We study how discount window policy affects the frequency of banking crises, the level of investment, and the scope for indeterminacy of equilibrium. Previous work has shown that providing costless liquidity through a discount window has mixed effects in terms of these criteria: It prevents episodes of high liquidity demand from causing crises but can lead to indeterminacy of stationary equilibrium and to inefficiently low levels of investment. We show how offering discount window loans at an above-market interest rate can be unambiguously beneficial. Such a policy generates a unique stationary equilibrium. Banking crises occur with positive probability in this equilibrium and the level of investment is suboptimal, but a proper combination of discount window and monetary policies can make the welfare effects of these inefficiencies arbitrarily small. The near-optimal policies can be viewed as approximately implementing the Friedman rule.

We develop a growth model with unemployment due to imperfections in the labor market. In this model, wage inertia and balanced budget rules cause a complementarity between capital and employment capable of explaining the existence of multiple equilibrium paths. Hysteresis is viewed as the result of a selection between these different paths. We use this model to arguea that, in contrast to the United States, those fiscal policies followed by most of the European countries after the shocks of the 1970s may have played a central role in generating hysteresis.

In this paper we empirically examine the sources of the volatility of the foreign exchange risk premia. Using a nonlinear structural Vector Autoregression (VAR) model based on no-arbitrage condition to identify various macroeconomic shocks and the foreign exchange risk premia, we find that more than 80% of the volatilities of the currency risk premia can be accounted for by the standard macroeconomic shocks that drive output and inflation. By explicitly modelling the currency risk premia in the VAR system, we also offer a potential reconciliation for the seemingly contradicting observations from the previous VAR analysis of the exchange rate “overshooting” behavior under exogenous monetary innovations.

This paper deals with macroeconomic aspects of widespread substance abuse with a reference to illicit drugs as an example. Substance abuse impedes the productivity of the labor force and reduces economic growth. Workers are either nonusers and therefore fully productive, a number of whom are employed by the government in drug-control activities, or users who are only partially productive. Efficient management of the nation's portfolio of workers involves eradicating drug use when initial user numbers are lower than a critical level, but allows user numbers to rise to, and be accommodated at, a stationary level when initial user numbers exceed a critical level.

We use Markov chain Monte Carlo methods to augment, via a novel multimove sampling scheme, a vector autoregressive (VAR) system with a latent business-cycle index that is negative during recessions and positive during expansions. We then sample counterfactual values of the macroeconomic variables in the case where the latent business-cycle index is held constant. These counterfactual values represent posterior beliefs about how the economy would have evolved absent business-cycle fluctuations. One advantage is that a VAR framework provides model-consistent counterfactual values in the same way that VARs provide model-consistent forecasts, so data series are not filtered in isolation from each other. We apply these methods to estimate the business-cycle components of industrial production, consumer price inflation, the federal funds rate, and the spread between long-term and short-term interest rates. These decompositions provide an explicitly counterfactual approach to isolating the effects of the business cycle and to deriving empirical business-cycle facts.

There is now a substantial theoretical literature arguing that inflation impedes financial deepening. Furthermore, it has been hypothesized that the relationship is a nonlinear one, in that there is a threshold level of inflation below which inflation has a positive effect on financial depth, but above which the effect turns negative. Using a large cross-country sample, empirical support is found for the existence of such a threshold. The estimates indicate that the threshold level of inflation is generally about 3–6 percent per annum, depending on the specific measure of financial depth that is utilized.

The article compares the social efficiency of monetary targeting and inflation targeting when central banks may have private information on shocks to money demand and the transparency solution is not feasible because of verifiability problems. Under inflation targeting and monetary targeting, central banks may have an incentive to signal their private information in order to influence the public's expectations about future inflation. We show that inflation targeting is superior to monetary targeting, as it makes it easier for central banks to commit to low inflation. Moreover, central banks that are weak on inflation prefer inflation targeting to monetary targeting.

