The authors are indebted to the anonymous referee for a very detailed and insightful report on an earlier version of this paper that has led to many improvements in the current version. Address correspondence to: Tony He, School of Finance and Economics, University of Technology, Sydney, P.O. Box 123 Broadway, NSW 2007, Australia; e-mail: [email protected]. This paper studies the dynamics of a simple discounted present-value asset-pricing model where agents have different risk attitudes and follow different expectation formation schemes for the price distribution. A market-maker scenario is used as the market-clearing mechanism, in contrast to the more usual Walrasian scenario. In particular, the paper concentrates on models of fundamentalists and trend followers who follow recursive geometric-decay (learning) processes (GDP) with both finite and infinite memory. The analysis depicts how the dynamics are affected by various key elements (or parameters) of the model, such as the adjustment speed of the market maker, the extrapolation rate of the trend followers, the decay rate of the GDP, the lag length used in the learning GDP, and external random factors.

A long-standing area of research and policy interest is the construction of a measure of monetary policy stance. One measure that has been proposed, as an alternative to indices that employ monetary aggregates or exchange rates, is the spread between the actual real interest rate and its flexible-price, or natural-rate, counterpart. We examine the properties of the natural real interest rate and real-interest-rate gap using a dynamic stochastic general equilibrium model. Issues we investigate include the response of the gap and its components to fundamental economic shocks and the indicator and forecasting properties of the real-interest-rate gap for inflation, both in the model and in the data. Our results suggest that the real-interest-rate gap has value as an inflation indicator, supporting a neo-Wicksellian framework.

Many authors have documented that it is challenging to explain exchange rate fluctuations with macroeconomic fundamentals: a random walk forecasts future exchange rates better than existing macroeconomic models. This paper applies newly developed tests for nested models that are robust to the presence of parameter instability. The empirical evidence shows that for some countries we can reject the hypothesis that exchange rates are random walks. This raises the possibility that economic models were previously rejected not because the fundamentals are completely unrelated to exchange rate fluctuations, but because the relationship is unstable over time and, thus, difficult to capture by Granger causality tests or by forecast comparisons. We also analyze forecasts that exploit the time variation in the parameters and find that, in some cases, they can improve over the random walk.

I consider an economy growing along the balanced growth path that is hit by an adverse shock to its capital accumulation process. The model integrates efficiency wages due to imperfect monitoring of the quality of labor in a search and matching framework with methods of dynamic general equilibrium analysis. I show that, depending on the firms' abilities to assess workers' performance, the discipline device role of unemployment may account for sharp declines in employment and jobless recoveries driven by exceptional increases in the work effort of employees. The model also explains why rigid real wages may prevail in equilibrium: the large movements in unemployment are indeed associated with real wage rigidity, which is generated endogenously by efficiency wages.

The interest in business-cycle asymmetry has been steadily increasing over the past 15 years. Most research has focused on the different behavior of macroeconomic variables during expansions and contractions, which by now is well documented. Recent evidence suggests that such a two-phase characterization of the business cycle might be too restrictive. In particular, it might be worthwhile to decompose the recovery phase in a high-growth phase (immediately following the trough of a cycle) and a subsequent moderate-growth phase. The issue of multiple regimes in the business cycle is addressed using smooth-transition autoregressive (STAR) models. A possible limitation of STAR models as they currently are used is that essentially they deal with only two regimes. We propose a generalization of the STAR model such that more than two regimes can be accommodated. It is demonstrated that the class of multiple-regime STAR (MRSTAR) models can be obtained from the two-regime model in a simple way. The main properties of the MRSTAR model and several issues that are relevant for empirical specification are discussed in detail. In particular, a Lagrange multiplier-type test is derived that can be used to determine the appropriate number of regimes. A limited simulation study indicates its practical usefulness. Application of the new model class to U.S. real GNP provides evidence in favor of the existence of multiple business-cycle phases.

In the United States wealth is highly concentrated and very unequally distributed: the richest 1% hold one third of the total wealth in the economy. Understanding the determinants of wealth inequality is a challenge for many economic models. We summarize some key facts about the wealth distribution and what economic models have been able to explain so far.

