城市滨水旧住区问题分析及对策研究——以上海市长风新村街道沿河旧住区为例

一、引言 进入21世纪以来,城市滨水地区由于其悠久的发展历史、丰厚的文化底蕴和重要的城市区位,成为政府、公众和开发商关注的焦点,因此,滨水地带的复兴成为中国城市发展的中心议题之一.     

Labor force participation and juvenile delinquency in Taiwan: a time series analysis

This study examines the null hypothesis of Granger no-causality between labor force participation (LFP) and juvenile delinquency in Taiwan. In order to explore this issue more thoroughly, this study adopts the approach proposed by Toda and Yamamoto (1995, Journal of Econometrics, 66(1–2), 225–250). It uses official time-series data provided by the Government of Taiwan. After estimating both a four- and five-variable VAR system, one that substitutes both male and female LFP rates for the aggregate LFP rate, the primary findings of this study reveal the following: The higher the past juvenile crime rate, the lower the future aggregate and female LFP rate will be. In addition, the higher the past male LFP rate, the higher the future juvenile crime rate will be. These findings are quite robust in terms of different lag-length structures.

论巴西在第二次世界大战期间的作用

第二次世界大战期间,巴西加入到世界反法西斯阵营,源源不断地供应盟军战略物资,派兵作战,积极配合盟军的军事行动,从政治、经济和军事各方面贡献出自己的人力、物力和财力,为世界反法西斯战争取得最终胜利铺平了道路。     

现代企业演化理论:方法论、核心概念及其解释逻辑

基于奥地利学派的知识理论,企业演化的方法论应是个体与环境的互动主义。现代企业演化理论的核心概念是企业家精神、适应性学习和资本结构等,以此为基础建立的启发式的企业演化逻辑,可用于考察企业在不同的演化环境下所采取的不同内外部协调机制(紧密或松散)、学习模式以及知识类型(默会或编码)。此外,企业学习过程和选择过程是交互作用的,企业的创新活动必须考虑时间因素,这将使企业演化变得更加复杂。     

Transparency and Resource Allocation of Grassroots Nonprofits in China

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Organizational transparency has become a prominent concern for the nonprofit sector as it expands globally. Transparency...     

近代广东商业人群在广西的分布面及其梯度差考详——粤港商业经济对广西经济辐射研究之二

文章从中国近代史上城镇经济主体——商业经济的角度切入,运用各类历史资料,分区逐县地确证广东商业人群以及所造成的“无东不成市”格局在全广西的分布范围,并揭示其在广西不同地域的程度等差和梯度分布状态。从而,以原始的生活场景原生态地呈现出粤港澳地区对广西经济辐射由东而西逐步推进、由城市而圩市逐层次渗透的基本节奏和客观规律。     

关于做好电视成就报道的思考

文章着重探讨了电视成就报道的创新方法,在理念上提出以个性化的受众为中心、结合电视传播特点、贴近工作实际;具体方法上则提出以四个方面为突破口,即:通过个人化的视角,贴近生活;用理性思维诠释热点;用情节化的叙述,加深人们的理解;调动多种电视表现手段,增强视觉冲击力.     

Quantile regression for large-scale data via sparse exponential transform method

In recent decades, quantile regression has received much more attention from academics and practitioners. However, most of existing computational algorithms are only effective for small or moderate size problems. They cannot solve quantile regression with large-scale data reliably and efficiently. To this end, we propose a new algorithm to implement quantile regression on large-scale data using the sparse exponential transform (SET) method. This algorithm mainly constructs a well-conditioned basis and a sampling matrix to reduce the number of observations. It then solves a quantile regression problem on this reduced matrix and obtains an approximate solution. Through simulation studies and empirical analysis of a 5% sample of the US 2000 Census data, we demonstrate efficiency of the SET-based algorithm. Numerical results indicate that our new algorithm is effective in terms of computation time and performs well for large-scale quantile regression.     

Instrumental variable based variable selection for generalized linear models with endogenous covariates

We study the variable selection problem for a class of generalized linear models with endogenous covariates. Based on the instrumental variable adjustment technology and the smooth-threshold estimating equation (SEE) method, we propose an instrumental variable based variable selection procedure. The proposed variable selection method can attenuate the effect of endogeneity in covariates, and is easy for application in practice. Some theoretical results are also derived such as the consistency of the proposed variable selection procedure and the convergence rate of the resulting estimator. Further, some simulation studies and a real data analysis are conducted to evaluate the performance of the proposed method, and simulation results show that the proposed method is workable.     

Policies for Recruiting Talented Professionals from the Diaspora: India and China Compared

Despite the continuous asymmetrical power relations between the Global North and South, the “global race for talent” is no longer a privilege enjoyed only by developed countries. Comparative analysis of policy content and effectiveness has attracted increasing interest. The examination of policy initiatives resulting in return migration of highly‐skilled migrants from the Global North to the Global South, however, remains inadequate. In this article, we provide a comparative analysis of policies targeting high‐level Chinese and Indian professionals including full‐time returnees. Two key differences in policy instruments and outcomes in the two countries are identified and they have implications for migration policies in other countries in the Global South and North.