Modeling the structure of gas distribution costs in urban areas

Urban-wide gas distribution cost models are developed and estimated, using capital costs, gas market, and population density data over cross-sections of communities served by two different utilities, with a particular emphasis on the multiproduct, multidimensional character of gas distribution: These models are used to clarify such policy issues as the allocation of joint costs through marginal cost pricing, the existence of ecpnomies of scale and density, and the appropriateness of natural monopoly status for gas distribution utilities.     

从人口老龄化探析调整徐州市城区生育政策的建议

徐州作为江苏省的人口大市,已经全面步入老龄化社会。人口老龄化对徐州的社会经济发展造成多方面的影响。从中国的情形看,计划生育带来的人口出生率下降是导致人口老化的最主要原因,适当改变生育政策的可以加速或延缓人口老龄化的过程。笔者主张,科学调整徐州主城区生育政策,把现行的追求低生育率政策平稳过渡为"低生育率水平与调控人口年龄结构质量并举"的政策,最大限度地发挥计划生育政策的积极作用,将计划生育政策所带来的消极作用限制在最小的范围内。     

Catastrophic structural change in a continuous regional model

This paper discusses a continuously dispersed production economy in two-dimensional space where one kind of output is produced by four primary inputs. Land is used as space and as a source of raw materials, which by the application of labour, capital equipment and energy are converted into the finished product. Land, capital and labour are available within the region, whereas energy is imported. Trade between locations is represented by continuous flows that follow routes minimizing transportation costs and are related to the local excess supplies and excess demands. The location pattern resulting from structural stability is studied. Afterwards umbilic catastrophes resulting from changes of, e.g., energy prices are discussed in detail.     

Topographical constraints and urban land supply indexes

This paper develops and applies a method for measuring the extent to which large bodies of water restrict urban land supply. The amount of land available for urban use is the sum of weighted annular areas, net of water, around the urban center. The weights exponentially decrease toward zero with distance from the center at a rate determined by the population density gradient. The method of measurement and the weights are derived from the theory of a monocentric city with a perfectly competitive land market. The method is applied to calculate land supply indexes for the 40 most populous U.S. urban areas in 1980, and indexes over time for two land-filled urban areas. Such indexes can be constructed to account for restrictions imposed by mountains and by zoning. They are useful in empirical studies of land, housing, transportation, and population density.     

The two‐sample linear regression model with interval‐censored covariates

There are surveys that gather precise information on an outcome of interest, but measure continuous covariates by a discrete number of intervals, in which case the covariates are interval censored. For applications with a second independent dataset precisely measuring the covariates, but not the outcome, this paper introduces a semiparametrically efficient estimator for the coefficients in a linear regression model. The second sample serves to establish point identification. An empirical application investigating the relationship between income and body mass index illustrates the use of the estimator.     

Trivariate non‐Gaussian copulas to analyze the spatial behavior of rat sightings

The brown rat lives with man in a wide variety of environmental contexts and adversely affects public health by transmission of diseases, bites, and allergies. Understanding behavioral and spatial correlation aspects of pest species can contribute to their effective management and control. Rat sightings can be described by spatial coordinates in a particular region of interest defining a spatial point pattern. In this paper, we investigate the spatial structure of rat sightings in the Latina district of Madrid (Spain) and its relation to a number of distance‐based covariates that relate to the proliferation of rats. Given a number of locations, biologically considered as attractor points, the spatial dependence is modeled by distance‐based covariates and angular orientations through copula functions. We build a particular spatial trivariate distribution using univariate margins coming from the covariate information and provide predictive distributions for such distances and angular orientations.     

Analysis of marginally specified semi-nonparametric models for clustered binary data

Generalized linear mixed models are widely used for analyzing clustered data. If the primary interest is in regression parameters, one can proceed alternatively, through the marginal mean model approach. In the present study, a joint model consisting of a marginal mean model and a cluster-specific conditional mean model is considered. This model is useful when both time-independent and time-dependent covariates are available. Furthermore our model is semi-parametric, as we assume a flexible, smooth semi-nonparametric density of the cluster-specific effects. This semi-nonparametric density-based approach outperforms the approach based on normality assumption with respect to some important features of 'between-cluster variation'. We employ a full likelihood-based approach and apply the Monte Carlo EM algorithm to analyze the model. A simulation study is carried out to demonstrate the consistency of the approach. Finally, we apply this to a study of long-term illness data.     

