Classification of longitudinal career paths

The aim of the present article is to classify, in terms of contractual stability, the careers of the workers in a specified territorial context (Province of Milan-Italy), utilizing large administrative archives. The final goal is a synthetic clustering that identifies individuals in homogeneous groups regarding the longitudinal sequences of contractual typologies occurring in the evolution of vocational experiences during their career, identifying, on the one hand, the worker profiles that remain stable in each contractual typology and on the other hand, the profiles that improve or worsen contractual stability over time. Methodologically, our approach uses a combination of scaling methods to estimate stability scores of each contractual typology and Latent mixture models to cluster similar trajectories. Specifically, the scores of contractual stability were performed by Multidimensional Scaling with individual preferences, taking into account the ordinal nature of distances among contractual typologies and the heterogeneity factors of the subjects. Further, Latent Growth Mixture models, capitalizing the longitudinal property of data sequences, were proposed to identify distinctive, prototypical developmental trajectories of contractual stability within the analyzed population.     

层次分析法在经济强县特征分析中的应用

本文用层次分析方法对影响县域经济社会发展的8个重要指标做层次分析,确定所研究的全部县域经济社会发展综合实力排序位次,找出主要因素和各影响因素影响程度的大小,为决策部门提供经济发展切实有效的理论依据。并用贵州省每个年度全部县域经济社会发展实际例子说明回归模型及层次分析法对经济强县特征分析作用。     

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.     

Casinos,casino size,and crime: A panel data analysis of Michigan counties

Growth in legal gaming in the United States over the past quarter century or so is well-documented. One important factor fueling this growth was the passage of the Indian Gaming Regulatory Act of 1988, which permitted Native American tribes to establish, under agreements or “compacts” with the states in which they are located, casinos offering what is known as Class III gaming: slot machines, blackjack, roulette, and other games. Since the passage of the Act, there have been 21 Native American casinos established in Michigan. Also, three non-Native American casinos opened in Detroit in 1999 and 2000. This growth in the number of casinos has sparked a wide-ranging debate over the social and economic impacts of casino development.The purpose of this research is to focus on the crime issue in the broader casino debate. We investigate the impact of these Michigan casinos on the rates of burglary, robbery, larceny and motor vehicle theft (property crimes) in casino host counties as well as in nearby counties. We employ a panel data set with annual observations on all 83 Michigan counties for the period 1994–2010. The dataset includes crime rates taken from the FBI crime data series, variables for the presence of a casino in a county or in a nearby county, the scale of a casino's operations as measured by revenues, and a variety of control variables suggested by the broader literature investigating the factors that determine crime rates generally.Our results suggest that in most cases the property crime rates studied are not affected by the presence or size of a casino in a county or in a nearby county. The largest such impact, which is negative, is for motor vehicle theft. The size of a casino does have a small positive effect on the motor vehicle theft rate.     

Psychological profiles for predicting leader performance

This study deals with the search for psychological profile(s) that can differentiate levels of leader performance. Although many have rejected the traditional trait theory approach to leadership, others continue to search for meaningful relationships between leader characteristics and leader behavior/effectiveness. Recent promising research focuses on profiles as opposed to individual traits as indicators of leader effectiveness. It is clearly the interaction of certain individual characteristics and situational variables that ultimately predict leader behavior. This requires continued search for person variables that may be relevant to this equation. Work with the 16 Personality Factor scale suggests some promising results. Research in this article focuses on the generation of specification equations that differentiate between high and low performers. The assumption is that there exist unique combinations (profiles) of characteristics that can aid in the prediction of leader performance. This research is an attempt to explore such profiles. Results show that a multitrait profile with weighted scale scores can predict performance. Significant correlations were obtained between 16PF profile scores and overall performance.     

Assessing the influence of external factors on agricultural production in Brazil

This article uses 2017 Brazilian agricultural census data (aggregated at county level) to evaluate the impact of external factors on agricultural efficiency in Brazil. The external factors are defined as access to credit, participation in cooperatives, proportion of literacy, technical assistance, and environmental production practices. All variables are transformed as the log of the municipal (county) rank. The response variable is defined as the free disposal hull (FDH) conditional ratio and a one-inflated beta regression is estimated. The results show that in counties where the FDH ratio is equal to 1, cooperatives have the biggest impact on efficiency, and where the FDH ratio is not equal to 1, environmental practices, which are most often associated with technology, have the largest effect on efficiency. Finally, the regions that are expected to see the largest gains in efficiency with increases in external factors are the Northeastern and the Northern regions of Brazil.     

