首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   605篇
  免费   48篇
  国内免费   7篇
财政金融   76篇
工业经济   34篇
计划管理   135篇
经济学   146篇
综合类   51篇
运输经济   4篇
旅游经济   4篇
贸易经济   98篇
农业经济   32篇
经济概况   80篇
  2023年   12篇
  2022年   10篇
  2021年   19篇
  2020年   24篇
  2019年   38篇
  2018年   30篇
  2017年   27篇
  2016年   37篇
  2015年   25篇
  2014年   51篇
  2013年   61篇
  2012年   58篇
  2011年   45篇
  2010年   44篇
  2009年   33篇
  2008年   32篇
  2007年   24篇
  2006年   16篇
  2005年   15篇
  2004年   14篇
  2003年   7篇
  2002年   9篇
  2001年   1篇
  2000年   8篇
  1999年   6篇
  1998年   2篇
  1997年   2篇
  1996年   3篇
  1995年   2篇
  1992年   2篇
  1990年   1篇
  1986年   1篇
  1984年   1篇
排序方式: 共有660条查询结果,搜索用时 15 毫秒
1.
In this paper, we investigate how the 5‐year Swedish municipal bond yield has been related to the corresponding yield on government bonds during the period that the Riksbank has conducted unconventional monetary policy in terms of bond purchases. Using daily Swedish data on bond yields from February 2015 to January 2018, we first conduct an event study to assess the short‐run effects of the Riksbank's bond‐purchase announcements. We then estimate bivariate vector autoregressive models to study the dynamic relationship between the yields. Results from the event study suggest that the accumulated short‐run effect of the Riksbank's announcements was to lower the government bond yield by approximately 40 to 50 basis points and municipal bond yields by 30 to 35 basis points. Our vector autoregressive analysis indicates—in line with the event study—that an unexpected decrease in the government bond yield initially increases the municipal bond‐yield spread. However, after approximately 4 weeks, the effect has been reversed and the municipal bond‐yield spread is lower than it was initially. By conducting this analysis, we contribute to the understanding of the transmission of unconventional monetary policy.  相似文献   
2.
This paper combines the discrete wavelet transform with support vector regression for forecasting gold-price dynamics. The advantages of this approach are investigated using a relatively small set of economic and financial predictors. I measure model performance by differentiating between a statistically-motivated out-of-sample forecasting exercise and an economically-motivated trading strategy. Disentangling the predictors with respect to their time and frequency domains leads to improved forecasting performance. The results are robust compared to alternative forecasting approaches. My findings on the relative importances of such wavelet decompositions suggest that the influences of short-term and long-term trends are not stable over the full evaluation period.  相似文献   
3.
基于我国34个工业行业的面板数据,采用面板向量自回归模型(PVAR)对单位劳动力成本、汇率风险与我国出口之间的互动关系进行研究。结果显示,单位劳动力成本与出口存在双向抑制作用,即工资上涨不利于出口规模的扩张,出口也无法促进工资增长率的上升,但出口显著地提升了劳动生产率;汇率变动对出口脉冲响应函数值正负交替,呈现出不确定性,出口对汇率变动产生了超调现象;我国存在"进口引致出口"机制,且出口也能通过收入效应和汇率两条路径影响进口;产出对出口的影响关系呈现不确定性,但出口可以带动产出。在方差分解中,单位劳动力成本变量对出口具有较强的解释能力,是导致我国出口变动的主要因素,汇率变动对出口的短期解释能力较强,进口在长期解释能力较强,产出在三个不同时期解释能力基本一致,但出口对其他变量的解释能力普遍较低。  相似文献   
4.
This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.  相似文献   
5.
Using a panel vector autoregression approach and industry breakdown data for financial constraints obtained from the Bank of Japan's Tankan (Short‐Term Economic Survey of Enterprises in Japan) database, this study empirically investigates whether and how Japanese firms' financial constraints (internal and external) influence the response of Japanese sectoral exports to an exchange rate shock. Furthermore, we use the industry‐specific real effective exchange rate data developed by to allow for different movements of real effective exchange rates across industries. It is found that financial constraints have a significant influence on Japanese exports in response to exchange rate shocks. Japanese exporters with either lower internal financial constraints or external financial constraints are less affected by the yen's appreciation. In addition, if firms face high external financial constraints, only reducing the internal financial constraints cannot help them mitigate the impact of the yen's appreciation on their exports. Thus, an accommodative financial environment also plays an important role in alleviating the impact that the yen's appreciation has on Japanese exports.  相似文献   
6.
