为了对我国城市水资源利用效率问题进行分析和评价,本文基于数据包络分析方法,从农业、工业、生活、社会等几个方面共选取了5个输入指标及6个输出指标,利用AIC信息准则(Akaike information criterion)进行了变量选择,构建了较为科学合...为了对我国城市水资源利用效率问题进行分析和评价,本文基于数据包络分析方法,从农业、工业、生活、社会等几个方面共选取了5个输入指标及6个输出指标,利用AIC信息准则(Akaike information criterion)进行了变量选择,构建了较为科学合理的用水效率评价指标体系.在此基础上,采用香农熵指数提升了传统CCR(由Charnes A,Cooper W W,Rhodes E提出)模型的识别能力,选取我国31个省会城市为研究对象,给出了省会城市水资源效率的完整排名。结果表明:①绝大部分城市综合效率得分(CES,Comprehensive efficiency score)普遍不高,投入产出比仍有较大的进步空间;②拉萨、北京、天津、银川、海口、上海等城市CES得分相对较高,这说明一个城市水资源利用效率的高低与经济发展水平可能没有必然的联系,其他城市应结合自身情况向CES得分靠前的城市进行学习;③重庆、南宁、南昌、长沙等水资源较丰富的城市CES得分反而较低,表明这些城市可能存在大量水资源被浪费,应建立起节水机制,同时优化产业结构。展开更多
Fast stepwise procedures of selection of variables by using AIC and BIC criteria are proposed inthis paper. We shall use a short name 'FSP' for these new procedures. FSP are similar to the well-known stepwise ...Fast stepwise procedures of selection of variables by using AIC and BIC criteria are proposed inthis paper. We shall use a short name 'FSP' for these new procedures. FSP are similar to the well-known stepwise regression procedures in computing steps. But FSP have two advantages. One of theseadvantages is that FSP are definitely convergent with a faster rate in finite computing steps. Anotheradvantage is that ESP can be used for large number of candidate variables. In this paper we alsoshow some asymptotic properties of FSP, and some simulation results.展开更多
The primary objective of the paper is to forecast the beta values of companies listed on Sensex,Bombay Stock Exchange(BSE).The BSE Sensex constitutes 30 top most companies listed which are popularly known as blue-chip...The primary objective of the paper is to forecast the beta values of companies listed on Sensex,Bombay Stock Exchange(BSE).The BSE Sensex constitutes 30 top most companies listed which are popularly known as blue-chip companies.To reach out the predefined objectives of the research,Auto Regressive Integrated Moving Average method is used to forecast the future risk and returns for 10 years of historical data from April 2007 to March 2017.Validation accomplished by comparison of forecasted and actual beta values for the hold back period of 2 years.Root-Mean-Square-Error and Mean-Absolute-Error both are used for accuracy measurement.The results revealed that out of 30 listed companies in the BSE Sensex,10 companies’exhibits high beta values,12 companies are with moderate and 8 companies are with low beta values.Further,it is to note that Housing Development Finance Corporation(HDFC)exhibits more inconsistency in terms of beta values though the average beta value is lowest among the companies under the study.A mixed trend is found in forecasted beta values of the BSE Sensex.In this analysis,all the p-values are less than the F-stat values except the case of Tata Steel and Wipro.Therefore,the null hypotheses were rejected leaving Tata Steel and Wipro.The values of actual and forecasted values are showing the almost same results with low error percentage.Therefore,it is concluded from the study that the estimation ARIMA could be acceptable,and forecasted beta values are accurate.So far,there are many studies on ARIMA model to forecast the returns of the stocks based on their historical data.But,hardly there are very few studies which attempt to forecast the returns on the basis of their beta values.Certainly,the attempt so made is a novel approach which has linked risk directly with return.On the basis of the present study,authors try to through light on investment decisions by linking it with beta values of respective stocks.Further,the outcomes of the present study undoubtedly useful to academicians,researchers,and policy makers in their respective area of studies.展开更多
文摘为了对我国城市水资源利用效率问题进行分析和评价,本文基于数据包络分析方法,从农业、工业、生活、社会等几个方面共选取了5个输入指标及6个输出指标,利用AIC信息准则(Akaike information criterion)进行了变量选择,构建了较为科学合理的用水效率评价指标体系.在此基础上,采用香农熵指数提升了传统CCR(由Charnes A,Cooper W W,Rhodes E提出)模型的识别能力,选取我国31个省会城市为研究对象,给出了省会城市水资源效率的完整排名。结果表明:①绝大部分城市综合效率得分(CES,Comprehensive efficiency score)普遍不高,投入产出比仍有较大的进步空间;②拉萨、北京、天津、银川、海口、上海等城市CES得分相对较高,这说明一个城市水资源利用效率的高低与经济发展水平可能没有必然的联系,其他城市应结合自身情况向CES得分靠前的城市进行学习;③重庆、南宁、南昌、长沙等水资源较丰富的城市CES得分反而较低,表明这些城市可能存在大量水资源被浪费,应建立起节水机制,同时优化产业结构。
文摘Fast stepwise procedures of selection of variables by using AIC and BIC criteria are proposed inthis paper. We shall use a short name 'FSP' for these new procedures. FSP are similar to the well-known stepwise regression procedures in computing steps. But FSP have two advantages. One of theseadvantages is that FSP are definitely convergent with a faster rate in finite computing steps. Anotheradvantage is that ESP can be used for large number of candidate variables. In this paper we alsoshow some asymptotic properties of FSP, and some simulation results.
文摘The primary objective of the paper is to forecast the beta values of companies listed on Sensex,Bombay Stock Exchange(BSE).The BSE Sensex constitutes 30 top most companies listed which are popularly known as blue-chip companies.To reach out the predefined objectives of the research,Auto Regressive Integrated Moving Average method is used to forecast the future risk and returns for 10 years of historical data from April 2007 to March 2017.Validation accomplished by comparison of forecasted and actual beta values for the hold back period of 2 years.Root-Mean-Square-Error and Mean-Absolute-Error both are used for accuracy measurement.The results revealed that out of 30 listed companies in the BSE Sensex,10 companies’exhibits high beta values,12 companies are with moderate and 8 companies are with low beta values.Further,it is to note that Housing Development Finance Corporation(HDFC)exhibits more inconsistency in terms of beta values though the average beta value is lowest among the companies under the study.A mixed trend is found in forecasted beta values of the BSE Sensex.In this analysis,all the p-values are less than the F-stat values except the case of Tata Steel and Wipro.Therefore,the null hypotheses were rejected leaving Tata Steel and Wipro.The values of actual and forecasted values are showing the almost same results with low error percentage.Therefore,it is concluded from the study that the estimation ARIMA could be acceptable,and forecasted beta values are accurate.So far,there are many studies on ARIMA model to forecast the returns of the stocks based on their historical data.But,hardly there are very few studies which attempt to forecast the returns on the basis of their beta values.Certainly,the attempt so made is a novel approach which has linked risk directly with return.On the basis of the present study,authors try to through light on investment decisions by linking it with beta values of respective stocks.Further,the outcomes of the present study undoubtedly useful to academicians,researchers,and policy makers in their respective area of studies.