Measuring Urban Well-Being

A BSTRACT . Studies attempting to measure social well-being that focus attention at national levels fail to provide insights into the actual conditions that are present at subnational levels. With increased attention being focused on the conditions of urban areas, the need for subnational evaluation is becoming more apparent. The growing diversity of the population and the increase in female-headed households leave researchers without resources for evaluating the conditions of these groups in smaller regional settings, in part due to the scarcity of well-being measurements at these levels. This study hopes to fill in the gap for measuring well-being at subnational levels by estimating indexes at the county level. Exactly how the level of urbanization and social well-being are related is the subject of our inquiry. Our estimations will focus on urban counties, with particular emphasis on the 50 largest counties. We aim to evaluate the well-being of the general population in metropolitan areas, comparing it to those for female heads of households and people of color.     

Effects of social and cultural processes on health1

Future advances in the planning and evaluation of health service systems are highly dependent upon the development of a methodology that permits the empirical validation of hypotheses concerning the effects of social and cultural processes on health. In this paper such a methodology has been proposed. A structural model has been developed and analyzed, using the causal modeling technique of path analysis, in which social, economic, and demographic characteristics of New Mexico counties have been related to the infant mortality rate as an index of health. Path coefficients have been estimated from census data and vital statistics. Dynamic programming has been utilized to predict the combined direct and indirect effects on the health of New Mexico's population that would result from changes in the composition of the population.Analysis of the model suggests that these structural characteristics are causally interrelated, with economic factors a major determinant of infant mortality. While urbanization and migration also significantly affect infant mortality rates, education surprisingly is not important causally when compared to other variables, nor is proportion nonwhite when other social and economic factors are taken into account. In contrast, the proportion of Spanish-Americans residing in a county has a rather unexpected effect in that infant mortality rates decline as the proportion of this ethnic group rises. This finding suggests that it is important in health planning to consider cultural factors that may be unique to particular ethnic groups.In general the model building techniques and the algorithms presented here provide a valuable means of generating and testing hypotheses regarding the effects of social and cultural processes on health.     

Industry Mix, Wages, and the Divergence of County Income in Pennsylvania

Per capita incomes have diverged across Pennsylvania counties. County incomes may differ because of differences in industrial structures and because of differences in earnings within industries; a county may have a below-average income because its industry mix is comprised of low paying jobs or because county jobs pay low wages compared to the same jobs in other counties. A procedure developed by Hanna (1951) is utilized to separate income differences into these two components by constructing two counterfactual incomes for each county. The handful of high-income counties in Pennsylvania have favorable wages while the counties with incomes below the state average, although with employment mixes comparable to the overall state mix, tend to have workers who receive low wages relative to the state industry average. Wages are low in the relatively poor counties due to less investment in physical and human capital.     

Scoring functions for ordered classifications in statistical analysis

The problem of scoring ordered classifications prior to the further statistical analysis is discussed. A review of some methods of scoring is provided. This includes linear transformations of integer scores, where previous applications to two way classifications are introduced. Also reviewed are scores based on canonical correlations, maximum likelihood scores under assumed logistic distributions for variables, ridits, and conditional mean scoring functions. The latter are shown to satisfy a reasonable set of postulates, and demonstrates that some earlier attempts to do this were incomplete. Examples of the conditional mean scoring function under different distributional assumptions are given. Methods based on compounded functions of proportions for categorical data are applied to many of the scores reviewed and introduced. Appropriate algorithms for these methods are introduced and exemplified. Through the medium of a range of existing data sets the sensitivity of their results to differing scoring systems applied to two way classifications is examined. It is seen that apart from data arising from highly skewed distributions little is to be lost by using simple integer scores.     

Recovering the Metric Structure in Ordinal Data: Linear Versus Nonlinear Principal Components Analysis

Two techniques for data reduction as part of the SPSS package are compared in a Monte Carlo study: principal components analysis (PCA) and nonlinear principal components analysis (NPCA). The relative performance of these techniques in recovering the component scores underlying subjects' scores on observed ordinal variables is studied for two-dimensional spaces. The relative performance is examined as a function of (a) the sample size, (b) the number of categories in the variables, (c) the amount of measurement error, (d) the type of nonlinearity in the data, and (e) the degree of heterogeneity of the marginal distributions of the variables. As expected, when the sample size increases the performance of NPCA improves when compared to PCA. For the range of values considered, there is no effect of the number of categories on the relative performance of PCA and NPCA. For the other factors the effects are more complicated: adding error does not affect PCA as strongly as NPCA, as expected, but not for heterogeneously distributed variables for a particular form of nonlinearity, in which case NPCA becomes more appropriate. PCA appears to outperform NPCA for linear data, but also for a substantial number of nonlinear data sets.     

The Quality of Life in England and Wales*

Local amenities play an important role in determining where we choose to live and our overall quality of life (QOL). In many cases, however, amenities do not have prices and will therefore be underprovided by the market. In this paper, we use individual and county level data for England and Wales to estimate implicit amenity prices and to calculate an index of QOL for each county. Among our findings is a large negative price on air pollution. The range in QOL across counties is estimated to be in excess of 2,000 pounds per year.     

