Shade T. Shutters

Urban economies and occupation space: can they get "there" from "here"?

Much of the socioeconomic life in the United States occurs in its urban areas. While an urban economy is defined to a large extent by its network of occupational specializations, an examination of this important network is absent from the considerable body of work on the determinants of urban economic performance. Here we develop a structure-based analysis addressing how the network of interdependencies among occupational specializations affects the ease with which urban economies can transform themselves. While most occupational specializations exhibit positive relationships between one another, many exhibit negative ones, and the balance between the two partially explains the productivity of an urban economy. The current set of occupational specializations of an urban economy and its location in the occupation space constrain its future development paths. Important tradeoffs exist between different alternatives for altering an occupational specialization pattern, both at a single occupation and an entire occupational portfolio levels.

Agricultural Trade Networks and Patterns of Economic Development

International trade networks are manifestations of a complex combination of diverse underlying factors, both natural and social. Here we apply social network analytics to the international trade network of agricultural products to better understand the nature of this network and its relation to patterns of international development. Using a network tool known as triadic analysis we develop triad significance profiles for a series of agricultural commodities traded among countries. Results reveal a novel network “superfamily” combining properties of biological information processing networks and human social networks. To better understand this unique network signature, we examine in more detail the degree and triadic distributions within the trade network by country and commodity. Our results show that countries fall into two very distinct classes based on their triadic frequencies. Roughly 165 countries fall into one class while 18, all highly isolated with respect to international agricultural trade, fall into the other. Only Vietnam stands out as a unique case. Finally, we show that as a country becomes less isolated with respect to number of trading partners, the countrys triadic signature follows a predictable trajectory that may correspond to a trajectory of development.

Punishment leads to cooperative behavior in structured societies

Altruistic punishment occurs when an agent incurs a cost to punish another but receives no material benefit for doing so. Despite the seeming irrationality of such behavior, humans in laboratory settings routinely pay to punish others even in anonymous, one-shot settings. Costly punishment is ubiquitous among social organisms in general and is increasingly accepted as a mechanism for the evolution of cooperation. Yet if it is true that punishment explains cooperation, the evolution of altruistic punishment remains a mystery. In a series of computer simulations I give agents the ability to punish one another while playing a continuous prisoners dilemma. In simulations without social structure, expected behavior evolves—agents do not punish and consequently no cooperation evolves. Likewise, in simulations with social structure but no ability to punish, no cooperation evolves. However, in simulations where agents are both embedded in a social structure and have the option to inflict costly punishment, cooperation evolves quite readily. This suggests a simple and broadly applicable explanation of cooperation for social organisms that have nonrandom social structure and a predisposition to punish one another. Results with scale-free networks further suggest that nodal degree distribution plays an important role in determining whether cooperation will evolve in a structured population.

Living in a Network of Scaling Cities and Finite Resources

Many urban phenomena exhibit remarkable regularity in the form of nonlinear scaling behaviors, but their implications on a system of networked cities has never been investigated. Such knowledge is crucial for our ability to harness the complexity of urban processes to further sustainability science. In this paper, we develop a dynamical modeling framework that embeds population–resource dynamics—a generalized Lotka–Volterra system with modifications to incorporate the urban scaling behaviors—in complex networks in which cities may be linked to the resources of other cities and people may migrate in pursuit of higher welfare. We find that isolated cities (i.e., no migration) are susceptible to collapse if they do not have access to adequate resources. Links to other cities may help cities that would otherwise collapse due to insufficient resources. The effects of inter-city links, however, can vary due to the interplay between the nonlinear scaling behaviors and network structure. The long-term population level of a city is, in many settings, largely a function of the city’s access to resources over which the city has little or no competition. Nonetheless, careful investigation of dynamics is required to gain mechanistic understanding of a particular city–resource network because cities and resources may collapse and the scaling behaviors may influence the effects of inter-city links, thereby distorting what topological metrics really measure.

