We investigate the quantitative behavior of business-cycle models in which the intermediation process acts either as a source of fluctuations or as a propagator of real shocks. In neither case do we find convincing evidence that the intermediation process is an important element of aggregate fluctuations. For an economy driven by intermediation shocks, consumption is not smoother than output, investment is negatively correlated with output, variations in the capital stock are quite large, and interest rates are procyclical. The model economy thus fails to match unconditional moments for the U.S. economy. We also structurally estimate parameters of a model economy in which intermediation and productivity shocks are present, allowing for the intermediation process to propagate the real shock. The unconditional correlations are closer to those observed only when the intermediation shock is relatively unimportant.

A noisy rational expectations model of asset trading is extended to incorporate costs of information acquisition and expectation formation. Because of the information costs, how much information to acquire becomes an important decision. Agents make this decision by choosing an expectations strategy about the future value of information. Because expectation formation is costly, agents often choose strategies that are simpler (and thus cheaper) than rational expectations. The model's dynamics can be expressed in terms of the market precision, which represents the amount of information acquired by the average agent. Under certain conditions, market precision follows an unstable and highly irregular time path. This irregularity directly affects observable market quantities. In particular, simulated time series for return volatility and trading volume display a copersistence similar to that found in actual financial data.

This paper analyzes the relationship between the expectational stability of rational expectations solutions and the possible convergence of adaptive learning processes. Both concepts are used as selection criteria in the case of multiple rational expectations solutions. Results obtained using recursive least squares lead to the conjecture that there exists a general one-to-one correspondence between these two selection criteria. On the basis of a simple linear model and a stochastic gradient algorithm as an alternative learning procedure, it is demonstrated that such a conjecture would be incorrect: There are cases in which stochastic gradient learning converges to rational expectations solutions that are not expectationally stable.

We consider a model that provides insight into the well-known Folk theorem in economics that when the discount factor β is sufficiently close to 1, expropriation will never occur. Although this Folk theorem is true in our model, our perspective is different. The discount factor β often is described as a “deep structural parameter” that is difficult to alter at a point in time. In contrast, we analyze the determinants of two thresholds β and β* that segment the unit interval on which β is defined into three subintervals. These subintervals correspond to the three possible equilibria for investment flows: autarky, underinvestment, and unconstrained optimal investment. These thresholds are of interest because they can be altered by specific policy interventions. As a consequence, even if β is small, some level of foreign investment can be supported. We construct measures of β for 40 countries, characterize β and β*, and discuss recent trends in investment flows.

This paper analyzes aggregate wealth based on separable risk aversion and intertemporal substitution. In an infinite-period overlapping-generations model with survival uncertainty, economic growth, and permanent and temporary income shocks, our closed-form solution permits us to derive rich behavioral conclusions and to assess the relative importance of the major components of aggregate wealth. In particular, the separation of the attitudes toward risk and substitution allows us to disentangle behaviors relating to the intertemporal substitution motive from behaviors relating to the precautionary motive.

We present a simple model of a stock market where a random communication structure between agents generically gives rise to heavy tails in the distribution of stock price variations in the form of an exponentially truncated power law, similar to distributions observed in recent empirical studies of high-frequency market data. Our model provides a link between two well-known market phenomena: the heavy tails observed in the distribution of stock market returns on one hand and herding behavior in financial markets on the other hand. In particular, our study suggests a relation between the excess kurtosis observed in asset returns, the market order flow, and the tendency of market participants to imitate each other.

I examine the robustness of monetary equilibria in a random-matching model, where a more efficient mechanism for trade is available. Agents choose between two trading sectors: the search and the intermediated sector. In the former, trade partners arrive randomly and there is a trading externality. In the latter, a costly matching technology provides deterministic double-coincidence matches. Multiple equilibria exist with the extent of costly matching endogenously determined. Money and “mediated” trade may coexist. This depends on the size of the probability of a trade, relative to the cost of deterministic matching. This outcome is inferior for an increasing-returns externality. Under certain conditions, regimes with only costly matching are welfare superior to monetary regimes with random matching.

