Regional growth and interstate migration

The current study examines a simultaneous equation model of interstate migration using income growth, employment growth, unemployment growth, population growth, gross migration, and employment in manufacturing as endogenous variables. The results show that neither the growth of employment nor the growth of income in the destination location has been directly important determinants of migration flow. However, an indirect effect through the population variable can be discerned for these variables, and this has important policy implications. A key feature of this migration model is that it incorporates most of the determinant factors as rates of change over time. The study sheds light on the joint and indirect effects of migration and other endogenous variables and draws some important policy implications pertaining to growth.     

U.S. interstate labor force migration: An analysis of trends, net exchanges, and migration subsystems

The rich geography and complex temporal trends of U.S. interstate labor force migration are portrayed. The most commonly reported net migration statistics hide multi-faceted patterns of state-to-state exchange. Maps depicting net migration balances show that much population redistribution has been taking place counter to the popularly conceived Frostbelt-to-Sunbelt flow. Significant net migration exchange takes place within each of the major regions of the U.S. as well as between them.

Principal component analyses carried out on gross state-to-state flow tables for 1960–1965, 1965–1970, and 1970–1975 suggest the existence of a set of remarkably stable migration subsystems, despite the heralded net migration turnarounds in nonmetropolitan-to-metropolitan and south-to-north patterns of flow.     

国防生担任高校学生军训教官的探索

学生军训工作全面开展以来,出现了许多新情况、新问题.特别是近年来我国高校不断扩大招生规模,学生军训任务越来越重.随着军队编制体制调整,部队的承训能力也面临着巨大的压力.国防生,作为部队的后备干部,具备较强的军政素养争组织管理能力.采取国防生担任军训教官,既缓解了参训部队人员不足的压力,又给国防生提供了难得的实践锻炼机会,可谓一举多得.     

A note on individual choice models of migration

In this paper individual probabilistic choice models are developed for the decision to migrate and the choice among alternative destinations. The models are developed to investigate how characteristics of decision makers and of alternative destinations affect choice. Several migration models in the literature (e.g., mover-stayer models) are shown to be special cases, their behavioral assumptions are made explicit, and a framework for testing these assumptions is provided.     

The effects of supportive management and job quality on the turnover intentions and health of military personnel

To be competitive in today's increasingly complex and rapidly changing envi‐ronment, organizations must retain personnel and promote the well‐being of employees. We examine the relationship of both support provided to person‐nel and job quality with employee health and turnover intentions among a sample of 450 military personnel. Factors involving the supportive manage‐ment of personnel (i.e., supervisory support, organizational support, and work‐life balance) and factors pertaining to job quality (i.e., work stimulation and job clarity) were indirectly related to health and to turnover intentions through the mediating influence of job satisfaction. © 2007 Wiley Periodicals, Inc.     

The effects of handling outliers on the performance of bankruptcy prediction models

Ratio type financial indicators are the most popular explanatory variables in bankruptcy prediction models. These measures often exhibit heavily skewed distribution because of the presence of outliers. In the absence of clear definition of outliers, ad hoc approaches can be found in the literature for identifying and handling extreme values. However, it is not clear how these different approaches can affect the predictive power of models. There seems to be consensus in the literature on the necessity of handling outliers, at the same time, it is not clear how to define extreme values to be handled in order to maximize the predictive power of models. There are two possible ways to reduce the bias originating from outliers: omission and winsorization. Since the first approach has been examined previously in the literature, we turn our attention to the latter. We applied the most popular classification methodologies in this field: discriminant analysis, logistic regression, decision trees (CHAID and CART) and neural networks (multilayer perceptron). We assessed the predictive power of models in the framework of tenfold stratified crossvalidation and area under the ROC curve. We analyzed the effect of winsorization at 1, 3 and 5% and at 2 and 3 standard deviations, furthermore we discretized the range of each variable by the CHAID method and used the ordinal measures so obtained instead of the original financial ratios. We found that this latter data preprocessing approach is the most effective in the case of our dataset. In order to check the robustness of our results, we carried out the same empirical research on the publicly available Polish bankruptcy dataset from the UCI Machine Learning Repository. We obtained very similar results on both datasets, which indicates that the CHAID-based categorization of financial ratios is an effective way of handling outliers with respect to the predictive performance of bankruptcy prediction models.     

Optimal control and differential game models of military expenditure in less developed countries

This paper presents optimal control and differential game models of military expenditure in less developed countries. We emphasise the strategic interconnections between aggressive neighbours and explicitly stress the optimal resource allocation problem between civilian and military expenditure. A major innovation of the analysis is to analyse the asymmetric reaction functions of the two agents and the formalisation of the stylised fact that most LDC arms races have taken place between participants of ‘unequal’ size.     

Econometrically accounting for identities and restrictions in models of interregional migration

"Interregional demographic identities and other restrictions are explicitly taken into account in a simple time-series model of interregional migration. This goal is accomplished through the imposition of adding-up constraints on the estimated coefficients of a multi-equation linear system and by testing for homogeneity and symmetry. The pitfalls of utilizing the described procedures for migration analysis and forecasting are discussed. Full implementation of the technique is shown to require far more time-series observations on interregional migration than are commonly available."     

