Project description:Prior research tends to propose and examine the negative relationship between market segmentation and energy efficiency. Does market segmentation necessarily impair energy efficiency? Considering the critical role that Chinaese government play in managing erergy efficiency, we propose a non-linear relationship between market segmentation and energy efficiency. Using data of 30 provinces in Mainland China during 2000 to 2017, we find an inverse U-shaped relationship between market segmentation and energy efficiency. Our findings remain robust after controlling endogeneity issues. Therefore, a moderate level of market segmentation is acceptable and beneficial for long-term improvement of energy efficiency in emerging economies.
Project description:Batched data is a type of data where each observed data value is the sum of a number of grouped (batched) latent ones obtained under different conditions. Batched data arises in various practical backgrounds and is often found in social studies and management sector. The analysis of such data is analytically challenging due to its structural complexity. In this article, we describe how to analyze batched service time data, estimate the mean and variance of each batch that are latent. We in particular focus on the situation when the observed total time includes an unknown proportion of non-service time. To address this problem, we propose a Gaussian model for efficiency as well as a semi-parametric kernel density model for robustness. We evaluate the performance of both proposed methods through simulation studies and then applied our methods to analyze a batched data.
Project description:With the development of information technology, improving the efficiency of public services with the help of the Internet has become an important work of local governments. However, under different institutional environments, the impact mechanism of Internet development on the supply efficiency of government public services is still unclear. Based on China's interprovincial panel data from 2011 to 2019, this paper constructs a threshold effect model, sets the institutional environment as the threshold variable, and empirically analyzes the impact of Internet development on the supply efficiency of government public services. The results show that the difference in regional institutional environment will lead to the obvious threshold effect of Internet development on the supply efficiency of government public services: When the institutional environment is poor, the role of Internet development on the supply efficiency of government public services is not significant. With the improvement of the institutional environment, the role of Internet development in promoting the supply efficiency of government public services gradually appears, but the marginal intensity of promotion weakens. Compared with existing studies that mostly use linear models, this paper incorporates the institutional environment into the complex relationship between Internet development and government public service supply efficiency, and clarifies the role of the institutional environment in the process of Internet development affecting government public service supply efficiency and the non-linear relationship among the three. This paper reveals the mechanism of Internet development affecting the supply efficiency of government public services under different institutional environments and provides a new perspective for solving the shortage of public services.
Project description:For estimating conditional survival functions, non-parametric estimators can be preferred to parametric and semi-parametric estimators due to relaxed assumptions that enable robust estimation. Yet, even when misspecified, parametric and semi-parametric estimators can possess better operating characteristics in small sample sizes due to smaller variance than non-parametric estimators. Fundamentally, this is a bias-variance trade-off situation in that the sample size is not large enough to take advantage of the low bias of non-parametric estimation. Stacked survival models estimate an optimally weighted combination of models that can span parametric, semi-parametric, and non-parametric models by minimizing prediction error. An extensive simulation study demonstrates that stacked survival models consistently perform well across a wide range of scenarios by adaptively balancing the strengths and weaknesses of individual candidate survival models. In addition, stacked survival models perform as well as or better than the model selected through cross-validation. Finally, stacked survival models are applied to a well-known German breast cancer study.
Project description:BackgroundWithin the current context of continued austerity and post-pandemic recovery, it remains important that Local Government services address the increasing needs of residents as cost-effectively as possible. Alliancing, whereby services work collaboratively focusing on the 'whole-system', has gained popularity as a tool with the potential to support collaborative whole systems approaches. This synthesis aims to identify how alliancing can be successfully operationalised in the commissioning of public health, wider National Health Service (NHS) and social care-related services.MethodsA realist literature synthesis was undertaken in order to identify underlying generative mechanisms associated with alliancing, the contextual conditions surrounding the implementation and operationalisation of the alliancing approach mechanisms, and the outcomes produced as a result. An iterative approach was taken, using a recent systematic review of the effectiveness of Alliancing, online database searches, and grey literature searches.ResultsThree mechanistic components were identified within the data as being core to the successful implementation of alliances in public health and social care-related services within Local Government: (i) Achieving a system-level approach; (ii) placing local populations at the heart of the system; and (iii) creating a cultural shift. Programme theories were postulated within these components.ConclusionsThe alliancing approach offers an opportunity to achieve system-level change with the potential to benefit local populations. The realist synthesis approach taken within this study has provided insights into the necessary contextual and mechanistic factors of the Alliancing approach, above and beyond effectiveness outcomes typically collected through more conventional evaluation methodologies.
