ارزیابی سیاست های پولی را با اطلاعات جنجالی

This study investigates the implications of noisy information regarding the measurement of economic activity for the evaluation of monetary policy. Using a simple model of the U.S. economy, I show that failing to account for the actual level of information noise in the historical data provides a seriously distorted picture of feasible macroeconomic outcomes and produces inefficient policy rules. Naive adoption of policies identified as efficient when this difficulty is ignored results in macroeconomic performance worse than actual experience. When the noise content of the data is properly taken into account, policy reactions are cautious and less sensitive to the apparent imbalances in the unfiltered data. The resulting policy prescriptions reflect the recognition that excessively activist policy can increase rather than decrease economic instability.

Monetary policy decisions are made in real time and are based, by necessity, on preliminary data and estimates that contain considerable noise and are often substantially revised months or years after the event. While part of everyday life for policymakers, this aspect of the monetary policy process is often neglected in theoretical formulations of monetary policy, introducing a wedge between the promise of macroeconomic theory and the reality of macroeconomic practice. Recognition of the complications resulting from the presence of noise is important for the study of monetary policy for two reasons: First, the evaluation of past policy is incorrect when it is based on the wrong data. That is, our understanding of the past becomes distorted. Second, the evaluation of alternative policy strategies is unrealistic and likely to mislead if it is based on the assumption that policy can react to either data that are not really available to policymakers when policy must be set or that are only available with substantial noise. That is, recommendations for better policy in the future become flawed. Failing to recognize the extent of our ignorance leads to the false promise that an activist stabilization policy can have considerable success in fine-tuning the economy. Policy reactions that are unduly influenced by apparent imbalances in the data that may be mere artifacts of faulty measurement, however, risk increasing rather than reducing economic instability. This problem is by no means new to macroeconomic policy. For at least the past fifty years, it has been articulated many times by Milton Friedman, for instance in several of the essays he collected in 1953 and 1969 (Friedman, 1969). As early as 1947, Friedman (1947) questioned the value of control theory for taming business cycle fluctuations by observing: Contemporary interpreters of the course of business have notoriously failed not only to predict the course of business but even to identify the current state of affairs. It is not abnormal for some to assert that we are in the early stages of deflation and others that we are entering into an inflation (1947, p. 414). Rather surprisingly, half a century later and despite considerable advances in the evaluation of monetary policy performance, the quantitative relevance of this issue for monetary policy design has yet to receive proper attention. On one hand, those who believe that our knowledge of the economy is seriously lacking suggest adopting passive rules that generally forego short-run stabilization. On the other, proponents of activist policy implicitly suggest that the information problem does not present a serious handicap.1 This paper attempts to bridge this gap. My analysis draws on recent work that evaluates the performance of monetary policy formulated in terms of reactive interest-rate-based policy rules. Using a simple estimated model of the U.S. economy, I follow recent studies and evaluate alternative policy rules to assess the proper degree of monetary policy responsiveness to fluctuations in inflation and economic activity. However, instead of only performing these evaluations based on the assumption that the policymaker can observe the data promptly and accurately, I perform parallel experiments that recognize that in real time the policymaker observes the data with noise. Using the actual historical data that were available to policymakers in real time I am able to calibrate the degree of data imperfections to exactly match the level of noise faced by policymakers in practice. Comparison of the resulting alternative counterfactual experiments then presents a straightforward quantification of the impact of data noise on monetary policy. The results confirm the common finding obtained in many recent stochastic simulation studies that, in the absence of noise, activist control could substantially improve upon the actual macroeconomic performance of the U.S. economy. However, I show that this improvement is illusory: It provides a seriously distorted picture of feasible outcomes that would occur once the noise in the data is taken into account. The resulting outcomes that would obtain had the supposedly optimal policies been adopted are in fact worse than the actual performance of the U.S. economy over the 1980s and early 1990s. The presence of noise acts as a counterweight to the highly responsive policy that would otherwise be appropriate to adopt. Recognition of the false promise of activist policies when the state of the economy cannot be confidently ascertained by the data leads to policy that tends to downplay the apparent short run fluctuations in the economy. Even considering the limitations of the information available to policymakers in real time, however, my results suggest that there may be some room for short-run stabilization policy. In this sense, the suggested strategy for monetary policy is neither at the extreme of total passivity nor at the alternative of reckless activism. Paradoxically, by demonstrating that actual monetary policy since 1980 has not been activist enough to live up to the “promise” of stabilization policies that appear optimal when the information limitations are ignored, my analysis suggests that policy over the past two decades may have actually exhibited a balance which may also explain its success. Indeed, recognition of the limitations facing policymakers in practice significantly enhances our understanding of forces that may have shaped policy over this period. The results provide an explanation both for the aversion of policy to commit to any specific reactive policy rule, as well as for the apparent caution characterizing monetary policy in practice. As Blinder (1998) noted explaining the policy process during his tenure as Vice-Chairman at the Federal Reserve, “a little stodginess at the central bank is entirely appropriate”. I show that data noise induces such stodginess. Further, since the degree of uncertainty regarding the reliability of incoming information continuously changes with the evolution of the economic environment, the apparent degree of caution in policy decisions changes in tandem. The result, as Chairman Greenspan (1997) pointed out, is that “some element of discretion appears to be an unavoidable aspect of policymaking,” and policy will appear eclectic, even though the Federal Reserve “has sought to exploit past patterns and regularities in a systematic way.” In the end, “policymakers shy away from rule-based decisions because the rules assume that they know too much”, as Kohn (1999, p. 197) observed.

Unless the practical limitations facing monetary policy are properly acknowledged, policy evaluations will always suggest that activist monetary policy can improve macroeconomic performance. Such gains may be illusory. As I show within the context of interest-rate-based monetary policy rules, while short-run economic stabilization gains from pursuing activist policies may appear substantial, these gains all but disappear once the informational limitations facing policymakers are taken into consideration. Indeed, a cautious response to apparent imbalances in the data is appropriate. A prudent policymaker should recognize that much of the information at his disposal is fraught with noise, and avoid overreaction. This caution is especially relevant when considering apparent deviations of aggregate demand from the economy's potential. Though well intentioned, naive policy that downplays such informational problems may become a source of instability. The main objective of this analysis is to serve as a reminder and provide some concrete evidence for some old wisdoms regarding monetary policy. As Modigliani (1977) pointed out, the recognition that inappropriately activist monetary policy can be destabilizing “has had a salutary effect on reassessing what stabilization policies can and should do, and on trimming down fine-tuning ambitions” (p. 17). For as Friedman (1968) observed: “The first and most important lesson that history teaches about what monetary policy can do—and it is a lesson of the most profound importance—is that monetary policy can prevent money itself from being a major source of economic disturbance.” (p. 12).