Individual position diversity in dependence socioeconomic networks increases economic output

The availability of big data recorded from massively multiplayer online role-playing games (MMORPGs) allows us to gain a deeper understanding of the potential connection between individuals' network positions and their economic outputs. We use a statistical filtering method to construct dependence networks from weighted friendship networks of individuals. We investigate the 30 distinct motif positions in the 13 directed triadic motifs which represent microscopic dependences among individuals. Based on the structural similarity of motif positions, we further classify individuals into different groups. The node position diversity of individuals is found to be positively correlated with their economic outputs. We also find that the economic outputs of leaf nodes are significantly lower than that of the other nodes in the same motif. Our findings shed light on understanding the influence of network structure on economic activities and outputs in socioeconomic system.Comment: 19 pages, 5 figure

Neighbourhood social capital and individual mental health

Neighbourhood social capital is often claimed benecial for health, yet evidence of this contextual eect in the UK has been thin. To examine this eect, I draw upon Grossman health production model and Blume-Brock-Durlauf social interaction model underpinning the effects of neighbourhood social capital on individual health. This study uses two most recent independent surveys on neighbourhood social capital and on individual mental health in Wales. Both are linked based on neighbourhood. I nd that many forms of neighbourhood social capital, measured with widely used questions, improve resident's mental health (SF36). Public health practitioners have these measures as additional tools to draw upon in formulating public health policy.social capital; SF36; quality of life

Use of a Bayesian belief network to predict the impacts of commercializing non-timber forest products on livelihoods

Commercialization of non-timber forest products (NTFPs) has been widely promoted as a means of sustainably developing tropical forest resources, in a way that promotes forest conservation while supporting rural livelihoods. However, in practice, NTFP commercialization has often failed to deliver the expected benefits. Progress in analyzing the causes of such failure has been hindered by the lack of a suitable framework for the analysis of NTFP case studies, and by the lack of predictive theory. We address these needs by developing a probabilistic model based on a livelihood framework, enabling the impact of NTFP commercialization on livelihoods to be predicted. The framework considers five types of capital asset needed to support livelihoods: natural, human, social, physical, and financial. Commercialization of NTFPs is represented in the model as the conversion of one form of capital asset into another, which is influenced by a variety of socio-economic, environmental, and political factors. Impacts on livelihoods are determined by the availability of the five types of assets following commercialization. The model, implemented as a Bayesian Belief Network, was tested using data from participatory research into 19 NTFP case studies undertaken in Mexico and Bolivia. The model provides a novel tool for diagnosing the causes of success and failure in NTFP commercialization, and can be used to explore the potential impacts of policy options and other interventions on livelihoods. The potential value of this approach for the development of NTFP theory is discussed

The impact of location on housing prices: applying the Artificial Neural Network Model as an analytical tool.

The location of a residential property in a city directly affects its market price. Each location represents different values in variables such as accessibility, neighbourhood, traffic, socio-economic level and proximity to green areas, among others. In addition, that location has an influence on the choice and on the offer price of each residential property. The development of artificial intelligence, allows us to use alternative tools to the traditional methods of econometric modelling. This has led us to conduct a study of the residential property market in the city of Valencia (Spain). In this study, we will attempt to explain the aspects that determine the demand for housing and the behaviour of prices in the urban space. We used an artificial neutral network as a price forecasting tool, since this system shows a considerable improvement in the accuracy of ratings over traditional models. With the help of this system, we attempted to quantify the impact on residential property prices of issues such as accessibility, level of service standards of public utilities, quality of urban planning, environmental surroundings and other locational aspects.

How change agents and social capital influence the adoption of innovations among small farmers: Evidence from social networks in rural Bolivia

"This paper presents results from a study that identified patterns of social interaction among small farmers in three agricultural subsectors in Bolivia—fish culture, peanut production, and quinoa production—and analyzed how social interaction influences farmers' behavior toward the adoption of pro-poor innovations. Twelve microregions were identified, four in each subsector, setting the terrain for an analysis of parts of social networks that deal with the diffusion of specific sets of innovations. Three hundred sixty farmers involved in theses networks as well as 60 change agents and other actors promoting directly or indirectly the diffusion of innovations were interviewed about the interactions they maintain with other agents in the network and the sociodemographic characteristics that influence their adoption behavior. The information derived from this data collection was used to test a wide range of hypotheses on the impact that the embeddedness of farmers in social networks has on the intensity with which they adopt innovations. Evidence provided by the study suggests that persuasion, social influence, and competition are significant influences in the decisions of farmers in poor rural regions in Bolivia to adopt innovations. The results of this study are meant to attract the attention of policymakers and practitioners who are interested in the design and implementation of projects and programs fostering agricultural innovation and who may want to take into account the effects of social interaction and social capital. Meanwhile, scholars of the diffusion of innovations may find evidence to further embrace the complexity and interdependence of social interactions in their models and approaches." from Author's AbstractSocial networks, Agricultural innovation, Change agent, Social capital,

Adverse Geography and Differences in Welfare in Peru

regional economics, spatial distribution, welfare, poverty, Peru

SELECTED PAPER ABSTRACTS, WAEA ANNUAL MEETINGS, LONG BEACH, CALIFORNIA, JULY 28-31, 2002

Teaching/Communication/Extension/Profession,