几种中国农村居民食品消费需求模型的比较研究

本文选取6种需求系统模型,运用中国30个省份农民食品消费截面数据进行了比较研究,得到以下结论:以希克斯需求为理论依据的需求模型拟合优度优于以马歇尔需求为理论依据的需求模型;需求支出弹性及其标准差比较显示,QUAIDS模型的估计结果表现最优,而QES模型的表现最差;数据的秩检验结果显示,3秩模型更适合于研究中国农民食品消费,说明现有研究可进一步改善。因此农民对食物消费需求结构更趋于合理化,但较低的收入水平和较差的消费环境仍是制约农民食品消费结构升级的重要因素。     

A customer’s utility measure based on the reliability of multi-state systems

The main focus of this paper is on the development of utility measures for dynamic multi-state systems that have M + 1 discrete states of working efficiency. To develop the utility measures for multi-state systems, we assume that the degradation of the multi-state systems follows a non-homogeneous semi-Markov process together with a backward recurrence time process and that the system can directly degrade into any lower state. The measure considers the immediate utility derived from the state of the system occupancy and the utility due to the system survival expectations derived from its reliability. Moreover, in order to measure the customer’s cumulative utility, the discounted non-homogeneous continuous time semi-Markov process with rewards is implemented. In such a way, the higher order moments of the reward process can be evaluated and then, in particular, the expectation and the standard deviation of the consumer’s accumulated discounted utility. These statistic indices are useful both to the industry in order to compare different system designs offered by the market and to the market itself, in order to know the customer’s utility deriving from the goods she/he consumes. Finally, a numerical example shows the possibility of implementing the model in real-life problems.     

On the robustness of the competitive equilibrium: Utility-improvements and equilibrium points

We show that the set of competitive equilibrium points of a pure exchange economy are the equilibrium points of a broader class of better-response demands than the usual utility-maximizing demand functions. The better-response demands are derived from assigning weights to all commodity bundles with higher utility than the current commodity bundle, with the greatest weights being placed on the commodity bundles with the highest utility gain. The usual utility-maximizing demand functions are then those in which the weight on the utility-maximizing bundle is one. We also show that these better-response demands belong to a large class of response maps that are generated by monotonic transformations of the utility functions and/or monotonic transformations of the weights assigned to the commodity bundles.     

Inference of Seasonal Cointegration: Gaussian Reduced Rank Estimation and Tests for Various Types of Cointegration*

An extension of Gaussian reduced rank estimation of Ahn and Reinsel (Journal of Econometrics, Vol. 62, pp. 317–350, 1994) to seasonal periods other than four is presented. Simple adjustments for estimation that are necessary because of complex‐valued seasonal unit roots are presented in detail and the asymptotic distribution of the estimators that takes the same form as that in Ahn and Reinsel (1994) is derived. Tests for contemporaneous cointegration and common polynomial cointegrating vectors (PCIVs) for different seasonal unit roots are presented. Finite sample properties are briefly examined through a small Monte Carlo simulation study and a numerical example is presented to illustrate the methods.     

Testing and imposing Slutsky symmetry in nonparametric demand systems

Maximization of utility implies that consumer demand systems have a Slutsky matrix which is everywhere symmetric. However, previous non- and semi-parametric approaches to the estimation of consumer demand systems do not give estimators that are restricted to satisfy this condition, nor do they offer powerful tests of this restriction. We use nonparametric modeling to test and impose Slutsky symmetry in a system of expenditure share equations over prices and expenditure. In this context, Slutsky symmetry is a set of nonlinear cross-equation restrictions on levels and derivatives of consumer demand equations. The key insight is that due to the differing convergence rates of levels and derivatives and due to the fact that the symmetry restrictions are linear in derivatives, both the test and the symmetry restricted estimator behave asymptotically as if these restrictions were (locally) linear. We establish large and finite sample properties of our methods, and show that our test has advantages over the only other comparable test. All methods we propose are implemented with Canadian micro-data. We find that our nonparametric analysis yields statistically significantly and qualitatively different results from traditional parametric estimators and tests.     

The relationship between revealed preference and the Slutsky matrix

This paper presents a method of calculating the utility function from a smooth demand function whose Slutsky matrix is negative semi-definite and symmetric. The calculated utility function is the unique upper semi-continuous function corresponding with the demand function. Moreover, we present an axiom for demand functions. We show that under the strong axiom, this new axiom is equivalent to the existence of the corresponding continuous preference relation. If the demand function obeys this axiom, the calculated utility function is also continuous. Further, we show that the mapping from the demand function into a continuous preference relation is continuous, which ensures the applicability of our results for econometrics. Moreover, if this demand function satisfies the rank condition, then our utility function is smooth. Finally, we show that under an additional axiom, the above results hold even if the demand function has corner solutions.     

