This article is a reexamination of the clearing and settlement process in financial markets (particularly the futures market) and its performance during the 1987 stock market crash. It provides both some institutional background and some conceptual perspective on the problems faced by the system during the week of October 19. Much of the discussion is based on the useful analogies that can be drawn between the clearinghouse and other financial intermediaries, such as banks and insurance companies. A major conclusion is that the Federal Reserve played a vital role in protecting the integrity of the clearing and settlements system during the crash.

Several recent papers have tested the permanent income-cum-rational expectations hypothesis using data on nondurable or semidurable consumption. We show how this approach can be extended to the case of durables. An application to panel data on automobile expenditures reveals no evidence against the permanent income hypothesis. This result is unchanged in subsamples segregated by family holdings of liquid assets.

Because it concentrates on the co-movements of jointly determined endogenous variables, the traditional analysts of labor productivity does not directly address the question of the causes of productivity change.This problem is solved by a modelling approach in which productivity and other choice variables are assumed to respond optimally to five broad classes of exogenous (causal) shocks.Although these shocks are unobservable to the econometrician, maximum likelihood estimates of their relative importance in the determination of productivity change are obtained.

Credit markets, including the market for bank loans, are characterized by imperfect and asymmetric information. These informational frictions can interact with other economic forces to produce periods of credit-market stress, in which intermediation is unusually costly and households and businesses have difficulty obtaining credit. A high level of credit-market stress, as in a severe financial crisis, may in turn produce a deep and prolonged recession. I present evidence that financial distress and disrupted credit markets were important sources of the Great Depression of the 1930s and the Great Recession of 2007–2009. Changes in the state of credit markets also play a role in “ garden-variety” business cycles and in the transmission of monetary policy to the economy. (JEL D82, E32, E44, E52, G21, N22)

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In recent decades, asset booms and busts have been important factors in macroeconomic fluctuations in both industrial and developing countries. In light of this experience, how, if at all, should central bankers respond to asset price volatility? We have addressed this issue in previous work (Bernanke and Gertler, 1999). The context of our earlier study was the relatively new, but increasingly popular, monetary-policy framework known as inflation-targeting (see e.g., Bernanke and Frederic Mishkin, 1997). In an inflation-targeting framework, publicly announced medium-term inflation targets provide a nominal anchor for monetary policy, while allowing the central bank some flexibility to help stabilize the real economy in the short run. The inflation-targeting approach gives a specific answer to the question of how central bankers should respond to asset prices: Changes in asset prices should affect monetary policy only to the extent that they affect the central bank’s forecast of inflation. To a first approximation, once the predictive content of asset prices for inflation has been accounted for, there should be no additional response of monetary policy to assetprice fluctuations. In use now for about a decade, inflationtargeting has generally performed well in practice. However, so far this approach has not often been stress-tested by large swings in asset prices. Our earlier research employed simulations of a small, calibrated macroeconomic model to examine how an inflation-targeting policy (defined as one in which the central bank’s instrument interest rate responds primarily to changes in expected inflation) might fare in the face of a boom-and-bust cycle in asset prices. We found that an aggressive inflationtargeting policy rule (in our simulations, one in which the coefficient relating the instrument interest rate to expected inflation is 2.0) substantially stabilizes both output and inflation in scenarios in which a bubble in stock prices develops and then collapses, as well as in scenarios in which technology shocks drive stock prices. Intuitively, inflation-targeting central banks automatically accommodate productivity gains that lift stock prices, while offsetting purely speculative increases or decreases in stock values whose primary effects are through aggregate demand. Conditional on a strong policy response to expected inflation, we found little if any additional gains from allowing an independent response of central-bank policy to the level of asset prices. In our view, there are good reasons, outside of our formal model, to worry about attempts by central banks to influence asset prices, including the fact that (as history has shown) the effects of such attempts on market psychology are dangerously unpredictable. Hence, we concluded that inflationtargeting central banks need not respond to asset prices, except insofar as they affect the inflation forecast. In the spirit of recent work on robust control, the exercises in our earlier paper analyzed the performance of policy rules in worst-case † Discussants: Robert Shiller, Yale University; Glenn Rudebusch, Federal Reserve Bank of San Francisco; Kenneth Rogoff, Harvard University.

Can monetary policy committees, accustomed to describing their plans and actions in terms of the level of a short-term nominal interest rate, find effective means of conducting and communicating their policies when that rate is zero or close to zero? The very low levels of interest rates in Japan, Switzerland, and the United States in recent years have stimulated much interesting research on this question and have led some central banks to make changes in their operating procedures and communications strategies. In this paper, we will give a brief overview of current thinking on the conduct of monetary policy when short-term interest rates are very low or even zero. Monetary policy works for the most part by influencing the prices and yields of financial assets, which in turn affect economic decisions and thus the evolution of the economy. When the short-term policy rate is at or near zero, the conventional means of effecting monetary ease (lowering the target for the policy rate) is no longer feasible. However, it would be a mistake to think that monetary policy was impotent. We discuss three strategies for stimulating the economy at an unchanged level of the policy rate: these involve (i) providing assurance to investors that short rates will be kept lower in the future than they currently expect, (ii) changing the relative supplies of securities in the marketplace by altering the composition of the central bank’s balance sheet, and (iii) increasing the size of the central bank’s balance sheet beyond the level needed to set the short-term policy rate at zero (“quantitative easing”). We also discuss the costs and benefits of very low interest rates, an issue that bears on the question of whether the central bank should take the policy rate all the way to zero before undertaking alternative policies.

Structural vector autoregressions (VARs) are widely used to trace out the effect of monetary policy innovations on the economy.However, the sparse information sets typically used in these empirical models lead to at least two potential problems with the results.First, to the extent that central banks and the private sector have information not reflected in the VAR, the measurement of policy innovations is likely to be contaminated.A second problem is that impulse responses can be observed only for the included variables, which generally constitute only a small subset of the variables that the researcher and policymaker care about.In this paper we investigate one potential solution to this limited information problem, which combines the standard structural VAR analysis with recent developments in factor analysis for large data sets.We find that the information that our factor-augmented VAR (FAVAR) methodology exploits is indeed important to properly identify the monetary transmission mechanism.Overall, our results provide a comprehensive and coherent picture of the effect of monetary policy on the economy.