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1.
While it is often recognised that agricultural technology adoption decisions are intertwined and best characterised by multivariate models, typical approaches to examining adoption and impacts of agricultural technology have focused on single technology adoption choice and ignored interdependence among technologies. We examine farm‐ and market‐level impacts of multiple technology adoption choices using comprehensive household survey data collected in 2010/11 and 2012/13 in Ethiopia. Economic surplus analysis combined with panel data switching endogenous regression models are used to compute the supply shift parameter (K‐shift parameter), while at the same time controlling for the endogeneity inherent in agricultural technology adoption among farmers. We find that our improved technology set choices have significant impacts on farm‐level maize yield and maize production costs, where the greatest effect appears to be generated when various technologies are combined. The change in maize yield and production costs results in an average 26.4% cost reduction per kilogram of maize output (the K‐shift parameter). This increases the producer and consumer surpluses by US$ 140 and US$ 105 million per annum, respectively. These changes in economic surplus help to reduce the number of poor people by an estimated 788 thousand per year. We conclude that deliberate extension efforts and other policies that encourage integration of technologies are important for maize technologies to yield their full potential at both farm and market levels.  相似文献   
2.
The objective of this paper is twofold. First, it develops a prediction system to help the credit card issuer model the credit card delinquency risk. Second, it seeks to explore the potential of deep learning (also called a deep neural network), an emerging artificial intelligence technology, in the credit risk domain. With real-life credit card data linked to 711,397 credit card holders from a large bank in Brazil, this study develops a deep neural network to evaluate the risk of credit card delinquency based on the client's personal characteristics and the spending behaviours. Compared with machine-learning algorithms of logistic regression, naive Bayes, traditional artificial neural networks, and decision trees, deep neural networks have a better overall predictive performance with the highest F scores and area under the receiver operating characteristic curve. The successful application of deep learning implies that artificial intelligence has great potential to support and automate credit risk assessment for financial institutions and credit bureaus.  相似文献   
3.
本文利用全国592个国家级贫困县的数据,采用空间计量模型实证分析了普惠金融对县域资金外流的影响,并验证了贫困县资金外流是否会产生致贫效应。本文研究发现:如果普惠金融只注重解决贫困地区对金融机构的接触性排斥,会进一步加剧资金外流,对减贫产生负向影响,即存在显著的致贫效应。这种致贫效应具有明显的空间外溢性,邻近县域的贫困状况在很大程度上会彼此“传染”,并具有空间衰减特征的地理边界。因而需要客观认识普惠金融的本质,有针对性地选择恰当有效的实施载体,解决好对信贷产品等关键金融服务的使用性排斥问题。  相似文献   
4.
中国特色社会主义的伟大实践使我国告别了贫困,实现了从站起来到富起来的飞跃,坚持走中国特色社会主义道路,坚持贯彻党的基本理论、基本路线、基本方略,坚持“五位一体”总体布局,坚持“四个全面”战略布局,贯彻新发展理念,建设现代化经济体系,一定能够使我们迈过“中等收入陷阱”,实现两个百年的发展目标,进一步提升“四个自信”,为解决人类问题进一步贡献中国智慧和中国方案。  相似文献   
5.
This article examines the welfare impact of foreign direct investment (FDI) in a panel of 20 African countries over the period 2000–2013. We explore the multifactor and nonmonetary measures of welfare and the nonlinear effect of FDI on welfare. We used the Driscoll and Kraay standard errors and augmented mean group (AMG) estimator by Eberhardt and Teal (2010) to account for cross‐sectional dependency, endogeneity, and heterogeneity within panel units. The results indicate that although FDI is welfare enhancing, the nonlinear terms report mixed findings. When a multifactor indicator is employed, the increase in the nonlinear term is lower than the linear part. However, there is strong evidence that FDI is ultimately welfare enhancing when a nonmonetary indicator is employed. From an international business perspective, the findings have unlocked the welfare effects of international business on African host economies. International businesses through FDI can enhance welfare in Africa countries. However, the optimal efficacy of FDI‐welfare impact differs across the various dimensions of welfare. © 2017 Wiley Periodicals, Inc.  相似文献   
6.
区域贫困程度测度是精准施策,打赢脱贫攻坚战的重要依据。在对已有贫困程度测度方法回顾的基础上,文章通过分析深度贫困地区的贫困特征,提出区域贫困程度测度原则,构建区域贫困程度测度指标体系,并以甘肃为例对深度贫困县贫困程度进行测算,进一步了解深度贫困县的贫困现状、集中区域、影响因素及贫困差距等,以期为地方打赢脱贫攻坚战提供借鉴。  相似文献   
7.
以福建省赤溪村农户为调研对象,运用相关性检验和二元Logistic回归模型对影响农户参与乡村旅游扶贫的因素进行研究。研究发现:农户参与乡村旅游扶贫的比例较高,但是旅游经营的项目单一;农户的学历、劳动力数量、地理位置、参与乡村旅游扶贫培训的次数对农户参与乡村旅游有显著地正向影响作用;农户生计资本和对旅游发展的感知中的权力关系、可借款能力、家庭年收入、了解乡村旅游扶贫政策、有资源用于发展乡村旅游也是影响农户参与的主要因素。在此基础上,提出了加大扶贫政策宣传力度,提高旅游扶贫政策利用程度完善旅游相关基础设施,扩大农户扶贫资金来源渠道,完善扶贫资金体系,完善旅游供给侧创新旅游经营模式,实行多项扶持的针对性建议。  相似文献   
8.
我国林业扶贫工作的主要问题及优化措施研究   总被引:2,自引:0,他引:2  
林业扶贫是当前我国扶贫工作的重要内容。通过介绍开展林业扶贫工作的政策背景、理论背景以及经济背景,分析林业扶贫工作开展过程中存在的基础设施落后、针对性差等问题,提出了因地制宜,互联网+林业扶贫,鼓励社会资本进入扶贫工作、志智双扶等应对措施。  相似文献   
9.
A number of chronic poverty measures are now empirically applied to quantify the prevalence and intensity of chronic poverty, vis‐à‐vis transient experiences, using panel data. Welfare trajectories over time are assessed in order to identify the chronically poor and distinguish them from the non‐poor, or the transiently poor, and assess the extent and intensity of intertemporal poverty. We examine the implications of measurement error in the welfare outcome for some popular discontinuous chronic poverty measures, and propose corrections to these measures that seeks to minimize the consequences of measurement error. The approach is based on a novel criterion for the identification of chronic poverty that draws on fuzzy set theory. We illustrate the empirical relevance of the approach with a panel dataset from rural Ethiopia and some simulations.  相似文献   
10.
Despite reductions in poverty generally, recent trends in Latin American countries show processes of both de-feminization and re-feminization of poverty. A rise in the numbers of women to men living in income-poor households has occurred despite feminized anti-poverty programs, most notably conditional cash transfers (CCTs), which target resources to women. This paper shows that methodological differences in what, how, and who is the focus of measurement may influence patterns of poverty “feminization.” It also suggests that feminized policy interventions might in themselves be playing a role in the re-feminization of poverty, not least because of data and definitional limitations in the way female-headed households and, relatedly, women’s poverty are understood. The somewhat paradoxical interactions between the feminization of household headship, the feminization of poverty, and the feminization of anti-poverty programs present interesting challenges for redressing gender gaps in poverty within the 2030 Agenda for Sustainable Development.  相似文献   
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