Monetary Policy, Investor Sentiment and Stock Price Bubble: Evidence From China

Previous articleNext article FreeCommentHarald Uhlig, Harald UhligUniversity of Chicago Search for more articles by this author , University of ChicagoFull TextPDF Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreThe paper by Boivin, Giannoni, and Mojon seeks to understand the transmission mechanism of monetary policy in the euro area and its constituent countries, document its change since the creation of the euro, and provide a structural interpretation by means of an open‐economy model. To do so, it is building on state‐of‐the‐art modeling techniques, most notably Bernanke, Boivin, and Eliasz’s (2005) factor‐augmented vector autoregressive (FAVAR) approach for the empirical part and Ferrero, Gertler, and Svensson’s (forthcoming) open‐economy dynamic stochastic general equilibrium (DSGE) model for the structural interpretation. The authors combine both with several innovations, well described in the paper, most notably adding a risk premium on intra‐area exchange rates. They report estimated responses to monetary policy largely consistent with conventional wisdom. They document that the creation of the euro has contributed to a widespread reduction in the effect of monetary policy shocks. They interpret this as stemming not only from the adoption of a single currency but also from European Central Bank policy, shifting toward a more aggressive response to inflation and output.Boivin et al.’s paper exemplifies the best of research that is currently done at central banks as well as in a number of academic departments, seeking to understand aggregate fluctuations and the role of monetary policy from both an empirical and a theoretical perspective. These approaches have started to replace the educated guesses with a serious analysis based on state‐of‐the‐art modeling as the starting point for policy debates. That, in principle, is a good development.Therefore, I hope that the approach taken here is right. But I fear that severe problems remain and that the route taken here is not yet convincing enough for others to follow. Below I shall explain why, including material found subsequently to my presentation in Boston. Much of what is stated here may apply with equal force to the predecessors on which the paper at hand is built, and that may seem like a good defense for the authors. But this is their paper in the end, and it is their choice which methodology to apply. Therefore, it is only fair to raise these points here.I need to warn the reader that this is a discussion. My aim shall be to throw up some challenges and questions and to provoke further thinking on some of these issues. Whether these are fatal flaws or whether all this can be repaired or whether everything is all right after all is something that future research urgently needs to clarify before this approach should be put to wider use. With this disclaimer, let me get in medias res.I. The FAVAR ModelThere are three basic premises of the empirical approach. First, there is considerable comovement in the selected macroeconomic time series so that their most relevant dynamics is captured by a few factors. Second, the strategy here correctly captures the dynamics associated with monetary policy shocks and correctly identifies their effects. Third, the data are sufficiently informative about the changing impact of monetary policy after the introduction of the euro. I am skeptical about all three.II. Is There Comovement in European Data?The idea that macroeconomic variables comove has considerable appeal in the United States, but perhaps less so in Europe, with its diverse set of countries. Nonetheless, the $$R^{2}$$’s reported by Boivin et al. in their table 1 seem impressive and convincing.But I was still skeptical. If indeed a few factors explain most of what is going on, then the sum of the few largest eigenvalues of the variance‐covariance matrix of the data should be near the entire sum of all eigenvalues: that ratio is essentially the $$R^{2}$$’s of all variables on the factors corresponding to these eigenvalues. In fact, one would want more: one would want that sum to be considerably larger than in an artificial data set, generated with the same univariate autocovariance structure as in the data, but no comovement among the artificially generated series.So, I did the following (and I am grateful to the authors for sharing their data set with me to do this). I transformed the data from 1987:Q1 to 2007:Q3 by taking the difference of the log of the current value and its fourth lag and multiplying by 100, except for interest rates, unemployment rates, and capacity utilization: that way, all data are in percents. This appears to be the transformation chosen by the authors. I call this my baseline data set. I calculated eigenvalues in three ways. First, I took the eigenvalues of the variance‐covariance matrix of the baseline data set, summing the largest and calculating the ratio of those partial sums to the total sum. Next, I took the residuals from a regression of the data on current oil and short‐term interest rates, that is, series 1 and 243, and a constant and calculated the eigenvalues from the variance‐covariance matrix of these residuals (and, as an aside, that seemed to me to be a simpler approach than what the authors have done). Finally, I rescaled all time series to have the same standard deviations before calculating the regression and the eigenvalues of the residuals: from discussions with the authors, it may be that this is closest to the route they have chosen. The results can be seen in figure 1, which lists the number of factors (or largest eigenvalues) on the x axis and