In this paper we investigate the effects of oil price uncertainty and its asymmetry on real economic activity in the United States, in the context of a bivariate vector autoregression with GARCH-in-mean errors. The model allows for the possibilities of spillovers and asymmetries in the variance–covariance structure for real output growth and the change in the real price of oil. Our measure of oil price uncertainty is the conditional variance of the oil price–change forecast error. We isolate the effects of volatility in the change in the price of oil and its asymmetry on output growth and employ simulation methods to calculate generalized impulse response functions and volatility impulse response functions to trace the effects of independent shocks on the conditional means and the conditional variances, respectively, of the variables. We find that oil price uncertainty has a negative effect on output, and that shocks to the price of oil and its uncertainty have asymmetric effects on output.

We use a general equilibrium model to study the impact of fully funding social security on the distribution of consumption across cohorts and over time. In an initial stationary equilibrium with an unfunded social security system, the capital/output ratio, debt/output ratio, and rate of return to capital are 3.2, 0.6, and 6.8%, respectively. In our first experiment, we suddenly terminate social security payments but compensate entitled generations by a massive one-time increase in government debt. Eventually, the aggregate physical capital stock rises by 40%, the return on capital falls to 4.4%, and the labor income tax rate falls from 33.9 to 14%. We estimate the size of the entitlement debt to be 2.7 times real GDP, which is paid off by levying a 38% labor income tax rate during the first 40 years of the transition. In our second experiment, we leave social security benefits untouched but force the government temporarily to increase the tax on labor income so as gradually to accumulate private physical capital, from the proceeds of which it eventually finances social security payments. This particular government-run funding scheme delivers larger efficiency gains (in both the exogenous and endogenous price cases) than privatization, an outcome stemming from the scheme's public provision of insurance both against life-span risk and labor income volatility.

This paper explores multiasset market dynamics. We consider a limited number of markets on which two types of agents are active. Fundamentalists specialize in a certain market to gather expertise. Chartists may switch between markets since they use simple extrapolative methods. Specifically, chartists prefer markets that display price trends but that are not too misaligned. The interaction between the traders causes complex dynamics. Even in the absence of random shocks, our artificial markets mimic the behavior of actual asset markets closely. Our model also offers reasons for the high degree of comovements in stock prices observed empirically.

The recent macroeconomic literature stresses the importance of managing heterogeneous expectations in the formulation of monetary policy. We use a simple frictionless dynamic stochastic general equilibrium (DSGE) model to investigate inflation dynamics under alternative interest rate rules when agents have heterogeneous expectations, and update their beliefs based on past performance, as in Brock and Hommes [Econometrica 65(5), 1059–1095 (1997)]. The stabilizing effect of different monetary policies depends on the ecology of forecasting rules (i.e., the composition of the set of predictors), on agents' sensitivity to differences in forecasting performance, and on how aggressively the monetary authority sets the nominal interest rate in response to inflation. In particular, if the monetary authority responds only weakly to inflation, a cumulative process with rising inflation is likely. On the other hand, a Taylor interest rate rule that sets the interest rate more than point for point in response to inflation stabilizes inflation dynamics, but does not always lead the system to converge to the rational expectations equilibrium, as multiple equilibria may persist.

This paper provides evidence on monetary policy transmission for five key emerging market economies: Brazil, Russia, India, China, and South Africa. Monetary policy (interest rate) shocks are identified using modern Bayesian methods along with the more recent sign restrictions approach. We find that contractionary monetary policy has a strong and negative effect on output. We also show that such contractionary monetary policy shocks do tend to stabilize inflation in these countries in the short term, while producing a strongly persistent negative effect on real equity prices. Overall, the impulse responses are robust to the alternative identification procedures.

A planner and agent in a permanent-income economy cannot observe part of the state, regard their model as an approximation, and value decision rules that are robust across a set of models. They use robust decision theory to choose allocations. Equilibrium prices reflect the preference for robustness and so embody a “market price of Knightian uncertainty.” We compute market prices of risk and compare them with a model that assumes that the state is fully observed. We use detection error probabilities to constrain a single parameter that governs the taste for robustness.

This paper presents an endogenous growth model in which the research activity is financed by intermediaries that are able to reduce the incidence of researcher's moral hazard. It is shown that financial activity is growth promoting because it increases research productivity. It is also found that a subsidy to the financial sector may have larger growth effects than a direct subsidy to research. Moreover, because of the presence of moral hazard, increasing the subsidy rate to R&D may reduce the growth rate. I show that there exists a negative relation between the financing of innovation and the process of capital accumulation. Concerning welfare, the presence of two externalities of opposite sign stemming from financial activity may cause the no-tax equilibrium to provide an inefficient level of financial services. Thus, policies oriented to balance the effects of the two externalities will be welfare improving.

