How different are the regional factors of high-tech and low-tech start-ups? Evidence from Japanese manufacturing industries

This paper analyzes regional determinants of the start-up ratio in the Japanese manufacturing sector. A major contribution of this study is the comparison between high-tech and low-tech industries. The empirical results using a sample of 253 industrial districts suggest that business density, weight of the manufacturing sector, and the average business size significantly influence the start-up ratio in both high-tech and low-tech industries. Distinct differences between these industries were found with regard to the effects of human capital, research institutes, and the weight of high-tech industries.

中外滚动轴承工业标准对比分析

文章从标准的发展概况、标准构成、采用国际标准等方面,比较了中国和德国、日本以及美国滚动轴承工业标准的异同,并指出中国轴承工业标准尚需由数量型向质量型转化,由微观操作型向宏观指导型转化,由生产型向贸易型转化,由被动采用型向主动创新型转化。     

构建跨区域农产品营销虚拟物流协作体系——以南北方果蔬农产品为例

针对我国农产品的营销物流实践,表现出的较为粗放性特点,我们提出跨区域虚拟物流协作体系的概念,并搭建农产品营销物流的虚拟运作平台,且寻求存在的理论基础,最终并设计其营销物流运作平台及流程。     

Forecasting the past: the case of US interest rate forecasts

This study evaluates 10-year US government bond yield forecasts and three-month US Treasury bill rate forecasts for the period between October 1989 and December 2004. In total, 136 forecast time series with approximately 13,800 forecast data were scrutinized, making this the most extensive analysis of interest rate forecasts to date. Not one of the forecast time series proved to be unbiased. In the majority of cases, information from the past was not efficiently integrated into the forecasts. The sign accuracy is significantly better than random walk forecasts in only a very few of the forecast time series. The modified Diebold–Mariano test for forecast encompassing reveals that the information content of most of the forecast time series is lower than that of the naïve forecasts, the simple ARIMA models, the implicit forward rates, or average interest rate expectations. The forecasting process is dominated by the present and past market situation.     

Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration

Several studies that have investigated a few stocks have found that the spacing between consecutive financial transactions (referred to as trade duration) tend to exhibit long-range dependence, heavy tailedness, and clustering. In this study, we empirically investigate whether a larger sample of stocks exhibit those characteristics. We do so by comparing goodness of fit in modeling trade duration data for stable distribution and fractional stable noise based on a procedure applying bootstrap methods developed by the authors with several alternative distributional assumptions in modeling trade duration data. The empirical results suggest that the autoregressive conditional duration model with stable distribution fits better than other combinations, while fractional stable noise itself fits better for the time series of trade duration. Our result is consistent with the general findings in the literature that trade duration is informative and that short trade durations move prices more than long trade duration. In addition, our result confirms the advantage of fractal models in the study of roughness in trade duration and provides some evidence for duration dependence. S. Rachev’s research was supported by grants from the Division of Mathematical, Life and Physical Science, College of Letters and Science, University of California, Santa Barbara, and the Deutschen Forschungsgemeinschaft. W. Sun’s research was supported by grants from the Deutschen Forschungsgemeinschaft. P.S. Kalev’s research was supported with a NCG grant from the Faculty of Business and Economics, Monash University. Data are supplied by Securities Industry Research Center of Asia-Pacific (SIRCA) on behalf of Reuters. The first draft of this paper was presented at the International Conference on High Frequency Finance 2006; the authors would like to thank the conference participants for their valuable comments.     

积极做市,树立银行间市场做市商品牌

中国农业银行资金交易中心作为银行间市场第一个资金交易中心,多年来始终是银行间市场上交易最活跃、最有实力、最具影响力的机构之一,2002年至2006年连续五年实现银行间市场交易量排名第一。作为银行间市场的首批双边报价商,农行已经连续6年多坚持每个交易日多券种、小价差报价,在发现市场价格和活跃市场交易方面发挥了积极作用,     

货币政策应对流动性过剩有效性研究:日本的经验

本文通过对日本流动性过剩与货币政策之间的关系进行实证研究,发现货币政策在应对流动性过剩的问题上缺乏足够的有效性,货币政策能够在一定程度上调节流动性,但宽松的货币政策容易制造过剩流动性而紧缩的货币政策却难以吸收过剩流动性,根除流动性过剩仅靠货币政策是不够的,需要进行产业和金融制度的升级和改革。     

贸易顺差与资产价格:内外经济失衡传导路径的一个检验

本文对一些学者提出的内外经济失衡的关系进行了考证。结果表明外部经济的失衡虽增强了货币供给的内生性,但并不必定导致内部资产价格的高涨。因此在政策选择上,要避免面对外部经济失衡采取一些应对内部经济失衡的政策工具来调节内部经济增长过快问题。同时,出于在经济发展过程中资产价格时间序列发生结构性变化的考虑,政策制定极有必要考虑资产价格因素。     

The role of oil futures intraday information on predicting US stock market volatility

This study investigates the role of oil futures price information on forecasting the US stock market volatility using the HAR framework. In-sample results indicate that oil futures intraday information is helpful to increase the predictability. Moreover, compared to the benchmark model, the proposed models improve their predictive ability with the help of oil futures realized volatility. In particular, the multivariate HAR model outperforms the univariate model. Accordingly, considering the contemporaneous connection is useful to predict the US stock market volatility. Furthermore, these findings are consistent across a variety of robust checks.     

欧盟否认中国市场经济地位对中国及世界经济影响的剖析

研究目标：探究欧盟否认中国市场经济地位,对中国、欧盟及世界经济的宏观、产业以及贸易的影响。研究方法：将“非市场经济地位”折算为“反倾销等值税”,利用全球贸易分析模型针对欧盟对中国征收的进口关税进行计算。研究发现：欧盟否认中国市场经济地位不会缓解欧盟就业压力,反而使欧盟出口在中国总进口占比下降0.01个百分点;同时,全世界资源配置效率下降,进一步导致全世界整体福利下降;虽然欧盟否认中国市场经济地位使中国对欧盟出口减少约50.6亿美元,但中国向世界其他地区的出口量均有所上升;而且有利于中国产业结构优化,对供给侧改革有一定的激励作用。研究创新：将“非市场经济地位”折算为“反倾销等值税”。研究价值：在研究非数值变量时（如市场经济地位）,可利用其直接影响的变量（反倾销）造成的直接经济损失,折算为适当的指标变量（等值关税）。中国对世界经济的贡献和影响巨大,市场经济地位不容否认。