the fraction of the total sum of eigenvalues on the y axis. For the x axis I stopped at 30 factors, although there would be 243 (or 83) in principle. One can see that 11 factors in the nonrescaled version explain about 90%, seven factors get you to about 80% (coinciding roughly with the individual series results in table 1 of the authors), and five factors (think: above and beyond short‐term rates and oil) explain about 75%. This initially looks like good news for the approach taken by the authors.Fig. 1. Calculated factors and their contribution to overall variance. Three methods of calculating eigenvalues. Authors’ original data. This appears to look good.View Large ImageDownload PowerPointNext, I calculated the first‐order autocorrelations of my baseline data set. I then generated an artificial data set as a set of independent AR(1) processes, driven by normally distributed shocks and with the calculated autocorrelations, starting at zero (rather than a draw from the stationary distribution) and rescaled, so that each artificial series has the same standard deviation as the corresponding series in the data. I redid the exact same calculation of the contribution of the factors as above, using the new artificial data series 1 and 243 as regressors: while they have the same autocorrelation as the original data series, there is obviously no reason to expect them to have any explanatory power for the other series. In fact, in the artificial data set, there is no genuine comovement among the series at all.The result for the artificial data set can be seen in figure 2. I would have expected that figure to be quite different from figure 1 and the factors with the largest eigenvalues to explain considerably less than in the original data set. But the figures look surprisingly and uncomfortably alike. When I first saw a first version of this figure, I thought that it had to be due to a programming error, accidentally storing the figure coming from the data. But it is really the figure coming from the random data. Yes, there are differences. One factor explains as much now, for either of the three methods. It takes a few more factors to get to the same fraction of variance explained. At five factors for the residual, one is at about 60% rather than 75%. Seven factors deliver about 70% for the baseline random data rather than 80% in the original baseline data. And 12 factors are at 85% rather than 90%. For the residuals from the scaled data, the differences are even somewhat bigger. New random draws will generate slightly different pictures anyhow. “Slightly” is important here. The differences from figure 1, while there, remain strikingly small.Fig. 2. Like fig. 1 but applied to artificial data: independent AR(1)’s, with autoregressive coefficients distributed as in the original data. This figure is not much different from fig. 1, even though there are no “true” factors in the artificial data. Thus perhaps in the original data, too, the true factors may account for much less comovement in the original data than fig. 1 or the authors’ calculations would lead one to believe.View Large ImageDownload PowerPointThe reason is easy to explain but perhaps tricky to formalize. There is considerable autocorrelation in the data. Figure 3 shows the autocorrelation coefficients, calculated by ordinary least squares and sorted by size: many are close to unity. With persistent roots, deviations from the mean will linger for many periods. Thus, the calculated correlation of two series with persistent roots may easily appear to be large in a finite sample, even though there is none asymptotically. The factors extracted from a finite sample interpret these large correlations as comovements, even though there is none. It all works nicely asymptotically; it just does not work in the short sample at hand and with the large autocorrelations that are in the data. There may be ways around this problem, for example, by prewhitening the series or, at the least, by calculating the factors from the residuals of univariate AR(1) regressions. But this is not what the authors appear to have done.Fig. 3. Distribution of the AR(1) coefficients in the original data, when fitting univariate AR(1)’s to each series. The artificial data for fig. 2 were created as independent AR(1)’s, with the same distribution of AR(1) coefficients.View Large ImageDownload PowerPointSo in sum, I fear that the approach taken and the evidence presented by the authors are quite consistent with a world in which there is no comovement among the series at all, and they are probably perfectly consistent with a world in which only very few factors matter at the European scale, but explaining considerably less than what the authors make us believe. And without such comovement or too little variation explained by too few factors, the approach has severe problems.III. Are Monetary Policy Shocks Identified and Identified Correctly?But let me give Boivin et al. the benefit of the doubt and hope that my arguments or calculations turn out to be somehow incorrect or not appropriate. That is, suppose that the authors did indeed capture the key comovements and 80% of the variance in the data with their seven factors, including interest rates and oil, even if the sample was truly large. Did they correctly identify monetary policy shocks? I have my doubts.For starters, it may be that all the movements due to monetary policy shocks have dropped from the sample, once one concentrates on the movement explained by the factors. Cochrane (1994) and many others have argued that monetary policy shocks explain no more than 20% of the movement in the data. It could be that much or even all of that is in the 20% not explained