دانلود مقاله ISI انگلیسی شماره 25638
عنوان فارسی مقاله

عدم اطمینان داده و نقش پول به عنوان یک متغیر اطلاعات برای سیاست های پولی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
25638 2005 32 صفحه PDF سفارش دهید محاسبه نشده
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عنوان انگلیسی
Data uncertainty and the role of money as an information variable for monetary policy
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : European Economic Review, Volume 49, Issue 4, May 2005, Pages 975–1006

کلمات کلیدی
    منطقه یورو -      فیلتر کالمن -      مدل سازی اقتصاد کلان -      خطای اندازه گیری -      قوانین سیاست های پولی -      انتظارات عقلایی -
پیش نمایش مقاله
پیش نمایش مقاله عدم اطمینان داده و نقش پول به عنوان یک متغیر اطلاعات برای سیاست های پولی

چکیده انگلیسی

In this study, we perform a quantitative assessment of the role of money as an indicator variable for monetary policy in the euro area. We document the magnitude of revisions to euro area-wide data on output, prices, and money, and find that monetary aggregates have a potentially significant role in providing information about current real output. We then proceed to analyze the information content of money in a forward-looking model in which monetary policy is optimally determined subject to incomplete information about the true state of the economy. We show that monetary aggregates may have substantial information content in an environment with high variability of output measurement errors, low variability of money demand shocks, and a strong contemporaneous linkage between money demand and real output. As a practical matter, however, we conclude that money has fairly limited information content as an indicator of contemporaneous aggregate demand in the euro area.

مقدمه انگلیسی

Many macroeconomic time series are subject to substantial revisions, and hence such data only provide imperfect information about the true state of the economy at a given point in time. In light of these data limitations monetary policymakers and researchers alike have long been interested in identifying indicator variables that provide precise and timely information. At least since the early 1970s, research on the information content of alternative indicators has highlighted the potential usefulness of monetary aggregates; these evaluations have typically been conducted in reduced-form models and models with adaptive expectations.1 More recently, research on Taylor-style interest rate rules has re-emphasized the importance of “real-time” data uncertainty for the design of monetary policy albeit without considering money's potential role as an information variable.2 In this study, we perform a quantitative assessment of the role of money as an indicator variable for monetary policy in the euro area. We begin by analyzing the sequence of revisions to euro area-wide data, and find that measures of real output have been subject to substantial revisions over a period of up to nine months, whereas measures of prices and money have generally been subject to relatively minor revisions that occur within a short period of the initial data release. Given this pattern of euro area data revisions, monetary aggregates have a potentially significant role in providing information about the current level of aggregate demand and hence about incipient pressures on the inflation rate. We then proceed to analyze the information content of money in a forward-looking model in which money has no causal role in influencing output or inflation.3 In particular, our analysis builds on the estimated rational expectations model of the euro area developed by Coenen and Wieland (2000); we augment this model with a calibrated specification for the output revision process, and with the estimated M3 demand equation of Coenen and Vega (2001), which was found to provide a remarkably stable representation of euro area money demand. We assume that the central bank optimally sets the short-term nominal interest rate to minimize a weighted average of inflation volatility and output gap volatility, subject to a small penalty on nominal interest rate movements. We further assume that the central bank and private agents share the same information set and utilize the Kalman filter to make optimal inferences about the true state of the economy (cf. Pearlman et al., 1986; Svensson and Woodford, 2000).4,5 Money can serve as a potentially useful indicator variable in our framework, because we assume that aggregate money demand depends on the true level of aggregate output, whereas the central bank and private agents only receive a noisy measure of aggregate output. The rationale behind this assumption is that individual agents’ demand for real balances depends on the true level of their individual incomes and the sum of these demands ought to be related to the aggregated actual income. On the other hand, money demand also fluctuates in response to unobserved velocity disturbances that attenuate the strength of its linkage to aggregate demand. Thus, the information content of money depends on the relative variances of output mismeasurements and money demand shocks, and on the strength of the contemporaneous linkage between money demand and real output. We assess the value of this information in terms of the improvement in the policymaker's loss function and in terms of several statistical measures used in the earlier literature, namely, the root mean-squared prediction error (RMSE), the coefficient of determination (R2), and the entropy of the system. Finally, since money has no causal role in the model, one may view our results as providing a reasonable lower bound on the extent to which money provides information about contemporaneous real output. While the information value of money could also be analyzed in an atheoretical forecasting model,6 such a model would not allow us to separate the potential roles of money for monetary policy and consider exclusively the information role motivated by data uncertainty. In the structural model we can exclude the possibility of a direct causal role of money due to real-balance effects or a direct effect on inflation. Furthermore, the structural model distinguishes dynamics due to expectations from those due to policy or adjustment dynamics due to lags of endogenous variables. Finally, it allows us to derive optimal monetary policy and evaluate the information gains in terms of the central bank's loss function. Our framework demonstrates that monetary aggregates may have substantial information content in an environment with high variability of output mismeasurements, low variability of money demand shocks, and a strong contemporaneous link between money and output. As a practical matter, however, we find that money has fairly limited information content as an indicator of current aggregate demand in the euro area, mainly because the contemporaneous link between M3 and real output is relatively weak. Of course, these results do not rule out other motivations for careful monitoring of monetary aggregates. For example, the prominent role for money in the ECB's monetary policy strategy that is signalled by the announcement of a reference value for the growth rate of M3 is motivated by the usefulness of money as an indicator of potential risks to the medium-term inflation outlook.7 Thus, its role under the first pillar of the ECB's strategy is quite different from the potential information value regarding uncertain current output explored in this paper. Finally, it should be emphasized that our analysis focuses solely on uncertainty regarding actual output, and does not address the problem of estimating potential output. While uncertainty about potential output has important consequences for the determination of monetary policy, we neglect this issue here because the money stock is related to actual output via money demand and thus cannot serve as a direct source of information regarding potential output.8 The remainder of this paper is organized as follows. Section 2 characterizes the timing and magnitude of revisions to euro area data on aggregate output, prices, and money. Section 3 outlines the behavioral equations of the model, and indicates alternative representations of the output revision process. Section 4 describes our methodology for determining the optimal filtering weights and for evaluating the information content of indicator variables. Section 5 considers the model without money in order to quantify the magnitude of the information problem associated with real-time output mismeasurement. Section 6 adds a highly stylized money demand equation to the model, facilitating a systematic analysis of how the information content of money is affected by the relative variability of output measurement errors and money demand shocks. In light of these findings, Section 7 uses the complete model described above to evaluate the quantitative significance of money as an indicator variable for monetary policy in the euro area. Finally, Section 8 summarizes our conclusions and suggests several directions for future research.

