In the aftermath of the global financial crisis, questions have been raised regarding the value and applicability of modern macroeconomics. Motivated by these developments and recent advances in dynamical systems theory, the papers in this special issue of Macroeconomic Dynamics deal with specific aspects of the economy as a complex evolving dynamic system.

We study the dynamics of the distribution of wealth in an economy with infinitely lived agents, intergenerational transmission of wealth, and redistributive fiscal policy. We show that wealth accumulation with idiosyncratic investment risk and uncertain lifetimes can generate a double Pareto wealth distribution.

We explore bifurcation phenomena in the open-economy New Keynesian model developed by Galí and Monacelli in 2005. We find that the open economy framework brings about more complex dynamics, along with a wider variety of qualitative behaviors and policy responses. Introducing parameters related to the open economy structure affects the values of bifurcation parameters and changes the location of bifurcation boundaries. As a result, the stratification of the confidence region, as previously seen in closed-economy New Keynesian models, remains an important research and policy risk to be considered in the context of the open-economy New Keynesian functional structures. In fact, econometrics and optimal policy design become more complex within an open economy. Dynamical inferences need to be qualified by the risk of bifurcation boundaries crossing the confidence regions. Policy design needs to take into consideration that a change in monetary policy can produce an unanticipated bifurcation, without adequate prior econometrics research.

We introduce public spending, financed through income taxation, into the Ramsey model with heterogeneous agents. Public spending as a source of welfare generates more complex dynamics. In contrast to previous contributions focusing on similar models but with wasteful public spending, limit cycles through Hopf bifurcation and expectation-driven fluctuations appear if the degree of capital–labor substitution is high enough to be compatible with capital income monotonicity. Moreover, unlike frameworks with a representative agent, our results do not require externalities in production and are compatible with a weakly elastic labor supply with respect to wage.

We propose a sectoral–shift theory of aggregate factor productivity for a class of multisector economies with AK technologies and a constant production possibilities frontier. Loans are partly secured by collateral and partly based on reputation. We find that both the growth rate and total factor productivity (TFP) respond to random and persistent endogenous fluctuations in the sectoral distribution of physical capital, which, in turn, responds to reversible exogenous shifts in relative sector productivities. Endogenous debt limits on secured and unsecured loans slow down capital reallocation, preventing the equalization of risk-adjusted equity yields across sectors. Economywide factor productivity and the aggregate growth rate are both negatively correlated with the dispersion of sectoral rates of return, sectoral TFP, and sectoral growth rates. We also find highly volatile limit cycles in economies with small amounts of collateral.

This paper distinguishes two kinds of endogenous business cycle models: EBC1 models, which display dynamic indeterminacy, and EBC2 models, which display steady-state indeterminacy. Both strands of the literature have their origins in the sunspot literature that developed at the University of Pennsylvania in the 1980s. I argue that EBC1 models are part of the evolution of modern macroeconomics that has classical roots dating back to the 1920s. EBC2 models provide a microfoundation for one of the most important ideas to emerge from Keynes's (1936) General Theory of Employment, Interest and Money: that high involuntary unemployment can persist as part of the steady-state equilibrium of a market economy.

We use an agent-based computational approach to show how inflation can worsen macroeconomic performance by disrupting the mechanism of exchange in a decentralized market economy. We find that, in our model economy, increasing the trend rate of inflation above 3% has a substantial deleterious effect, but lowering it below 3% has no significant macroeconomic consequences. Our finding remains qualitatively robust to changes in parameter values and to modifications to our model that partly address the Lucas critique. Finally, we contribute a novel explanation for why cross-country regressions may fail to detect a significant negative effect of trend inflation on output even when such an effect exists in reality.

We formulate a central bank's problem of selecting an optimal long-run inflation rate as the choice of a distorting tax by a planner who wishes to maximize discounted stationary utility for a heterogeneous population of infinitely lived households in an economy with constant aggregate income and public information. Households are segmented into agents who store value in currency alone and agents who have access to both currency and loans. We show that the optimum inflation rate is positive, because inflation reduces the value of the outside option for credit agents and raises their debt limits.

This paper suggests that we need an alternative approach to economic modeling in general, and macroeconomic modeling in particular, if we are to capture salient characteristics of recent economic developments. Rather than focusing on models built on the basis of isolated, rational, optimizing agents, we should recognize that much simpler individuals following basic rules can collectively generate complex behavior. We have lessons to learn from studying the behavior of social insects for example. Noisy systems of interactive agents can generate aggregate phenomena such as sudden changes in the state of an economy or market, with no external shock. I give two examples of simple models of financial markets to illustrate this but would argue more generally that such models are indispensible if we are to understand aggregate economic phenomena.