Tuesday, April 16, 2019

Emissions Reduction Survey 2019

I again carried out a contingent valuation study of climate change using my environmental economics class as respondents. The survey was exactly as in 2018. Participants could vote yes or no on proposals to raise the Medicare levy by 0.125% or 0.25% to help fund the Emissions Reduction Fund. I designed the survey to follow the NOAA panel guidelines. I also asked the students to explain why they voted the way they did.


The results differ from 2018. Only 42% voted for a 0.125% increase in the Medicare levy, while 53% voted for a 0.25% increase. Five people voted against the smaller tax and for the larger tax. So there was quite a lot of irrational behavior where the perfect could have been the enemy of the good if one person had voted differently on the higher tax. This kind of thinking is in large part, IMO, why Australia doesn't now have a carbon price...

Of those voting no on both proposals, there were a mix of responses. Only one seemed to be saying that they couldn't afford the tax given the benefit! And that is what such a survey is supposed to measure. Others objected to the payment vehicle, by suggesting that the government should price carbon or reduce the diesel rebate etc. or borrow/print money instead. I agree with the first two of these, but again that leads here to nothing happening on the climate front if that is what you care about. Others worried about the distributional impact. That is a valid criticism of the Medicare levy proposal, which is a tax on all ones income rather than a progressive or marginal tax. One person incorrectly thought the Medicare levy was unethical, as it was a tax on healthcare. Actually, it is just an extra income tax.

Of those voting yes to the lower tax and no to the higher tax, only one mentioned the cost. The others said that the government should find other funding (borrowing?) or polluters should pay – of course in the end it is the consumer who will pay to the degree that polluters can pass on costs…

Those voting yes on both proposals all said the tax increase was affordable, so they did consider actual willingness/ability to pay.

The bottom line, is that there is a lot of behavior going on in the responses to this survey which doesn’t fit with the model of paying for a public good model where people state their honest WTP, even with a supposedly state of the art design. There is some free-riding - other people should pay or the government should borrow – and on the other hand some altruism as well as protest votes about the policy design. There is also irrational behavior represented by voting no, yes, though we probably can assume that some of these didn't understand the potential implication of voting against the lower tax rate.

Tuesday, February 19, 2019

Energy Efficiency Improvements Do Not Save Energy

I have a new working paper out, coauthored with Stephan Bruns and Alessio Moneta, titled: "Macroeconomic Time-Series Evidence That Energy Efficiency Improvements Do Not Save Energy". It's another paper from our ARC funded project: "Energy Efficiency Innovation: Diffusion, Policy and the Rebound Effect". We estimate the economy-wide effect on energy use of energy efficiency improvements in the U.S. We find that the rebound is around 100%, implying that in the long run energy efficiency improvements do not save energy or reduce greenhouse gas emissions.


At the micro level, we might naïvely expect a 1% improvement in energy efficiency to reduce energy use by 1%. But people adjust their behavior. Efficiency improvements reduce the cost of energy services like heating, transport, or lighting. Because these are now cheaper to produce, people consume more of them, and so the percentage reduction in energy use is less than the improvement in efficiency. This is known as the direct rebound effect.

People might also redirect their spending to consume more of complementary goods, like larger houses in the case of residential heating improvements, and reduce their consumption of substitute goods and services, like bus rides or cycling, in the case of car fuel economy improvements. These changes have implications for the energy used to produce these goods and services. Additionally, the reduction in demand for energy should lower the price of energy further boosting the rebound in energy use. Finally, the improvement in energy efficiency is an increase in productivity, which should result in economic growth. Higher incomes mean higher demand for energy. Adding these indirect rebound effects to the direct rebound effect we get the economy-wide rebound effect.

The size of the economy-wide rebound effect is crucial for estimating the contribution that energy efficiency improvements can make to reducing energy use and greenhouse gas emissions. Our study provides the first empirical general equilibrium estimate of the economy-wide rebound effect. Previous studies use simulation models, known as computable general equilibrium models, or partial equilibrium econometric models that don't allow the price of energy to adjust. Some of the latter studies also measure rebound incorrectly, for example assuming that energy intensity – energy used per dollar of GDP – measures energy efficiency. In fact, the majority of the rebound effect happens when energy intensity rebounds as people shift to more energy intensive consumption after an energy efficiency improvement. Economic growth induced by the efficiency improvement is expected to contribute less to total rebound.

We use a structural vector autoregressive model, or SVAR, that is estimated using search methods developed in machine learning. We apply the SVAR to U.S. monthly and quarterly data. An SVAR explains changes in the vector of variables, x, in terms of its past values and a vector of serially and mutually uncorrelated shocks, ε:

In our basic model, the vector, x, contains three variables: primary energy use, GDP, and the price of energy. The first of the shocks is a shock to energy use, holding constant shocks to GDP and the price of energy and the past values of all three variables. We think this is a reasonable definition of an energy efficiency shock. The other two shocks are income and price shocks.

The matrix, B, which transmits the shocks to the dependent variables cannot be estimated without imposing some restrictions or conditions on the model. Usually economists use economic theory to impose restrictions on the coefficients in B (short-run restrictions) and the Π_i (long-run restrictions). Alternatively, they sample a range of models, rejecting only those that don't meet qualitative "sign restrictions" on the matrix B. Instead, we use independent component analysis, an approach that is relatively new to econometrics. This imposes conditions on the nature of the shocks instead and estimates B without direct restrictions. Unlike the short- and long-run restrictions approach, it doesn't impose a priori restrictions on the data, and unlike the sign restrictions approach, it estimates a unique model.

Using the estimated SVAR model we compute the impulse response functions of the dependent variables to the shocks:


The top left graph shows the effect of an energy efficiency shock on energy use. The grey shading is a 90% confidence interval, the x-axis is in months, and the y-axis in log units.

Initially, an energy efficiency shock strongly reduces energy use, but this effect wears off over the following years as consumers and the economy adjusts. Eventually, there is no change in energy use so that rebound is 100%.

The other graphs in the first column show the effect of the energy efficiency shock on GDP and the price of energy. The second column shows the effect of a shock to GDP, and the final column an energy price shock.

The implications for policy are that encouraging energy efficiency innovation is unlikely to make a contribution to reducing greenhouse gas emissions. This is one reason why I am skeptical of projections that predict that energy intensity will fall much faster in the future than in the past because of energy efficiency policies.

On the other hand, if these policies raise rather than reduce the costs of producing energy services then the direct rebound (and presumably the economy-wide rebound) will be negative rather than positive. As, apart from their environmental effects, these would reduce economic welfare, it seems that there would be better options to reduce emissions by switching to low carbon energy.