A PCA–DEA approach to measure the quality of life in Estonian counties

This paper investigates the application of a PCA–DEA model to assess the quality of life (QOL) scores in Estonian counties and analyses the model's results. The dataset is a balanced panel of 15 Estonian counties covering the period from 2000 to 2011. We consider a PCA–DEA model as an alternative method to estimate and predict QOL scores and rankings of Estonian counties. The method consists of a two-stage analysis that begins with a principal component analysis. In the second stage, the standard DEA is used. The results from the conventional DEA model and the PCA–DEA model are compared and discussed. A comparison of the methodologies demonstrates that a PCA–DEA model provides a powerful tool for performance ranking. The rankings of Estonian counties using QOL scores for different model specifications are presented. Finally, the QOL ranking of Estonian counties is revised using PCA–DEA.     

Centralized versus decentralized decision-making in a county government setting

During the November 1988 election cycle, the residents of Mississippi's 82 counties were allowed to choose whether or not to switch to an alternative system for governing the construction and repair of county roads. Under the system then used statewide – the so-called beat system – each of a county's five elected supervisors determined spending priorities and allocated funds within the boundaries of his or her own district. Under the alternative system – the so-called unit system – such choices were to be made by the supervisors collectively and then executed by a hired professional road manager. This paper models the decision of voters to retain the beat system (38 counties) or to switch to the unit system (44 counties). Theory and evidence suggest that the choice between centralized versus decentralized governance depends on the perceived costs and benefits of the alternatives to voters and their elected representatives. Received: February 24, 2000; Accepted: September 20, 2001     

Population growth in U.S. counties, 1840–1990

We examine the location and growth of the U.S. population using county-level census data from 1840 and 1990. Natural characteristics (e.g., access to water transportation) heavily influenced where populations located in 1840, and produced characteristics in existence in 1840 (e.g., educational infrastructure) had a significant influence on subsequent growth. Evidence of population convergence appears only when the most-heavily-populated counties in 1840 are excluded from the sample. Moreover, when counties located on the western frontier are excluded from the full sample, on the assumption that they were relatively far from their steady-state populations, there is evidence of population divergence.     

Organisational form and quality,service, and cleanliness inspection scores in restaurant franchise chains: Evidence from Spain

This study investigates how the organisational form (company ownership vs. franchising) of individual restaurants of a large Spanish restaurant company influences their inspection scores in terms of quality, service, and cleanliness (QSC). The research uses a panel data set that includes bimonthly restaurant-level data on QSC inspection scores. The aggregate data initially reveal substantial differences between company-owned and franchised restaurants. Nevertheless, after controlling for other variables, we observe that such differences are in fact minor, or even nonexistent. In addition, when we endogenise the selection of the restaurants' organisational form, the differences become statistically insignificant.     

Decomposing the Triple-Helix synergy into the regional innovation systems of Norway: firm data and patent networks

The Triple Helix model of university-industry-government relations allows us to use mutual information among geographical, sectorial, and size distribution of firms to measure synergy at various geographical scales in a nation. In this paper we decompose the synergy in Triple Helix relations and analyze the decomposition at the county level. We use micro-level data for all Norwegian firms from 2002 to 2014. This provides new and more detailed insight into the factors explaining the previously reported variation in synergy at county level in Norway. Furthermore, we analyze the county and city level distributions of all national as well as USPTO granted patents with at least one Norwegian inventor. Co-inventor networks for Norwegian USPTO patents are visualized using Google maps. The counties with technology-dominated synergies and strong knowledge institutions have a higher level of international co-inventor networks. Sectorial and geographical networks characterize the oil and gas dominated county, Rogaland. In contrast the knowledge institution dominated county of Sør-Trøndelag has broader networks both with regard to sectors and geography. In the small industry dominated county of Møre og Romsdal with high synergy, the lack of international co-inventor network is striking. This might be interpreted as a sign of industrial lock-in. The use of both firm level and patent data together give a broader and more precise picture of the innovation systems under study. The use of both national and international patent data also broadens the picture of the innovation activity of the nation.     

Urban ecology and residential location theories: Application in nigeria's socio-cultural milieu

Urban ecological studies are generally concerned with the spatial distribution of population characteristics, organisations, activities and behaviours across the urban terrain. These spatial distributions are taken to reflect the operation of socio-economic processes. Anglo-American urban ecological investigators had formulated much of the prevailing urban ecological theories of today. These theories were based on studies of their own socio-cultural and economic environments, which were by no means universal. This study, applies the principles of these well-known theories to a different socio-economic and cultural environment—Nigerian, with a view to testing their cross-cultural validity. This is done (i) by testing some empirical data on the city of Lagos, upon some specific propositions embodied in these theories; with a view towards their verification and validation; and (ii) by examining the over-all explanatory power of the theories in accounting for broad urban ecological patterns as revealed by data or information on the study city, and culture. The findings suggest that while similarities in urban ecological patterns in the two environments are discernible in some variables, they significantly differ in others, and even where the patterns appear to be similar, they are explainable by quite different factors. Urban ecological patterns could therefore be said to be culture-specific.     

