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.

This paper diagnoses the symptoms of the Dutch disease in a two-sector stochastic endogenous growth model. A productive, low-skill-intensive primary sector causes the currency to appreciate in real terms, thus hampering the development of a high-skill-intensive secondary sector and thereby reducing growth. Moreover, the volatility of the primary sector generates real-exchange-rate uncertainty and may thus reduce investment and learning in the secondary sector and hence also growth. Cross-sectional and panel regressions based on data for 125 countries in the period 1960–1992 confirm a statistically significant inverse relationship between the size of the primary sector and economic growth, but not between the volatility of the real exchange rate and growth.

This paper reviews some of the literature on the macroeconomic effects of oil price shocks with a particular focus on possible nonlinearities in the relation and recent new results obtained by Kilian and Vigfusson [http://www-personal.umich/~lkilian/kvsubmission.pdf (2009)].

We consider two kinds of answers to the title question: Do random shifts in monetary policy account for historical recessions, and would changes in the systematic component of monetary policy have allowed reductions in inflation or output variance without substantial costs. The answer to both questions is no. We use weak identifying assumptions and include extensive discussion of these assumptions, including a completely specified dynamic stochastic equilibrium model in which our identifying assumptions can be shown to be approximately satisfied.

We examine a decision theoretic model of portfolio choice in which investors face income risk that is not directly insurable. We consider the sensitivity of savings and portfolio allocation rules to different assumptions about utility, the stochastic process for income and asset returns, and market frictions (transactions costs and short-sale constraints). Under CRRA time additive utility, habit persistence utility, and for a broad range of parameterizations, the model predicts that investors wish to borrow and invest all of their savings in stocks. This qualitative implication is robust to the introduction of significant transaction costs in the stock market, and contrasts sharply with portfolio allocation models in which there is no labor income.

It is customary to suggest that the asymmetry in the transmission of oil price shocks to real output is well established. Much of the empirical work cited as being in support of asymmetry, however, has not directly tested the hypothesis of an asymmetric transmission of oil price innovations. Moreover, many of the papers quantifying these asymmetric responses are based on censored oil price VAR models that have recently been shown to be invalid. Other studies are based on dynamic correlations in the data and do not distinguish between cause and effect. Recently, several new methods of testing and quantifying asymmetric responses of U.S. real economic activity to positive and negative oil price innovations have been developed. We put this literature into perspective, contrast it with more traditional approaches, highlight directions for further research, and reconcile some seemingly conflicting results reported in the literature.

This paper finds evidence of nonlinearities in the dynamics of the euro area demand for the narrow aggregate M1. A long-run money demand relationship is first estimated over a sample period covering the past three decades. Although the parameters of the relationship are jointly stable, there are indications of nonlinearity in the residuals of the error-correction model. This nonlinearity is explicitly modeled using a fairly general Markov switching error-correction model with satisfactory results. The empirical findings of the paper are consistent with theoretical predictions of nonlinearities in the dynamics of adjustment to equilibrium stemming from “buffer stock” and “target-threshold” models and with analogous empirical evidence for European countries and the United States.

In this paper we assess the effects of increasing competition in the service sector in one country of the euro area. We focus on Italy, which, based on cross-country comparisons, stands out as the country with the highest markups in nonmanufacturing industries among the OECD countries. We propose a two-region (Italy and the rest of the euro area) dynamic stochastic general equilibrium model where we introduce nontradable goods as a proxy for services and we allow for monopolistic competition in labor, manufacturing, and services markets. We then use the model to simulate the macroeconomic and spillover effects of increasing the degree of competition in the Italian services sector. According to the results, reducing the markups in services to the levels prevailing in the rest of the euro area induces in the long run an increase in Italian GDP equal to 11% and an increase in welfare (measured in terms of steady state consumption equivalents) of about 3.5%. Half of the GDP increase would be realized in the first three years. The spillover effects to the rest of the euro area are limited: consumption, investment, and GDP increases are relatively small.

The U.S. economy has experienced a reduction in volatility since the mid-1980s. In this paper we investigate the changes in the response of the economy to an oil price shock and the role of the systematic monetary policy response in accounting for changes in the response of output, prices, inventories, sales, and the overall decline in volatility. Our results suggest a smaller and more short-lived response of most macro variables during the Volcker-Greenspan period. It also appears that whereas the systematic monetary policy response dampened fluctuations in economic activity during the 1970s, it has had virtually no effect after the “Great Moderation.”