This paper examines an agent's choice of forecast method within a standard asset pricing model. A representative agent may choose: (1) a fundamentals-based forecast that employs knowledge of the dividend process, (2) a constant forecast that is based on a simple long-run average, or (3) a time-varying forecast that extrapolates from the last observation. I show that an agent who is concerned about minimizing forecast errors may inadvertently become “locked-in” to an extrapolative forecast. In particular, the initial use of extrapolation alters the law of motion of the forecast variable so that the agent perceives no accuracy gain from switching to one of the alternative forecast methods. The model can generate excess volatility of stock prices, time-varying volatility of returns, long-horizon predictability of returns, bubbles driven by optimism about the future, and sharp downward movements in stock prices that resemble market crashes.

An overlooked topic is the treatment of worker claims when firms are shutting down. In fact, when firms close, worker claims such as severance pay often go unfulfilled. To evaluate the quantitative importance of this observation, this paper develops a general equilibrium model with close attention to the exit margin, and examines how macroeconomic outcomes vary with the treatment of firing costs on exit. In the model, the impact of firing costs on employment weakens by a third when closing plants do not have to pay them, even though closure accounts for considerably less than one-third of total job destruction. Thus, the distribution of firm characteristics is a new channel for labor market rigidities to affect aggregates. The model also accounts for cross-country differences in the relationship between the structure of job flows and firm turnover.

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.

The paper employs an extended Yaari-Blanchard model of overlapping generations to study how the macroeconomy is affected over time by various demographic changes. It is shown that a proportional decline in fertility and death rates has qualitatively similar effects to capital income subsidies; both per capita savings and per capita consumption increase in the new steady state. A drop in the birth rate, although keeping the death rate constant, reduces per capita savings, but increases per capita consumption if the generational turnover effect is dominated by the intertemporal labor supply effect. If the generational turnover effect is sufficiently strong, however, a decline in the birth rate may, contrary to standard results, give rise to an increase in per capita savings. Finally, a fertility rate reduction that leaves unaffected the rate of generational turnover is shown to have effects qualitatively similar to those of a fall in public consumption. Both per capita savings and per capita output decline, but per capita private consumption rises.

In the modern world, the main assets are immaterial ideas. Such assets are much more easily stolen than traditional factors such as physical capital and land. In this paper, we investigate the long-run growth effects of intellectual misappropriation at the R&D level. We adopt a generalized framework with both vertical and horizontal innovation. Inspired by recent evidence and by the patent law, we assume that only vertical innovations can be spied, because they are less easily patented than horizontal innovations. The main results are: (1) despite growing population, the fraction of labor engaged in spying activities tends to be constant; (2) in economies in which the R&D process is more vulnerable to ideas theft, growth rates are lower but product differentiation will be more intense; (3) intellectual misappropriation neutralizes the positive growth effect of R&D subsidies but not their positive level effects.

In this paper we investigate the effects of herding on asset price dynamics during continuous trading. We focus on the role of interaction among traders, and we investigate the dynamics emerging when we allow for a tendency to mimic the actions of other investors, that is, to engage in herd behavior. The model, built as a mean field in a binary setting (buy/sell decisions of a risky asset), is expressed by a three-dimensional discrete dynamical system describing the evolution of the asset price, its expected price, and its excess demand. We show that such dynamical system can be reduced to a unidirectionally coupled system. In line with the rational herd behavior literature [Bikhchandani, S., Sharma, S. (2000), Herd Behavior in Financial Markets: A Review. Working paper, IMF, WP/00/48], situations of multistability are observed, characterized by strong path dependence; that is, the dynamics of the system are strongly influenced by historical accidents. We describe the different kinds of dynamic behavior observed, and we characterize the bifurcations that mark the transitions between qualitatively different time evolutions. Some situations give rise to high sensitivity with respect to small changes of the parameters and/or initial conditions, including the possibility of invest or reject cascades (i.e., sudden uncontrolled increases or crashes of the prices).

