on investment (ROI). So we created a new variable to represent the ROI provided by each tariff and ran one final test. The results were, again, striking. Whereas countries with a FIT for solar do not necessarily install more solar capacity, countries with a FIT that significantly increases the ROI on solar investments install much more solar capacity. In other words, simply having a FIT means nothing; designing a FIT that intelligently works with existing market conditions to produce a favorable investment environment means everything.
Time for a Tune-Up
What does this imply for the climate and energy policy debate in the U.S.? It shows that not all policies are created equal, and that the differences between policies are actually more important than the presence of a policy in the first place. It also teaches us we have much to learn.
The next few years will be a dynamic and challenging time for energy policy in the U.S. Though only a few U.S. states currently have a FIT, many are considering following Europe’s lead. Also, a national climate bill or set of bills is likely to emerge as a new battleground for debate over the proper response to climate change. Rather than descend into ideological gridlock, we can use data-driven analysis of existing policies as a powerful tool to customize and optimize our approach in the U.S. How large must a FIT be set to be effective? At what size does a tariff become overkill, wasting taxpayer money? Do producers prefer large tariffs that last only a few years or smaller tariffs that support generation for decades? More importantly, is a FIT even the best choice for a given state, or would the populace’s goals be better served by a renewable portfolio standard or tax break instead? How does the best policy choice change in regions with different production costs, electricity prices, and market structures? We can make progress toward answering these questions by stepping back from the political melee, using quantitative analysis to take a look under the hood of a policy type, and examining what really makes it tick.
As we move forward, it is exciting to think that lawmakers can glean insights from policy successes (and failures) around the world in increasingly sophisticated ways. Though researchers have only scratched the surface of this potential, we would do well keep in mind the lessons already learned from our analysis and others like it. Policy design matters—and in some cases, it is the only thing that matters.
Author: Joe Indvik is consultant in the Energy, Environment, and Transportation group at ICF International in Washington, DC. He holds a degree in Economics and Environmental Studies from Dartmouth College. His academic research is focused on using the tools of quantitative analysis to make climate and energy policies smarter.
4 Comments
1970 earth is getting colder/ 2010 earth is getting hotter . better hot then cold . try to grow food on ice!
Excellent article! Lays out the promise and potential of quantitative policy analysis to guide the future of U.S. climate policy design. If a major national climate bill does come up again, this research will serve as a clear and communicable reminder that simple act of enacting a poorly designed policy is not necessarily better than having no policy at all.
Excellent article Joe. If politicians could only align rational methodologies for analysis and put aside partisanship, we could finally start to make some progress. I would be deeply curious to read an article that answers the question in your text: “Is a FIT even the best choice for a given state, or would the populace’s goals be better served by a renewable portfolio standard or tax break instead?”
Thanks Tim. Comparisons across policy types are harder, but also an incredibly useful tool for lawmakers if done right. One of the next lines of research we’re planning is a comparison of price-based vs. quantity-based renewable energy incentives (primarily FIT and RPS) in both the U.S. and E.U. The underlying question is “which policies have worked, in which regions, and why?” I’d still love to work with you on this sort of stuff if you’re interested.