Microeconometric Models of Rationing, Imperfect Markets, and Non-Negativity Constraints

This paper provides a theoretically consistent approach to estimating demand relationships in which kink points occur either in the interior or on the vertices of the budget set. There are important classes of problems in developing countries which demonstrate such kinked budget sets including binding non-negativity constraints. This paper also extends these methods to the estimation of production structures. As an application a translog cost function for three energy inputs is estimated from cross-sections of individual Indonesian firms.Political Economy,

Simulated Maximum Likelihood Estimation of the Linear Expenditure System with Binding Non-Negativity Constraints

This paper discusses issues on the estimation of consumer demand equations subject to binding non-negative constraints. We propose computationally feasible specifications and a simulated maximum likelihood (SML) method for demand systems. Our study shows that the econometric implementation of the SML estimates can avoid high-dimensional integration problems. As contrary to the simulation method of moments and simulated pseudo-likelihood methods that require the simulation of demand quantities subject to nonnegativity constraints for consumers in the sample, the SML approach requires only simulation of the likelihood function. The SML approach avoids solving for simulated demand quantities because the likelihood function is conditional on observed demand quantities. We have applied SML approach for the linear expenditure system (LES) with non-negativity constraints. The results of a seven-goods demand system are presented. The results provide empirical evidence on the importance of taking into account possible cross equation correlations in disturbances.Simulated likelihood, Linear expenditure system, Non-negativity constraints, Multivariate censored variables, Nonlinear simultaneous equations

Thinking, Feeling, and Worrying: How Uncertainty and Anticipatory Anxiety Affect Technology Use

How does uncertainty and anticipatory anxiety affect technology use? Earlier research has consistently suggested that uncertainty and anticipatory anxiety adversely impels one’s logical judgments, decisions, and behaviors in many situations. In this paper, we examine the combined influence of uncertainty and anticipatory anxiety on technology use. While the Technology Acceptance Model (TAM) has been widely adopted and used, it has shown limited explanatory and predictive power (Chuttur, 2009). The low explanatory power begs for an explanation to what is missing? We believe that uncertainty and anticipatory anxiety could provide a substantial addition to explaining technology use. We suggest that investigating a person’s uncertainty and anticipatory anxiety due to unforeseen/unpredictable circumstances and outcomes could lend to a better understanding of a user’s behavioral intention and use. Thus, the contribution of this study will shed light on the role of uncertainty and anticipatory anxiety on the fundamental issue of technology use

Energy-efficient, On-demand Reprogramming of Large-scale Sensor Networks

As sensor networks operate over long periods of deployment in difficult to reach places, their requirements may change or new code may need to be uploaded to them. The current state of the art protocols (Deluge and MNP) for network reprogramming perform the code dissemination in a multi-hop manner using a three way handshake whereby meta-data is exchanged prior to code exchange to suppress redundant transmissions. The code image is also pipelined through the network at the granularity of pages. In this paper we propose a protocol called Freshet for optimizing the energy for code upload and speeding up the dissemination if multiple sources of code are available. The energy optimization is achieved by equipping each node with limited non-local topology information, which it uses to determine the time when it can go to sleep since code is not being distributed in its vicinity. The protocol to handle multiple sources provides a loose coupling of nodes to a source and disseminates code in waves each originating at a source, with mechanism to handle collisions when the waves meet. The protocol’s performance with respect to reliability, delay, and energy consumed, is demonstrated through analysis, simulation, and implementation on the Berkeley mote platform

Computational fluid dynamics modeling of symptomatic intracranial atherosclerosis may predict risk of stroke recurrence.