by the leading factors. It is easy to see how this can happen when extracting factors in an unrestricted manner. The authors smartly include the key monetary policy instrument in their factors, but even then, it could happen if the majority of the interest rate movements are not due to monetary policy shocks and if other parts of the movement in interest rates get captured by the seven‐factor dynamics and across‐variable correlation.To be more specific, it is worrisome that the fractions explained for M1 and M3 by the factors are among the lowest of all the series (see table 1). We used to think that moving money or moving interest rates is just as good a tool for a central bank to pick a particular point on the demand curve for money. But table 1 would have to be read as if that demand curve is subject to huge and idiosyncratic fluctuations having nothing to do with the rest of the economy. To put it differently, according to these estimates, money has little or nothing to do with monetary policy and the main movements in aggregate activity, but rather has a life on its own. If you believe this, you have an interesting research agenda at hand.But even leaving these arguments aside, I seriously wonder whether the approach to identify monetary policy shocks is reasonable. Section IV. A states that it is assumed that “the latent factors … and the oil price inflation … cannot respond contemporaneously to a surprise interest rate change.” The argument for this approach is in Bernanke et al. (2005), in which the authors argue that the movement in the factors is movement due to “slow‐moving” variables, since any additional systemic movement in the “fast‐moving” variables is one‐dimensional; they interpret this as being largely explained by the surprise in interest rate movements. But there are no such things as slow‐moving variables. After all, all variables have a nonzero one‐step‐ahead prediction error: they thus move fast with respect to something. The identifying assumption here really is that whatever it is they are reacting to contemporaneously and quickly, it cannot be monetary policy. Why should that be the case? If inflation and employment can suddenly jump a bit because of shifts in market demands, why can they not do so when monetary policy surprisingly changes interest rates?The defense seems to be that the impulse responses look conventional. But they don’t. As figure 1c in Boivin et al.’s paper shows, consumer price index inflation in Germany, France, Italy, and the euro area as a whole tends to move up rather than down after a monetary tightening, and wage inflation moves up in Germany, Italy, and Spain. Additionally, these responses are estimated with a fairly wide error band. The reaction seems to be somewhere between −0.3% and 0.3% in the year following the shock. By contrast, the reaction of GDP is fairly sharp and always down, ranging from −1% or below to about −0.2% in the year following the shock. That seems large compared to the (non)movement in inflation.A more convincing approach to identification is to employ the conventional wisdom and therefore sign restrictions for identification, as I have proposed in Uhlig (2005). With a panel of macroeconomic time series and a factor approach, as in the paper at hand, there are considerably more sign restrictions that can aid in identification, and the methodology then provides for considerably sharper bounds as well as reasonable results (see Ahmadi and Uhlig 2008).IV. Are the Data Informative about the Change after the Introduction of the Euro?I do not need to answer that question. Boivin et al. themselves provide ample warning in their paper that this is not so. Note in particular that no error bands have been provided to the post‐euro responses in figures 1a–c or the comparison pictures. Be wary of econometricians who draw conclusions by comparing means without telling you the degree of uncertainty! It is a fair guess that it is large. There simply was not much time‐series variation in monetary policy since the introduction of the euro. Figure 4 shows what is going on: large and heterogeneous movements in interest rates before the introduction of the euro. Hardly any movements afterward.Fig. 4. Short‐term interest rates in the EMU, authors’ data: euro area, Germany, France, Italy, Spain, Netherlands, and Belgium.View Large ImageDownload PowerPointThe authors are probably happy that the impulse responses did not change too dramatically for several key variables. Unfortunately, there are some in which the responses did change, leading us even further away from conventional wisdom. Consumption moves up after a monetary tightening. M3 moves up substantially now after a monetary tightening, quite in contrast to what happened before the euro.One explanation within the philosophy of the authors is that post‐euro monetary policy shocks identified here are really capturing movements in the stock market. For suppose that there are practically no monetary policy shocks and that monetary policy is instead also reacting to movements in some other fast‐moving variable, such as the stock market. Suppose an econometrician knew that and wanted to identify stock market surprise movements above and beyond those of slow‐moving variables. That econometrician would have proceeded exactly as the authors did, except that the impulse responses now would have to be interpreted as responses to stock market shocks rather than monetary policy shocks. How can one tell them apart? Again, sign restrictions might help.V. The Structural ModelThe paper complements the empirical analysis with a structural model that allows one to interpret the data from that vantage point. The key difficulty for