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1.
数字化时代的经济运行方式呈现出数据驱动、万物互联、创新迭代的特征,数字经济的数字化、网络化、智能化属性对创新活动产生了深刻影响。运用空间杜宾模型,对361座城市2010-2018年度数据进行实证检验。检验结果表明,数字经济发展不仅能够带动本地创新绩效提升,而且对周边城市创新绩效也具有显著正向影响;与中、西部地区相比,东部地区数字经济对创新绩效的促进作用更强,空间溢出效应也更显著。由此,建议可从挖掘数据要素价值、搭建数字化平台、推动数字技术创新等角度发展数字经济,促进本地区和周边地区创新绩效共同提升。  相似文献   
2.
基于2005—2016年我国省际面板数据,首先通过OLS、DIFF GMM、SYS GMM3种基准线性回归方法论证了OFDI逆向技术溢出对我国区域创新能力的促进作用。以OFDI为核心解释变量,分别构建以地区腐败、市场化程度和知识产权保护为门槛变量的动态门槛回归模型。结果发现:随着地区腐败程度加深,我国区域创新能力逐渐减弱;以市场化程度、知识产权保护为门槛变量,跨越门槛点后OFDI对我国区域创新能力的拉动作用依次增强。最后,结合面板向量自回归模型进一步研究对外直接投资过程中地区腐败、市场化程度和知识产权保护对区域创新能力的动态即期冲击。结果显示:市场化程度单位变动对区域创新能力的影响呈现正向冲击且持续性较强,知识产权保护对区域创新能力的拉动最为迅速但后期持续性较弱,地区腐败对区域创新能力产生负向冲击作用。  相似文献   
3.
A new class of forecasting models is proposed that extends the realized GARCH class of models through the inclusion of option prices to forecast the variance of asset returns. The VIX is used to approximate option prices, resulting in a set of cross-equation restrictions on the model’s parameters. The full model is characterized by a nonlinear system of three equations containing asset returns, the realized variance, and the VIX, with estimation of the parameters based on maximum likelihood methods. The forecasting properties of the new class of forecasting models, as well as a number of special cases, are investigated and applied to forecasting the daily S&P500 index realized variance using intra-day and daily data from September 2001 to November 2017. The forecasting results provide strong support for including the realized variance and the VIX to improve variance forecasts, with linear conditional variance models performing well for short-term one-day-ahead forecasts, whereas log-linear conditional variance models tend to perform better for intermediate five-day-ahead forecasts.  相似文献   
4.
REITs draw attention from investors around the world, yet our understanding of the various risks associated with such securities is limited. Using the introduction of Arrowhead, a low-latency high-frequency trading platform, to the Tokyo Stock Exchange and the financial crisis of 2008 as natural experiments, we compare the resilience of REITs and equities in terms of liquidity and volatility. The results indicate that the introduction of Arrowhead improved the quality of the Japanese REIT market but also increased the probability of flash crashes. We also find that although the financial crisis significantly deteriorated overall equity market quality, the Japanese REIT market was resilient. Finally, using a difference-in-differences regression model, we show that the higher transparency and better price discovery of REITs, compared to non-REITS, protected them from the negative effects of the financial crisis and the introduction of Arrowhead. Overall, our analysis shows that REITs are more resilient than non-REITs.  相似文献   
5.
基于我国区际产业转移大背景,使用1999-2016内地年30个省市、27个二位数工业行业数据定量测度区际产业转移,选择产业关联较强的电子设备制造业为研究对象,使用投入产出法识别关联产业、测算其关联产业溢出,利用2004—2016年内地28个省市面板数据构建模型对关联产业溢出效应与电子设备制造业转移的关系、产业转移中的关联产业溢出与电子设备制造业高质量发展的关系分别进行了实证检验。研究发现:①2014年中国工业空间基尼系数出现拐点,总体工业由之前的分散转移转为新的集中转移,而电子设备制造业仍处在向中部地区和西南地区集聚的分散转移中;②电子设备制造业转移中的产业关联溢出效应确实存在,且促进了电子设备制造业生产效率的提高和产业高质量发展;③产业转移中第三产业关联溢出效应对电子设备制造业分散转移的作用高于工业,但工业的关联溢出对电子设备制造业生产效率提升的作用明显高于第三产业。  相似文献   
6.
There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.  相似文献   
7.
This paper discusses the specifics of forecasting using factor-augmented predictive regressions under general loss functions. In line with the literature, we employ principal component analysis to extract factors from the set of predictors. In addition, we also extract information on the volatility of the series to be predicted, since the volatility is forecast-relevant under non-quadratic loss functions. We ensure asymptotic unbiasedness of the forecasts under the relevant loss by estimating the predictive regression through the minimization of the in-sample average loss. Finally, we select the most promising predictors for the series to be forecast by employing an information criterion that is tailored to the relevant loss. Using a large monthly data set for the US economy, we assess the proposed adjustments in a pseudo out-of-sample forecasting exercise for various variables. As expected, the use of estimation under the relevant loss is found to be effective. Using an additional volatility proxy as the predictor and conducting model selection that is tailored to the relevant loss function enhances the forecast performance significantly.  相似文献   
8.
李政  杨思莹 《南方经济》2019,38(12):49-67
文章基于2003年至2016年我国215个城市面板数据,运用双重差分模型、空间双重差分模型和分位数回归模型等方法,实证检验了国家高新区对城市创新水平的影响及其空间异质性特征。研究结果表明,国家高新区建设显著提升了城市创新水平,并且高新区设立带动的城市投资集聚是推动城市创新水平提升的重要原因。空间双重差分结果表明,国家高新区对城市创新水平的提升作用并非源于其对周边城市创新资源的掠夺,相反高新区设立对周边城市和省内城市均产生了显著的溢出效应,提升了本省城市和周边外省城市创新水平。此外,国家高新区对城市创新水平的影响具有空间异质性特征,在省会城市、直辖市和副省级城市,高新区对城市创新水平的影响并不显著,而能够显著提升一般地级市创新水平;随着城市创新水平的提升,高新区建设对城市创新水平的促进作用呈现出先增强、后减弱直至不再显著的非对称"倒V型"变化特征。但是研究也发现,国家高新区对城市创新水平影响的区位异质性并不显著,高新区对东部地区和中西部地区城市创新水平提升均具有显著的促进作用。  相似文献   
9.
We extend the GARCH–MIDAS model to take into account possible different impacts from positive and negative macroeconomic variations on financial market volatility: a Monte Carlo simulation which shows good properties of the estimator with realistic sample sizes. The empirical application is performed on the daily S&P500 volatility dynamics with the U.S. monthly industrial production and national activity index as additional (signed) determinants. We estimate the Relative Marginal Effect of macro variable movements on volatility at different lags. In the out-of-sample analysis, our proposed GARCH–MIDAS model not only statistically outperforms the competing specifications (GARCH, GJR-GARCH and GARCH–MIDAS models), but shows significant utility gains for a mean-variance investor under different risk aversion parameters. Attention to robustness is given by choosing different samples and estimating the model in an international context (six different stock markets).  相似文献   
10.
Using data on a five-minute interval basis, this article analyses the effects of intraday seasonality on volatility transmission between the spot and futures markets of the CAC40, DAX30 and FTSE100. Remarkable differences in the impulse response analysis and in the dynamic and directional measurement of volatility spillovers are encountered depending on whether the intraday periodic component is considered. Thus, the convenience of removing intraday seasonality seems to be critical to reduce the risk of spurious causality when employing high-frequency data in volatility transmission. Moreover, the impact of market microstructure noise seems negligible when using an optimal frequency of observations.  相似文献   
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