13,171 research outputs found
The role of social interaction in farmers' climate adaptation choice
Adaptation to climate change might not always occur, with potentially\ud
catastrophic results. Success depends on coordinated actions at both\ud
governmental and individual levels (public and private adaptation). Even for a “wet” country like the Netherlands, climate change projections show that the frequency and severity of droughts are likely to increase. Freshwater is an important factor for agricultural production. A deficit causes damage to crop production and consequently to a loss of income. Adaptation is the key to decrease farmers’ vulnerability at the micro level and the sector’s vulnerability at the macro level. Individual adaptation decision-making is determined by the behavior of economic agents and social interaction among them. This can be best studied with agentbased modelling. Given the uncertainty about future weather conditions and the costs and effectiveness of adaptation strategies, a farmer in the model uses a cognitive process (or heuristic) to make adaptation decisions. In this process, he can rely on his experiences and on information from interactions within his social network. Interaction leads to the spread of information and knowledge that causes learning. Learning changes the conditions for individual adaptation decisionmaking. All these interactions cause emergent phenomena: the diffusion of adaptation strategies and a change of drought vulnerability of the agricultural sector. In this paper, we present a conceptual model and the first implementation of an agent-based model. The aim is to study the role of interaction in a farmer’s social network on adaptation decisions and on the diffusion of adaptation strategies\ud
and vulnerability of the agricultural sector. Micro-level survey data will be used to parameterize agents’ behavioral and interaction rules at a later stage. This knowledge is necessary for the successful design of public adaptation strategies, since governmental adaptation actions need to be fine-tuned to private adaptation behavior
A Description of Experimental Tax Evasion Behavior Using Finite Automata: the case of Chile and Italy
In this paper we use a Moore Automata with Binary Stochastic Output Function for exploring the extensive decision on tax evasion made by subjects in experiments run in Chile and Italy. We show first how an hypothesis about subject behavior is converted into an automaton and how do we compute the probabilities of evading for every states of an automaton. We use this procedure for searching the automaton which is able to anticipate the highest number of decisions made by the subjects during the experiments. Finally we show that automata with few states perform better than automaton with many states, and that the bomb crater effect described in [1] is a well identified pattern of behavior in a subset of subjects.
Agent-Based Models and Human Subject Experiments
This paper considers the relationship between agent-based modeling and economic decision-making experiments with human subjects. Both approaches exploit controlled ``laboratory'' conditions as a means of isolating the sources of aggregate phenomena. Research findings from laboratory studies of human subject behavior have inspired studies using artificial agents in ``computational laboratories'' and vice versa. In certain cases, both methods have been used to examine the same phenomenon. The focus of this paper is on the empirical validity of agent-based modeling approaches in terms of explaining data from human subject experiments. We also point out synergies between the two methodologies that have been exploited as well as promising new possibilities.agent-based models, human subject experiments, zero- intelligence agents, learning, evolutionary algorithms
An Agent-Based Model of Multifunctional Agricultural Landscape Using Genetic Algorithms
Landowner characteristics influence his/her willingness to change landuse practices to provide more or less environmental benefits. However, most studies of agricultural/environmental polices identify landowners as homogenous. And, the primary cause of failure of many environmental and other polices is the lack of knowledge on how humans may respond to polices based on changes in their behavior (Stern, 1993). From socioeconomic theory and empirical research, landowners can be identified as individuals who make agricultural landuse decisions independently based on their objectives. Identifying possible classes of landowners, assessing how each would potentially respond to policy alternatives, and the resulting pattern of land uses in a watershed or a riparian corridor would be very useful to policy makers as they evaluated alternatives. Agricultural landscapes are important producers of ecosystem services. The mix of ecosystem services and commodity outputs of an agricultural landscape depends on the spatial pattern of land uses emerging from individual land use decisions. However, many empirical studies show that the production of ecosystem services from agricultural landscapes is declining. This is consistent with research conducted over the last few decades showing there is a narrow range of social circumstances under which landowners are willing to make investments in the present to achieve public benefits in the future through investing in natural capital resulting in public goods which are frequently produced as ecosystem services. In this study an agent-based model within a watershed planning context is used to analyze the tradeoffs involved in producing a number of ecosystem services and agricultural commodities given price and policy scenarios while assuming