The German SAVE survey: documentation and methodology

The purpose of this document is to describe methodological details of the German SAVE survey and to provide users of SAVE with all necessary information for working with the publicly available SAVE dataset.

Explaining heterogeneity in utility functions by individual differences in decision modes

The curvature of utility functions varies between people. We suggest that there is a relationship between individual differences in preferred decision mode (intuition vs. deliberation) and the curvature of the individual utility function. If a person habitually prefers a deliberative mode, the utility function should be nearly linear, while it should be curved when a person prefers the intuitive mode. In this study the utility functions of the subjects were assessed using a lottery-based elicitation method and related to a measurement of the habitual mode preference for intuition and deliberation. Results confirm that people who prefer the deliberative mode have a utility function that is more linear than for people who prefer the intuitive mode. Our findings indicate a stronger affective bias of subjective values in intuitive than deliberate decision makers. While deliberative decision makers may have rather used the stated values, intuitive decision makers may have additionally integrated affective reactions towards the stimuli into the decision.

Search behaviour with reference point preferences:

People are heterogeneous with respect to their behaviour in sequential decision situations. This paper develops models for search behaviour under the assumption of expected-utility maximisation and a new search model that assumes sequential updating of utility reference points during the search process. I find experimental evidence that supports the new reference point model: Individual loss aversion is systematically related to the observed search behaviour in a way that is consistent with the predictions of the reference point model. Risk attitude is not related to search behaviour. The finding that many people set reference points in sequential decision tasks is of interest in, e.g. consumer economics, labour economics, finance, and decision theory.

Explaining heterogeneity in utility functions by individual differences in preferred decision modes

The curvature of utility functions varies between people. We suggest that there exists a relationship between the mode in which a person usually makes a decision and the curvature of the individual utility function. In a deliberate decision mode, a decision-maker tends to have a nearly linear utility function. In an intuitive decision mode, the utility function is more curved. In our experiment the utility function is assessed with a lottery-based utility elicitation method and related to a measure that assesses the habitual preference for intuition and deliberation (Betsch, submitted). Results confirm that for people that habitually use the deliberate decision mode, the utility function is more linear than for people that habitually use the intuitive decision mode. The finding and its implications for the research on individual decision behavior in economics and psychology are discussed.

Spatial Dynamic Modeling and Urban Land Use Transformation:

Assessing the economic impacts of urban land use transformation has become complex and acrimonious. Although community planners are beginning to comprehend the economic trade-offs inherent in transforming the urban fringe, they find it increasingly difficult to analyze and assess the trade-offs expediently and in ways that can influence local decisionmaking. New and sophisticated spatial modeling techniques are now being applied to urban systems that can quickly assess the probable spatial outcomes of given communal policies. Applying an economic impact assessment to the probable spatial patterns can provide to planners the tools needed to quickly assess scenarios for policy formation that will ultimately help inform decision makers. This paper focuses on the theoretical underpinnings and practical application of an economic impact analysis submodel developed within the Land use Evolution and Impact Assessment Modeling (LEAM) environment. The conceptual framework of LEAM is described, followed by an application of the model to the assessment of the cost of urban sprawl in Kane County, Illinois. The results show the effectiveness of spatially explicit modeling from a theoretical and a practical point of view. The agent-based approach of spatial dynamic modeling with a high spatial resolution allows for discerning the macro-level implications of micro-level behaviors. These phenomena are highlighted in the economic submodel in the discussion of the implications of land use change decisions on individual and communal costs; low-density development patterns favoring individual behaviors at the expense of the broader community.

Trust Games Measure Trust

The relationship between trust and risk is a topic of enduring interest. Although there are substantial differences between the ideas the terms express, many researchers from different disciplines have pointed out that these two concepts become very closely related in personal exchange contexts. This raises the important practical concern over whether behaviors in the widely-used “trust game†actually measure trust, or instead reveal more about risk attitudes. It is critical to confront this question rigorously, as data from these games are increasingly used to support conclusions from a wide variety of fields including macroeconomic development, social psychology and cultural anthropology. The aim of this paper is to provide cogent evidence on the relationship between trust and risk in “trust†games. Subjects in our experiment participate either in a trust game or in its risk game counterpart. In the trust version, subjects play a standard trust game and know their counterparts are human. In the risk version, subjects know their counterparts are computers making random decisions. We compare decisions between these treatments, and also correlate behavior with subjects’ risk attitudes as measured by the Holt and Laury (2002) risk instrument. We provide evidence that trusting behavior is different than behavior under risk. In particular, (i) decisions patterns in our trust and risk games are significantly different; and (ii) risk attitudes correlate with decisions in the risk game, but not the trust game.trust; risk attitudes; laboratory experiments

The German SAVE Survey: Documentation and Methodology

The purpose of this document is to describe methodological details of the German SAVE survey and to provide users of SAVE with all necessary information for working with the publicly available SAVE dataset.

Trust Games Measure Trust

The relationship between trust and risk is a topic of enduring interest. Although there are substantial differences between the ideas the terms express, many researchers from different disciplines have pointed out that these two concepts become very closely related in personal exchange contexts. This raises the important practical concern over whether behaviors in the widely-used “trust game” actually measure trust, or instead reveal more about risk attitudes. It is critical to confront this question rigorously, as data from these games are increasingly used to support conclusions from a wide variety of fields including macroeconomic development, social psychology and cultural anthropology. The aim of this paper is to provide cogent evidence on the relationship between trust and risk in “trust” games. Subjects in our experiment participate either in a trust game or in its risk game counterpart. In the trust version, subjects play a standard trust game and know their counterparts are human. In the risk version, subjects know their counterparts are computers making random decisions. We compare decisions between these treatments, and also correlate behavior with subjects’ risk attitudes as measured by the Holt and Laury (2002) risk instrument. We provide evidence that trusting behavior is different than behavior under risk. In particular, (i) decisions patterns in our trust and risk games are significantly different; and (ii) risk attitudes predict decisions in the risk game, but not the trust game.

Modeling the Use of Nonrenewable Resources Using a Genetic Algorithm

This paper shows, how a genetic algorithm (GA) can be used to model an economic process: the interaction of profit-maximizing oil-exploration firms that compete with each other for a limited amount of oil. After a brief introduction to the concept of multi-agent-modeling in economics, a GA-based resource-economic model is developed. Several model runs based on different economic policy assumptions are presented and discussed in order to show how the GA-model can be used to gain insight into the dynamic properties of economic systems. The remainder outlines deficiencies of GA-based multi-agent approaches and sketches how the present model can be improved.

Trust Games Measure Trust

The relationship between trust and risk is a topic of enduring interest. Although there are substantial differences between the ideas the terms express, many researchers from different disciplines have pointed out that these two concepts become very closely related in personal exchange contexts. This raises the important practical concern over whether behaviors in the widely-used “trust game” actually measure trust, or instead reveal more about risk attitudes. It is critical to confront this question rigorously, as data from these games are increasingly used to support conclusions from a wide variety of fields including macroeconomic development, social psychology and cultural anthropology. The aim of this paper is to provide cogent evidence on the relationship between trust and risk in “trust” games. Subjects in our experiment participate either in a trust game or in its risk game counterpart. In the trust version, subjects play a standard trust game and know their counterparts are human. In the risk version, subjects know their counterparts are computers making random decisions. We compare decisions between these treatments, and also correlate behavior with subjects’ risk attitudes as measured by the Holt and Laury (2002) risk instrument. We provide evidence that trusting behavior is different than behavior under risk. In particular, (i) decisions patterns in our trust and risk games are significantly different; and (ii) risk attitudes predict decisions in the risk game, but not the trust game.