Essays on parametric and nonparametric modeling and estimation with applications to energy economics

Simple item page
dc.contributor.advisorBrown, Bryan W.en_US
dc.contributor.advisorSickles, Robinen_US
dc.creatorGao, Weiyuen_US
dc.date.accessioned2009-06-04T08:28:58Zen_US
dc.date.available2009-06-04T08:28:58Zen_US
dc.date.issued1999en_US
dc.description.abstractMy dissertation research is composed of two parts: a theoretical part on semiparametric efficient estimation and an applied part in energy economics under different dynamic settings. The essays are related in terms of their applications as well as the way in which models are constructed and estimated. In the first essay, efficient estimation of the partially linear model is studied. We work out the efficient score functions and efficiency bounds under four stochastic restrictions---independence, conditional symmetry, conditional zero mean, and partially conditional zero mean. A feasible efficient estimation method for the linear part of the model is developed based on the efficient score. A battery of specification test that allows for choosing between the alternative assumptions is provided. A Monte Carlo simulation is also conducted. The second essay presents a dynamic optimization model for a stylized oilfield resembling the largest developed light oil field in Saudi Arabia, Ghawar. We use data from different sources to estimate the oil production cost function and the revenue function. We pay particular attention to the dynamic aspect of the oil production by employing petroleum-engineering software to simulate the interaction between control variables and reservoir state variables. Optimal solutions are studied under different scenarios to account for the possible changes in the exogenous variables and the uncertainty about the forecasts. The third essay examines the effect of oil price volatility on the level of innovation displayed by the U.S. economy. A measure of innovation is calculated by decomposing an output-based Malmquist index. We also construct a nonparametric measure for oil price volatility. Technical change and oil price volatility are then placed in a VAR system with oil price and a variable indicative of monetary policy. The system is estimated and analyzed for significant relationships. We find that oil price volatility displays a significant negative effect on innovation. A key point of this analysis lies in the fact that we impose no functional forms for technologies and the methods employed keep technical assumptions to a minimum.en_US
dc.format.extent136 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS ECON. 1999 GAOen_US
dc.identifier.citationGao, Weiyu. "Essays on parametric and nonparametric modeling and estimation with applications to energy economics." (1999) Diss., Rice University. <a href="https://hdl.handle.net/1911/19381">https://hdl.handle.net/1911/19381</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/19381en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectEconomicsen_US
dc.subjectEconomic theoryen_US
dc.subjectEnergyen_US
dc.titleEssays on parametric and nonparametric modeling and estimation with applications to energy economicsen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentEconomicsen_US
thesis.degree.disciplineSocial Sciencesen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
9928534.PDF
Size:
4.84 MB
Format:
Adobe Portable Document Format
Download
Collections
Rice University Theses and Dissertations