Comparison of different estimation methods in growth curve models for categorical data: A simulation study

This simulation study aims at investigating the performance of maximum likelihood and weighted least-square estimation approaches in growth curve models with categorical data. The goodness-of-fit indices were compared with a number of scenarios (different trajectories, sample sizes, replications, and number of categories). The results show that when the number of categories and replications are small, using weighted least-square estimating methods leads to better goodness-of-fit indices. However, when the number of categories and replications are large, both maximum likelihood and weighted least squares in estimating methods will result in similar fit indices.     

Growth of tuber crops and almost sure band for quantiles

Some tuber crops are governed by memoryless property of exponential distribution leading to a mixture distribution with heavy tail. Quantile-based estimators may then be appropriate than mean as a measure of central tendency. We prove almost sure representation theorems for sample quantiles in a general setup of U statistics, under slightly stronger assumption than assuming the existence of a continuously differentiable distribution function F for the kernel h. We obtain almost sure (a.s.) upper and lower estimate for F^{? 1}(p), p ∈ (0, 1) as a band for p varying. As an application, dataset arising from two varieties of potato cultivation are analyzed.     

Growth impact of climate change and response policies: The advanced climate change long-term (ACCL) model

This paper provides a tool to build climate change scenarios to forecast Gross Domestic Product (GDP), modelling both GDP damage due to climate change and the GDP impact of mitigating measures. It adopts a supply-side, long-term view, with 2060 and 2100 horizons. It is a global projection tool (30 countries/regions), with assumptions and results both at the world and the country/regional level. Five different types of energy inputs are taken into account according to their CO₂ emission factors. Full calibration is possible at each stage, with estimated or literature-based default parameters. Compared to other models, it provides a comprehensive modelisation of Total Factor Productivity (TFP), which is the most significant determinant of the GDP projected path. We present simulation results of different energy policy scenarios. They illustrate both the “tragedy of the horizon” and the “tragedy of the commons”, which call for a policy framework that adequately integrates a long run perspective, through a low-enough discount rate and an effective intergenerational solidarity as well as international cooperation.     

On the analysis of unbalanced two-level supersaturated designs via generalized linear models

Supersaturated designs (SSDs) are factorial designs in which the number of experimental runs is smaller than the number of parameters to be estimated in the model. While most of the literature on SSDs has focused on balanced designs, the construction and analysis of unbalanced designs has not been developed to a great extent. Recent studies discuss the possible advantages of relaxing the balance requirement in construction or data analysis of SSDs, and that unbalanced designs compare favorably to balanced designs for several optimality criteria and for the way in which the data are analyzed. Moreover, the effect analysis framework of unbalanced SSDs until now is restricted to the central assumption that experimental data come from a linear model. In this article, we consider unbalanced SSDs for data analysis under the assumption of generalized linear models (GLMs), revealing that unbalanced SSDs perform well despite the unbalance property. The examination of Type I and Type II error rates through an extensive simulation study indicates that the proposed method works satisfactorily.     

Forecasting, growth management and public policy decision making

This paper's objective is to describe the interplay between forecasting and decision making. It shows how a forecast helped shape public policy and, in turn, how public policy influenced a forecast, within the context of the growth management effort underway in the San Diego region. The forecast identified economic challenges and land use issues facing the region and public policy actions were developed to address them. Normative forecasting best describes the relationship between the forecast and these public policy decisions. This active approach to forecasting involves first deciding what future outcome is desirable and, then, designing policies and actions to achieve these outcomes.     

论智力资源对物质资源的替代

本文认为,智力资源对物质资源不断进行替代,是一个普遍的和重要的经济规律;认识并利用这一规律,对我国经济发展具有相当的必要性、迫切性和现实性。基此,本文对智力资本替代物质资本这一经济规律进行了初步的研究:说明了这一规律的含义、表现、原因及作用,并在此项研究基础上对我国现实的经济发展提出了自己的一点思考。     

我国图书馆2.0研究领域论文的计量规律分析

目前,图书馆2.0文献正呈指数模式快速增长,发表该领域论文的期刊多为图书情报方面的期刊。通过关键词词频分析得出图书馆2.0、web2.0、高校图书馆、个性化服务、数字图书馆、图书馆服务、OPAC、图书馆员和服务模式等问题是国内的研究重点;维基、信息共享空间、Dru-pal、RSS、博客、信息服务等代表着图书馆2.0领域的最新发展趋势。     

小新月菱形藻固定化培养初步研究

用褐藻酸钙对小新月菱形藻进行固定化培养实验,测定不同胶粒大小、胶珠密度、CaCl2浓度及不同接种量对该藻的影响,比较了自由化生长与固定化细胞的生长曲线。小新月菱形藻在褐藻酸钙凝胶中仍具有呼吸和光合作用的能力。球径为3.5mm,CaCl2浓度为2%时,细胞生长快,每50mL培养液中加入200个胶珠时细胞生长量大,接种量不能低于104个细胞/mL。与游离的小新月菱形藻相比,固定化小新月菱形藻生长慢,但生长周期长。     

断裂在文本与秩序之间——《劳动合同法》立法元问题反思

新《劳动合同法》在施行后出现严重的法律规避现象,因此特别需要反思如此一个立法元问题:意旨良善的法律文本何以无法顺利生成良好的预期秩序?论文通过探析对从文本到秩序生成机理,确认了立法正当性追问对于此生成机理的特别意义。为消解立法正当性追问所蕴含的程序正当与实体正义两个面相之内在张力,特别考察了在中国语境下,立法正当程序所具备的可促进预期秩序生长的反思性整合的特别功效。此种探源可为理解相关法律规避现象提供更深切的理论参照。     

教育对经济增长贡献的计量分析--以云南省为例

作者采用劳动简化法和相关系数法以云南省为例对教育对经济增长的作用进行了量化分析,结果表明:教育对经济增长的贡献率大约在40%左右,人均教育事业费和人均国内生产总值的相关性为0 98。这些数据说明了教育在地方经济建设中具有重要的作用。