The Rise and Fall of Catastrophe Theory Applications in Economics: Was the Baby Thrown out with the Bathwater?

Rosser, Barkley

doi:10.1037/e404992008-001

Cited by 30 publications

(32 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In economics, principles of self-organization have been applied as an explanation for the complexity of macro-and microeconomics (Arthur, 1999;Rosser, 1999Rosser, , 2007. In psychology and neuroscience, recent research has included studies of leadership behavior (Guastello & Bond, 2007), self-esteem (Delignières, Fortes, & Ninot, 2004), self-control (Warren, Sprott, & Hawkins, 2002), emotion (Lewis, 2000(Lewis, , 2005, empathy (Guastello, Pincus, & Gunderson, 2006), motor development and coordination (Athènes, Sallagoïty, Zanone, & Albaret, 2004;Bardy, Oullier, Bootsma, & Stoffregen, 2002;Clearfield, Diedrich, Smith, & Thelen, 2006;Kelso & Zanone, 2002;Lagarde & Kelso, 2006), cognitive development (Thelen et al, 2001), social development (Granic & Patterson, 2006), judgment (van Rooij & Bongers, 2000), learning (Churchill, 2008;de Bot, Lowie, & Verspoor, 2007;Kostrubiec, Tallet, & Zanone, 2006), language and speech (Almonte, Jirsa, Large, & Tuller, 2005;McDougall, 2006), dynamic adaptation in complex tasks (Kozma, Harter, & Achunala, 2007), perception (Giraudo & Pailhous, 1999;Rodriguez et al, 1999), and neural coordination (Freeman, 2003;Kerick, Hatfield, & Allender, 2007;Varela, Lachaux, Rodriguez, & Martinerie, 2001).…”

Section: An Example: Intertemporal Choicementioning

confidence: 99%

Making decisions with a continuous mind

Scherbaum

Dshemuchadse

Kalis

2008

Cognitive, Affective, & Behavioral Neuroscience

View full text Add to dashboard Cite

Section: An Example: Intertemporal Choicementioning

confidence: 99%

Making decisions with a continuous mind

Scherbaum

Dshemuchadse

Kalis

2008

Cognitive, Affective, & Behavioral Neuroscience

View full text Add to dashboard Cite

“…Although catastrophe theory is well established and applied in the physical sciences, its applications in the biological sciences, and especially in the social and behavioral sciences, has been criticized (Sussmann and Zahler 1978;Rosser 2007). Applications in the latter fields range from modeling of exchange market crashes in economics (Zeeman 1974), to…”

Section: Introductionmentioning

confidence: 99%

“…The first of these seems to stem from the fact that catastrophe theory concerned deterministic dynamical systems, whereas applications in these sciences concern data that are more appropriately considered stochastic. For an historical summary of the developments and critiques of catastrophe theory we refer the reader to Rosser (2007).…”

mentioning

confidence: 99%

Fitting the Cusp Catastrophe inR: AcuspPackage Primer

Grasman¹,

Maas²,

Wagenmakers³

2009

J. Stat. Soft.

112

169

View full text Add to dashboard Cite

Of the seven elementary catastrophes in catastrophe theory, the "cusp" model is the most widely applied. Most applications are however qualitative. Quantitative techniques for catastrophe modeling have been developed, but so far the limited availability of flexible software has hindered quantitative assessment. We present a package that implements and extends the method of Cobb (Cobb and Watson 1980;Cobb, Koppstein, and Chen 1983), and makes it easy to quantitatively fit and compare different cusp catastrophe models in a statistically principled way. After a short introduction to the cusp catastrophe, we demonstrate the package with two instructive examples.Keywords: catastrophe theory, cusp, modeling.Catastrophe theory studies qualitative changes in behavior of systems under smooth gradual changes of control factors that determine their behavioral state. In doing so, catastrophe theory has been able to explain for example, how sudden abrupt changes in behavior can result from minute changes in the controlling factors, and why such changes occur at different control factor configurations depending on the past states of the system. Specifically, catastrophe theory predicts all the types of qualitative behavioral changes that can occur in the class of so called gradient systems, under influence of gradual changes in controlling factors (Poston and Stewart 1996).Catastrophe theory was popularized in the 1970's (Thom 1973;Thom and Fowler 1975;Gilmore 1993), and was suggested as a strategy for modeling in various disciplines, like physics, biology, psychology, and economics, by Zeeman (1971)-as cited in Stewart and Peregoy (1983), Zeeman (1973), Zeeman (1974), Isnard and Zeeman (1976), and Poston and Stewart (1996. Although catastrophe theory is well established and applied in the physical sciences, its applications in the biological sciences, and especially in the social and behavioral sciences, has been criticized (Sussmann and Zahler 1978;Rosser 2007). Applications in the latter fields range from modeling of exchange market crashes in economics (Zeeman 1974), to

show abstract

“…The significance of this lies in the role of the Ising model (and it's approximations) as a representation of social interactions between homogeneous agents [6]. Also see Rosser [40] for an interpretation of this model in terms of economics. The QRE might then be interpreted as a generalisation of equation 29 as the mean field model of interacting agents in which one part of the population is different from another, further generalisations to many different types of agents in a population interacting in different ways strongly suggest themselves.…”

Section: The Qre and The Non-linear Effects Of Group Interactionsmentioning

confidence: 99%

Strategic Islands in Economic Games: Isolating Economies From Better Outcomes

Harré

Bossomaier

2014

Entropy

View full text Add to dashboard Cite

Many of the issues we face as a society are made more problematic by the rapidly changing context in which important decisions are made. For example buying a petrol powered car is most advantageous when there are many petrol pumps providing cheap petrol whereas buying an electric car is most advantageous when there are many electrical recharge points or high capacity batteries available. Such collective decision-making is often studied using economic game theory where the focus is on how individuals might reach an agreement regarding the supply and demand for the different energy types. But even if the two parties find a mutually agreeable strategy, as technology and costs change over time, for example through cheaper and more efficient batteries and a more accurate pricing of the total cost of oil consumption, so too do the incentives for the choices buyers and sellers make, the result of which can be the stranding of an industry or even a whole economy on an island of inefficient outcomes. In this article we consider the issue of how changes in the underlying incentives can move us from an optimal economy to a sub-optimal economy while at the same time making it impossible to collectively navigate our way to a better strategy without forcing us to pass through a socially undesirable "tipping point". We show that different perturbations to underlying incentives results in the creation or destruction of "strategic islands" isolated by disruptive transitions between strategies. The significant result in this work is the illustration that an economy that remains strategically stationary can over time become stranded in a suboptimal outcome from which there is no easy way to put the economy on a path to better outcomes without going through an economic tipping point.

show abstract

The Rise and Fall of Catastrophe Theory Applications in Economics: Was the Baby Thrown out with the Bathwater?

Cited by 30 publications

References 0 publications

Making decisions with a continuous mind

Making decisions with a continuous mind

Fitting the Cusp Catastrophe inR: AcuspPackage Primer

Strategic Islands in Economic Games: Isolating Economies From Better Outcomes

Contact Info

Product

Resources

About