BackgroundPatients with symptomatic intracranial atherosclerosis (ICAS) of ≥ 70% luminal stenosis are at high risk of stroke recurrence. We aimed to evaluate the relationships between hemodynamics of ICAS revealed by computational fluid dynamics (CFD) models and risk of stroke recurrence in this patient subset.MethodsPatients with a symptomatic ICAS lesion of 70-99% luminal stenosis were screened and enrolled in this study. CFD models were reconstructed based on baseline computed tomographic angiography (CTA) source images, to reveal hemodynamics of the qualifying symptomatic ICAS lesions. Change of pressures across a lesion was represented by the ratio of post- and pre-stenotic pressures. Change of shear strain rates (SSR) across a lesion was represented by the ratio of SSRs at the stenotic throat and proximal normal vessel segment, similar for the change of flow velocities. Patients were followed up for 1 year.ResultsOverall, 32 patients (median age 65; 59.4% males) were recruited. The median pressure, SSR and velocity ratios for the ICAS lesions were 0.40 (-2.46-0.79), 4.5 (2.2-20.6), and 7.4 (5.2-12.5), respectively. SSR ratio (hazard ratio [HR] 1.027; 95% confidence interval [CI], 1.004-1.051; P = 0.023) and velocity ratio (HR 1.029; 95% CI, 1.002-1.056; P = 0.035) were significantly related to recurrent territorial ischemic stroke within 1 year by univariate Cox regression, respectively with the c-statistics of 0.776 (95% CI, 0.594-0.903; P = 0.014) and 0.776 (95% CI, 0.594-0.903; P = 0.002) in receiver operating characteristic analysis.ConclusionsHemodynamics of ICAS on CFD models reconstructed from routinely obtained CTA images may predict subsequent stroke recurrence in patients with a symptomatic ICAS lesion of 70-99% luminal stenosis

Can the target set for reducing childhood overweight and obesity be met? : a system dynamics modelling study in New South Wales, Australia

The persistent prevalence of childhood overweight and obesity raises significant concerns about the impact on health, society and the economy. Responding to a target announced in September 2015 by the New South Wales (Australia) Premier to reduce childhood overweight and obesity by five percentage points by 2025, a system dynamics model was developed to support Government and stakeholders responsible for meeting the target. A participatory model building process, drawing cross-sectorial expertise, was undertaken to estimate the individual and combined impact of interventions on meeting the target. The model demonstrated that it is theoretically possible to meet the target by implementing a comprehensive combination of policies and programmes. When limited to existing and enhanced population health interventions, the modelled result did not reach the target. The project provides an example of how participatory simulation modelling can combine a broad range of interventions together into likely scenarios and usefully inform government decision-making

Air Quality Health Benefits of the Nevada Renewable Portfolio Standard

In recent years, renewable portfolio standards (RPS), which require a certain percentage of electricity sold to consumers to come from renewable resources, have been established by many state governments to mitigate emissions of greenhouse gases and air pollutants in the United States. Nevada’s RPS set a target of 50% of electricity to come from renewable sources by 2030. By coupling the U.S. Environmental Protection Agency’s AVoided Emissions and geneRation Tool (AVERT) and CO–Benefits Risk Assessment (COBRA) model, this study assesses potential emission reductions from fossil fuels owing to this requirement and regional health benefits via improved air quality, as well as how these benefits vary spatially under high and low projected electricity demands in 2030. Successful implementation of the RPS could produce health benefits equivalent to USD 3–8 million per year for Nevada residents and up to USD 164 million per year for the entire U.S. Nevada is ranked only 6th among states benefiting from the policy, while California and Washington obtain the most health benefits. There is also inequity among Nevada counties, partly caused by the county population and proximity to major fossil fuel power plants. Lowering electricity demands by 5% in Nevada would lead to a ~10% increase in health benefits. These findings should empower public support of RPS policies and energy conservation to reduce air pollution and public health inequity for the region

Validation and recalibration of the Framingham cardiovascular disease risk models in an Australian Indigenous cohort: Does the current Framingham risk calculator accurately estimate true CVD risk for Indigenous Australians?

In this study, we validated both the 1991 and 2008 Framingham CVD models using a cohort of Aboriginal and Torres Strait Islander adults drawn from remote Indigenous communities in Far North Queensland. Recalibration was also conducted to help generate more accurate CVD risk predictions for this population. Finally, we developed a CVD risk chart that could help improve the assessment and management of CVD in the Australian Indigenous population, particularly those in remote regions of Australia.The research reported in this paper is a project of the Australian Primary Health Care Research Institute, which is supported by a grant from the Australian Government Department of Health and Ageing under the Primary Health Care Research, Evaluation and Development Strategy