that they would be exposed to risk from fluctuations in their electricity cost. The concern seems to be that a customer … larger than it had budgeted for. I analyze the magnitude of this risk, using demand data from 1142 large industrial customers …, and then ask how much of this risk can be eliminated through various straightforward financial instruments. I find that …

in one of the world's most valuable agricultural areas: California. Using rich administrative data and exogenous … discrete choice model, we estimate that a counterfactual $10 per-acre-foot groundwater tax--a level consistent with California …

the fuels with a large survey of California households' energy use, we calculate the distribution of annual fuel costs for …

electricity prices in California. We match a spatially-disaggregated panel dataset of monthly EV registration records to detailed … records of gasoline and electricity prices in California from 2014-2017, and use these to estimate the effect of energy prices …

-hour rises as a household consumes more electricity per month. More recently, in California, opponents of a proposal to lower …

inflation process is well described by an unobserved component trend-cycle model with stochastic volatility or, equivalently, an …

(2000). Stochastic volatility aries in our two-factor model as a natural consequence of production for oil and natural gas …

volatility forecast, coupled with a parametric lognormal-normal mixture distribution implied by the theoretically and empirically … forecasting of daily and lower frequency volatility and return distributions. Most procedures for modeling and forecasting … ARCH or stochastic volatility models, which often perform poorly at intraday frequencies. Use of realized volatility …

the agricultural production cycle. We show theoretically that a forecast of good weather can lower wages in the planting … allocations on average but exacerbate wage volatility because they are imperfect …