Multiple generation product life cycle predictions using a novel two-stage fuzzy piecewise regression analysis method

Product life cycle (PLC) prediction plays a crucial role in strategic planning and policy definition for high-technology products. Forecast methodologies which can predict PLCs accurately can help to achieve successful strategic decision-making, forecasting, and foresight activities in high-technology firms, research institutes, governments, and universities. Over the past few decades, even though analytic framework strategies have been proposed for production, marketing, R&D (research and development), and finance, aiming at each stage of PLCs, forecast methodologies with which to predict PLCs are few. The purpose of this research is to develop a novel forecast methodology to allow for predictions of product life time (PLT) and the annual shipment of products during the entire PLC of multiple generation products. A novel two-stage fuzzy piecewise regression analysis method is proposed in this paper. In the first stage, the product life-time of the specific generation to be analyzed will be predicted by the fuzzy piecewise regression line that is derived based upon the product life-time of earlier generations. In the second stage of the forecast methodology, the annual shipment of products of the specified generation will be predicted by deriving annual fuzzy regression lines for each generation, based upon the historical data on the earlier generations' products. An empirical study predicting the life-time and the annual shipment of the 16 Mb (Mega bit) DRAM (Dynamic Random Access Memory) PLC is illustrated to validate the analytical process. The results demonstrate that two-stage fuzzy piecewise regression analysis can predict multiple generation PLT and PLC precisely, thereby serving as a foundation for future strategic planning, policy definitions and foresights.     

Cultural industry development and multiple group participation in Taiwan

Based on the unique historical site culture assets, series of culture activities and constructions are held by Taiwan municipal government positively in recent years to raise local strength. Though the city landscape of Taiwan is far away from the traditional one, the comparison and analysis of foundation of cultural industry and the situation of cultural participation should be carried on to find out the real issues in Taiwan＇s cultural industry and cultural marketing so as to strengthen the ability of local development. This study finds out the resources of culture administration and the social participation in hope for clearing up the matters of Taiwan＇s cultural industry development, avoiding type Ⅲ errors, and giving suggestions.     

Are Securitizations in Substance Sales or Secured Borrowings? Capital‐Market Evidence*

Two standard‐setting approaches have emerged globally to guide the choice of accounting for securitizations: the control and components approach (SFAS No. 125 and SFAS No. 140) and the risks and rewards transfer approach (IAS No. 39). A lack of consensus about derecognition accounting is a major impediment to achieving convergence in global standards that must be resolved. Thus, both SFAS No. 140 and IAS No. 39 will be reexamined, and evidence pertinent to the debate is timely and important. In this study, we present evidence consistent with the view of credit‐rating analysts, who view many securitizations as, in substance, secured borrowings. Specifically, for a sample of originators applying sale accounting guidance in SFAS No. 125 / 140 during the period 1997‐2003, we show that off‐balance‐sheet debt related to securitizations has, on average, the same risk‐relevance for explaining market measures of risk (that is, CAPM beta) as on‐balance‐sheet debt. We also find that, in a returns and earnings association framework, the pricing multiple on securitization gains declines as the amount of off‐balance‐sheet debt increases, implying that investors take off‐balance‐sheet debt into account when assessing the valuation‐relevance of such gains. For those who advocate the control and components approach to securitization accounting, our results suggest that, at least for frequent securitizers, the put option arising from implicit recourse is a “missing piece” that is not currently accounted for when calculating securitization gains. Our results challenge the extant measurement standards in SFAS No. 140.     

组织人力资源管理部门设置实证研究——基于北京市的非随机抽样调查

组织人力资源管理部门的重要性虽然日益得到认可,但是否独立设置人力资源管理部门却缺乏实证性研究。通过对调查问卷的分析,发现近80%的组织独立设置了人力资源管理部门。再通过进一步的计量分析,发现一个组织是否独立设置人力资源管理部门与其人员规模和从事人力资源管理工作人数具有顺序效应,并进而构建了人力资源管理部门设置的二值Logistic回归模型     

运用Logistic回归模型加强高收入者纳税遵从的实证研究

加强高收入者的个人所得税征管、促进纳税遵从一直是税务部门的重要工作之一。利用多元有序因变量Logistic回归模型,以江苏某市2010年度年所得12万元以上个人所得税纳税申报的数据为样本,以＂应补税额＂等级的五分类有序变量为因变量,以纳税申报表中纳税人的年龄、应纳税所得额、应纳税额、性别、职业大类、行业大类6个影响因素为自变量,进行多元有序因变量的Logistic回归分析,研究结果可为税务系统加强年所得12万元以上高收入者个人所得税的申报与征管、促进纳税遵从提供新的思路。     

