基于Panel Data和SEA的环境Kuznets曲线分析 ——与马树才、李国柱两位先生探讨

 针对当前学者研究中国环境Kuznets曲线存在的问题，本文使用了面板数据模型和空间计量模型，以克服使用时间序列模型时样本数量偏少和使用截面数据时易引起空间自相关性等问题。结果表明中国有部分环境指标满足环境Kuznets曲线的倒U型特征。     

Improvement of financial management by local government: Computer model implementation

Abstract

We develop a computerized optimization model and present its implementation for improvement of financial management at the local government (LG) level. An example of the real-life long-term budget planning and analysis, helped by the model, is presented. The analysis exemplifies good governance practice and observation of standards of efficient management in the area of long-term financial, investment and safe debt planning. These analyses also demonstrate ways of accessing maximum, feasible level of investment expenditure and maximum capacity of a municipality to borrow with all safety measures provided. The model supports informed decision-making process by LG managers, decreases the level of risk and enhances quality and transparency of governance.     

Quantitative refinements for comparisons of institutional performance

In the context of the data and issues discussed by Goldstein and Spiegelhalter, we suggest refinements which can be used by decision makers when confronted with ranking problems associated with 'league tables'. Two ranking criteria are defined and their performance illustrated for one of the studies reported by Goldstein and Spiegelhalter.     

Ramifications of Monitoring Service Quality Through Passively Solicited Customer Feedback*

It is common for service providers to collect data from customers as part of efforts to monitor quality. Often, this data is passively collected, meaning (a) any solicitation of feedback is done without direct customer interaction, and (b) the customer initiates any response given. Examples include customer comment cards, toll-free telephone numbers, and comment links on World Wide Web pages. This article compares passive data collection with active methods (e.g., interviews and mail surveys). Passive methods generally have lower response rates and are inherently biased, but have cost and sample frame advantages when used to monitor quality on a continuous basis. Despite the biased nature of passive methods, this article describes the successful validation of a common customer-response model with passively collected empirical data. The model is expanded to consider the impact of complaint and compliment solicitation on customers' evaluation of the service provider. Results show that this impact is negative, and that customers who spontaneously register complaints generally record higher ratings of the service provider than customers who complain in response to a complaint solicitation. Discussion and conclusions are given.     

Welfare deservingness opinions from heuristic to measurable concept: The CARIN deservingness principles scale

A steadily growing number of studies investigate how popular support for social policies targeting particular groups is rooted in citizens’ deservingness opinions. According to theory, people fall back on five criteria – Control, Attitude, Reciprocity, Identity and Need (CARIN) – to distinguish the deserving from the undeserving. Deservingness opinions are assumed to be important predictors of support for particular welfare arrangements. A striking feature of this emerging research, however, is that there is no agreed-upon strategy to measure deservingness. Most previous studies rely on proxy-variables rather than measuring the actual deservingness criteria. Deservingness functions as a heuristic rather than as a measured concept, which leads to conceptual confusion. To remedy this shortcoming, this contribution proposes and validates a new instrument –the CARIN deservingness principles scale- that captures the five basic deservingness principles. We analyse data from the Belgian National Election Study by means of structural equation modelling (SEM) to (1) test the dimensionality, validity and reliability of the scale, and (2) verify to what extent the five deservingness principles predict specific policy preferences (as a test of construct validity). Our analyses confirm that the five deservingness principles are distinct dimensions that are differently related to social structural variables and have divergent consequences for policy preferences. The finding of theoretically meaningful patterns of differentiated effects illustrates that the CARIN criteria represent distinct logics of social justice, and corroborates that our measurement instrument is capable of tapping into the essence of these criteria.     