Project description:Semi-continuous data present challenges in both model fitting and interpretation. Parametric distributions may be inappropriate for extreme long right tails of the data. Mean effects of covariates, susceptible to extreme values, may fail to capture relevant information for most of the sample. We propose a two-component semi-parametric Bayesian mixture model, with the discrete component captured by a probability mass (typically at zero) and the continuous component of the density modeled by a mixture of B-spline densities that can be flexibly fit to any data distribution. The model includes random effects of subjects to allow for application to longitudinal data. We specify prior distributions on parameters and perform model inference using a Markov chain Monte Carlo (MCMC) Gibbs-sampling algorithm programmed in R. Statistical inference can be made for multiple quantiles of the covariate effects simultaneously providing a comprehensive view. Various MCMC sampling techniques are used to facilitate convergence. We demonstrate the performance and the interpretability of the model via simulations and analyses on the National Consortium on Alcohol and Neurodevelopment in Adolescence study (NCANDA) data on alcohol binge drinking.
Project description:We propose a Bayesian variable selection method in semi-parametric models with applications to genetic and epigenetic data (e.g., single nucleotide polymorphisms and DNA methylation, respectively). The data are individually standardized to reduce heterogeneity and facilitate simultaneous selection of categorical (single nucleotide polymorphisms) and continuous (DNA methylation) variables. The Gaussian reproducing kernel is applied to the transformed data to evaluate joint effect of the variables, which may include complex interactions between, e.g., single nucleotide polymorphisms and DNA methylation. Indicator variables are introduced to the model for the purpose of variable selection. The method is demonstrated and evaluated using simulations under different scenarios. We apply the method to identify informative DNA methylation sites and single nucleotide polymorphisms in a set of genes based on their joint effect on allergic sensitization. The selected single nucleotide polymorphisms and methylation sites have the potential to serve as early markers for allergy prediction, and consequently benefit medical and clinical research to prevent allergy before its manifestation.
Project description:Eco-efficiency assessment of municipal solid waste (MSW) suppliers is a useful tool in the transition to a circular economy. Furthermore, it provides evidence of the economic and environmental performance of municipalities that can be used for decision-making and/or elaboration of regulatory policies. In this study, eco-efficiency scores were computed for a sample of 140 Chilean municipalities in the provision of MSW services. In doing so, the stochastic semi-parametric envelopment of data method was applied. It is a novel technique which overcomes the limitations of parametric (stochastic frontier analysis) and non-parametric (data envelopment analysis) methods previously employed to evaluate the eco-efficiency of MSW services. The average eco-efficiency of the 140 assessed municipalities was 0.332 which indicates that they could save 66.8% of their operational costs and recycling the same amount of waste. Moreover, 61.4% of the evaluated municipalities presented an eco-efficiency score which was lower than 0.4, whereas the other municipalities (38.6% of the sample) exhibited an eco-efficiency which raged between 0.4 and 0.80. Hence, none of the municipalities assessed was identified as eco-efficient which, implies that there is room for all municipalities to reduce operational costs in the management of MSW. Population density, tourism and location of the municipality were identified as factors influencing the eco-efficiency of the municipalities in MSW management.
Project description:Employer attractiveness is an important variable for any organization. It is therefore not surprising that organizations try to control this facet when communicating recruitment messages for positions to be filled. This study aims to capture this process for public sector organizations, while looking at the role that a particular type of prosocial motivation - public service motivation: the motivation people have to contribute to society - plays in this process. To this end, a survey-experiment (N = 192) with prospective employees is carried out in which recruitment messages with three different value statements (public, private, neutral) are presented to the respondents. The effect of these message on both attractiveness and person-organization fit, as moderated by public service motivation, is tested. The results indicate that public service motivation indeed moderates the effect of these messages. However, the results do not fully corroborate the theoretical expectations. Therefore, additional exploratory analyses are performed in order to better understand the variables included in this process. This provides a direction for further research. Theoretical and practical implications are discussed.
Project description:OBJECTIVE:To examine whether market competition is associated with improved health outcomes in hemodialysis. DATA SOURCES:Secondary analysis of data from a national dialysis registry between 2001 and 2011. STUDY DESIGN:We conducted one- and two-part linear regression models, using each hospital service area (HSA) as its own control, to examine the independent associations among market concentration and health outcomes. DATA COLLECTION:We selected cohorts of patients receiving in-center hemodialysis in the United States at the start of each calendar year. We used information about dialysis facility ownership and the location where patients received dialysis to measure an index of market concentration-the Hirschman-Herfindahl Index (HHI)-for HSA and year, which ranges from near zero (perfect competition) to one (monopoly). PRINCIPAL FINDINGS:An average reduction in HHI by 0.2 (one standard deviation in 2011) was associated with 2.9 fewer hospitalizations per 100 patient-years (95 percent CI, 0.4 to 5.4). If these findings were generalized to the entire in-center hemodialysis population, this would translate to 8,100 (95 percent CI 1,200 to 15,000) fewer hospitalizations in 2011. There was no association between change in market competition and mortality. CONCLUSIONS:Market competition in dialysis may lead to improved health outcomes.