Abstract: Andrews (1985) investigates the theoretical coherence and policy relevance of our (1982) model and concludes, contrary to our own findings, that a positive rate of profit is not necessary to obtain a two-signed derivative of the profit rate with respect to agriculture's terms of trade. She characterizes the model as ‘Neo-Ricardian’ on the grounds that the technology is the ‘culprit’ and also questions the empirical relevance of our ‘fixed profit equilibrium’ or ‘land-price treadmill’. We show here that if a viability condition stated in our original paper holds, parameter values of the model must yield a positive rate of profit if the profit rate is to fall following an improvement in the terms of trade. We then contrast our model with a more neoclassical one in which the sign of the derivative does strictly depend on the ‘technology’, that is, upon factor intensities. Finally, we present empirical evidence from a detailed study of the U.S. economy based on our original model. These data support the existence of a land-price treadmill in agriculture, especially for countries in which workers are successful in defending a given real wage.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).