The failure of consumption-based asset pricing models to match the stochastic properties of the equity premium and the risk-free rate has been attributed by some authors to frictions, transaction costs, or durability. However, such frictions primarily would affect the higher-frequency data components: Consumption-based pricing models that concentrate on long-horizon returns should be more successful. We consider two consumption-based models: time-separable utility, and the habit model of Constantinides. We estimate a vector ARCH model that includes the pricing kernel and the equity return, and use the fitted model to assess the model's implications for the equity premium and for the risk-free rate. Neither model performs well at a quarterly horizon, but at longer horizons the Constantinides model can match the mean and the variance of the observed equity premium, captures time variation of the equity premium, and can better match the observed risk-free rate. We conclude that the equity-premium and risk-free-rate puzzles are primarily problems for shorter-horizon returns.

We show that absence of arbitrage in frictionless markets implies a lower bound on the average of the logarithm of the reciprocal of the stochastic discount factor implicit in asset pricing models. The greatest lower bound for a given asset menu is the average continuously compounded return on its growth-optimal portfolio. We use this bound to evaluate the plausibility of various parametric asset pricing models to characterize financial market puzzles such as the equity premium puzzle and the risk-free rate puzzle. We show that the insights offered by the growth-optimal bounds differ substantially from those obtained by other nonparametric bounds.

It is argued that standard impulse response analysis based on vector autoregressive models has a number of shortcomings. Although the impulse responses are estimated quantities, measures for sampling variability such as confidence intervals sometimes are not provided. If confidence intervals are given, they often are based on bootstrap methods with dubious theoretical properties. These problems are illustrated using two German monetary systems. Proposals are made for improving current practice. Special emphasis is placed on systems with cointegrated variables.

We construct portfolios of stocks and bonds that are maximally predictable with respect to a set of ex-ante observable economic variables, and show that these levels of predictability are statistically significant, even after controlling for data-snooping biases. We disaggregate the sources of predictability by using several asset groups — sector portfolios, market-capitalization portfolios, and stock/bond/utility portfolios — and find that the sources of maximal predictability shift considerably across asset classes and sectors as the return horizon changes. Using three out-of-sample measures of predictability — forecast errors, Merton's market-timing measure, and the profitability of asset-allocation strategies based on maximizing predictability — we show that the predictability of the maximally predictable portfolio is genuine and economically significant.

This paper applies panel cointegration tests and panel vector error correction models for 17 OECD countries and considers cross-sectional dependence and structural breaks to investigate the interrelationship between an insurance market's development and real output, controlling for banking activities. We first obtain evidence of a fairly strong long-run equilibrium relationship among them. Second, we find that insurance market development has positive effects on real output and that banking activities have an unfavorable, if not negative, effect on real output. In fact, insurance market activity is much more productive than banking sector activity. Finally, there exists bidirectional causality between insurance premiums and economic growth in the long run, suggesting the existence of the feedback hypothesis for the insurance–output nexus.

This paper constructs an endogenous growth model with productive government spending. In this model, the government can finance its costs through income tax and government debt and has a target level of government debt relative to the size of the economy. We show that there are two steady states. One is associated with high growth and the other with low growth. It is also shown that whether the government uses income taxes or government bonds makes the results differ significantly. In particular, an increase in government bonds reduces the growth rate in the high-growth steady state and raises the growth rate in the low-growth steady state. Conversely, an increase in the income tax rate reduces the growth rate in the low-growth steady state and there exists some tax rate that maximizes the growth rate in the high-growth steady state. Finally, the level of welfare in the low-growth steady state is lower than that in the high-growth steady state.

The emerging consensus in monetary policy and business cycle analysis is that money aggregates are not useful as an intermediate target for monetary policy or as an information variable. The uselessness of money as an intermediate target is driven, at least in part, by empirical research that suggests that money demand is unstable. In addition, the informational quality of money has been called into question by empirical research that fails to identify a relationship between money growth and inflation, nominal income growth, and the output gap. Nevertheless, this research is potentially flawed by the use of simple sum money aggregates, which are not consistent with economic, aggregation, or index number theory. This paper therefore reexamines previous empirical evidence on money demand and the role of money as an information variable, using Divisia monetary aggregates. These aggregates have the advantage of being derived from microtheoretic foundations, as well as being consistent with aggregation and index number theory. The results of the reevaluation suggest that previous empirical work might be driven by mismeasurement.