this model is to explain the interest rate convergence in figure 4, happening without correspondingly large inflation differences. The authors readily admit this problem in Section V.C.1, when they write that “the basic version of the model cannot replicate the transmission of monetary policy observed in low‐credibility regimes since long‐term rates are tightly tied to expected future riskless short‐term rates.” One possibility would be to scrap the model at this point.The authors instead invent a clever deus ex machina: shocks to the uncovered interest rate parity (UIP) condition, which furthermore are tied with a key parameter to foreign (or “German”) monetary policy shocks (see Sec. V.B.3). Let me put it differently. Most of the interesting action in monetary policy in Europe over the last 20 years is the convergence process seen in figure 4. The authors sweep all that away by an add‐on to the UIP condition, which, however, has no further implications for aggregate dynamics. Next, they then seek to study how the changes in monetary policy from the pre‐euro regime to the post‐euro regime have affected macroeconomic variables. Shouldn’t one worry a bit that the baby has already been thrown out with the bath water? There is something really interesting happening here: it is the major big thing in the transition to the euro. We cannot quite put it into the theory, so thus let us ignore it? Shove it into a random shock, leaving everything else unchanged?I can see the desperation of the authors here, and I laud them for their frankness. Figure 4 is hard to explain within this theory. It is my guess too that it has a lot to do with perceptions of risk and updating the probabilities of membership in the European Monetary Union (EMU). So, having gotten so far in setting up this beautiful model and all, I understand that the quick fix of declaring it to be completely uninteresting and tangential was a way to proceed with the rest. But here is a memo to subsequent research: forget about the rest and instead put this at center stage, to understand the role of changing monetary policy in Europe!The authors instead plug in reaction coefficients of monetary policy, which are not obtained from the previous empirical exercise and not obtained from estimating the structural model, but instead from another empirical exercise described in Section V.B.2. One has to wonder whether this is consistent with the initial FAVAR approach or with the structural model at hand. Anyway, given that they use different coefficients before and after EMU, they find different quantitative results of their model. This is what the main comparison of pre‐euro and post‐euro in the paper rests on. Perhaps a more serious subsample stability test, using the structural DSGE model for estimation rather than an auxiliary model (or, at least, a with the of would be more to the empirical approach of the first of the paper is rather and more than may appear at For example, the identification assumption that all other variables do not to monetary policy shocks within the is But that essentially just from an of is the difference between a monetary policy that is happening at the of a and a monetary policy happening at the of the It just on the artificial way the time is up into periods. In figure one could read the impulse responses by moving them to the by one and having all variables within the to the monetary policy shock. it would be interesting to the monetary policy shocks as identified by the DSGE model to the monetary policy shocks as identified by the this a good model to study the impact of monetary policy in Note that there is no here. There is no that could get in from There is no worry about less when interest rates because there is no and no in the model to the of European and the many by policy and the are also essentially only that monetary policy about is due to the of for the model, and here are no different from But exchange rates substantially more than post‐euro inflation If are the main monetary policy perhaps be much more on the that the exchange rate from to the in the of than the created by some not being to but others differently, is the main of that it cannot its for in is it more important to them that their as they are to at wage which while the value of the And if that is the more important how much might that have a role in the transition to the for monetary policy, as a currency and for monetary policy sum, the model here is at the current of quantitative research on monetary policy. But I am that several of the most interesting which really matter for monetary policy and really matter for the transition to the EMU, have been out before the analysis has even And if so, then the problems with this approach are severe We then to different to the main of monetary Boivin et al.’s I really some may The paper is a analysis at the current of research and among the best that one can find on the at hand, building on the best I the authors for what they have this is no I am that the approach is and that can serious monetary policy discussions on this I fear that severe problems remain and that the route taken here is not yet convincing enough for others to follow. I have fear that the approach taken and the evidence presented by the authors are quite consistent with a world in which there is no comovement among the series at they are probably perfectly consistent with a world in which only very few factors matter at the European scale, but explaining considerably less than what the authors make us believe. And without such comovement or too little variation explained by too few factors, the approach has severe if there are factors, the monetary policy shocks