The changing distribution of physicians.

Over the past decade the problem of physician distribution has been the object of much research. Most past studies, however, have been cross sectional. In this study, ecological (county level) data for two decades are examined. Six consistent predictors of the physician/population ratio (PPR) were identified: the hospital bed/population ratio, per capita retail sales, percentage male professionals, per cent families with high income, the presence of a medical school and percentage of the population over 65 years of age. The percentage of physicians in group practice, recently lauded as a solution to problems of maldistribution, was found to be negatively related to change in the physician/population ratio. Predictions for more populous counties were found to be more accurate than those for less populous counties. Policy implications are discussed.     

Direct and indirect effects of continuous treatments based on generalized propensity score weighting

This paper proposes semi- and nonparametric methods for disentangling the total causal effect of a continuous treatment on an outcome variable into its natural direct effect and the indirect effect that operates through one or several intermediate variables called mediators jointly. Our approach is based on weighting observations by the inverse of two versions of the generalized propensity score (GPS), namely the conditional density of treatment either given observed covariates or given covariates and the mediator. Our effect estimators are shown to be asymptotically normal when the GPS is estimated by either a parametric or a nonparametric kernel-based method. We also provide a simulation study and an empirical illustration based on the Job Corps experimental study.     

Community Classification and Growth in Effective Property Tax Rates: A Case Study of Rate Divergence in 39 Rhode Island Towns

Abstract . A multiple regression analysis of cross-sectional data for 39 Rhode Island towns indicates that variation in the level of effective property tax rates among communities can be substantially explained. The determinants are a community's population density, median family income, real property per capita, and the ratio of commercial to total property tax, revenue. Population density serves as a criterion for judging the “cityness” (1) of a community, that is, its degree of urbanization. A positive relationship exists between population density and effective property tax rate. Communities with the highest population density tend to have the highest tax rates. This relationship is shown in each analyzed year. Covariance analysis applied to the regression coefficients for the various years reveals a significant change in the population density coefficient. This coefficient change indicates a divergence in effective property tax rates among city, suburban, and rural communities.     

The Asymptotics of MM-Estimators for Linear Regression with Fixed Designs

MM-estimators achieve simultaneous high efficiency and high breakdown point over contamination neighborhoods. Inference based on these estimators relies on their asymptotic properties, which have been studied for the case of random covariates. In this paper we show that, under relatively mild regularity conditions, MM-estimators for linear regression models are strongly consistent when the design is fixed. Moreover, their strong consistency allows us to show that these estimators are also asymptotically normal for non-random covariates. These results justify the use of a normal approximation to the finite-sample distribution of MM-estimators for linear regression with fixed explanatory variables. Additionally, these results have been used to extend the robust bootstrap (Salibian-Barrera and Zamar in Ann Stat 30:556–582, 2002) to the case of fixed designs [see Salibian-Barrera 2004, submitted].Research supported by an NSERC Research Grant (Individual)     

Projecting the future size and health status of the U.S. elderly population

"A projection model based on a multivariate continuous state, stochastic process is presented. The model allows multiple time-varying covariates to be used so parameters can be estimated from time series information on health changes and mortality, and their interaction. Health changes are simulated by altering parameters controlling the age trajectory and diffusion of risk factor means, variances, and covariances....By increasing the information used in projections it may be possible to better (a) anticipate the state of health at extreme ages, (b) forecast changes in health at specific ages over time, (c) stimulate the effects of specific interventions, and (d) determine the sensitivity of outcomes to a range of interventions."     

Determinants of the Choice of Migration Destination*

This paper examines migrants’ choice of destination conditional on migration. The study uses data from two rounds of Nepal Living Standard Surveys and a Population Census and examine how the choice of a migration destination is influenced by various covariates, including income differentials across possible destinations. We find that migrants move primarily to nearby, high population density areas where many people share their language and ethnic background. Better access to amenities is significant as well. Differentials in average income across destination districts are significant in univariate comparisons but not once we control for other covariates. Differentials in consumption expenditures are statistically significant but smaller in magnitude than other determinants. It is differentials in absolute, not relative, consumption between destination districts that are correlated with the destination of work migrants. Except for the latter, results are robust to different specifications and datasets.     