The Likelihood Ratio Test for the Rank of a Cointegration Submatrix*

This paper proposes a likelihood ratio test for rank deficiency of a submatrix of the cointegrating matrix. Special cases of the test include the one of invalid normalization in systems of cointegrating equations, the feasibility of permanent–transitory decompositions and of subhypotheses related to neutrality and long‐run Granger noncausality. The proposed test has a chi‐squared limit distribution and indicates the validity of the normalization with probability one in the limit, for valid normalizations. The asymptotic properties of several derived estimators of the rank are also discussed. It is found that a testing procedure that starts from the hypothesis of minimal rank is preferable.     

Differentiability properties of rank-linear utilities

We study the differentiability properties of concave functionals defined as integrals of the quantile. These functionals generalize the rank dependent expected utility and are called rank-linear utilities in decision theory. Their superdifferential is described as well as the set of random variables where they are Gâteaux-differentiable. Our results generalize those obtained for the rank dependent expected utility in Ref. [Carlier, G., Dana, R.-A., 2003. Core of a convex distortion of a probability. Journal of Economic Theory 113, 199–222.].     

Estimation in large and disaggregated demand systems: an estimator for conditionally linear systems

Empirical demand systems that do not impose unreasonable restrictions on preferences are typically non-linear. We show, however, that all popular systems possess the property of conditional linearity. A computationally attractive iterated linear least squares estimator (ILLE) is proposed for large non-linear simultaneous equation systems which are conditionally linear in unknown parameters. The estimator is shown to be consistent and its asymptotic efficiency properties are derived. An application is given for a 22-commodity quadratic demand system using household-level data from a time series of repeated cross-sections. Copyright © 1999 John Wiley & Sons, Ltd.     

构建以就业为导向的物流教育体系

充分发挥行业及企业在高职教育及实践中的作用,企业积极参与学校决策、管理、教学、考评等工作,实现学校和企业对学生的共同培养,使物流专业围绕市场需求实现教育效用最大化。以就业为导向的物流教育体系理论的提出,确立了基于五个方面的具体表现:加强实践教学、加强实习基地建设、订单模式培养、多证书制和双向式教学。这些理念是依据实际的工作岗位需求确立的,其目的是为了满足市场需求,提升就业质量。因此,实施学习领域课程体系的开发,其本质是围绕市场需求,以就业为导向的、基于工作过程的教学实施过程。     

Measuring utility from demand

This study presents a new method to calculate a preference relation from a demand function. Our method works well under the weak axiom and can calculate a smooth utility function if the demand function obeys the strong axiom. Further, if the demand function is derived from a customary utility function, our method restores the original preference. Our method provides a complete and rigorous proof of Samuelson’s conjecture. In addition to these results, we guarantee the recoverability: i.e., the uniqueness of the preference relation corresponding to a demand function.     

Structure of the demand function and Pareto optimal set with natural boundary conditions

We consider utility functions defined on P?, the closure of the positive orthant of R^l, that satisfy the differentiable monotonicity and differentiable convexity conditions. We show that the demand function derived from such a utility function is piecewise smooth in a strong sense. We use this result to show that the Pareto optimal subset of a pure exchange economy derived from the kind of utility functions we consider is generically the union of a finite number of compact manifolds-with-corners.     

Significance levels of linear rank tests using Edgeworth expansions

We study one aspect of applying Edgeworth expansions to linear rank statistics. Since the use of such expansions is often recommended already for moderate sample sizes we investigate for this case the gain of accuracy for the level of significance of some linear rank tests when their critical values are derived from an Edgeworth expansion instead of from a normal approximation. We verify Does' conditions (1983) for the validity of the expansions for four rank statistics of general interest and show by a numerical study that an Edge-worth expansion does not outperform the normal approximation in all situations. A considerable improvement shows up however for the Klotz test at the 5% level.     

Characterizing systems of distributions by quantile measures

Modelling an empirical distribution by means of a simple theoretical distribution is an interesting issue in applied statistics. A reasonable first step in this modelling process is to demand that measures for location, dispersion, skewness and kurtosis for the two distributions coincide. Up to now, the four measures used hereby were based on moments.
In this paper measures are considered which are based on quantiles. Of course, the four values of these quantile measures do not uniquely determine the modelling distribution. They do, however, within specific systems of distributions, like Pearson's or Johnson's; they share this property with the four moment-based measures.
This opens the possibility of modelling an empirical distribution—within a specific system—by means of quantile measures. Since moment-based measures are sensitive to outliers, this approach may lead to a better fit. Further, tests of fit—e.g. a test for normality—may be constructed based on quantile measures. In view of the robustness property, these tests may achieve higher power than the classical moment-based tests.
For both applications the limiting joint distribution of quantile measures will be needed; they are derived here as well.     

