We test the efficiency of the California electricity reserves market by examining systematic differences between its day- and hour-ahead prices. We uncover significant day-ahead premia, which we attribute to market design characteristics. On the demand side, the market design established a principal-agent relationship between the markets' buyers (principal) and their supervisory authority (agent). The agent had very limited incentives to shift reserve purchases to the lower priced hour-ahead markets. On the supply side, the market design raised substantial entry barriers by precluding purely speculative trading and by introducing a complicated code of conduct that induced uncertainty about which actions were subject to regulatory scrutiny. We use a high-dimensional vector moving average model to estimate the premia and conduct correct inferences. To obtain exact maximum likelihood estimates of the model, we develop a new EM algorithm that seamlessly incorporates missing data and applies directly to general moving average time series models. Our algorithm uses only analytical expressions: the Kalman filter and a fixed interval smoother in the E step and least squares-type regressions in the M step.