This paper addresses the problem of multiple equilibria in a model of time-consistent monetary policy. It suggests that this problem originates in the assumption that agents have rational expectations and proposes several alternative restrictions on expectations that allow the monetary authority to build credibility for a disinflationary policy by demonstrating that it will stick to that policy even if it imposes short-run costs on the economy. Starting with these restrictions, the paper derives conditions that guarantee the uniqueness of the model's steady state; monetary policy in this unique steady state involves the constant deflation advocated by Milton Friedman.

In the context of I(1) time series, we provide some asymptotic results for the Davidson-MacKinnon J-type test. We examine both the case where our regressor sets x1t and x2t are not cointegrated, and the case where they are. In the former case, the OLS estimator of the weighting coefficient from the artificial compound model converges at rate T to a mixed normal distribution, and the associated t-statistic has an asymptotic standard normal distribution. In the latter case, we find that the J-test also has power against violation of weak exogeneity (with respect to the short-run coefficients of the null model), which is caused by correlation between the disturbance of the null model and that of the cointegrating equation linking x1t and x2t. Moreover, unlike the previous case, the OLS estimator of the weighting coefficient from the artificial compound model converges at \sqrt{T} to an asymptotic normal distribution when the null model is specified correctly. In an empirical illustration, we use the tests to examine an industrial production data set for six countries.

In aggregation theory, index numbers are judged relative to their ability to track the exact aggregator functions nested within the economy's structure. We compare two statistical index numbers—the Divisia monetary aggregate and the simple-sum monetary aggregate—with the exact rational expectations monetary aggregate, using actual data. Because we are not using simulated data, we estimate the parameters of the Euler equations, and thereby of the nested monetary aggregator function, using the generalized method of moments. We explore the tracking errors of the two index numbers relative to the estimated exact aggregate. We investigate the circumstances under which risk aversion increases tracking error. We also use polyspectral methods to test for the existence of remaining nonlinear structure in the residual tracking errors.

We examine whether annual, quarterly, and monthly U.S. aggregate consumption data could have been generated by a utility-maximizing representative agent with intertemporally separable utility. The model appears inapplicable over the full time periods covered by the NIPA data, which are the sample periods often used in the literature. The model does appear applicable, however, over long subsamples. The data also are inconsistent with separability assumptions routinely made in the literature. In particular, the main categories of consumption (nondurables, services, and durables) are not mutually separable. We consider the implications of our results for inference about consumption based on the representative-agent model.

We present a class of stochastic regime-switching models. The time-series models may have periodic transition probabilities and the drifts may be seasonal. In the latter case, the model exhibits seasonal dummy variation that may change with the regime. The processes entail nontrivial interactions between so-called business and seasonal cycles. We discuss the stochastic properties as well as their relationship with periodic ARMA processes. Estimation and testing are also discussed in detail.

This paper analyzes the empirical interdependecies among asset returns, real activity, and inflation from multicountry and international points of view. We find that innovations in nominal stock returns are not significantly related to inflation or real activity, that the U.S. term structure of interest rates predicts both domestic and foreign inflation rates and domestic future real activity, and that innovations in inflation do not significantly affect real activity. An interpretation of the dynamics and some policy implications of the results are provided.

We recast Diamond's search equilibrium model into that with a finite number of agents. The state of the model is described by a jump-Markov process, the transition rates of which are functions of the reservation cost, which are endogenously determined by value maximization by rational agents. The existence of stochastic fluctuations causes the fraction of the employed to move from one basin of attraction to the other with positive probabilities when the dynamics have multiple equilibria. Stochastic asymmetric cycles that arise are quite different from the cycles of the set of Diamond–Fudenberg nonlinear deterministic differential equations. By taking the number of agents to infinity, we get a limiting probability distribution over the stationary state equilibria. This provides a natural basis for equilibrium selection in models with multiple equilibria, which is new in the economic literature.

This honorary lecture is the first to appear in Macroeconomic Dynamics. Other honorary lectures and addresses on topics of importance to macroeconomics will appear occasionally in this journal. Many unpublished honorary lectures and addresses have become well known and heavily cited. As a means of making such valuable “named” lectures and addresses available in published form, journals of some professional societies annually publish an invited lecture presented at society meetings.

