Ethnic Networks and Employment Outcomes

We analyse the effect of strong and weak ties on the individual probability of finding a job. Using the dynamic model of Calvó-Armengol and Jackson (2004), two results are put forward: (i) the individual probability of finding a job is increasing in the number of strong and weak ties; (ii) the longer the length of ties, the lower is this effect. We approximate the social space by the geographical space. Ethnicity is the chosen dimension along which agents’ social contacts develop and, as a result, we use ethnic population density to capture social interactions within the given ethnic group. Using a panel of local authority-level data in England between 1993 and 2003, we find that (i) the higher the percentage of a given ethnic group living nearby, the higher the employment rate of this ethnic group; (ii) this effect decays very rapidly with distance, losing significance beyond approximately 90 minutes travel time.ethnic minorities, social interactions, population density, weak and strong ties

Ethnic Networks and Employment Outcomes

This paper explores the relationship between residential proximity of individuals from the same ethnic group and the probability of finding a job through social networks, relative to other search methods. Using individual-level data from the UK Labour Force survey and spatial statistics techniques, we find that (i) the higher is the percentage of a given ethnic group living nearby, the higher is the probability of finding a job through social contacts; (ii) this effect decays very rapidly with distance. The magnitude, statistical significance and spatial decay of such an effect differ depending on the ethnic group considered. We provide an interpretation of our findings using the network model of Calvó-Armengol and Jackson (2004).Ethnic minorities, population density, social interactions, weak and strong ties,spatial statistics.

Consistency in Models for Distributed Learning under Communication Constraints

Motivated by sensor networks and other distributed settings, several models for distributed learning are presented. The models differ from classical works in statistical pattern recognition by allocating observations of an independent and identically distributed (i.i.d.) sampling process amongst members of a network of simple learning agents. The agents are limited in their ability to communicate to a central fusion center and thus, the amount of information available for use in classification or regression is constrained. For several basic communication models in both the binary classification and regression frameworks, we question the existence of agent decision rules and fusion rules that result in a universally consistent ensemble. The answers to this question present new issues to consider with regard to universal consistency. Insofar as these models present a useful picture of distributed scenarios, this paper addresses the issue of whether or not the guarantees provided by Stone's Theorem in centralized environments hold in distributed settings.Comment: To appear in the IEEE Transactions on Information Theor

Exploring the trend of New Zealand housing prices to support sustainable development

The New Zealand housing sector is experiencing rapid growth that has a significant impact on society, the economy, and the environment. In line with the growth, the housing market for both residential and business purposes has been booming, as have house prices. To sustain the housing development, it is critical to accurately monitor and predict housing prices so as to support the decision-making process in the housing sector. This study is devoted to applying a mathematical method to predict housing prices. The forecasting performance of two types of models: autoregressive integrated moving average (ARIMA) and multiple linear regression (MLR) analysis are compared. The ARIMA and regression models are developed based on a training-validation sample method. The results show that the ARIMA model generally performs better than the regression model. However, the regression model explores, to some extent, the significant correlations between house prices in New Zealand and the macro-economic conditions

Performance Measures to Assess Resiliency and Efficiency of Transit Systems

Transit agencies are interested in assessing the short-, mid-, and long-term performance of infrastructure with the objective of enhancing resiliency and efficiency. This report addresses three distinct aspects of New Jersey’s Transit System: 1) resiliency of bridge infrastructure, 2) resiliency of public transit systems, and 3) efficiency of transit systems with an emphasis on paratransit service. This project proposed a conceptual framework to assess the performance and resiliency for bridge structures in a transit network before and after disasters utilizing structural health monitoring (SHM), finite element (FE) modeling and remote sensing using Interferometric Synthetic Aperture Radar (InSAR). The public transit systems in NY/NJ were analyzed based on their vulnerability, resiliency, and efficiency in recovery following a major natural disaster

Monopoly quality degradation and regulation in cable television

Using an empirical framework based on the Mussa-Rosen model of monopoly quality choice, we calculate the degree of quality degradation in cable television markets and the impact of regulation on those choices. We find lower bounds of quality degradation ranging from 11 to 45 percent of offered service qualities. Furthermore, cable operators in markets with local regulatory oversight offer significantly higher quality, less degradation, and greater quality per dollar, despite higher prices