No abstract

We measure the pass-through of emissions costs to electricity prices. We perform both reduced-form and structural estimations based on optimal bidding in this market. Using rich micro-level data, we estimate the channels affecting pass-through in a flexible manner, with minimal functional form assumptions. Contrary to many studies in the general pass-through literature, we find that emissions costs are almost fully passed through to electricity prices. Since electricity is traded through high-frequency auctions for highly inelastic demand, firms have weak incentives to adjust markups after the cost shock. Furthermore, the costs of price adjustment are small. (JEL D44, L11, L94, L98, Q52, Q54)

We are grateful for the contribution of Antonio Jesús Sánchez-Fuentes to this project. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Complementary Bidding Mechanisms and Startup Costs in Electricity MarketsAbstract I extend multi-unit auction estimation techniques to a setting in which firms can express cost complementarities over time. In the context of electricity markets, I show how the auction structure and bidding data can be used to estimate these complementarities, which in these markets arise due to startup costs. I find that startup costs are substantial and that taking them into account helps better explain firm bidding strategies and production patterns. As in other dynamic settings, I find that startup costs limit the ability of firms to change production over time, exacerbating fluctuations in market prices. These fluctuations can induce estimates of market power that ignore dynamic costs to overstate markup volatility, with predicted markups that can be even negative in periods of low demand. I show how accounting for startup costs can provide a natural correction for these markup biases.