Management problems in energy and sustainability
Abstract/Contents
- Abstract
- This thesis studies management problems in energy and sustainability. Motivated by applications in oil exploration and investment, Chapter 1 considers a firm that can use one of several costly learning modes to dynamically reduce uncertainty about the unknown value of a project. Each learning mode incurs cost at a particular rate and provides information of a particular quality. In addition to dynamic decisions about its learning mode, the firm must decide when to stop learning and either invest or abandon the project. Using a continuous-time Bayesian framework, and assuming a binary prior distribution for the project's unknown value, we solve both the discounted and undiscounted versions of this problem. In the undiscounted case, the optimal learning policy is to choose the mode that has the smallest cost per signal quality. When the discount rate is strictly positive, an optimal learning and investment policy can be summarized by a small number of critical values, and the firm only uses learning modes that lie on a certain convex envelope in cost-rate-versus-signal-quality space. Chapter 2 extends the analysis in Chapter 1 to consider a firm that can choose multiple learning modes simultaneously, which requires the analysis of both investment timing and dynamic subset selection decisions. We solve both the discounted and undiscounted versions of this problem, and explicitly identify sets of learning modes that are used under the optimal policy. We show that more complex dynamic "subset selection problem" actually reduces, in a certain sense, to the dynamic "single-mode selection problem" studied in Chapter 1. In Chapter 3, we analyze the effect of different greenhouse gas emissions allocation rules on emissions, importers' profits and import quantity. States with climate policy are likely to impose a carbon tax (or equivalent) on imports from regions with no such policy. When a process yields co-products in fixed proportions, how should the process carbon dioxide emissions be allocated among those co-products? Production and hence emissions will vary with the allocation rule when only some of the co-products are exported (as in the example of the Chinese firm that mines rare earth oxides with iron ore, and exports only the rare earth oxides). Current emissions accounting standards allow importers to allocate process emissions in proportion to the economic values of co-products, or in proportion to their masses, or based on the emissions associated with a substitute for one of the coproducts. We show that requiring importers to use a specific one of those allocation rules will reduce emissions if and only if it is chosen correctly. Requiring the maximal allocation rule or increasing the carbon tax may increase emissions. To validate our theoretical findings empirically, we construct a numerical example by using the data that we collect on rare earth element industry. Focusing on imports of cerium oxide by the U.S. flat glass industry, the numerical study demonstrates that under value-based allocation, emissions strictly increase with emissions cost when it ranges from $21.5 to $35.7 per tonne carbon dioxide, as predicted by our theoretical finding.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2013 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Sunar, Nur |
|---|---|
| Associated with | Stanford University, Graduate School of Business. |
| Primary advisor | Harrison, J. Michael, 1944- |
| Primary advisor | Plambeck, Erica L |
| Thesis advisor | Harrison, J. Michael, 1944- |
| Thesis advisor | Plambeck, Erica L |
| Thesis advisor | Grenadier, Steven R |
| Advisor | Grenadier, Steven R |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Nur Sunar. |
|---|---|
| Note | Submitted to the Graduate School of Business. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2013. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2013 by Nur Sunar
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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