نتیجه گیری انگلیسی

To explore the information role of money in the presence of data uncertainty we have extended the euro area macroeconomic model of Coenen and Wieland (2000) by incorporating the euro area-wide money demand model of Coenen and Vega (2001) and an empirically calibrated model of the revision process of aggregate euro area output. Using this framework we have found that money can play an important role as an information variable and may result in major improvements in current output estimates. However, the specific nature of this role depends on the magnitude of the output measurement error relative to the money demand shock. In particular, we have found noticeable but small improvements in output estimates due to the inclusion of money growth in the information set when the standard deviation of money demand shocks equals the estimated value from Coenen and Vega (2001). Sensitivity analyses indicate that money plays a quantitatively more important role with regard to output estimation if the central bank assigns a high weight to output stabilization, if current output is completely unobserved, or if the direct contemporaneous link between output and money growth strengthens. Of course, as the construction of euro area aggregate output data is improved over time, the magnitude of the revisions discussed in Section 2 is likely to decline. Nevertheless, evidence concerning U.S. data vintages collected by Croushore and Stark (1999) indicates that data uncertainty will remain an important issue even once the data collection technology has matured. Throughout the paper we consider a relatively limited role of money by focusing exclusively on the information content of money with respect to output measurement and by excluding the possibility of a direct role of money in output and inflation determination. In this sense, our quantitative results only indicate a lower bound on the usefulness of money. An alternative model that allows for significant direct effects of money on inflation and could be used in future research is the so-called model. Also, as noted earlier, we have focused attention on a framework with symmetric information regarding aggregate output data as far as private market participants and the central bank are concerned. We have also conducted some exploratory analysis under the assumption of asymmetric information regarding aggregate data that is used by Dotsey and Hornstein (2000), Svensson and Woodford (2001) and Aoki (2003). However, in our view this assumption is undesirable if it implies that a representative agent by knowing his individual income can also infer aggregate income and demand while the policymaker only observes a noisy estimate of aggregate demand. We plan to study the asymmetric case in more detail in the future in a model that would allow us to differentiate more carefully between individual and aggregate uncertainty. Finally, another interesting avenue for future research would be to compare optimal filtering to simple filtering rules in keeping with the recent debate on optimal versus simple monetary policy rules. For example, one could investigate the performance of simple rules that respond only to observed output growth, inflation and money growth instead of optimal estimates of the output gap. A recent study that considers an example of a simple filtering rule in the context of NAIRU uncertainty is Meyer et al. (2001).

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