The Labor Market and Macro Volatility: A Nonstationary General-Equilibrium Analysis

The evolution of the aggregate labor market is far from smooth. I investigate the success of a macro model in replicating the observed levels of volatility of unemployment and other key variables. I take variations in productivity growth and in exogenous product demand (government purchases plus net exports) as the primary exogenous sources of fluctuations. The macro model embodies new ideas about the labor market, all based on equilibrium %u2013 the models I consider do not rest on inefficiency in the use of labor caused by an inappropriate wage. I find that non-standard features of the labor market are essential for understanding the volatility of unemployment. These models include simple equilibrium wage stickiness, where the sticky wage is an equilibrium selection rule. A second model based on modern bargaining theory delivers a different kind of stickiness and has a unique equilibrium. A third model posits fluctuations in matching efficiency that may arise from variations over time in the information about prospective jobs among job-seekers. Reasonable calibrations of each of the three models match the observed volatility of unemployment.

Joint evolution of multiple social traits: a kin selection analysis

General models of the evolution of cooperation, altruism and other social behaviours have focused almost entirely on single traits, whereas it is clear that social traits commonly interact. We develop a general kin-selection framework for the evolution of social behaviours in multiple dimensions. We show that whenever there are interactions among social traits new behaviours can emerge that are not predicted by one-dimensional analyses. For example, a prohibitively costly cooperative trait can ultimately be favoured owing to initial evolution in other (cheaper) social traits that in turn change the cost-benefit ratio of the original trait. To understand these behaviours, we use a two-dimensional stability criterion that can be viewed as an extension of Hamilton's rule. Our principal example is the social dilemma posed by, first, the construction and, second, the exploitation of a shared public good. We find that, contrary to the separate one-dimensional analyses, evolutionary feedback between the two traits can cause an increase in the equilibrium level of selfish exploitation with increasing relatedness, while both social (production plus exploitation) and asocial (neither) strategies can be locally stable. Our results demonstrate the importance of emergent stability properties of multidimensional social dilemmas, as one-dimensional stability in all component dimensions can conceal multidimensional instability

Interpreting selection when individuals interact

A useful interpretation of quantitative genetic models of evolutionary change is that they (i) define a set of phenotypes that have a causal effect on fitness and on which selection acts, and (ii) define a set of breeding values that change as a correlated response to that selection because they covary with the phenotypes. When the expression of one trait causes variation in other traits then there are multiple paths by which a trait can cause fitness variation. Because of this, there are multiple ways in which selection can be defined, and still be consistent with a causal effect of traits on fitness. We use this result to show that genetical theories of natural/kin selection ignore causation and because of this we suggest they shed little light on the nature of selection. When traits expressed by an individual are affected by traits of their social partners (indirect genetic effects), we suggest a causal partitioning that allows selection to be cast in terms of Hamilton's costs and benefits. We show that previous attempts to understand Hamilton's rule in the context of indirect genetic effects either lack generality, or do not adequately describe all the ways in which an individual's actions constitute a cost to the individual or a benefit to its social partner(s). Our results allow us to explore Hamilton's rule in a multitrait setting. We show that evolution always increases inclusive fitness, and when the traits are measured in units of generalised genetic distance evolutionary change in the traits is in the direction in which inclusive fitness increases the fastest. However, we show that Hamilton's rule only holds in a multitrait context when the suite of traits are at equilibrium. When they are out of equilibrium, the conditions for altruism to evolve may be more or less stringent depending on genetic architecture and how costs and benefits are defined.</p

Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics

Evolutionary game dynamics is one of the most fruitful frameworks for studying evolution in different disciplines, from Biology to Economics. Within this context, the approach of choice for many researchers is the so-called replicator equation, that describes mathematically the idea that those individuals performing better have more offspring and thus their frequency in the population grows. While very many interesting results have been obtained with this equation in the three decades elapsed since it was first proposed, it is important to realize the limits of its applicability. One particularly relevant issue in this respect is that of non-mean-field effects, that may arise from temporal fluctuations or from spatial correlations, both neglected in the replicator equation. This review discusses these temporal and spatial effects focusing on the non-trivial modifications they induce when compared to the outcome of replicator dynamics. Alongside this question, the hypothesis of linearity and its relation to the choice of the rule for strategy update is also analyzed. The discussion is presented in terms of the emergence of cooperation, as one of the current key problems in Biology and in other disciplines.Comment: Review, 48 pages, 26 figure

Dynamics of growth factor production in monolayers of cancer cells and evolution of resistance to anticancer therapies

Tumor heterogeneity is well documented for many characters, including the production of growth factors, which improve tumor proliferation and promote resistance against apoptosis and against immune reaction. What maintains heterogeneity remains an open question that has implications for diagnosis and treatment. While it has been suggested that therapies targeting growth factors are robust against evolved resistance, current therapies against growth factors, like antiangiogenic drugs, are not effective in the long term, as resistant mutants can evolve and lead to relapse. We use evolutionary game theory to study the dynamics of the production of growth factors by monolayers of cancer cells and to understand the effect of therapies that target growth factors. The dynamics depend on the production cost of the growth factor, on its diffusion range and on the type of benefit it confers to the cells. Stable heterogeneity is a typical outcome of the dynamics, while a pure equilibrium of nonproducer cells is possible under certain conditions. Such pure equilibrium can be the goal of new anticancer therapies. We show that current therapies, instead, can be effective only if growth factors are almost completely eliminated and if the reduction is almost immediate

Evolution of cooperation driven by zealots

Recent experimental results with humans involved in social dilemma games suggest that cooperation may be a contagious phenomenon and that the selection pressure operating on evolutionary dynamics (i.e., mimicry) is relatively weak. I propose an evolutionary dynamics model that links these experimental findings and evolution of cooperation. By assuming a small fraction of (imperfect) zealous cooperators, I show that a large fraction of cooperation emerges in evolutionary dynamics of social dilemma games. Even if defection is more lucrative than cooperation for most individuals, they often mimic cooperation of fellows unless the selection pressure is very strong. Then, zealous cooperators can transform the population to be even fully cooperative under standard evolutionary dynamics.Comment: 5 figure