用几何画板软件探讨二元函数的条件极值问题

利用几何画板软件先绘制出约束条件的图象,再把图象上的动点代入二元函数,观测函数性态,寻求极值。     

Parallel Neutrality

This paper develops the notion of parallel-neutral technical change for inputs and outputs. It is shown that parallel-neutral technical change generalizes existing radial notions of neutral technical change. A taxonomy of the structural consequences of parallel-neutral technical change is developed.     

Properties of Census Dual System Population Size Estimators

We study parametric and non‐parametric approaches for assessing the accuracy and coverage of a population census based on dual system surveys. The two parametric approaches being considered are post‐stratification and logistic regression, which have been or will be implemented for the US Census dual system surveys. We show that the parametric model‐based approaches are generally biased unless the model is correctly specified. We then study a local post‐stratification approach based on a non‐parametric kernel estimate of the Census enumeration functions. We illustrate that the non‐parametric approach avoids the risk of model mis‐specification and is consistent under relatively weak conditions. The performances of these estimators are evaluated numerically via simulation studies and an empirical analysis based on the 2000 US Census post‐enumeration survey data.     

On the existence of a regulated production function

This paper examines the generalization of the regulated production function. It characterizes the set of admissible regulatory constraints that are compatible with the existence of a regulated production function in a sufficiently weak framework to encompass the usual rate-of-return constraints à la Averch and Johnson and value constraints.     

Outsourcing, Imports and Labour Demand

This paper examines the effects of purchased services and imported intermediate materials on the labour demand for different skills in German manufacturing sectors. We derive and estimate a factor demand system based on the generalised Box–Cox cost function nesting both the normalised quadratic and the translog functional form. We find that the impacts of output and capital growth are more important in explaining the demand for heterogeneous labour than substitution effects between labour and non–labour inputs. Similarly, the increasing use of both imported materials and purchased services is a consequence of output growth rather than input substitution.
JEL classification : J 23; O 33     

基础设施资本对经济增长贡献的研究进展--生产函数法综述

在影响经济增长的各种因素中,基础设施资本是一个重要的因素.本文在简单回顾基础设施资本与经济增长关系的理论研究发展历史的基础上,对国际上有关基础设施资本影响经济增长(总产出)的效应的研究文献进行了回顾,重点对生产函数法在研究中的应用进行了综述.本文分为3个部分.1、引言;2、生产函数法的应用研究;3、总结和评价.     

复变函数课程的对比教学法研究

复变函数主要研究复数域上的函数,是高等数学课程的延伸。本文阐述了复变函数和高等数学在理论体系上的异同,并强调其差异性。在复变函数的授课中,采用对比教学法,以加深学生对知识的理解,提高分析和解决问题的能力。     

Quantiles as optimal point forecasts

Loss functions play a central role in the theory and practice of forecasting. If the loss function is quadratic, the mean of the predictive distribution is the unique optimal point predictor. If the loss is symmetric piecewise linear, any median is an optimal point forecast. Quantiles arise as optimal point forecasts under a general class of economically relevant loss functions, which nests the asymmetric piecewise linear loss, and which we refer to as generalized piecewise linear (GPL). The level of the quantile depends on a generic asymmetry parameter which reflects the possibly distinct costs of underprediction and overprediction. Conversely, a loss function for which quantiles are optimal point forecasts is necessarily GPL. We review characterizations of this type in the work of Thomson, Saerens and Komunjer, and relate to proper scoring rules, incentive-compatible compensation schemes and quantile regression. In the empirical part of the paper, the relevance of decision theoretic guidance in the transition from a predictive distribution to a point forecast is illustrated using the Bank of England’s density forecasts of United Kingdom inflation rates, and probabilistic predictions of wind energy resources in the Pacific Northwest.     

基于BP神经网络的茶叶物流金融模式仿真优化

针对茶叶物流金融运作模式选择中的复杂性以及传统优化方法的局限性,将BP神经网络理论和仿真方法引入茶叶物流金融模式优化,考虑样本数量不足的实际问题,采用B样条函数插值方法扩充数据量,构建BP神经网络模型并加以训练。结果表明:BP神经网络具有精度较高的智能学习能力,适合于茶叶物流金融模式选择优化。