A new method for measuring congestion in data envelopment analysis

In data envelopment analysis (DEA), there are two principal methods for identifying and measuring congestion: Those of Färe et al. [Färe R, Grosskopf S. When can slacks be used to identify congestion. An answer to W. W. Cooper, L. Seiford, J. Zhu. Socio-Economic Planning Sciences 2001;35:1–10] and Cooper et al. [Cooper WW, Deng H, Huang ZM, Li SX. A one-model approach to congestion in data envelopment analysis. Socio-Economic Planning Sciences 2002;36:231–8]. In the present paper, we focus on the latter work in proposing a new method that requires considerably less computation. Then, by proving a selected theorem, we show that our proposed methodology is indeed equivalent to that of Cooper et al.     

高职院校经济类专业经济法案例教学探析

在高职院校经济类专业的经济法课程教学中,案例教学是普遍采用的教学方法之一。为提高经济法案例教学的效果,本文分析了经济法案例教学中存在的问题,提出了改进方法。     

A panel data analysis for housing affordability in Taiwan

Although the equilibrium relationship between household income and house price is well documented in previous theoretical studies, the empirical results are usually unfavorable. This article examines whether a long-term relationship between house price and income exists through a panel integration and cointegration methodology in analyzing data from four cities in Taiwan from 1980 to 2007. The findings support the existence of a long-term equilibrium relationship between income and house price, which indicate that housing affordability in Taiwan is stable. After controlling other variables, the income elasticity of house prices on average is close to one. Furthermore, evidence points to a bi-directional causality between income and house price.     

Tackling selection bias in sentencing data analysis: a new approach based on a scale of severity

For reasons of methodological convenience statistical models analysing judicial decisions tend to focus on the duration of custodial sentences. These types of sentences are however quite rare (7% of the total in England and Wales), which generates a serious problem of selection bias. Typical adjustments employed in the literature, such as Tobit models, are based on questionable assumptions and are incapable to discriminate between different types of non-custodial sentences (such as discharges, fines, community orders, or suspended sentences). Here we implement an original approach to model custodial and non-custodial sentence outcomes simultaneously avoiding problems of selection bias while making the most of the information recorded for each of them. This is achieved by employing Pina-Sánchez et al. (Br J Criminol 59:979–1001, 2019) scale of sentence severity as the outcome variable of a Bayesian regression model. A sample of 7242 theft offences sentenced in the Crown Court is used to further illustrate: (a) the pervasiveness of selection bias in studies restricted to custodial sentences, which leads us to question the external validity of previous studies in the literature limited to custodial sentence length; and (b) the inadequacy of Tobit models and similar methods used in the literature to adjust for such bias.     

造价员考试新大纲对高职工程造价专业课程影响分析

高等职业教育改革要求高职学生在毕业时取得毕业证书和相应的职业资格证书.工程造价专业对应的职业资格证书是"建设工程造价员".学历教育和职业资格取证工作需要在高职教学工作中同时进行,二者是相辅相成的关系.应当在对新版建设工程造价员资格考试大纲进行分析的基础上,结合教学实际情况,有针对性地进行高职工程造价专业课程改革和实训基地建设.     

A visualization tool for exploratory analysis of cyclic multivariate data

This paper presents an interactive visualization tool for the qualitative exploration of multivariate data that may exhibit cyclic or periodic behavior. Glyphs are used to encode each multivariate data point, and linear, stacked, and spiral glyph layouts are employed to help convey both intra-cycle and inter-cycle relationships within the data. Users may interactively select glyph and layout types, modify cycle lengths and the number of cycles to display, and select the specific data dimensions to be included. We validate the usefulness of the system with case studies and describe our future plans for expanding the system's capabilities.     