The effects of virtualness on teamwork behavioral components: The role of shared mental models

Virtual teams are an essential part of work organizations. They help organizations utilize skills and expertise regardless of where they are located. The virtual team literature suggests that these teams often experience process losses compared to their face-to-face counterparts. In this paper we propose that as virtualness increases, a team's shared mental models become more complex; this limits the effectiveness of particular teamwork behaviors: mutual performance monitoring, backup behavior and adaptation. We identify specific factors that are reflected in increased mental model complexity of virtual teams. Further we examine the moderating role that the accuracy and similarity of these shared mental models as well as the level of virtualness has on the relation between complexity and teamwork behaviors. Finally, we examine the effects of training inventions on mental model accuracy. To this end, we review the existing literature to develop a model and specific propositions.     

The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models

The finite sample behavior is analyzed of particular least squares (LS) and a range of (generalized) method of moments (MM) estimators in panel data models with individual effects and both a lagged dependent variable regressor and another explanatory variable. The latter may be affected by lagged feedbacks from the dependent variable too. Asymptotic expansions indicate how the order of magnitude of bias of MM estimators tends to increase with the number of moment conditions exploited. They also provide analytic evidence on how the bias of the various estimators depends on the feedbacks and on other model characteristics such as prominence of individual effects and correlation between observed and unobserved heterogeneity. Simulation results corroborate the theoretical findings and reveal that in small samples of models with dynamic feedbacks none of the techniques examined dominates regarding bias and mean squared error over all parametrizations examined.     

网络文化对当代大学生影响及对策研究

互联网的产生和发展,为高校思想政治教育创造了一个全新的网络环境,网络已成为当代大学生学习与生活的重要内容。文章着重分析了网络文化对大学生的影响,阐述了网络文化的负面作用对高校思想政治教育的严峻挑战,并对如何应对这些挑战提出了意见。     

Neighborhood effects,college education,and social mobility

This study models the impact of environmental factors on upward social mobility, where the educational environment is measured by the proportion of college-educated individuals, and social mobility is measured by a change in proportion of people in different income classes. The dynamics of the educational environment is modeled using a modified version of the invasion/extinction ecological model of Richard Levins. The educational environment influences the educational choices of poor people, becoming effective only after a threshold point is reached. The rate of growth in influence is modeled using a monotonically increasing saturation function, which includes a delay parameter referred to as handling time, that measures the speed of influence. Our simulations indicate that poor people choose to become educated at a rate that primarily depends on the density of the local environment.     

激光技术的军事应用与前景

自1960年第一台激光器发明以来,经过四十多年的发展,科学家在激光的研究上突破了许多技术难题并取得非凡的成就,激光技术广泛应用于人们生活的各个领域。文中主要探讨激光的军事应用以及前景展望。     

高校国库集中支付的实践与探讨

国库集中支付是目前国家财政管理制度改革的一项重要内容,随着国库集中支付制度在高校的实施,这项改革对高校的财务管理理念和职能产生了深远的影响。文章论述了这项制度在高校具体实施过程中起到的积极作用以及所引发的问题,并对高校推进国库集中支付制度改革进行探讨。     

The effects of various treatments of truncation remainders on tests of hypotheses in distributed lag models

In the maximum likelihood estimation of distributed lag models, it makes no difference asymptotically whether one drops or estimates the ‘truncation remainder’ terms. However, in small samples the decision to drop or estimate these terms does have an effect on tests of hypotheses.This paper reports the results of a Monte Carlo experiment performed to see which treatment of these terms leads to the most accurate tests of hypotheses. The results are mixed, but generally it seems better to estimate the truncation remainder than to drop it.     

Econometrically accounting for identities and restrictions in models of interregional migration: further thoughts

The authors reply to some comments concerning "specification, estimation, and hypothesis testing in models of interregional migration which are internally consistent." They also attempt to clarify some additional conceptual matters in these three areas.     

Econometrically accounting for identities and restrictions in models of interregional migration : A comment

This comment clarifies and expands on an earlier article in this Journal by Greenwood and Hunt which addresses problems of estimating interregional migration models when non-stochastic adding-up constraints are present. The comment focuses on issues of specification, estimation and hypothesis testing within a closed system of migration equations stressing solutions to the degrees of freedom problem and tests for homogeneity and symmetry.     

The demographics of migration

The author discusses policies of encouraging immigration as a means to counteract demographic aging in developed countries. Consideration is given to policy development and the effects of migration on age distribution.     

Individual effects and dynamics in count data models

In this paper we examine the panel data estimation of dynamic models for count data that include correlated fixed effects and predetermined variables. Use of a linear feedback model is proposed. A quasi-differenced GMM estimator is consistent for the parameters in the dynamic model, but when series are highly persistent, there is a problem of weak instrument bias. An estimator is proposed that utilises pre-sample information of the dependent count variable, which is shown in Monte Carlo simulations to possess desirable small sample properties. The models and estimators are applied to data on US patents and R&D expenditure.     

Fixed effects estimation of structural parameters and marginal effects in panel probit models

Fixed effects estimators of nonlinear panel models can be severely biased due to the incidental parameters problem. In this paper, I characterize the leading term of a large-T expansion of the bias of the MLE and estimators of average marginal effects in parametric fixed effects panel binary choice models. For probit index coefficients, the former term is proportional to the true value of the coefficients being estimated. This result allows me to derive a lower bound for the bias of the MLE. I then show that the resulting fixed effects estimates of ratios of coefficients and average marginal effects exhibit no bias in the absence of heterogeneity and negligible bias for a wide variety of distributions of regressors and individual effects in the presence of heterogeneity. I subsequently propose new bias-corrected estimators of index coefficients and marginal effects with improved finite sample properties for linear and nonlinear models with predetermined regressors.