In Raising Keynes: A Twenty-First Century General Theory, Stephen A. Marglin offers a provocative reformulation of Keynes’ theoretical framework, stressing the importance of modeling the dynamics of wage and price adjustment. This review explains and assesses Marglin’s argument for the possibility of a persistent equilibrium in which goods and/or labor markets continue not to clear in the absence of active stabilization policy. It also compares Marglin’s analysis with that of New Keynesian models, and shows that the two approaches are more similar than might be immediately evident.

This paper considers the desirability of the observed tendency of central banks to adjust interest rates only gradually in response to changes in economic conditions. It shows, in the context of a simple model of optimizing private-sector behaviour, that assignment of an interest-rate smoothing objective to the central bank may be desirable, even when reduction of the magnitude of interest-rate changes is not a social objective in itself. This is because a response of policy to “irrelevant” lagged variables may be desirable owing to the way it steers private-sector expectations of future policy.

We study the movements in output, consumption and hours that are forecastable from a VAR and analyze how they differ from those predicted by standard real-business-cycle models. We show that actual forecastable movements in output have a variance about one hundred times larger than those predicted by the model. We also find that forecastable changes in the three series are strongly positively correlated with each other. On the other hand, for parameters whose implications are plausible in other respects, the model implies that output, consumption, and hours should not all be expected to move in the same direction.

We construct a dynamic general equilibrium model in which the typical industry colludes by threatening to punish deviations from an implicitly agreed-on pricing path. We use methods similar to those of Kydland and Prescott to calibrate linearized versions of both our model and an analogous perfectly competitive model. We then compute the two models' predictions concerning the economy's responses to a change in military spending. The responses predicted by the oligopolistic model are closer to the empirical responses estimated with postwar U.S. data than the corresponding predictions of the competitive model.

An adaptive learning rule is exhibited for the Azariadis (1981) overlapping generations model of a monetary economy with multiple equilibria, under which the economy may converge to a stationary equilibrium, even if agents do not initially believe that outcomes are significantly different in different sunspot states. The learning rule studied is of the stochastic approximation form studied by H. Robbins and S. Monro (1951); methods for analyzing the convergence of this form of algorithm are presented that may be of use in many other contexts as well. Conditions are given under which convergence to a equilibrium occurs with probability one. Copyright 1990 by The Econometric Society. (This abstract was borrowed from another version of this item.)

The challenge for stabilization policy presented by the COVID-19 pandemic stems above all from disruption of the circular flow of payments, resulting in a failure of what Keynes (1936) calls “effective demand.” As a consequence, economic activity in many sectors can be inefficiently low, and interest-rate policy cannot eliminate the distortions—not because of a limit on the extent to which interest rates can be reduced, but because interest-rate reductions fail to stimulate demand of the right sorts. Fiscal transfers are instead well suited to addressing the fundamental problem, and can under certain circumstances achieve a first-best allocation of resources.

A model is proposed in which stochastic choice results from noise in cognitive processing rather than random variation in preferences. The mental process used to make a choice is nonetheless optimal, subject to a constraint on available information-processing capacity that is motivated by neurophysiological evidence. The optimal information-constrained model is found to offer a better fit to experimental data on choice frequencies and reaction times than either a purely mechanical process model of choice (the drift-diffusion model) or an optimizing model with fewer constraints on feasible choice processes (the rational inattention model).