Capturing judgments to clarify production strategy and policy

Recent years have brought a reawakening of the importance of shaping the operations function to support the broader strategy of each organization. Doing so, however, can be a complex, controversial, and highly subjective matter. Determining production's relationships to marketing, engineering, and finance requires executive-level judgments on the relative emphases among these policy areas. Other judgments about internal capabilities, external factors, and production policies are also involved. Assessing these relationships is a subjective process that is often subtle and usually hidden. For managers, these judgmental areas are sources of disagreement, confusion, and controversy in policy determination.Within this context, the authors applied a judgment-capturing process, called ProPol (Production Policy), to reveal and clarify managers' judgmental processes. The procedure uses correlational methods to identify where and how managers diverge from a common policy focus. The application settings were two executive development programs—one in manufacturing and the other in the public utility industry. Grouped into teams, the executives competed in week-long computer simulation games. ProPol was introduced to assist in clarifying their production policies and strategies.In the manufacturing setting, five general policy areas—marketing effort, cost efficiency of production, R&D effort, product pricing, and service flexibility—were identified as salient variables prior to the simulation. We sought to reveal managers' subjective views on the appropriate balance among these variables. The variables were scaled and embedded within questionnaires to present alternative strategy and policy postures within the context of the simulated organizations. From analyzing the resulting judgments, ProPol served the following purposes: (1) to reveal to each manager his own decision structure; (2) to permit intermanager comparisons of decision structures among team members; (3) to provide explicit bases for focused discussions on overall strategy agreement/disagreement within teams; and (4) to serve as the basis for determining a consensus strategy by each team. The managers' judgment processes were compared in terms of judgmental consistency, complexity, and espoused versus in-useimportances of the policy variables. Consistency, the amount of uniformity in the manager's decision structure, varied widely among team members and across teams. While some executives held firm, consistent views of policy-outcome relationships, others applied their structure inconsistently or shifted from one relationship structure to another in making their judgments. Judgmental complexity also varied widely within and across teams. The judgmental structures for most managers were simple linear relationships. Several, however, used more complex quadratic and interactive structures in relating the policy areas to overall effectiveness. Even when individuals were identically complex, however, they differed as to which policy variables were significant. Furthermore, although every manager espoused that all five variables were important, they were not all significantly used. The discovery of these discrepancies had a surprise affect: managers became aware of their personal inconsistencies and were stimulated toward understanding why they occurred. The group judgments, in contrast to the individuals, were more consistent and the espoused versus empirically-derived importances were more in agreement. This occurred from group interactions following individual feedback. The feedback clarified specific areas of policy agreement, provided a productive way for resolving basic policy differences, and facilitated the groups in clarifying their strategic directions.In the utility environment, executives participated in a decision-making simulation of a consumer-owned electric utility. As before, five key policy variables for this industry were chosen. Some of the five policy variables are indirectly related to operations (e.g., rate setting and employee relations), while others are more specifically related to operations (e.g., cost efficiency, dependability, and flexibility). Analyses of the judgments revealed characteristics similar to those in the manufacturing environment. Overall, however, utility executives displayed somewhat more complex judgment structures than did manufacturing executives. As a result, there seemed to be more common ground for intrateam policy agreement. For eight of the nine teams, the group consistency exceeded the average of their members' individual consistencies. Otherwise the various teams displayed diverse functional forms for their strategy and policy judgments, and they were relatively consistent in doing so.These results indicate that ProPol can help managers clarify specific directions for the production function. By doing so, a more focused production thrust, one that is clearly and explicitly articulated, will enhance any organization's competitive strategy and provide clear guidance for subsequent decisions.     

The socio-economic determinants of COVID-19: A spatial analysis of German county level data

The study explores the association of socioeconomic, demographic, and health-related variables at the regional level with COVID-19 related cases and deaths in Germany during the so-called first wave through mid-June 2020. Multivariate spatial models include the 401 counties in Germany to account for regional interrelations and possible spillover effects. The case and death numbers are, for example, significantly positively associated with early cases from the beginning of the epidemic, the average age, the population density and the share of people employed in elderly care. By contrast, they are significantly negatively associated with the share of schoolchildren and children in day care as well as physician density. In addition, significant spillover effects on the case numbers of neighbouring regions were identified for certain variables, with a different sign than the overall effects, giving rise to further future analyses of the regional mechanisms of action of COVID-19 infection. The results complement the knowledge about COVID-19 infection beyond the clinical risk factors discussed so far by a socio-economic perspective at the ecological level.