may be the price and the sharp reaction of compared to the reaction of needs to the deus ex of shocks to UIP in to explain what be the key of monetary policy in Europe, convergence of interest rates (see fig. other key of central to monetary policy no role in the And if so, then the problems with this approach are severe We then to different to the main of monetary there is a between the and the this is for Whether these are fatal flaws or whether all this can be repaired or whether everything is all right after all is something that future research urgently needs to clarify before this approach should be put to wider and Harald the of Monetary Policy A FAVAR with University and University of in Boivin, and Monetary A (FAVAR) of in on Policy in Gertler, and and Monetary In of Monetary and University of Chicago in Are the of a to Monetary from an of Monetary in Previous articleNext article by by the of are reported from by the of the following articles this of the of large factor with factors, of The Monetary

Understanding the current global regime shift and the standing of the macro-financial system resilience

Author reviews: Alan Greenspan, The Age of Turbulence: Adventures in a New World. London: Penguin Books, 2007, 531 p.

Toward a “New” Inflation-Targeting Framework:The Case of Uruguay Matías Escudero (bio), Martín Gonzalez-Rozada (bio), and Martín Solá (bio) Empirical studies in the late 1980s, suggesting that monetary policy might influence the short-run dynamics of the real economy, contributed to the widespread use of inflation-targeting policy rules by central banks. More recent research on monetary economics provide a theoretical framework for the implementation of such rules. For example, Taylor (1993) recommends the use of a simple interest rate rule that is a function of inflation and the output gap. Nowadays it is standard to use the dynamic stochastic general equilibrium (DSGE) model and New Keynesian models to evaluate the effects of Federal Reserve policies. The success of alternative policy rules is usually assessed in terms of the short-run dynamics of the relevant macroeconomic variables. Many central banks use the reference interest rate as a conventional instrument to signal to the public changes in the monetary policy stance. In this way they attempt to achieve the convergence of inflation, and its expectation, upon a given target. Recently several central banks in Latin American countries (LAC) adopted stabilization policies using conventional and unconventional tools to meet their inflationary or financial stability objectives. Among the unconventional tools are reserve requirements (see Glocker and Towbin, 2012, and the references there for several emerging countries outside Latin America; for LACs, see Carvalho and Acevedo, 2008; Ocampo and Tovar, 2003; Ribeira and Barbosa, 2005; [End Page 89] Vargas and others, 2010). In highly dollarized LAC, changes in reserve requirements have been used as a macroeconomic prudential tool, with the main objective of accumulating liquidity being to address financial stress (see León and Quispe, 2010; Vargas and Cardozo, 2012; Tovar, Garcia-Escribano, and Vera Martin, 2012; Carrera and Vega, 2012) and to complement the use of the reference interest rate in order to achieve the inflation target objective (see Comunicados del COPOM, 2007–12, for Uruguay; Glocker and Towbin, 2012). However, most of the literature on the use of reserve requirements in LAC is not only empirical but is mostly focused on the impact of these requirements on interest spreads and bank profits. The main conclusion from those studies is that an increase in reserve requirements induces an increment in interest rate spreads and a fall in bank profits. An increment in reserve requirements acts as a tax on the banks and widens the spread between lending and deposit rates (see Glocker and Towbin, 2012). Monetary policy shocks typically generate a short-run fall in inflation through a contractionary effect on economic activity. Furthermore, in highly dollarized economies, these shocks may also have undesirable effects on the foreign exchange market (Montoro and Moreno, 2011). Therefore, the use of reserve requirements may be an important unconventional monetary policy tool, since it could help to achieve the inflationary target without having major effects on the exchange rate market (that is, without attracting capital inflows), and it may also reduce the negative impact of the increase in interest rates on output. Nevertheless, the short-run effects of this type of policy are not obvious, since it depends on, among other things, the combination of instruments chosen to achieve the target and the type of target under consideration. The main objective of this paper is to describe the impact of using conventional and unconventional tools to meet inflationary or financial stability objectives in a dollarized economy. This paper explores, for the Uruguayan economy, the impact of these policies, using a relatively standard model of a small open economy with sticky prices, financial frictions, and a banking sector that is subject to legal reserve requirements.1 The three main findings of the paper are as follows. One, reserve requirements can be used to achieve the inflationary objectives of the central bank. [End Page 90] However, reducing inflation using this instrument also produces a real appreciation of the Uruguayan peso. Two, when the central bank uses the monetary policy rate as an instrument, the effect of the reserve requirements is to reduce the negative impact on consumption, investment, and output of an eventual increase in the interest rate. Nevertheless, the quantitative results in terms...