This paper studies asset returns adopting an alternative strategy to assess a model's goodness of fit. Based on spectral analysis, this approach considers a model as an approximation to the process generating the observed data, and characterizes the dimensions for which the model provides a good approximation and those for which it does not. Our aim is to offer new evidence regarding the size and the location of approximation errors of a set of stochastic growth models considered to be decisive steps in the progress of the asset pricing research program. Our specific objective is to reevaluate the results of Jermann's (1998) model extending the calculations to the spectral domain. Spectral results are relatively satisfactory: the benchmark model needs very few contributions of approximation errors to account for the empirical equity premium. Second, the location of the approximation errors, when they are substantial, seems to be essentially concentrated at high frequencies.

This research develops a theory about the role of within-country income inequality in the emergence of overtaking in economic performance among countries. The theory captures two opposing effects of inequality on factor accumulation and suggests that the qualitative change in their combined effect is a prime cause of overtaking. Because of the initial dominance of the positive effect of inequality, a less egalitarian economy follows a higher growth path in the short run, with a lower growth path in the long run. It also is shown that divergence or convergence may arise instead of overtaking, depending on the initial levels of development and inequality.

Progress in stochastic macroeconomic modeling justifies revisiting Milton Friedman's program on the relation between macroeconomic stability and active stabilization policies. In the lecture, we use a standard new Keynesian model but depart from rational expectations by assuming that agents behave in line with adaptive learning, which increase the potential for instability in the economy.

Optimal policy under adaptive learning displays some similarity with optimal policy under commitment in the rational expectations setting. Specifically, we find that optimal policy responds in a persistent manner when expectations threaten to become unhinged. Finally, we illustrate the dynamics associated with the change from a simple regime that ignores the expectation formation, to the optimal policy that does. The results are not unlike the behavior of the U.S. economy around the Volcker transition (October 1979).

This paper investigates the quantitative importance of different savings motives on the distributions of wealth and consumption and aggregate capital accumulation by solving an overlapping generations model with intragenerational heterogeneity. Agents differ in age, ability, earnings shocks, and inherited bequests. In the baseline economy, there are uninsurable idiosyncratic risks associated with uncertain lifetime and earnings shocks. The model is calibrated to the U.S. economy and solved numerically. Then the allocations of the baseline economy are compared with those of an economy with complete annuity markets, one without earnings uncertainty, and one without altruism.

This paper is concerned with the empirical relevance of indeterminacy and sunspots in explaining the business cycle. It argues that financial constraints provide a propagation mechanism able to generate business cycle facts observed in data in response to sunspot shocks. This point is demonstrated using an equilibrium business cycle model featuring heterogeneous households, endogenous labor supply and liquidity constraints. We first show that the model exhibits indeterminacy for roughly constant returns to scale. We then establish that our model accounts for stylized facts that neither the standard RBC model nor previous sunspots models have been able to capture. More specifically, the model driven purely by sunspots matches the procyclical movements in aggregate consumption, and the positively correlated forecastable changes of basic macroeconomic variables.

This paper uses recent advances in financial econometrics to test the Friedman hypothesis that money supply volatility Granger-causes velocity. Comparisons are made among simple-sum and Divisia velocity series at the M1 and M2 levels of monetary aggregation, using quarterly data from 1959:1 to 2004:3. The conclusion is that the Friedman hypothesis cannot be rejected if money supply volatility is modeled explicitly, using models that capture important volatility effects that previous work has ignored.

We investigate the economic importance of modeling nonlinearities in the dynamics of exogenous processes on the implied moments of endogenous variables in the context of the consumption-based asset pricing model. For this purpose, we model the endowment process alternatively as a linear autoregression and as a nonlinear threshold autoregression. The asset pricing model with nonlinear endowment is solved using quadrature techniques. A comparison of the moments of the model-implied rates of return in the two cases suggests that the economic impact of modeling nonlinearities is small.