Evaluation of Bayesian multiple stage estimation under spatial CAR model variants

In this study, an evaluation of Bayesian hierarchical models is made based on simulation scenarios to compare single-stage and multi-stage Bayesian estimations. Simulated datasets of lung cancer disease counts for men aged 65 and older across 44 wards in the London Health Authority were analysed using a range of spatially structured random effect components. The goals of this study are to determine which of these single-stage models perform best given a certain simulating model, how estimation methods (single- vs. multi-stage) compare in yielding posterior estimates of fixed effects in the presence of spatially structured random effects, and finally which of two spatial prior models – the Leroux or ICAR model, perform best in a multi-stage context under different assumptions concerning spatial correlation. Among the fitted single-stage models without covariates, we found that when there is low amount of variability in the distribution of disease counts, the BYM model is relatively robust to misspecification in terms of DIC, while the Leroux model is the least robust to misspecification. When these models were fit to data generated from models with covariates, we found that when there was one set of covariates – either spatially correlated or non-spatially correlated, changing the values of the fixed coefficients affected the ability of either the Leroux or ICAR model to fit the data well in terms of DIC. When there were multiple sets of spatially correlated covariates in the simulating model, however, we could not distinguish the goodness of fit to the data between these single-stage models. We found that the multi-stage modelling process via the Leroux and ICAR models generally reduced the variance of the posterior estimated fixed effects for data generated from models with covariates and a UH term compared to analogous single-stage models. Finally, we found the multi-stage Leroux model compares favourably to the multi-stage ICAR model in terms of DIC. We conclude that the mutli-stage Leroux model should be seriously considered in applications of Bayesian disease mapping when an investigator desires to fit a model with both fixed effects and spatially structured random effects to Poisson count data.     

Case-based methods and agent-based modelling: bridging the divide to leverage their combined strengths

Two leading camps for studying social complexity are case-based methods (CBM) and agent-based modelling (ABM). Despite the potential epistemological links between ‘cases’ and ‘agents,’ neither camp has leveraged their combined strengths. A bridge can be built, however, by drawing on Abbott’s insight that ‘agents are cases doing things’, Byrne’s suggestion that ‘cases are complex systems with agency’, and by viewing CBM and ABM within the broader trend towards computational modelling of cases. To demonstrate the utility of this bridge, we describe how CBM can utilise ABM to identify case-based trends; explore the interactions and collective behaviour of cases; and study different scenarios. We also describe how ABM can utilise CBM to identify agent types; construct agent behaviour rules; and link these to outcomes to calibrate and validate model results. To further demonstrate the bridge, we review a public health study that made initial steps in combining CBM and ABM.     

Exploring gillnet catch efficiency of sardines in the coastal waters of Sri Lanka by means of three statistical techniques: a comparison of linear and nonlinear modelling techniques

The present investigation was undertaken to study the gillnet catch efficiency of sardines in the coastal waters of Sri Lanka using commercial catch and effort data. Commercial catch and effort data of small mesh gillnet fishery were collected in five fisheries districts during the period May 1999–August 2002. Gillnet catch efficiency of sardines was investigated by developing catch rates predictive models using data on commercial fisheries and environmental variables. Three statistical techniques [multiple linear regression, generalized additive model and regression tree model (RTM)] were employed to predict the catch rates of trenched sardine Amblygaster sirm (key target species of small mesh gillnet fishery) and other sardines (Sardinella longiceps, S. gibbosa, S. albella and S. sindensis). The data collection programme was conducted for another six months and the models were tested on new data. RTMs were found to be the strongest in terms of reliability and accuracy of the predictions. The two operational characteristics used here for model formulation (i.e. depth of fishing and number of gillnet pieces used per fishing operation) were more useful as predictor variables than the environmental variables. The study revealed a rapid tendency of increasing the catch rates of A. sirm with increased sea depth up to around 32 m.     

An extended Gaussian max-stable process model for spatial extremes

The extremes of environmental processes are often of interest due to the damage that can be caused by extreme levels of the processes. These processes are often spatial in nature and modelling the extremes jointly at many locations can be important. In this paper, an extension of the Gaussian max-stable process is developed, enabling data from a number of locations to be modelled under a more flexible framework than in previous applications. The model is applied to annual maximum rainfall data from five sites in South-West England. For estimation we employ a pairwise likelihood within a Bayesian analysis, incorporating informative prior information.