On the foundations of land use theory : Discrete versus continuous populations

Urban economists and location theorists have long employed land use models with a continuum of agents distributed over a continuum of locations. However, these continous models have been criticized on behavioral grounds in that individual households can consume only zero amounts of land in equilibrium. Hence the central purpose of this paper is to propose an alternative interpretation of these continous models as limiting approximations of discrete population models. In particular, it is shown that for large population sizes, the population distributions of the classical continuous model uniformly approximate the equilibrium population distributions generated by an appropriately defined class of discrete population models.     

谈农村高压输电线路设计

在农村电网建设与改造中,笔者根据农村电网建设与改造有关要求,并结合桂平市气象条件及地形等情况,合理规划线路网络,使输电线路的路径选择和杆塔布置合理、适当,达到安全经济的要求。在设计过程中,笔者会同施工、运行单位有关人员共同参加确定方案,完成初、终勘察及内、外业的有关工作,合理使用新型产品,以高质量、高效率完成农村电网建设与改造高压输电线路工程。     

Semiparametric estimation of logistic regression model with missing covariates and outcome

We consider a semiparametric method to estimate logistic regression models with missing both covariates and an outcome variable, and propose two new estimators. The first, which is based solely on the validation set, is an extension of the validation likelihood estimator of Breslow and Cain (Biometrika 75:11–20, 1988). The second is a joint conditional likelihood estimator based on the validation and non-validation data sets. Both estimators are semiparametric as they do not require any model assumptions regarding the missing data mechanism nor the specification of the conditional distribution of the missing covariates given the observed covariates. The asymptotic distribution theory is developed under the assumption that all covariate variables are categorical. The finite-sample properties of the proposed estimators are investigated through simulation studies showing that the joint conditional likelihood estimator is the most efficient. A cable TV survey data set from Taiwan is used to illustrate the practical use of the proposed methodology.     

Bounds on average causal effects in studies with a latent response variable

Consider a case where cause-effect relationships between variables can be described as a directed acylic graph and the corresponding recursive factorization of a joint distribution. In order to provide the bounds on average causal effects in studies with a latent response variable, this paper proposes a graphical criterion for selecting covariates and variables caused by the response variable. The result enables us not only to judge from the graph structure whether the bounds on an average causal effect can be expressed through the observed quantities, but also to provide their closed-form expressions in case where its answer is affirmative. The graphical criterion of this paper is helpful to evaluate the bounds on average causal effects when it is difficult to observe a response variable.     

Simulating the spatial diffusion of innovation: A gaming experimental approach

This article reports the results of a computer game experiment that allows spatial aspects of the diffusion of innovation to be examined in a controlled environment. Factors found to affect outlet density were population and the population by distance interaction. Time of initial outlet establishment was generally influenced by population and distance, but the strength of the effect varied by experimental treatment.     

Robust building evacuation planning in a dynamic network flow model under collapsible nodes and arcs

Rapid urbanization has caused various social problems. One typical example is the high population density of a building, particularly in a commercial building or a mega-mall. When an emergency, such as a natural or human-made disaster, occurs in a building with a high population, establishing a proper evacuation plan is required to minimize casualties. Accordingly, the evacuation planning problem, which determines optimal routes for evacuees from disaster-prone areas to safe areas, has been actively studied in various fields. However, research considering the possibility of further collapse of a specific area or intermediate route in the building has been overlooked. We propose a robust evacuation planning problem based on a dynamic network flow model that determines the optimal routes for evacuees from a building that has the potential to collapse. Computational results show that routes passing through areas with the potential to collapse may or may not be optimal for evacuees, depending on the given timeframe. If the timeframe is sufficient, detouring around the collapsible areas could be the optimal plan; however, if the timeframe is insufficient, passing through collapsible areas, with taking the risk, could be the optimal plan.