Previous articleNext article FreeEvolving Perceptions of Central Bank Credibility: The European Central Bank ExperienceLinda S. Goldberg and Michael W. KleinLinda S. GoldbergFederal Reserve Bank of New York and NBER Search for more articles by this author and Michael W. KleinTufts University and NBER Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreI. IntroductionWhat are the preferences of a central bank over inflation and output-gap stabilization objectives, and what is its preferred long-run inflation rate? While statements of priorities and goals are important, the credibility of such statements and the market perception of the policy reaction function of a central bank play a key role in determining economic outcomes. This point, early on described as the "credibility" of central bank policies, is a standard theoretical result with recent interpretation in the New Keynesian paradigms.1 It is also received wisdom among practitioners.The importance of the market perception of the central bank's acceptable trade-offs between inflation and output goals as well its specific targets naturally leads to the question of how the market acquires this perception and whether and how it evolves over time. One view is that establishing an appropriate institutional structure is the key element in insulating the monetary authority from political pressure and thereby convincing markets that a central bank has a strong and unvarying aversion to inflation. A second, more dynamic, view focuses on the role that actual policy conduct plays in building the reputation of a central bank. These two different views have distinct implications for the relative importance of the institutional structure of a central bank, as compared to its conduct, for attaining and maintaining its credibility.2A survey of the heads of central banks and prominent monetary economists reflects a belief that the credibility of a central bank is based more on its past actions than on institutional structures that afford it independence by insulating it from political concerns, although there is also a consensus that structure matters (Blinder 2000). Empirical research has found that institutional features related to central bank independence are associated with economic performance in cross sections of countries, perhaps because these features indicate the ability of an institution to "tie its hands" and commit to a policy that may cause short-term pain in the pursuit of longer-run gain.3 There is less evidence, however, as to whether and how the credibility of a particular central bank's policy stance evolves over time in response to the conduct of policy and other related decisions. This is a particularly timely issue. Questions were raised about the commitment of the Federal Reserve to price stability after its response to the financial crisis of 2007–9. Even more recently, similar concerns were raised about the European Central Bank (ECB) to its primary mandate of price stability after it introduced a Securities Markets Program to purchase euro area debt securities to "ensure depth and liquidity in those market segments which are dysfunctional" in May 2010.These episodes raise a relevant question of how to determine whether market perceptions of central bank policies are changing. We show how high-frequency data from asset markets can be used to address this by providing a methodology for tracking the evolution of related market perceptions. Our analysis focuses on the experience of the ECB during its early years of operation, which is a natural experiment for this issue.The ECB offers an example of both structure and conduct aimed toward achieving policy credibility. Its architects were mindful of lessons from economic theory concerning the importance of a structure that provided independence from political considerations.4 The role of conduct was also clearly apparent. At its inception, the directors of the ECB were acutely aware that their policies were closely scrutinized for indications of general tendencies. This is, of course, a specific example of a more general tendency for relatively large updating of market priors when there is the establishment of a new central bank, an adoption of new policies (such as inflation targeting or extraordinary emergency lending at the time of a crisis), or a change in leadership (Blinder 2000).5We begin by developing insights about the response of asset prices to inflation news in Section II. The key point is that these responses reflect market perceptions of the policy reaction function of the central bank, as shown in the work of Gürkaynak, Sack, and Swanson (2005) and Gürkaynak et al. (2007).6 Their calibration exercises demonstrate the responses of short interest rates, long interest rates, and the yield curve to output and inflation shocks. We build on their work by demonstrating that the patterns in these calibrations are closely tied to the public's perception of the policy reaction function. In particular, we use this model to illustrate the change in the relationship between economic news and the term structure of interest rates with changes in the perceived anti-inflation stance of the policy reaction