知识生产函数、规模报酬和经济增长模式——R＆D模型对中国的实证检验

R&D模型是经济增长理论的一个重要、前沿的部分,它认为技术进步和创新是一个国家经济增长的动力。R&D模型将经济长期增长的源泉归结于知识生产函数中两种投入要素——知识和资本的规模报酬,并且把经济的长期增长模式区分成三种类型:稳定性均衡、非稳定性均衡和半稳定性均衡。文章首次对知识生产函数进行实证检验,以此来判断我国经济增长模式。通过对2004-2006年中国243个城市面板数据的研究,发现中国的经济增长模式属于稳定性均衡的类型,新知识的生产对知识和资本的规模报酬是递减的,经济会在某个增长率稳定下来,劳动力和资本存量中用于研究和开发的比例和储蓄率的上升,在长期内都不会改变这个稳定的增长率。     

宏观经济与股票价格波动之间的关系研究

利用Copula模型,研究宏观经济变量与上证股指收益率之间的相关关系,在选择合适的边缘分布函数的基础上,分别建立了常相关的二元正态Copula函数、t—Copula函数、FrankCopula函数、ClaytonCopula函数以及Gum—belCopula函数模型,并且利用欧氏距离方法选择出最佳拟合Copula模型。选取2001年1月至2011年12月的月度数据作为处理对象,并利用最佳拟合模型分析宏观经济变量与上证股指收益率间相关关系及相关结构,从而揭示了中国宏观经济与股票市场之间的相关性。     

企业规模与货币政策的非对称效应

在金融加速器模型的基础上,本文构建了含有企业异质性的动态随机一般均衡模型,并以此考察了我国货币政策对不同规模企业的非对称效应。研究结果表明,相对于大企业,中小企业更易受到紧缩性货币政策冲击的影响,中小企业产出下降幅度约是大企业的三倍。造成这种非对称效应的主要原因在于中小企业外部融资受到限制。此外,货币政策冲击通过信贷市场放大了经济波动,经济中存在着明显的金融加速器效应现象。因此,央行在制定货币政策时应考虑到货币政策对不同规模企业的非对称效应,并谨慎选择名义利率的调整幅度。     

我国寿险公司范围经济效应的实证研究

我国自1996年实施产寿分业经营以来,人身保险业务快速增长,寿险公司数量急剧增加,寿险公司业务中新型寿险的比重不断上升,呈现出"一险独大"的市场状况。运用超越对数成本函数,对国内29家具有代表性的寿险公司2005-2010年期间的范围经济状况进行检验的结果显示:不同规模和背景的寿险公司的范围经济系数均比较明显,但是很多寿险公司所表现出来的范围经济性具有"欺骗性"。因此,寿险业务结构调整缺乏内部的市场激励,需要强有力的外部力量推动。     

基于关联交易的企业集团信用风险研究

基于合作博弈理论构建了企业集团关联交易基本模型,刻画了企业集团的公允关联交易以及两种广泛存在的、典型的非公允关联交易行为。利用一类Survival Copula函数刻画了不同类型关联交易下的企业集团信用风险,从理论上阐明了关联交易影响企业集团信用风险的基本机制。研究结果表明:通过关联交易"掏空"母公司的行为会使企业集团的信用风险显著增加;存在最优内部资源配置方式可使企业集团的信用风险水平最低。     

全球化、柔性化、复合化、差异化:信息时代城市功能演变研究

结合信息技术对中国城市影响的实际,从信息技术影响下城市空间相互作用方式、空间结构的构成要素及其影响因素的变化出发,对信息时代国内城市功能特征进行研究变得尤为重要.全球化、柔性化、复合化、差异化已成为信息时代城市功能的主要特征;信息流和接入信息的能力变得尤为重要;每个城市都成为全球或区域城市网络的一个节点;部分服务的区位选择因此也表现出较大的弹性;城市居住空间分异仍然存在,影响因素越来越复杂.     

Economies of scale in the Australian tourism industry

The measurement of economies of scale in the tourism industry has not been done to this point, as tourism is not a specific industry according to international statistical standards. Among many industries related to tourism, four sectors (accommodation, transport, retail trade and recreational services) across six states and two territories from 1997 to 2007 are studied as they contribute nearly 70% of tourism output in Australia. By comparing regression results from the Cobb–Douglas (C–D) production function and the translog production function, we find that there is evidence of increasing returns in transport, retail trade and recreational services at the industry level. However, accommodation is characterized by constant returns to scale at the industry level. As accommodation is responsible for the biggest share of tourism output, this suggests that overall the tourism sector is not characterized by increasing returns. We also find that the degrees of returns to scale from the C–D and translog production functions are different and that the imposition of input share also influences the empirical results. Both of these factors stress the importance of model specification to the measurement of economies of scale.     

The information content of the Reserve Bank of Australia's inflation forecasts

In this article, the inflation forecasts produced by the Reserve Bank of Australia (RBA) and that generated by private forecasters, are used to assess whether the Reserve Bank possesses information about inflation that the private sector does not have. The results show that the Reserve Bank inflation forecasts embody useful predictive information about inflation, beyond that contained in private forecasts, over the recent inflation targeting period.     

Oil price forecasting under asymmetric loss

Based on the approach developed by Elliott et al. (2005), we found that the loss function of a sample of oil price forecasters is asymmetric in the forecast error. Our findings indicate that the loss oil price forecasters incurred when their forecasts exceeded the price of oil tended to be larger than the loss they incurred when their forecast fell short of the price of oil. Accounting for the asymmetry of the loss function does not necessarily make forecasts look rational.     

What explains the performance of students in a heterogeneous environment? Conditional efficiency estimation with continuous and discrete environmental variables

Efficiency estimations which do not account for the operational environment where production units are operating in may have only a limited value. This article presents a fully nonparametric framework to estimate relative performance of production units when accounting for continuous and discrete background variables. Using insights from recent developments in nonparametric econometrics, we show how conditional efficiency scores can be estimated using a tailored mixed kernel function with a data-driven bandwidth selection. The methodology is applied to the sample of Dutch pupils from the Organization for Economic Co-operation and Development's Programme for International Student Assessment (OECD PISA) data set. We estimate students' performance and the influence of its background characteristics. The results of our application show that several family- and student-specific characteristics have a statistically significant effect on the educational efficiency, while school-level variables do not have impact on performance.