In this paper we investigate whether a standard life-cycle model in which households purchase nondurable consumption and consumer durables and face idiosyncratic income and mortality risk as well as endogenous borrowing constraints can account for two key patterns of consumption and asset holdings over the life cycle. First, consumption expenditures on both durable and nondurable goods are hump-shaped. Second, young households keep very few liquid assets and hold most of their wealth in consumer durables. In our model durables play a dual role: they both provide consumption services and act as collateral for loans. A plausibly parameterized version of the model predicts that the interaction of consumer durables and endogenous borrowing constraints induces durables accumulation early in life and higher consumption of nondurables and accumulation of financial assets later in the life cycle, of an order of magnitude consistent with observed data.

We derive asset-pricing and portfolio-choice implications of a dynamic incomplete-markets model in which consumers are heterogeneous in several respects: labor income, asset wealth, and preferences. In contrast to earlier papers, we insist on at least roughly matching the model's implications for heterogeneity — notably, the equilibrium distributions of income and wealth — with those in U.S. data. This approach seems natural: Models that rely critically on heterogeneity for explaining asset prices are not convincing unless the heterogeneity is quantitatively reasonable. We find that the class of models we consider here is very far from success in explaining the equity premium when parameters are restricted to produce reasonable equilibrium heterogeneity. We express the equity premium as a product of two factors: the standard deviation of the excess return and the market price of risk. The first factor, as expected, is much too low in the model. The size of the market price of risk depends crucially on the constraints on borrowing. If substantial borrowing is allowed, the market price of risk is about one one-hundredth of what it is in the data (and about 15% higher than in the representative-agent model). However, under the most severe borrowing constraints that we consider, the market price of risk is quite close to the observed value.

This paper extends the Diamond-Mortensen-Pissarides (DMP) matching model with endogenous job destruction by introducing postmatch labor turnover costs. We consider training and separation costs that create heterogeneity among workers. In particular, there are two types of employed workers: (i) new entrants who need training in order to become fully productive, and (ii) incumbents who are fully productive and whose departure from the firm imposes costs on it. We find that our calibrated model, relative to the standard DMP model, comes closer to the data regarding the volatility of vacancies and unemployment without introducing unrealistic sensitivity to policy changes. Moreover, our extended model nearly reproduces the downward-sloping Beveridge curve, which is unusual when endogenous job destruction exists in this type of model.

This paper proposes a general method based on a property of zero-sum two-player games to derive robust optimal monetary policy rules—the best rules among those that yield an acceptable performance in a specified range of models—when the true model is unknown and model uncertainty is viewed as uncertainty about parameters of the structural model. The method is applied to characterize robust optimal Taylor rules in a simple forward-looking macroeconomic model that can be derived from first principles. Although it is commonly believed that monetary policy should be less responsive when there is parameter uncertainty, we show that robust optimal Taylor rules prescribe in general a stronger response of the interest rate to fluctuations in inflation and the output gap than is the case in the absence of uncertainty. Thus model uncertainty does not necessarily justify a relatively small response of actual monetary policy.

This paper tests the three leading specifications of asymmetric and possibly nonlinear feedback from the real price of oil to U.S. industrial production and its sectoral components. We show that the evidence for such feedback is sensitive to the estimation period. Support for a nonlinear model is strongest for samples starting before 1973. Instead, using post-1973 data only, the evidence against symmetry becomes considerably weaker. For example, at the aggregate level, there is no evidence against the hypothesis of symmetric responses to oil price innovations of typical magnitude, consistent with results of Kilian and Vigfusson [Quantitative Economics, 2(3), 419–453 (2011)] for U.S. real GDP. There is strong evidence of asymmetries at the disaggregate level, however, especially for industries that are energy-intensive in production (such as chemicals) or that produce goods that are energy-intensive in use (such as transportation equipment). Our analysis suggests that these asymmetries may be obscured in the aggregate data and highlights the importance of developing multisector models of the transmission of oil price shocks.

