Investment under Uncertainty in Electricity Generation

Klaus Gugler (), Mario Liebensteiner (), Adhurim Haxhimusa () and Nora Schindler ()
Additional contact information
Klaus Gugler: Department of Economics and Research Institute for Regulatory Economics, Vienna University of Economics and Business
Adhurim Haxhimusa: Research Institute for Regulatory Economics, Vienna University of Economics and Business
Nora Schindler: Department of Economics, Vienna University of Economics and Business

Department of Economics Working Papers from Vienna University of Economics and Business, Department of Economics

Abstract: The recent transformation of European electricity markets with increasing generation from intermittent renewables brings about many challenges. Among them, decaying wholesale prices, partly due to support schemes for renewables, may send insufficient investment signals for other technologies. We investigate the investment decision in a structural equation based on the Tobin’s q-model, which we extend by both industry- and firm-technology-specific uncertainty. We utilize rich and novel data at the disaggregated firm generation technology level of European electricity generating firms for the period 2006–2014. Our results show that investment in any generation technology follows market incentives despite sunk and irreversible capital, confirming the implications of the q-model. Moreover, while firm-technology-specific uncertainty decreases firms’ investment activity, especially in coal and gas, aggregate uncertainty triggers firms’ investment. Our results raise concerns about system reliability in the long run since conventional technologies still serve as a flexible system back-up.

Keywords: Tobin's q; Uncertainty; Investment; Electricity (search for similar items in EconPapers)
JEL-codes: L22 L25 L51 Q48 (search for similar items in EconPapers)
Date: 2016-09
New Economics Papers: this item is included in nep-bec, nep-ene, nep-eur and nep-reg
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Citations: View citations in EconPapers (2)

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Working Paper: Investment under Uncertainty in Electricity Generation (2016)
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