中国要素产出弹性估计

要素产出弹性是分析经济增长的绩效、特征与可持续性等问题的重要参数。我国改革开放以来要素产出弹性估计结果是:1978-2004年,资本的产出弹性平均为0.56,劳动的产出弹性平均为0.44,并且资本的产出弹性呈不断下降趋势,而劳动产出弹性呈不断上升趋势;东部地区的资本产出弹性高于中部地区,中部地区又高于西部地区;全要素生产率年均增长率在3.7%~3.9%之间。  

Logistic模型参数估计与我国城市化水平预测

本文探讨了Logistic模型描述城市化过程中的合理性．提出模型参数估计的新方法．计算和预测了我国的城市化水平及其发展趋势。新方法简单实用，预测精度高。  

基于创新扩散的快速消费品品牌生命周期研究

品牌生命周期研究主要集中于模型构建、参数估计、阶段划分及相应营销策略研究等方向。本文基于创新扩散理论，在考虑品牌重复购买因素并结合品牌形成机理的基础上，提出快速消费品品牌生命周期模型；并应用非线性最小二乘法进行参数估计，且通过实例对模型进行检验；根据首次购买和重复购买的变化趋势，提出了较为科学合理的阶段划分方法，从而为企业做出营销决策提供理论依据。  

A New Economy Forecasting Method Based on Data Barycentre Forecasting Method

A new and useful method of technology economics, parameter estimation method, was presented in light of the stability of gravity center of object in this paper. This method could deal with the fitting and forecasting of economy volume and could greatly decrease the errors of the fitting and forecasting results. Moreover, the strict hypothetical conditions in least squares method were not necessary in the method presented in this paper, which overcame the shortcomings of least squares method and expanded the application of data barycentre method. Application to the steel consumption volume forecasting was presented in this paper. It was shown that the result of fitting and forecasting was satisfactory. From the comparison between data barycentre forecasting method and least squares method, we could conclude that the fitting and forecasting results using data barycentre method were more stable than those of using least squares regression forecasting method, and the computation of data barycentre forecasting method was simpler than that of least squares method. As a result, the data barycentre method was convenient to use in technical economy.  

农户收入结构效率变动及其增收效应的DEA分析--以山西农户为例

农户收入结构效率变动能够综合反映市场化进程中农户家庭经营结构、规模、效率的走势。实证表明,不同市场化程度农户在各业上的效率存在差异性,其中高市场化程度农户在家庭经营中的效率高于中低市场化程度农户;而中低市场化程度的农户在外出劳务上的效率高于市场化程度较高的农户。同时,各业TFP增长的差异性使得中低市场化程度农户的非农业收入增长率较高,而高市场化程度农户在农业以及外出劳务收入上的增长率较高。  

Assimilation of Time Series Data into a Dynamic Bioeconomic Fisheries Model: An Application to the North East Arctic Cod Stock

This paper combines the elegant technique of Data Assimilation and a Monte Carlo procedure to analyze time series data for the North East Arctic Cod stock (NEACs). A simple nonlinear dynamic resource model is calibrated to time series data using the variational adjoint parameter estimation method and the Monte Carlo technique. By exploring the efficient features of the variational adjoint technique coupled with the Monte Carlo method, optimal or best parameter estimates with their error statistics are obtained. Thereafter, the weak constraint formulation resulting in a stochastic ordinary differential equation (SODE) is used to find an improved estimate of the dynamical variable, i.e. the stock. Empirical results show that the average fishing mortality imposed on the NEACs is about 16% more than the intrinsic growth rate of the biological species.  

Implementing a Stochastic Bioeconomic Model for the North-East Arctic Cod Fishery

In this paper, we study how a stochastic model can be used to determine optimal levels of exploitation of the North-East Arctic Cod (NEAC, Gadus morhua). A non-critical depensation growth model is developed for this species in order to examine both deterministic and stochastic cases. Estimation of the biological and the noise term parameters in the stochastic biomass dynamics is based on simulation and use of empirical NEAC data sets for the years 1985–2001. The Kolmogorov– Smirnov criterion-based method is used to estimate both drift and diffusion parameters simultaneously. The estimates turn out to be reasonable and the model is able to capture the salient features of the NEAC dynamics. The model is used to derive optimal levels of exploitation with different diffusion functions in the stochastic case and various discount rates in the deterministic case. Optimal catches are compared to the historical catch records. A striking feature of our modeling results is that these records fit surprisingly well with the infinite discounting tracks, i.e., the bliss solution. Our general results indicate that over fishing has resulted from lack of long-term planning as well as inadequate response to uncertainty.  

Estimation of Biological and Economic Parameters of a Bioeconomic Fisheries Model Using Dynamical Data Assimilation

A new approach of model parameter estimation is used with simulated measurements to recover both biological and economic input parameters of a natural resource model. The data assimilation technique is the variational adjoint method (VAM) for parameter estimation. It efficiently combines time series of artificial data with a simple bioeconomic fisheries model to optimally estimate the model parameters. Using identical twin experiments, it is shown that the parameters of the model can be retrieved. The procedure provides an efficient way of calculating poorly known model parameters by fitting model results to simulated data. In separate experiments with exact and noisy data, we have demonstrated that the VAM can be an efficient method of analyzing bioeconomic data.  

高等教育能打破社会阶层固化吗?--基于有序probit半参数估计及夏普里值分解的实证分析

文章基于2013年中国综合社会调查(CGSS2013)数据，首先运用有序probit 模型的半参数估计方法检验高等教育对社会阶层的影响，其次采用最新发展的基于 R2的夏普里值方法测度高等教育对社会分层形成的贡献率，并从区域视角管窥经济发展和市场化转型条件下高等教育受影响的演进趋势。结果显示：(1)接受过高等教育的居民，确实拥有更高的社会阶层评估。但若剔除家庭背景带来的接受高等教育机会的差距，高等教育促进社会阶层流动的能力明显弱化。基于R2的夏普里值分解表明，高等教育变量的贡献率不到10%，撇去高等教育的代际传递效应后，净效应更低。(2)东部地区有微弱的证据显示高等教育带来的社会阶层提升效应正在展现。无论是从总贡献率还是分解后的直接贡献率看，东部地区的百分比贡献都要高于中西部地区。这说明随着经济发展和市场化改革的推进，高等教育改善社会分层的效果有可能会强化。(3)影响社会分层差异最重要的因素为家庭过去的社会阶层，即社会阶层分布存在明显的代际传递现象。另外，个体特征及经济特征也是影响社会分层的重要因素。文章研究显示，要进一步推进开放型社会阶层的形成，需要在构建市场化导向能力本位的新型社会流动体系制度框架下，确立更为公平的高等教育竞争机制及补偿机制。