A decomposition analysis of managerial efficiency for the insurance companies: A data envelopment analysis approach

The insurance industry worldwide has become less fragmented through liberalization reforms. Yet, following the transformational changes, there is little empirical evidence on identifying the determinants of managerial efficiency. This paper employs a truncated regression analysis to determine the factors driving managerial efficiency of Malaysian insurers. Overall and divisional efficiencies are derived using data envelopment analysis. The decomposition analysis reveals that the observed inefficiency is mainly caused by investment capability division. The regression findings reveal that determinants of efficiency have dissimilar impacts on overall and divisional efficiencies. This study broadly supports financial liberalization as a means of promoting managerial efficiency.     

Open data in Nepal: a webometric network analysis

This study examines the current open data trends in Nepal based on the webometric analysis method by using search engines to trawl through websites and obtain data. The results indicate that various national and international nonprofit organizations, public sector organizations, educational institutions , and a few commercial organizations were the initial actors fostering open data in Nepal. Therefore, these organizations were analyzed in terms of their networking patterns and the extent to which they are exposed internationally in cyberspace by using Webometric Analyst 2.0. Inter-linkage analysis, co-mention analysis, and link impact analyses were conducted to explore the networking behavior in the World Wide Web. The results revealed that international organizations (IOs) were strongly interlinked. Nongovernmental organizations (NGOs), government organizations (GOs), and IOs were interlinked, but weakly. In terms of the co-mention network analysis, IOs with IOs were more significant than NGOs with NGOs, GOs, or business organizations because IOs had been working actively for many years, their web presence was high, and they worked in other fields, including open data. A link impact analysis was also conducted using its indicators of seed sites linked to external websites in terms of the estimated number of top-level domains and country-code top-level domains.     

Habits and heterogeneity in demands: a panel data analysis

We examine demand behaviour for intertemporal dependencies, using Spanish panel data. We present evidence that there is both state dependence and correlated heterogeneity in demand behaviour. Our specific findings are that food outside the home, alcohol and tobacco are habit forming, whereas clothing and small durables exhibit durability. We conclude that demand analyses using cross‐section data that ignore these effects may be seriously biased. On the other hand, the degree of intertemporal dependence is not sufficiently strong to make composite ‘consumption’ significantly habit forming, as has been suggested in some recent analyses. Copyright © 2007 John Wiley & Sons, Ltd.     

Capital market integration in ASEAN: A non-stationary panel data analysis

Motivated by the establishment of ASEAN Economic Community (AEC) at the end of 2015, we examine saving-investment relationship in various subgroups of ASEAN to assess their capital market integration. The results from second generation panel unit-root and cointegration tests that account for cross-sectional dependence as well as estimates of long-run saving-retention rate provide some evidence of market integration in ASEAN. The analysis of short-run dynamics suggests that capital mobility in ASEAN during 1980–2014 appears similar to that in OECD countries during 1970–1999. More importantly, across different panel estimators and subgroups of membership, there is considerable heterogeneity among the member countries. The saving-investment association is very weak, thereby implying very high capital mobility, in more developed members such as Singapore, Malaysia, and Brunei; the association is very strong, implying very low capital mobility, for much less developed members such as Laos, Myanmar, and Cambodia. The results call for renewed effort to develop capital markets in less developed nations and integrate them with the rest of the membership in ASEAN. In this paper, we also address several major shortcomings of the original Feldstein-Horioka framework.     

Reverse efficiency measures for environmental assessment in data envelopment analysis

Environmental issues are becoming more and more important in our everyday life. Data Envelopment Analysis (DEA) is a tool developed for measuring relative operational efficiency. DEA can also be employed to estimate environmental efficiency where undesirable outputs like greenhouse gases exist. The classical DEA method identifies best practices among a given empirical data set. In many situations, however, it is advantageous to determine the worst practices and perform efficiency evaluation by comparing DMUs with the full-inefficient frontier. This strategy requires that the conventional production possibility set is defined from a reverse perspective. In this paper, presence of both desirable and undesirable outputs is assumed and a methodological framework for performing an unbiased efficiency analysis is proposed. The reverse production possibility set is defined and new models are presented regarding the full-inefficient frontier. The operational, environmental and overall reverse efficiencies are studied. The important notion of weak disposability is discussed and the effects of this assumption on the proposed models are investigated. The capability of the proposed method is examined using data from a real-world application about paper production.     