function parameters. These results also hold for changes in the perceived inflation target.7In Section III we propose and implement a novel method for measuring the market's view of evolving central bank "credibility." The method applies newly developed econometric tests for persistent time variation in regression coefficients (from Elliott and Müller [2006]) to high-frequency financial market data.8 Specifically, we use these tests to explore the evolution of the effects of news announcements on the yield curve for euro area countries for the period beginning January 1999, the time the ECB began its operations, through mid-2005, using hourly data on the term structure of bonds of euro area countries and the United States, as well as the euro-dollar exchange rate. These econometric techniques are especially informative in this context since they allow for a gradual evolution of estimated parameters rather than an abrupt change at a single moment. This evolution will capture the consequences of an ongoing updating by market participants of their views of the central bank reaction function. This type of updating can occur as market participants gradually learn through observing central bank actions and communications.The results in Section IV show significant and persistent parameter instability in the effects of economic news on European term structures and on the euro-dollar exchange rate. The identified patterns are consistent with market participants updating their views of the policy reaction function of the ECB. Additional support for our updating hypothesis is provided by considering the smoothed time path of the estimated parameters of the coefficient on the news announcement, estimated through another new, and related, econometric technique (Müller and Petalas 2010). Parameter values evolved in a manner consistent with the perception of an increasing aversion to inflation by the ECB as it tightened its monetary policy or, alternatively, as consistent with a perceived decline in the inflation target of the ECB. These results on time-varying consequences of economic news for the yield curve are complemented by results of discrete structural break tests (Andrews 1993) that demonstrate the robustness of our findings.Overall, these empirical results support the view that actions, and not just institutional structure, influence market perceptions of the policy stance of a new central bank. Benchmark test results for the term structure of U.S. interest rates present no evidence of persistent parameter instability in the response of the U.S. term structure to news, a result consistent with stable perceived weights in the Fed's reaction function over this same interval.9 The results demonstrate that the tools introduced can capture evolving views of central bank preferences and credibility.II. Central Bank Policy Reaction Functions and Market Responses to NewsIn this section we present a model in order to demonstrate the effects of changing perceptions on the actual response of interest rates to economic news.10 The insights from this model inform our interpretation of the empirical results on the evolution of the response of the yield curve to news that are presented in Section IV. The basic argument is that market perceptions of a central bank's stance on policy have an important impact on the performance of an economy and the consequences of policy decisions. While these market perceptions are, by nature, unobservable, we argue that actions such as changing views of the relative weight a central bank places on inflation versus the output gap in its monetary policy reaction function should be identifiable through analysis of the high-frequency response of asset prices to economic news.The model that we use to frame our analysis follows from Gürkaynak et al. (2005). This standard New Keynesian approach allows for a significant fraction of backward-looking agents (who, equivalently, can be assumed to act in a rule-of-thumb manner) and also allows for forward-looking agents.11 The model consists of six basic equations:The first two equations represent the macroeconomic structure of the economy. Equation (1) specifies current inflation, πt, as a function of expected future inflation and lagged inflation, which contributes to inflation persistence through the lag function Aπ(L). The parameter μ describes the balance of these forward-looking and backward-looking pressures. Current inflation also depends on yt, which captures the stance of current output relative to its potential (i.e., the output gap). Equation (2) describes this output gap as also having a forward-looking component and a persistent lagged effect. The output gap (if negative) declines as monetary policy is more expansionary, as reflected in declining real interest rates. The latter are introduced via the difference between the nominal rate it and inflation expectations over a comparable maturity horizon.Shocks to inflation and output are represented by and in equations (1) and (2), respectively. The source of these shocks may be either domestic or foreign in origin. Owing to international transmission, either foreign or domestic shocks could be a source of domestic