交接计量误差与管理方法浅析

从误差的来源分析了原油交接计量过程中产生的误差及原因,阐述了控制计量误差的方法,并结合靖咸管道5年来的计量运营,总结了科学高效的计量管理方法。     

The Spatial Durbin Model and the Common Factor Tests

Abstract

The spatial Durbin model occupies an interesting position in the field of spatial econometrics. It is the reduced form of a model with cross-sectional dependence in the errors and it may be used as the nesting equation in a more general approach of model selection. Specifically, in this equation we obtain the common factor tests (of which the likelihood ratio is the best known) whose objective is to discriminate between substantive and residual dependence in an apparently misspecified equation. Our paper tries to delve deeper into the role of the spatial Durbin model in the problem of specifying a spatial econometric model. We include a Monte Carlo study related to the performance of the common factor tests presented in the paper in small sample sizes.     

Cross Validation Calibration Based Shrinkage – Revisited for the Construction of Prognostic Indices

The use of shrinkage methods for the construction of prognostic indices has been paid increasing attention in the literature on medical statistics in the last years. One approach for the construction of a shrinkage factor is cross validation calibration as suggested by van H ouwelingen and le C essie (1990). We investigate this approach in more detail. First we try to clarify why shrinkage factors constructed by cross validation calibration tend to be smaller than 1. Second we explain why use of this shrinkage factor can result in an improvement of the average prediction error. Third we investigate the possible gain for constellations relevant in medical research by means of a simulation study, focusing on the dilemma, that the improvement on average has to be paid by distinct deteriorations for some patients. Finally we conclude that it is necessary to rethink the choice of loss functions in constructing prognostic indices before recommendations about the use of shrinkage methods can be made.     

Mean squared error of the empirical best linear unbiased predictor in an orthogonal finite discrete spectrum linear regression model

The mean squared error (MSE) of the empirical best linear unbiased predictor in an orthogonal finite discrete spectrum linear regression model is derived and a comparison with the MSE of the best linear unbiased predictor in this model is made. It is shown that under weak conditions these two mean square errors are asymptotically the same.     

Modelling the spot prices of various coffee types

We investigate long-run relationships among the spot prices of four coffee types. Two cointegrating vectors emerge: one between the prices of Arabica coffee varieties, and the other one between Unwashed Arabicas and Robusta. A persistence profile analysis shows a more rapid adjustment to equilibrium for the first compared to the second vector due to the fact that the former involves the Arabica coffees, which are more homogeneous. Adjustment is relatively fast, implying that economic forces act rapidly and discrepancies in the equilibrium relationships are short-lived. We also find evidence of non-linear adjustment back to equilibrium; when prices are too high, adjustment takes place at a slower rate than when they are too low.     

ARBITRAGE BOUNDS FOR PRICES OF WEIGHTED VARIANCE SWAPS

We develop a theory of robust pricing and hedging of a weighted variance swap given market prices for a finite number of co‐maturing put options. We assume the put option prices do not admit arbitrage and deduce no‐arbitrage bounds on the weighted variance swap along with super‐ and sub‐replicating strategies that enforce them. We find that market quotes for variance swaps are surprisingly close to the model‐free lower bounds we determine. We solve the problem by transforming it into an analogous question for a European option with a convex payoff. The lower bound becomes a problem in semi‐infinite linear programming which we solve in detail. The upper bound is explicit. We work in a model‐independent and probability‐free setup. In particular, we use and extend Föllmer's pathwise stochastic calculus. Appropriate notions of arbitrage and admissibility are introduced. This allows us to establish the usual hedging relation between the variance swap and the “log contract” and similar connections for weighted variance swaps. Our results take the form of a FTAP: we show that the absence of (weak) arbitrage is equivalent to the existence of a classical model which reproduces the observed prices via risk‐neutral expectations of discounted payoffs.     

Intersectoral wage linkages: the case of Sweden

The purpose of this study is to investigate whether wage-setting in certain sectors of the Swedish economy affects wage-setting in other sectors. The theoretical background is the Scandinavian model of inflation, which states that wage-setting in the sectors exposed to international competition lead wage-setting in the sheltered sectors of the economy. The Johansen maximum likelihood cointegration approach is applied to quarterly data on Swedish sector wages for the period 1980:1–2002:2. Different vector error correction (VEC) models are created, based on assumptions as to which sectors are exposed to international competition and which are not. Granger causality tests are then carried out in the different restricted/unrestricted VEC models to test for sector wage leadership. The Granger causality tests provide strong evidence for the presence of intersectoral wage causality, but no evidence of a wage-leading role for the internationally exposed manufacturing sector.      

重心位置误差对隔振系统性能的影响

论述了机载电子设备的重心位置与隔振系统的几何中心不重合误差对其安装架隔振系统性能的影响，并提出了解决该问题的方法。     

中部地区固定资产投资与经济增长关系的实证分析——以阜阳市为例

本文对阜阳市固定资产投资与经济增长之间的关系进行了定量分析,通过建立误差修正模型来反映二者之间长期均衡和短期波动关系,分析固定资产投资对当地经济增长的贡献水平,结果表明固定资产投资能有效的拉动当地经济增长。