Estimating class‐specific parametric models under class uncertainty: local polynomial regression clustering in an hedonic analysis of wine markets

We introduce a method for estimating multiple class regression models when class membership is uncertain. The procedure—local polynomial regression clustering—first estimates a nonparametric model via local polynomial regression, and then identifies the underlying classes by aggregating sample observations into data clusters with similar estimates of the (local) functional relationships between dependent and independent variables. Finally, parametric functions specific to each class are estimated. The technique is applied to the estimation of a multiple‐class hedonic model for wine, resulting in the identification of four distinct wine classes based on differences in implicit prices of the attributes. Copyright © 2009 John Wiley & Sons, Ltd.     

Locally Most Powerful and Other Rank Tests for Independence – with a Contaminated Weighted Alternative

Several authors in the literature have attempted the quantification of the concept of stochastic dependence for bivariate distribution. Two weighted rank tests for testing independence against a weighted contamination alternative is proposed and their distributional properties are studied. We also derived a locally most powerful rank test for the alternative setting. The rank tests proposed are shown to be asymptotic locally most powerful for specific distributions.     

Specification and estimation of dynamic demand systems incorporating polynomial price response functions: An application to U.S. clothing imports

Numerous recent empirical demand studies utilize the habit formation and state variable approaches to describe dynamic demand behavior. In this paper, we suggest the introduction of polynomial price response functions as an alternative method of generating dynamic conditional demand systems. This approach allows direct estimation of the degree of price substitutability among products and the timing of price effects. The application presented here involves the estimation of dynamic CES and indirect additive translog demand systems for U.S. clothing imports. The estimated price response lag structures and matrices of long-run price elasticities are presented and analyzed. Also, the precision of the non-parametric price elasticity estimates is evaluated by computing approximate asymptotic standard errors.     

Theoretical tests of the rational expectations hypothesis in economic dynamical models

This paper examines different theoretical stability tests of infinite-horizon rational expectations equilibria. These ‘tests’ have different status: two of them express that the considered equilibrium is ‘isolated’ [neither (non-sunspot) equilibria (test 1) nor (well-behaved) sunspot equilibria exist in a neighbourhood (test 2)] and two of them are learning criteria [either standard ‘evolutive learning’ (test 3) or game-theoretical ‘eductive’ learning (test 4)]. Surprisingly, these four tests select the same steady state equilibria in the class of one-dimensional one-step-forward looking economic models. The extension of this equivalence theorem to n-dimensional and then more complex systems is discussed.     

On Tests for a Normal Mean with Known Coefficient of Variation

Hinkley (1977) derived two tests for testing the mean of a normal distribution with known coefficient of variation (c.v.) for right alternatives. They are the locally most powerful (LMP) and the conditional tests based on the ancillary statistic for μ. In this paper, the likelihood ratio (LR) and Wald tests are derived for the one‐ and two‐sided alternatives, as well as the two‐sided version of the LMP test. The performances of these tests are compared with those of the classical t, sign and Wilcoxon signed rank tests. The latter three tests do not use the information on c.v. Normal approximation is used to approximate the null distribution of the test statistics except for the t test. Simulation results indicate that all the tests maintain the type‐I error rates, that is, the attained level is close to the nominal level of significance of the tests. The power functions of the tests are estimated through simulation. The power comparison indicates that for one‐sided alternatives the LMP test is the best test whereas for the two‐sided alternatives the LR or the Wald test is the best test. The t, sign and Wilcoxon signed rank tests have lower power than the LMP, LR and Wald tests at various alternative values of μ. The power difference is quite large in several simulation configurations. Further, it is observed that the t, sign and Wilcoxon signed rank tests have considerably lower power even for the alternatives which are far away from the null hypothesis when the c.v. is large. To study the sensitivity of the tests for the violation of the normality assumption, the type I error rates are estimated on the observations of lognormal, gamma and uniform distributions. The newly derived tests maintain the type I error rates for moderate values of c.v.     

Nonlinear dynamical systems and inventory management

Surprisingly, deterministic time series can generate highly irregular, random-appearing trajectories. These deterministic time series result from nonlinear dynamical systems of differential or difference equations. The random appearance displayed by these systems is called nonlinear dynamical complexity. Properties of nonlinear complex systems include aperiodic random appearance, sensitive dependence on initial conditions and model parameters, and nonstationarity. Experiments involving the operation of simulated business environments and theoretical nonlinear dynamical models for inventory are reviewed to explore motivating factors that can give rise to demand with nonlinear complexities. The experimental and theoretical evidence reviewed indicates that nonlinear complexities in demand have significant implications for inventory management. Thus, researchers and practitioners in inventory management need to consider these properties when choosing inventory management methods. Characteristics of nonlinear dynamical systems and their implications for inventory management are presented in this paper. The use of the Brock, Dechert, and Scheinkman (1987) (BDS) test for nonlinear dependence is demonstrated on actual demand data.