The efficient use of enterprise information for strategic advantage: A data envelopment analysis

A majority of manufacturers make use of some form of enterprise systems (ES), yet on average, the financial impact of ES adoption is essentially neutral. We propose that in an ES environment of easy information access, competitive success depends, in part, on the policies regulating enterprise information use. To explore this proposition, we examine the efficient use of different types of enterprise information in the realization of strategic performance. Efficient firms will devote fewer resources to information use to achieve the same strategic performance as less efficient firms.     

Modelling the iron ore price index: A new perspective from a hybrid data reconstructed EEMD-GORU model

As iron ore is the fundamental steel production resource, predicting its price is strategically important for risk management at related enterprises and projects. Based on a signal decomposition technology and an artificial neural network, this paper proposes a hybrid EEMD-GORU model and a novel data reconstruction method to explore the price risk and fluctuation correlations between China’s iron ore futures and spot markets, and to forecast the price index series of China’s and international iron ore spot markets from the futures market. The analysis found that the iron ore futures market in China better reflected the price fluctuations and risk factors in the imported and international iron ore spot markets. However, the forward price in China’s iron ore futures market was unable to adequately reflect the changes in the domestic iron ore market, and was therefore unable to fully disseminate domestic iron ore market information. The proposed model was found to provide better market risk perceptions and predictions through its combinations of the different volatility information in futures and spot markets. The results are valuable references for the early-warning and management of the related enterprise project risks.     

A covariate‐adjusted adaptive design for two‐stage clinical trials with survival data

A randomized two‐stage adaptive design is proposed and studied for allocation of patients to treatments and comparison in a phase III clinical trial with survival time as treatment responses. We consider the possibility of several covariates in the design and analysis. Several exact and limiting properties of the design and the follow‐up inference are studied, both numerically and theoretically. The applicability of the proposed methodology is illustrated by using some real data.     

A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model

It is well known that the standard Breusch and Pagan (1980) LM test for cross-equation correlation in a SUR model is not appropriate for testing cross-sectional dependence in panel data models when the number of cross-sectional units (n)$\left(n\right)$ is large and the number of time periods (T)$\left(T\right)$ is small. In fact, a scaled version of this LM test was proposed by Pesaran (2004) and its finite sample bias was corrected by Pesaran et al. (2008). This was done in the context of a heterogeneous panel data model. This paper derives the asymptotic bias of this scaled version of the LM test in the context of a fixed effects homogeneous panel data model. This asymptotic bias is found to be a constant related to n$n$ and T$T$, which suggests a simple bias corrected LM test for the null hypothesis. Additionally, the paper carries out some Monte Carlo experiments to compare the finite sample properties of this proposed test with existing tests for cross-sectional dependence.     

A methodology for testing a new spatial model of elections

The purpose of this paper is to offer a methodology for testing a new spatial theory of elections. Specifically, it is shown that the new spatial model of elections developed by Enelow and Hinich (1984a) is statistically equivalent to assuming that a classical factor structure underlies the data that voters provide concerning the issue positions of themselves and the candidates. A factor analysis of the sample correlation matrix of candidate variables averaged over voters and issues provides consistent estimates of the candidate locations in the space of predictive dimensions postulated by Enelow and Hinich, and the facor scores assigned to the voters can be used to project the voters onto the same predictive space with the candidates. This new scaling method is used to locate the positions of voters and candidates in the underlying predictive space of the 1980 Presidential election. Internal checks confirm the empirical adequacy of the candidate locations, and probit analysis is used as an external check on the empirical adequacy of the voter locations. For the pre-election data, no loss of accuracy in predicting voter choice was found in moving from the issue data to the estimated factor locations of voters and candidates. For the post-election data, a modest drop in accuracy was discovered. Overall, the empirical adequacy of factor analysis was confirmed as a methodology for testing the new Enelow-Hinich spatial model of elections.