Forecasting China's GDP growth using dynamic factors and mixed-frequency data

Forecasting GDP growth is important and necessary for Chinese government to set GDP growth target. To fully and efficiently utilize macroeconomic and financial information, this paper attempts to forecast China's GDP growth using dynamic predictors and mixed-frequency data. The dynamic factor model is first applied to select dynamic predictors among large amount of monthly macroeconomic and daily financial data and then the mixed data sampling regression is applied to forecast quarterly GDP growth based on the selected monthly and daily predictors. Empirical results show that forecasts using dynamic predictors and mixed-frequency data have better accuracy comparing to traditional forecasting methods. Moreover, forecasts with leads and forecast combination can further improve forecast performance.     

创新驱动下中国区域高质量发展——基于平衡充分发展水平的门槛分析

创新驱动是破解中国区域不平衡不充分发展的突破口,是实现高质量发展的助推器。采用2003—2017年中国30个省市(因数据缺失,不包括西藏地区和港澳台地区)面板数据,运用全局参比Malmquist模型测度了中国区域高质量发展水平,并通过构建指标体系分别对中国各省市的平衡发展和充分发展水平进行了评价,然后通过门槛回归模型分析了在不同平衡和充分发展水平下创新驱动对于高质量发展的影响机制。结果发现:①区域高质量发展水平呈现出先下降后上升的变化趋势;②各省市平衡和充分发展水平均呈现上升趋势,但各省市之间的变化情况差异较大,有明显的空间集聚特征;③在不同的平衡及充分发展水平下,创新驱动对高质量发展的影响机制是不同的,当平衡充分发展水平较低时,创新驱动对高质量发展没有显著影响;当平衡充分发展达到一定水平时,创新驱动对高质量发展起到一定的促进作用;随着平衡充分发展水平的进一步提高,创新驱动对高质量发展的促进作用越来越大。     

Inter-Industry Wage Differentials in Greece: Evidence from Quantile Regression Analysis

Using a consistent estimator of the covariance matrix of the asymptotic distribution of the quantile regression estimator with intra-cluster correlation of the error terms, the paper investigates whether and to what extent inter-industry wage differentials derive from worker heterogeneity in the form of unobserved quality. To conduct this study, we pioneer in utilizing a unique data set, the European Union Structure of Earnings Survey for Greece, which follows a two-stage random sampling approach of employees clustered within firms. Data refer to 2010 when the first elements of the economic adjustment programme to deal with the chronic deficiencies of the Greek economy and restore sustainable public finances, competitiveness and set the foundation for long-term growth, gained visibility. Results point to high wage dispersion across industries at the mean of the conditional wage distribution, even after controlling for personal and workplace characteristics. However, evidence for the unobserved heterogeneity hypothesis is rather scant. Therefore, there is room for efficiency wage or rent-sharing theories in accounting for a large part of inter-industry wage differentials tentatively implying that firm heterogeneity in the ability to pay matters more than employee unobservable attributes in the wage determination process.     

中国股票型基金业绩持续性实证研究

本文采用动量检验法和回归系数法,检验了存续时间超过24个月的中国股票型基金业绩是否存在持续性.结果发现,101只样本基金的业绩在6个月存在显著的持续性.在此基础上,本文从风险收益和基金管理人能力两个角度检验了基金业绩持续性的来源,结果发现,CAPM和“三因素模型”,以及考虑了基金投资风格的管理人选股能力、择时能力及投资风格持续收益,均不能解释中国股票型基金的业绩持续性.     

Choosing propensity score matching over regression adjustment for causal inference: when,why and how it makes sense

Summary

This study identified when regression adjustment fails to adjust adequately for differences in observed covariates and where propensity score matching is the only alternative.

Multivariate analysis might fail to adjust for observed confounders if:

• 1. The means of the propensity scores in the two groups are more than one-half a standard deviation apart unless distributions of the covariates in both groups are nearly symmetric, sample sizes of the two groups are approximately the same and distributions of the covariates in the two groups have similar variances;

• 2. The ratio of the propensity score variances in the two groups is significantly different from one;

• 3. The ratio of residual variances in the two groups after adjusting for the propensity score is significantly different from one.

Conducted retrospective analysis showed that the treatment effect would be an estimated $305 (or 26%) less if the misspecified outcome model had been chosen.