Summary and concluding remarks

Abstract

One can find many economic models embedded in well accepted frameworks such as utility maximizing agents in overlapping generations models, neoclassical growth models, or IS/LM models that generate irregular behavior. Variables like the GDP, the stock of capital, or the level of employment undergo persistent cycles that look as if they were random, but are grounded on fixed equations of motion that do not have a stochastic component. These models strongly indicate the possibility of nonlinear deterministic and chaotic dynamics in economics. The models that are discussed above try to widen the spectrum of endogenous and irregular dynamics to labor markets. Various models are developed that sketch the impact of nonlinearities on labor market dynamics. It is shown that by incorporating nonlinear relationships into standard models of the labor market, dynamic properties arise that include long lasting adjustment periods and locally or globally unstable equilibria. Variables such as real wages and employment may undergo persistent cycles of finite and infinite order. Although these models are highly stylized, and would not perform satisfactorily when confronted with real data, they can make an important contribution to the understanding of labor market dynamics. They shift attention to endogenous explanations of labor market dynamics that linear stochastic approaches are not able to provide. In particular, we develop models where real wages adjust to disequilibrium quantities assuming a backward bending labor supply, a nonlinear but monotonous supply curve, or a discontinuous demand curve that arises from increasing returns in the underlying production technology. Two further approaches focus on the adjustment dynamics in the level of unemployment, either driven by diverging flows into and from unemployment, or by the hiring and firing behavior of firms in a ‘right to manage model’ that has a U-shaped wage setting curve.KeywordsLabor MarketLabor SupplyReal WageLabor DemandPhillips CurveThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.