Recent research has shown the importance of time horizons in models of learning in finance. The dynamics of how agents adjust to believe that the world around them is stationary may be just as crucial in the convergence to a rational expectations equilibrium as getting parameters and model specifications correct in the learning process. This paper explores the process of this evolution in learning and time horizons in a simple agent-based financial market. The results indicate that, although the simple model structure used here replicates usual rational expectations results with long-horizon agents, the route to evolving a population of both long- and short-horizon agents to long horizons alone may be difficult. Furthermore, populations with both short- and long-horizon agents increase return variability, and leave patterns in volatility and trading volume similar to actual financial markets.

We propose the relaxation algorithm as a simple and powerful method for determining the transition process in growth models numerically. This method has a number of important advantages: (1) It can easily deal with a wide range of dynamic systems including stiff differential equations and systems giving rise to a continuum of stationary equilibria. (2) The application of the procedure is fairly user-friendly. The only input required consists of the dynamic system. (3) The variant of the relaxation algorithm we propose exploits in a natural manner the infinite time horizon, which usually underlies optimal control problems in economics. As an illustrative application, we compute the transition process of the models of Jones [Jones, C.I. (1995) R&D-based models of economic growth. Journal of Political Economy 103 (3), 759–784] and Lucas [Lucas, R.E., Jr. (1988) On the mechanics of economic development. Journal of Monetary Economics 22, 3–42].

Public capital subject to congestion is introduced into an endogenous growth model and the transitional dynamic paths under alternative fiscal policies are characterized. Several new insights are obtained from this more general framework. During the transition, the two capital stocks always approach their common equilibrium growth rate from opposite directions. Government policy induces the more volatile response in the capital stock upon which it impinges most directly: private capital in the case of a tax, public capital in the case of expenditure. Finally, we characterize a time-varying income tax that enables the decentralized economy to replicate both the first-best transitional dynamics and steady-state equilibrium of a centrally planned economy. The steady-state component corrects for externalities that arise when government expenditure deviates from its social optimum, and the effects of congestion. The transitional component corrects for myopic behavior by the representative agent along the adjustment path.

This paper examines monetary policy in a two-equation macroeconomic model when the policymaker recognizes that the model is an approximation and is uncertain about the quality of that approximation. It is argued that the minimax approach of robust control provides a general and tractable alternative to the conventional Bayesian decision theoretic approach. Robust control techniques are used to construct robust monetary policies. In most (but not all) cases, these robust policies are more aggressive than the optimal policies absent model uncertainty. The specific robust policies depend strongly on the formulation of model uncertainty used, and we make some suggestions about which formulation is most relevant for monetary policy applications.

This book is an ambitious effort by three well-known and well-respected scholars to fill an acknowledged void in the literature—a text covering the burgeoning field of empirical finance. As the authors note in the preface, there are several excellent books covering financial theory at a level suitable for a Ph.D. class or as a reference for academics and practitioners, but there is little or nothing similar that covers econometric methods and applications. Perhaps the closest existing text is the recent addition to the Wiley Series in Financial and Quantitative Analysis. written by Cuthbertson (1996). The major difference between the books is that Cuthbertson focuses exclusively on asset pricing in the stock, bond, and foreign exchange markets, whereas Campbell, Lo, and MacKinlay (henceforth CLM) consider empirical applications throughout the field of finance, including corporate finance, derivatives markets, and market microstructure. The level of anticipation preceding publication can be partly measured by the fact that at least three reviews (including this one) have appeared since the book arrived. Moreover, in their reviews, both Harvey (1998) and Tiso (1998) comment on the need for such a text, a sentiment that has been echoed by numerous finance academics.

The paper discusses a simple univariate nonlinear parametric time-series model for unemployment rates, focusing on the asymmetry observed in many OECD unemployment series. The model is based on a standard logistic smooth transition autoregressive model for the first difference of unemployment, but it also includes a lagged level term. This model allows for asymmetric behavior by permitting “local” nonstationarity in a globally stable model. Linearity tests are performed for a number of quarterly, seasonally unadjusted, unemployment series from OECD countries, and linearity is rejected for a number of them. For a number of series, nonlinearity found by testing can be modeled satisfactorily by use of our smooth transition autoregressive model. The properties of the estimated models, including persistence of the shocks according to them, are illustrated in various ways and discussed. Possible existence of moving equilibria in series not showing asymmetry is investigated and modeled with another smooth transition autoregressive model.