參數(shù)和非參數(shù)模型與估計及在能源經(jīng)濟學(xué)中的應(yīng)用

前言

　　Nonparametricand semiparametric modeling and estimationprocedures are now widely applied in econometrics. Their popularitygenerallycomesfromthereductionoftheprobabilityofmisspecification compared with their parametric counterpart. Myresearch is composed of two parts： a theoretical part on semiparametricefficient estimation of partially linear model and an applied part inenergy economics under different dynamic settings. The chapters arerelated in terms of their applications as well as the way in which modelsare constructed and estimated. In the second chapter， estimation of thepartially linear model is studied under different stochastic restrictions ofthe residual term. We work out the efficient score functions andefficiency bounds under four stochastic assumptions partiallyuncorrelated， independence， conditional symmetry， and conditional zeromean. A feasible efficient estimation method for the linear part of themodel is also developed based on the efficient score function associatedwith each parametric submodel. A battery of specification test thatallows for choosing between the alternative assumptions is provided.

內(nèi)容概要

　　Nonparametric and semiparametric modeling and estimation procedures are now widely applied in econometrics. Their popularity generally comes from the reduction of the probability of misspecification compared with their parametric counterpart. My research is composed of two parts： a theoretical part on semiparametric efficient estimation of partially linear model and an applied part in energy economics under different dynamic settings.

書籍目錄

1.　Introduction1.1.　Parametric and Nonparametric Modeling and Estimation1.2.　Book Structure2.　Semiparametric Efficient Estimation of Partially Linear Model2.1.　Introduction2.2.　Model and Previous Results2.3.　Semiparametric Efficiency Bounds2.4.　Feasible and Efficient Estimation2.5.　Specification Test2.6.　Sampling Results2.7.　Conclusion3.　Optimal Dynamic Production Policy： The Case of a Large Oil Field in Saudi Arabia3.1.　Introduction3.2.　Dynamic Modeling of Oil Production Decisions3.3.　Data and Estimations3.4.　Theoretical Issues3.5.　Simulation Results3.6.　Conclusion4.　The Effects of Oil Price Volatility on Technical Change4.1.　Introduction4.2.　Channels of Transmission and Oil Price Volatility4.3.　A Measure of Volatility4.4.　A Measure of Innovation （Technical Change）4.5.　Vector Autoregression4.6.　Conclusion5.　Promoting Renewable Electricity Generation in Imperfect Markets： Price vs.Quantity Control5.1.　Introduction5.2.　Promoting Renewable Electricity in a Perfectly Competitive Market5.3.　Duopoly Market and Quasi-symmetric Costs5.4.　Welfare Comparison Between Subsidy and Quota-based Policies5.5.　Policy Implications5.6.　ConclusionAppendixReferences

章節(jié)摘錄

　　A comparison of the optimal oil production policy paths underdifferent simulation scenarios indicates that the discount rate does have asignificant effect on the optimal extraction rates and the number of newwells drilled for capacity expansion. A lower discount rate like 0.7, whichmight indicate a high demand for short-term oil income, would lead to ahigher production rate in the short-am but a lower capacity in the futurecompared with the outcome when r= 0.9. Figure 3.12 suggests that Saudioil production is relatively better approximated by scenario I （β = 0.9）before 1990. After Gulf crisis occurred in 1989 - 1990, scenario II （β =0.7） approximates the real path better, and actually in 1990 the two pathscoincide.

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