Franco Modigliani's contributions in economics and finance have transformed both fields. Although many other major contributions in those fields have come and gone, Modigliani's contributions seem to grow in importance with time. His famous 1944 article on liquidity preference has not only remained required reading for generations of Keynesian economists but has become part of the vocabulary of all economists. The implications of the life-cycle hypothesis of consumption and saving provided the primary motivation for the incorporation of finite lifetime models into macroeconomics and had a seminal role in the growth in macroeconomics of the overlapping generations approach to modeling of Allais, Samuelson, and Diamond. Modigliani and Miller's work on the cost of capital transformed corporate finance and deeply influenced subsequent research on investment, capital asset pricing, and recent research on derivatives. Modigliani received the Nobel Memorial Prize for Economics in 1985.

In macroeconomic policy, Modigliani has remained influential on two continents. In the United States, he played a central role in the creation of a the Federal Reserve System's large-scale quarterly macroeconometric model, and he frequently participated in the semiannual meetings of academic consultants to the Board of Governors of the Federal Reserve System in Washington, D.C. His visibility in European policy matters is most evident in Italy, where nearly everyone seems to know him as a celebrity, from his frequent appearances in the media. In the rest of Europe, his visibility has been enhanced by his publication, with a group of distinguished European and American economists, of “An Economists' Manifesto on Unemployment in the European Union,” which was signed by a number of famous economists and endorsed by several others.

This interview was conducted in two parts on different dates in two different locations, and later unified. The initial interview was conducted by Robert Solow at Modigliani's vacation home in Martha's Vineyard. Following the transcription of the tape from that interview, the rest of the interview was conducted by William Barnett in Modigliani's apartment on the top floor of a high-rise building overlooking the Charles River near Harvard University in Cambridge, Massachusetts. Those concluding parts of the interview in Cambridge continued for the two days of November 5–6, 1999 with breaks for lunch and for the excellent espresso coffee prepared by Modigliani in an elaborate machine that would be owned only by someone who takes fine coffee seriously.

Although the impact that Modigliani has had on the economics and finance professions is clear to all members of those professions, only his students can understand the inspiration that he has provided to them. However, that may have been adequately reflected by Robert Shiller at Yale University in correspondence regarding this interview, when he referred to Modigliani as: “my hero.”

This paper provides a survey of the applications of evolutionary algorithms in macroeconomic models. Discussion is organized around the issues related to stability of equilibria, equilibrium selection, transitional dynamics, and the long-run evolutionary dynamics different from rational-expectations equilibrium outcomes. The survey also discusses criteria that can be used to evaluate the performance and usefulness of evolutionary algorithms in the macroeconomic context.

Two alternative theories of aggregate supply, both with a New Keynesian “flavor,” are compared. The first assumes that prices are rigid due to the existence of menu costs. The second derives price stickiness endogenously as one equilibrium in an economy with multiple equilibria. In both cases I show that the Ball–Romer concept of real rigidities is essential to explain why monetary policy has real persistent effects. I argue that dynamic menu cost models are determinate because they make special assumptions about the way that money enters the economy. For example, most authors assume either a cash-in-advance constraint or that money enters separably into utility or production functions. Once one moves beyond these special cases, menu cost models that display real rigidity are also likely to display indeterminacy.

This paper embeds time-varying volatility into a dynamic equilibrium model of returns and trading. The model allows us to ask how time-varying volatility might affect the relation among return autocorrelation, volatility, and trading volume, as opposed to the pairwise relations that have been studied previously. It is shown analytically that, with time-varying volatility, the relationship between volume and stock return autocorrelation is ambiguous even if agents have symmetric information, which may explain the contradictory findings in the empirical literature. In the numerical exercise, the model is simulated in a way that mimics the persistent volatility of high-frequency stock data documented in numerous empirical studies. Specially, the time-varying volatility of stock returns is approximated with a highly persistent chaotic tent map, which is known to have the same autocorrelation coefficients as an AR(1) process. The simulated data can approximate GARCH-type behavior very well. Whereas in the simulated data, no significant relation between volume and return autocorrelation can be found, there is a significantly positive relation between volume and one-step-ahead stock return volatility. The ambiguous volume–persistence and positive volume–volatility relations are confirmed empirically by using four heavily traded individual stocks. Therefore, the data simulated from the highly stylized asset pricing model with deterministic time-varying volatility can mimic well the volume–return dynamics revealed in the observed data in these two respects.