Browsing by Author "Gao, Weiyu"

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    Essays on parametric and nonparametric modeling and estimation with applications to energy economics
    (1999) Gao, Weiyu; Brown, Bryan W.; Sickles, Robin
    My 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.
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    Optimal Dynamic Production Policy: The Case of a Large Oil Field in Saudi Arabia
    (James A. Baker III Institute for Public Policy, 2004) Gao, Weiyu; Hartley, Peter R.; Sickles, Robin C.; James A. Baker III Institute for Public Policy
    We model the optimal dynamic oil production decisions for a stylized oilfield resembling the largest developed light oil field in Saudi Arabia, Ghawar. We use data from a number of sources to estimate the cost and revenue functions used in the dynamic programming model. We also pay particular attention to the dynamic aspects of oil production. We use a nonparametric smoothing technique – tensor splines – to approximate the value function. The optimal solution depends on assumptions about various exogenous variables such as the discount rate and the timing of breakthroughs in the use of alternative energy, which we take to be solar energy. We account for uncertainty about the forecasts by examining the solutions under a number of scenarios. Our model is based on the hypothesis that oil production is chosen to maximize the discounted value of profits. Saudi oil policy reflects many political and strategic motives. Our analysis enables one to quantify the cost of pursuing these non-economic objectives.
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    Optimal Dynamic Production Policy: The Case of a Large Oil Field in Saudi Arabia
    (2004) Gao, Weiyu; Hartley, Peter R.; Sickles, Robin C.; James A. Baker III Institute for Public Policy
    We model the optimal dynamic oil production decisions for a stylized oilfield resembling the largest developed light oil field in Saudi Arabia, Ghawar. We use data from a number of sources to estimate the cost and revenue functions used in the dynamic programming model. We also pay particular attention to the dynamic aspects of oil production. We use a nonparametric smoothing technique – tensor splines – to approximate the value function. The optimal solution depends on assumptions about various exogenous variables such as the discount rate and the timing of breakthroughs in the use of alternative energy, which we take to be solar energy. We account for uncertainty about the forecasts by examining the solutions under a number of scenarios. Our model is based on the hypothesis that oil production is chosen to maximize the discounted value of profits. Saudi oil policy reflects many political and strategic motives. Our analysis enables one to quantify the cost of pursuing these non-economic objectives.