我国城镇职工养老保险待遇水平的影响因素研究

文章以2001-2012年省级面板数据为基础,利用可行的广义最小二乘法(FGLS),对影响我国养老保险待遇水平的因素进行了定量研究。研究表明:在职职工年人均缴费额、职退比、人均GDP、人均财政收入对我国养老保险待遇水平有显著的正向影响,城市化率对养老保险待遇水平有显著的负向影响,其中,在职职工年人均缴费额和职退比是影响我国养老保险待遇水平的最主要因素。我国调整养老保险待遇水平缺乏科学的依据,具体表现在养老保险待遇水平与居民人均消费性支出不相关。     

投资者情绪、市场波动与股市泡沫

我国投资者情绪容易受到噪音交易者影响,其他类型交易者可利用噪音交易者的交易策略在博弈中获取超额利润,这为投机性泡沫的产生提供了微观基础。在市场波动机制中,投资者情绪与股价变化存在动态关系,股价泡沫存在内在持续性,引发市场正反馈效应,从而促成投机性泡沫的生成。     

LME镍、铜期货价格变动的时间序列分析

本文基于2003～2008年伦敦金属交易所（LME）3月镍、铜期货价格的日线数据,运用经典的时间序列R／S分析方法来研究镍、铜期货市场价格的非线性特征。分析结果显示：LME镍、铜期货市场价格波动是典型的有偏随机游动,H值均大于0．5,期货价格时间序列具有持久性趋势;LME镍、铜期货存在大约分别为447天和442天的非周期循环长度。     

操作风险损失的广义帕累托分布参数估计及其应用

极值理论表明大于某一阀值的样本服从广义帕累托分布,该结论在金融风险计量和保险精算中有着广泛的应用。然而,由于其参数没有可接受的估计方法,致使其应用受到限制。论文在推导出广义帕累托分布的条件矩的基础上,研究了基于操作风险损失的广义帕累托分布的参数估计问题。并且基于我国商业银行1994~2008年的操作风险损失数据对经济资本配置进行了算例分析。     

Forecasting economic time series using score-driven dynamic models with mixed-data sampling

We introduce a mixed-frequency score-driven dynamic model for multiple time series where the score contributions from high-frequency variables are transformed by means of a mixed-data sampling weighting scheme. The resulting dynamic model delivers a flexible and easy-to-implement framework for the forecasting of low-frequency time series variables through the use of timely information from high-frequency variables. We verify the in-sample and out-of-sample performances of the model in an empirical study on the forecasting of U.S. headline inflation and GDP growth. In particular, we forecast monthly headline inflation using daily oil prices and quarterly GDP growth using a measure of financial risk. The forecasting results and other findings are promising. Our proposed score-driven dynamic model with mixed-data sampling weighting outperforms competing models in terms of both point and density forecasts.     

Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis

Considering the interrelationships between periods and the influences of non-operational factors, a new framework based generalized three-stage DEA model, grey relational analysis theory and disparity disassembly model is proposed in this paper. Then, we measure the technical efficiency, scale efficiency, and pure technical efficiency of innovation in China's semiconductor industry between 2009 and 2014. In addition, we conducted projection analysis of the inputs to innovation and the disparities analysis in innovation efficiency across the industrial chain and within each segment. The results of our analyses reveal four key findings. The overall innovation efficiency of China's semiconductor industry is increasing; however, each segment of the industrial chain had different trends and different levels of innovation efficiency. All segments show a consistently upward trend except for package testing, which dipped in 2012 due to the time lag between the inputs and outputs associated with major technological advancements. The most efficient innovation is occurring in design and package testing, followed by manufacturing, materials, and equipment, in that order. Low levels of innovation efficiency were found to be the most significant factor restricting further improvement in the design, manufacturing, and equipment segments of the industrial chain. But the opposite is true for the package testing segment, where pure technical efficiency is the main factor. A range of redundancies in input were found across the industrial chain, mostly in manufacturing and equipment. These two segments are capital-intensive and characterized by a high level of technical complexity coupled with a long research cycle. The disparities in innovation efficiency in and between the segments decreased over the period. However, interestingly, the main disparities were found among the enterprises within each segment, which we attribute to the Chinese government's concerted efforts to support particular companies. Package testing and manufacturing had the highest levels of disparity due to relatively high agglomeration of these two segments. The materials segment had the lowest disparity, with equipment and design falling somewhere in-between.     

Women Mayors and Management of Spanish Councils: An Empirical Analysis

This paper analyzes the relationship between the gender of mayors in Spanish local government and different budget items. It uses a sample of local budgets for 8,112 town councils between 2002 and 2010, totaling 64,361 observations. The Spanish context is characterized by decentralization of public responsibility to a greater extent than in neighboring countries, feeding the debate on the operational efficiency of local government and the importance of gender in public management. Results show that councils with women mayors have lower annual interest and debt repayment obligations and have higher expenditure on security, protection, and social promotion. Thus, the presence of women in politics may serve to improve councils’ economic situations, which is necessary not only for social justice but also for economic efficiency. In addition, in councils with more inhabitants, women mayors are more common, but women are less likely to occupy the office for longer periods.     

Systemic risk in European financial and energy sectors: Dynamic factor copula approach

We perform an analysis of systemic risk in financial and energy sectors in Europe using daily time series of CDS spreads. We employ the factor copula model with GAS dynamics from Oh and Patton (2018) for the purpose of estimating dependency structures between market participants. Based on the estimated models, we perform Monte Carlo simulations to obtain future values of CDS spreads, and then measure the probability of systemic events at given time points. We conclude that substantially higher systemic risk is present in the financial sector compared to the energy sector. We also find that the most systemically vulnerable financial and energy companies come from Spain.     

Alternative evolutionary theories: A historical survey

Our overview has the objective of making our study relevant to bioeconomists. The need for the ‘alternatives’ to the Synthetic Theory of Evolution in social-economic studies was substantiated, for example, by Colombatto (Journal of Bioeconomics, 5, 1–25, 2003), who maintains that the natural-selection theory is ‘ill suited’ to describing evolutionary processes in economics. He proposed an alternative ‘non-Darwinian’ approach by equating the ‘non-Darwinian’ approach with a definite version of neo-Lamarckism. Yet, as we will show, there is a palette of alternative approaches within and beyond the neo-Lamarckism. We hope to give bioeconomists more choice in their theoretical modeling and constructing of analogies between biology and economics. It will also be shown that in the light of suggested definitions the concept of ‘universal Darwinism’ recently discussed in bioeconomics makes little sense as a generalizing category. In addition, in the concluding part of the paper we demonstrate that the majority of alternative approaches are far from being pigeonholed as archaic and once and for all wiped off the theoretical landscape. On the contrary, in recent years one can observe some revival of interest in the theoretical ‘heresies’.      

Inference on Reliability in Two-parameter Exponential Stress–strength Model

The problem of hypothesis testing and interval estimation of the reliability parameter in a stress–strength model involving two-parameter exponential distributions is considered. Test and interval estimation procedures based on the generalized variable approach are given. Statistical properties of the generalized variable approach and an asymptotic method are evaluated by Monte Carlo simulation. Simulation studies show that the proposed generalized variable approach is satisfactory for practical applications while the asymptotic approach is not satisfactory even for large samples. The results are illustrated using simulated data.