Constrained pathways to a creative urban economy

Creative (knowledge-intensive) occupations are now widely seen as a basis for urban economic prosperity. Yet the transitional pathways from a city’s current economy to a more creative economy are often difficult to discern or to navigate. Here we use a network perspective of occupational interdependencies to address questions of urban transitions to a creative economy. This perspective allows us to assess alternative pathways and to compare cities with regard to their progress along these pathways. We find that US urban areas follow a general trajectory towards a creative economy that requires them to increasingly specialise, not only in creative occupations, but also in non-creative ones – presumably because certain non-creative occupations complement the tasks performed by related creative occupations. This creates a pull towards non-creative occupations that becomes ever stronger as a city moves more towards a creative economy. All in all, cities with the most creative economies must undergo an overall diversification of specialised occupations, with a greater diversification rate for creative occupations, and maintain those creative specialisations despite the pull towards a non-creative economy.

Towards a rigorous framework for studying 2-player continuous games

The use of 2-player strategic games is one of the most common frameworks for studying the evolution of economic and social behavior. Games are typically played between two players, each given two choices that lie at the extremes of possible behavior (e.g. completely cooperate or completely defect). Recently there has been much interest in studying the outcome of games in which players may choose a strategy from the continuous interval between extremes, requiring the set of two possible choices be replaced by a single continuous equation. This has led to confusion and even errors in the classification of the game being played. The issue is described here specifically in relation to the continuous prisoners dilemma and the continuous snowdrift game. A case study is then presented demonstrating the misclassification that can result from the extension of discrete games into continuous space. The paper ends with a call for a more rigorous and clear framework for working with continuous games.

How hard is it for urban economies to become ‘green’?:

Home to over half the worlds population, cities are the drivers of the global economy and the primary influencers of the Earths sustainability. Thus, the burden of sustainable economic development falls ever more on cities, with many global organizations and governments calling for the promotion of ‘green’ economies. Yet how does a city move from its current economic structure to a green economy? Using detailed occupational data for US cities, we develop a green jobs index based on the network of interdependencies between occupational specializations. Using this index we quantify how close a citys current economy is to the green economy. We further show that movement or transition through this ‘occupation space’ toward a green economy is a slow and difficult process, with the average annual movement towards a green economy across all US cities being close to zero. Such difficulty is uncorrelated with a citys current population size, density, per capita GDP, per capita income, or even the citys current green jobs index. Furthermore, the structure of occupational interdependencies gives rise to suboptimal movements towards the green economy.

Public Representation in Water Management—A Network Analysis of Organization and Public Perceptions in Phoenix, Arizona

To better accomplish their mission of an informed public, environmental education organizations often exchange ideas, share financing, and distribute overhead through collaboration. Yet it remains to be seen whether benefits of these collaborations extend to the public. We examine two possible benefits: the ability of the organizations to act as representatives of the public interest, and equitable access to environmental educational materials. We model patterns of public access to water-related education across organizations using two surveys in metropolitan Phoenix, AZ. This enables the study of interorganizational social networks and public outcomes. Results support the idea that environmental education organizations could provide a credible proxy for direct citizen participation. However, not all organizations are equivalently engaged with historically underrepresented groups like women, minority racial and ethnic groups, and those who rent their home. The implications for more inclusive environmental policy decisions are discussed.

Cultural Polarization and the Role of Extremist Agents: A Simple Simulation Model

Cultural dynamics can be heavily influenced by extremists. To better understand this influence, temporal dynamics of an arbitrary cultural belief are simulated in a simple computational model. Extremist agents, holding an immutable and extreme belief, are used to examine the process of polarization --- adoption of the extremist belief by the entire population. Two possible methods of counteracting polarization are examined, removal of the extremist agent and introducing a counter-extremist which holds an immutable belief at the opposite extreme. Eliminating the extremist agent is only effective at the onset of cultural transition, while introducing a counter-extremist is effective at any time and will lead to a dynamic intermediate belief. Finally, a parameter governing the societys willingness to adopt new beliefs is varied. As it decreases, extremist agents are unable polarize a society. Instead the population breaks permanently into two or more belief groups. The study closes with a possible pathway for extremists to nevertheless polarize a society not open to new beliefs.

Cooperation through the Endogenous Evolution of Social Structure

A number of recent models demonstrate sustained and high levels of cooperation within evolutionary systems supported by the endogenous evolution of social structure. These dynamic social structures co-evolve, under certain conditions, to support a form of group selection in which highly cooperative groups replace less cooperative groups. A necessary condition is that agents are free to move between groups and can create new groups more quickly than existing groups become invaded by defecting agents who do not cooperate.