A network-based analysis of the impact of structural damage on urban accessibility following a disaster: the case of the seismically damaged Port Au Prince and Carrefour urban road networks

The magnitude 7.0 earthquake that struck Haiti in January 2010 led to an unprecedented effort in collecting and providing geographical information in support of humanitarian aid. Although most of the compiled datasets and generated maps were able to provide specific and detailed information regarding the location of damaged buildings and road interruptions, none or little information was available to describe the accessibility—or otherwise—of the urban space. Here we try to offer an alternative method to define the urban accessibility landscape in the aftermath of earthquake damage, by combining simple graph theory concepts and GIS-based spatial analysis to assess how the urban space accessibility decreases when the road network is damaged.     

Global Entrepreneurship Monitor: Data Collection Design and Implementation 1998–2003

The Global Entrepreneurship Monitor research program was designed as a comprehensive assessment of the role of entrepreneurship in national economic growth. The conceptual model reflected in a wide range of factors associated with national variations in entrepreneurial activity and the major contextual features. Empirical tests of the many relationships in the model required four major data collection activities: adult population surveys, unstructured interviews with national experts, self-administered questionnaires completed by national experts, and assembly of relevant standardized measures from existing cross-national data sets. Adult population surveys were implemented to identify those entrepreneurially active, which required a set of precise criteria and careful processing to ensure harmonized counts and prevalence rates across 41 countries. Existing evidence on measures of reliability indicates that the measures met contemporary standards and the project was cost-effective.     

Job mobility and the gender wage gap in Italy

This paper investigates the contribution of gender differences in job mobility to the emergence of a gender wage gap in the Italian labour market. We show that over the first 10 years of labour market experience job mobility accounts for up to 30% of total log wage growth for men and only 8.3% for women, and that this difference is mainly due to differences in returns to mobility. The gender mobility gap is robust to the inclusion of individual, job and firm characteristics, to different ways of accounting for individual unobserved heterogeneity, and is mainly found for voluntary job moves. Looking at the characteristics of the jobs and the firms' workers move to, we find that moves to larger firms represent by far the main source of gender differences in returns to mobility. We offer two possible explanations for this finding; one which involves differences in bargaining behaviour and one which relates to the theory of compensating differentials.     

Ideas About Thinking: Excerpts from Edward de Bono's "Letter to Thinkers"

How often do we stop to think about how we think? For years, Edward de Bono has been getting us to think about thinking. It was Dr. de Bono, for example, who coined the term "'lateral thinking" where, he says, richness is what matters, compared to vertical thinking where Tightness matters. In his periodic Letters to Thinkers, he stimulates lateral thinking by the way he gets his readers to turn problems around and look at them from a fresh perspective. This article is made up of excerpts from his Letters to Thinkers, published by Cower Publishing Company Limited, with permission.     

Regional Inequalities in Consumption Patterns: A Multilevel Approach to the Case of Italy

The main aim of this paper is to evaluate the disparities in the Italian regions on the demand side. In more detail, an attempt will be made to find if the consumption behaviour of Italian households is different in the regions. With this in mind, Istat's 2000 Italian Family Budget data set was analysed. The data in question, which were collected through a two‐stage sample over Italy's 20 regions, contains information regarding the expenses of approximately 23,000 households. In this analysis, both households and regions are considered as units: households are nested in the regions so that the basic data structure is hierarchical. In order to take this hierarchical structure into account, a multilevel model was used, making it possible for parameters to vary randomly from region to region. The model in question also made it possible to consider heterogeneity across different groups (regions), such as stochastic variation. First, regional inequalities were tested using a simple model in which households constituted the first level of analysis and were grouped according to their region (the second level). As a second step, and in order to investigate the interaction between geographical context and income distribution, another model was used. This was cross‐classified by income and regions. The most relevant results showed that there is wide fragmentation of consumption behaviour and, at the same time, various differentiated types of behaviour in the regions under analysis. These territorial differentials become clear from income class and items of consumption.     

Work without Wages; the Motivation for Valunteer Firefighters

A bstract . This is a theoretical and empirical exploration into the motivation of volunteer firefighters. After a brief discussion of methodology, the activities in which these volunteers engage are described and a theoretical model of volunteer motivation is presented. The central hypothesis is that individuals engage in voluntary activities to struggle against the pervasive alienating nature of productive activity in capitalist economies in an effort to achieve a greater degree of self actualization. This theoretical model is illustrated using data from a survey administered to 354 volunteer firefighters in Ulster County, New York. Lastly, the relationships between volunteer firefighting, alienation , and self-actualization are empirically explored, focusing upon comparisons between individuals' firefighting and career endeavors.     

Short Time Series Analysis: C Statistic vs Edgington Model

Young's C statistic (1941) makes it possible to compare the randomization of a set of sequentially organized data and constitutes an alternative of appropriate analysis in short time series designs. On the other hand, models based on the randomization of stimuli are also very important within the behavioral content applied. For this reason, a comparison is established between the C statistic and the Edgington model. The data analyzed in the comparative study have been obtained from graphs in studies published in behavioral journals. According to the results obtained, it is concluded that the Edgington model in experimental designs AB involves many measurements while the C statistic requires fewer observations to reach the conventional significance level.     

Sales contests,promotion decisions and heterogeneous risk

This paper examines a general model of sales contests in which agents have heterogeneous attitudes toward risk. It shows that agents that are less risk averse have a higher probability of success. A corollary to this result shows that when absolute risk aversion is decreasing in wealth, wealthier agents have a higher probability of promotion. The same wealth effect makes it possible for more risk averse agents to take greater risks in a multi‐round promotion tournament. Next, a stability analysis shows that these equilibria are attractors under a best response dynamic. While it is well‐known that sales contests can be an effective incentive device for eliciting effort from employees, this research suggests the added benefit that when used as a basis for promotion decisions, sales contests act to filter the hardest working agents to the top of the corporate hierarchy. Copyright © 2008 John Wiley & Sons, Ltd.     

Autocorrelation and Bias in Short Time Series: An Alternative Estimator

The conventional first-order autocorrelationcoefficient r₁ generates an empiricalbias when it is applied to short time series.The properties of this estimator have beenexamined with a Monte Carlo simulation studyusing the MATLAB program (version5.2). This study also analyzes the functionof the empirical bias with the polynomicregression and derives a polynomic fittingmodel for different sample sizes. In thisway, a new estimator that has been correctedby the absolute value of the fitting model(r_1') is proposed. Having analyzed thestatistical properties of the estimator r_1',it is shown that the empirical bias generatedby r_1' is less in relationship to r₁ andr₁₊. The results of the study make itpossible to verify that the mean squared errorassociated to the estimator r₁ isless than that of r₁. Thus, the coefficient r_1'is recommended to estimate the lag-oneautocorrelation coefficient in samples under 50observations.