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101.
本文基于2002年1月-2018年3月的时间序列数据,采用TVP-SVAR模型实证检验了棚户区改造背景下非常规货币政策对房地产价格的影响及其机制。研究发现:2013年之后,常规货币政策数量型工具对房地产价格的影响基本是失效的,非常规货币政策中的抵押补充贷款逐渐取代M2成为影响房地产价格的主要货币政策工具;从政策效果来看,虽然抵押补充贷款是房地产价格短期上涨的主要因素,但其长期影响并不明显;从影响机制来看,抵押补充贷款不仅能够直接影响房地产价格,还能够通过降低实际利率间接地影响房地产价格;分城市来看,抵押补充贷款对大城市的影响是非结构性的,但对中等城市的影响是结构性的,意味着通过抵押补充贷款支持棚户区改造的做法很可能导致中等城市房地产市场蕴含更大的价格波动风险。本文的研究加深了对非常规货币政策与房地产价格关系的理解,从而能够为棚户区改造与维护房地产市场平稳健康发展提供有益的政策启示。 相似文献
102.
罗家喜 《粤港澳市场与价格》2008,(3)
通过对中国城市燃气供给和需求的分析,一般情况下,各省、市城市燃气的消费量与管道长度、用气人口数量同方向变化。通过对不同城市天然气价格的分析,本文发现了天然气价格的几个特点。通过对不同城市人均国内生产总值和城市燃气价格的比较分析,不仅消费者收入水平影响天然气价格,而且政府产业政策、由消费者集中度高而形成的规模经济效益、市场竞争等因素也影响天然气价格。最后,本文提出了对城市燃气终端价格比较后的几点看法。 相似文献
103.
本文利用大型微观数据库CGSS2006,首次对城市住房价格、住房产权和城市居民主观幸福感之间的关系进行实证分析。研究发现:(1)城市房价上涨程度对居民幸福感具有显著的负面影响,房价上涨越快,民众主观幸福感越低;(2)住房产权状况和幸福感显著相关,仅有一套房产者和多房者幸福感显著高于租房者,多房者幸福感显著高于仅有一套房产者;(3)房价上涨对租房者幸福感具有显著负效应,对多房者和仅有一套房产者的幸福感带来显著正向效应,且对多房者幸福感的正向效应显著高于仅有一套房产者;(4)住房质量显著影响居民主观幸福感。这些发现具有重要的现实政策意义。 相似文献
104.
This paper assesses the implications of China’s trade and domestic policies for incentives to producers in China. It uses a price comparison methodology (nominal rates of assistance—at the border and the farmgate), with adjustments for exchange rate distortions in the first part of the sample period (1981–1994). On average, distortions to agricultural incentives have been reduced. In the early 1980s, on average, China’s domestic prices were far below international prices. There were substantial variations, however, between imported (which were being protected) and exported goods. During the 1980s and 1990s the gap between domestic and international prices for both imports and exports narrowed initially mainly due to the elimination of domestic policy distortions. Between the mid-1990s and 2004, trade liberalization policy furthered narrowed the gap between world and China farmgate prices. By the mid-2000s, China’s agriculture was operating with only small price distortions. 相似文献
105.
Victor S.H. Wong Suzanna El Massah 《International Journal of the Economics of Business》2018,25(2):297-312
The recent plunge in the price of oil affected many countries, especially major oil producers and exporters, such as the Gulf Cooperation Council (GCC), which accounts for half of the global oil reserves. This paper examines the impact of oil price changes on GCC stock markets, including Bahrain, Kuwait, Oman, Qatar, Kingdom of Saudi Arabia, and United Arab Emirates over a 10-year period, 2005–2015. We examine the direction of influence and influence absorption through Granger causality and impulse response function. The results are important for portfolio management at the international level, and provide insights for government and regulatory authorities in times of oil price change. Additionally, the evidence suggests the need for more economic diversification at the country level in the GCC region to mitigate high volatility in the event of oil shocks. 相似文献
106.
107.
This paper empirically examines the effect of the U.S. Corporate Average Fuel Economy (CAFE) standards on the technological progress in automobile fuel efficiency. Using detailed vehicle attributes data from 1978 through 2018, we find that more stringent fuel economy standards increase the rate of technological improvements in new passenger cars, and this effect is primarily driven by the response of U.S. automakers. We do not find evidence that CAFE standards have a similar effect on the technical change in light-duty trucks. Our results also indicate that higher gasoline prices have a significant and positive effect on the improvement of fuel-saving technology in both passenger cars and light trucks. Using our empirical estimates, we project that the recent rollback of Obama-era CAFE standards would forego an approximately 2-percent increase in cars’ fuel economy over the 2021–2025 period as a result of technological progress. 相似文献
108.
109.
摘要:反馈交易理论是金融市场最经典的理论之一,长期以来,对这一理论的研究与建模并不多见。本文给出了在一个具有反馈交易特征的市场中,情绪冲击对资产价格的长期影响模型。我们发现,总的来说,反馈交易会影响认知偏差效应和交易诱导效应,认知偏差效应随反馈交易系数递增。但是,交易诱导效应并不与反馈交易系数呈简单的单调关系,交易诱导效应在一定情形下随着反馈交易系数减小。 相似文献
110.
The study of tourism demand is attracting more and more attention. Hence, it is important to understand the variables that
affect tourism demand and to forecast the demand. Many studies have been conducted to analyze the demands in various countries.
Recently, China has been expected to become one of the largest originators of outbound tourists in the world. Hence, it is
interesting to explore what the variables are that affect the Mainland Chinese arrivals to Taiwan and to forecast its corresponding
tourism demand. This study applies neural networks to select proper models, and then to forecast the demand. 相似文献