This study investigates price relationships between organic and conventional carrots, tomatoes, and lettuce in the U.S. utilizing Nielsen scanner data from 2006–2015. We employ a threshold vector error correction model (TVECM), threshold vector autoregressive model (TVAR), and threshold cointegration test to test whether market integration exists between organic and conventional vegetables as well as the existence of asymmetric price transmission. The results find positive long-run relationships between organic and conventional prices of carrots and tomatoes and show the existence of asymmetric price transmission in price pairs of lettuce and tomatoes. Our findings suggest that the price relationship between organic and conventional vegetables varies by characteristics, such as shelf life, volatility in the price premium, and substitutability.  相似文献   
7.
This paper investigates not only the question of whether there is exchange rate pass‐through (ERPT) but also the extent to which the pass‐through is asymmetric or state‐dependent in the BRICS countries. Using monthly data from 1999:M1 to 2019:M12 and non‐linear smooth transition vector autoregressive (STVAR) model, our results provide evidence of period‐specific ERPT between the upper and lower regime periods, governed by the selected transition variables. The results further suggest that the pass‐through of exchange rate is higher when the economy is experiencing large appreciations and expansions as well as large depreciations and recessions. Theimplication for these findings is that ERPT is strongly affected by the state of the economy.  相似文献   
8.
ABSTRACT

A compact cat swarm optimization scheme (cCSO) is proposed in this paper, which is designed to solve application domains plagued with limited memory and less-computation power, as a member of cat swarm optimization algorithms (CSO), it composes of two sub-modes, i.e., tracing and seeking modes, so it keeps the same search logic of CSO. On the other hand, cCSO inherits the main feature of compact algorithms, a normal probabilistic model is used to represent the population of solutions instead of processing an actual population, which ensures the cCSO to have the modest memory requirement. The updating vector for the probabilistic model provides a clear moving direction for cats in next step. A cat without historical position and velocity is applied in the algorithm. When the cat is in seeking mode, it employs a differential operator to update the cat’s position, which makes it possible for the cat to have multiple searching directions. Experimental results show that cCSO has pretty performance compared with respect to some population-based testing benchmarks. And it also shows superior performance in convergence rate to some compact optimization algorithms. The case study of gray image segmentation proves that it suits for solving the optimization problem by limited hardware.  相似文献   
9.
针对斜坡堤越浪量预测方法,分别建立集成神经网络(ensemble neural network,ENN)、随机森林(random for-eset,RF)和支持向量回归机(suppport vector regression,SVR)3种机器学习模型对斜坡堤越浪量进行预测,并利用决定系数R2和均方根误差RMSE来评估模型性能.最后,对3种模型的性能进行分析.结果显示,集成神经网络模型的决定系数R2和均方根误差RM S E分别约为0.96和0.0018,随机森林模型的决定系数R2和均方根误差RMSE分别约为0.97和0.0014,支持向量回归机模型的决定系数R2和均方根误差RMSE分别约为0.94和0.002.对比发现,3种模型的决定系数都达到0.9以上,都具有较高的预测精度,随机森林相比其他两个模型精度更高.  相似文献   
10.
微表情是人们处在一些与平时生活环境不同的高强度环境下试图控制和掩饰的情感表现,也是一种不曾意识到的瞬时脸部表情,持续时间短,强度弱。为了提高其准确率,提出了基于Radon变换的微表情识别算法。首先,对数据库中的视频序列进行灰度归一化、尺寸归一化和二维主成分分析法(Two-dimensional Principal Component Analysis,2DPCA)降维预处理,使用光流法对降维后图像提取运动特征;然后使用Radon变换算法对光流图像进行处理,得到对应微表情的特征值和特征图像;最后使用支持向量机进行微表情分类识别。实验结果表明,使用Radon变换后得到的微表情特征图像得到了较好的识别效果,在微表情数据集CASME和CASMEⅡ上识别率分别为81.48%和82.17%,通过与选取的其他方法对比说明了该方法具有更好的识别性能。  相似文献   
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号