Coordinating expectations through central bank projections

Central banks are increasingly communicating their economic outlook in an effort to manage the public and financial market participants' expectations. We provide original causal evidence that the information communicated and the assumptions underlying a central bank's projection can matter for expectation formation and aggregate stability. Using a between-subject design, we systematically vary the central bank's projected forecasts in an experimental macroeconomy where subjects are incentivized to forecast the output gap and inflation. Without projections, subjects exhibit a wide range of heuristics, with the modal heuristic involving a significant backward-looking component. Ex-Ante Rational dual projections of the output gap and inflation significantly reduce the number of subjects' using backward-looking heuristics and nudge expectations in the direction of the rational expectations equilibrium. Ex-Ante Rational interest rate projections are cognitively challenging to employ and have limited effects on the distribution of heuristics. Adaptive dual projections generate unintended inflation volatility by inducing boundedly-rational forecasters to employ the projection and model-consistent forecasters to utilize the projection as a proxy for aggregate expectations. All projections reduce output gap disagreement but increase inflation disagreement. Central bank credibility is significantly diminished when the central bank makes larger forecast errors when communicating a relatively more complex projection. Our findings suggest that inflation-targeting central banks should strategically ignore agents' irrationalities when constructing their projections and communicate easy-to-process information.

Optimal investment in electric generating capacity under climate policy

Mitigating climate change will require reduced use of fossil fuels to generate electricity. To do so while eschewing nuclear power, countries have turned to wind and solar energy. In this paper, load duration and screening curves are used to investigate the extent to which a jurisdiction should invest in intermittent (solar and wind) sources of energy, gas and nuclear power. The application is to the Alberta electricity grid because it is nearly 90 percent reliant on fossil fuels, particularly coal, and recent policy intends to eliminate coal generating capacity by 2030 and replace two-thirds of the lost capacity with renewables. Results suggest that solar and wind are unable to replace two-thirds of coal generation, and that larger than anticipated investments in natural gas capacity will be required. However, if Alberta is serious about reducing emissions, it will need to rely on nuclear energy; at high carbon prices, nuclear power could reduce CO₂ emissions by some 95% compared to only 55% when relying totally on solar and wind.