three different types of agents in terms of their goals. The agents represent landowners who have been divided into a number of different groups based on their goals and the size of their farm operations. The multi-agent-based model is developed using a heuristic search and optimization technique called genetic algorithm (GA) (Holland), which belongs to a broader class of evolutionary algorithms. GAs exhibit three properties (1) they start with a population of solution, (2) they explore the solution space through recombination and mutation and (3) they evaluate individual solutions based on their appropriate fitness value(s), for example given profit maximizing agents this would be gross margin. A GA is a heuristic stochastic search and optimization method, which works by mimicking the evolutionary principles and chromosomal processing in natural genetics. The three economic agents that are modeled are based on variations in their objective functions and constraints. This study will help in identifying the tradeoffs associated with various agents in the provision of ecosystem services and agricultural commodities. The agent model developed here will help policy and decision maker identify the various agents within the watershed and assess various policy options based on that information. The study will also help to understand the interaction and feedback between the agents and their environment associated with various policy initiatives. The results of the study indicate that the agent model correctly predicts the actual landuse landcover map by 75 percent.Multifunctional agriculture, Agent based modeling, Genetic Algorithm, Environmental Economics and Policy, Land Economics/Use,
Beyond fatalism: An empirical exploration of self-efficacy and aspirations failure in Ethiopia
Fatalism is considered pervasive, especially in many poor communities. In this paper, we explore whether fatalistic beliefs have implications for the attitudes and behavior of poor rural households toward investment in the future. To explore the idea of fatalism, we draw inspiration from theories in psychology focusing on the role of locus of control and self-efficacy and also from the theoretical framework of aspiration failure as developed in recent economic literature. Using survey data from rural Ethiopia, we find evidence of fatalistic beliefs among a substantial group of rural households, as well as indicators consistent with narrow aspirations gap and low self-efficacy. We also find that such beliefs consistently correlate with lower demand for credit, in terms of loan size, repayment horizon, and productive purposes.aspirations, aspirations failure, aspirations gap, aspirations window, fatalism, self-efficacy,
Satisfaction and adaptation in voting behavior: an empirical exploration
Dynamic models of learning and adaptation have provided realistic predictions in terms of voting behavior. This study aims at contributing to their scant empirical verification. We develop a learning algorithm based on bounded rationality estimating the pattern of learning process through a two-stage econometric model. The analysis links voting behavior to past choices and economic satisfaction derived from previous period election and state of the economy. This represents a novelty in the literature on voting that assumes given voter preferences. Results show that persistence is positively affected by the combination of income changes and past behavior and by union membership.voting; bounded rationality; learning; political accountability
Satisfaction and adaptation in voting behavior: an empirical exploration
Dynamic models of learning and adaptation have provided realistic predictions in terms of voting behavior. This study aims at contributing to their scant empirical verification. We develop a learning algorithm based on bounded rationality estimating the pattern of learning process through a two-stage econometric model. The analysis links voting behavior to past choices and economic satisfaction derived from previous period election and state of the economy. This represents a novelty in the literature on voting that assumes given voter preferences. Results show that persistence is positively affected by the combination of income changes and past behavior and by union membership.voting; bounded rationality; learning; political accountability
Adaptive voting: an empirical analysis of participation and choice
Dynamic models of learning and adaptation have provided realistic predictions in terms of voting behavior. This study aims at contributing to their empirical verification by investigating voting behavior in terms of participation as well as choice. We test through panel data methods an outcome-based learning mechanism based on the following assumptions: (a) people expect that the party they do not support will be unable to bring economic improvements; (b) they receive a feedback whose impact depends on the consistency between their last voting behavior and personal economic improvements (or worsening) from the last election; (c) they tend to discard choices associated to an inconsistent feedback. Results show that feedbacks of this sort affect persistence of voting behavior, interpreted as participation and voting choice. Age and trade union affiliation reinforce this adaptive behavior. The analysis also investigates the intensity of the learning feedback, differentiating between a strong inconsistent feedback, which leads to a vote switch in favor of the opponent party, and a weak inconsistent feedback, which induces just abstention rather than a vote switch.voting, bounded rationality, learning, political accountability
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