inflation and lead to policy reactions (Clarida, Galí, and Gertler 2002).12Equation (3) specifies the policy reaction function of the central bank. The equation augments concerns about the output gap, which enters with weight b, and inflation, , relative to its target, , which enters with weight a, with policy rate smoothing. Greater values of the parameter c indicate a relative unwillingness of the central bank to deviate sharply from the prior period's policy rate. Equation (3) also affords a role to recent inflation history with representing a 4-quarter moving average of inflation and includes , an independently and identically distributed shock.Equations (4) and (5) describe updating of views of the central bank inflation target, , by the central bank (eq. [4]) and by private agents as denoted by the hat notation of equation (5). As shown by Erceg and Levin (2003) and Gürkaynak et al. (2005), the inflation target of the central bank has a tendency to rise when inflation goes above the prior target, with this effect depending on the size of the θ parameter, and can be subject to exogenous changes captured by . Private-sector agents infer such changes by observing the deviation of it from their prior expectation for policy and update their view of the target according to the strength of a Kalman gain parameter κ and when the observed policy rate is higher or lower than what they would have expected given the prior perceived target. This approach provides a mechanism for central banks to update their policy reaction function and for the private sector to assess and learn about this change. The model also imposes the expectations hypothesis, as in Gürkaynak et al. (2007), in which long interest rates of maturity m, it(m), are the cumulated sum of short interest rates captured by 1-year forward rates j years ahead, fj(i, 1).Consider the consequences of varying values of a and b for the long rate, the short rate, and the slope of the yield curve (i.e., the difference between the long rate and the short rate). The impulse examined is news about inflation, which occurs through a realization of either or .13 The experiment explores the effects of this news over time and the changes in the effects under parameterizations of the central bank reaction function. In particular, suppose that there is an increase in a relative to b in equation (3), which Fuhrer and Hooker (1993) describe as greater central bank credibility in fighting inflation. There are marked differences in the response of interest rates to news with changes in the perceived values of a and b. Indeed, when a and b are varied, the entire time path of adjustment to shocks is altered in the model.14 Clarida and Waldman (2008) show that the larger the weight on the output gap, the slower the economy's convergences to the central bank's output and inflation targets.The graphs presented in figure 1 present the impact effects on the long interest rate, the short interest rate, and the difference between the two (i.e., the slope of the yield curve) to a positive shock to inflation, (in the top three graphs), and a positive shock to output, (in the bottom three graphs), for a wide set of pairs of the parameters a and b. The surfaces in the third graph in each of the two rows show that an increase in the relative importance of the weight the central bank places on fighting inflation (a) versus the weight it places on stabilizing output (b) decreases the yield curve slope (i.e., short rates rise by more than long rates rise) after an inflationary shock. The central bank moves more aggressively to combat inflation, placing less importance on output and employment goals. Under higher a (or lower b), there still are consequences for both and , since a positive realization of either shock will have a smaller positive effect on the long rate than on the short rate. Indeed, the model's quantitative result is that the yield curve response is negative for all cases except when output stabilization has a very high weight compared to inflation stabilization in the central bank's objective function. Another set of quantitative results also can be constructed for exchange rates, as analyzed more broadly in Engel and West (2005), Clarida and Waldman (2008), and much earlier by Hardouvelis (1988).Fig. 1. Impact effects of inflation and output news. Note: a represents the weight on the inflation gap, and b represents the weight on the output gap.View Large ImageDownload PowerPointEmpirically, however, it has long been recognized that there is excess sensitivity of the long end of the yield curve to news, as discussed in Ellingsen and Söderström (2001). While Gurkaynak et al. (2005) provide a range of explanations for this excess sensitivity in the data, the implication is that the unexplained excess sensitivity of the long end of the yield curve would shift up the contours shown in the far right graphs of figure 1, potentially locating that plane in more positive space. For our purposes, the main point is not whether quantitatively there is a net positive or a net negative impact effect of news for a given set of values of a and b. Rather, the key issue is that an increase in central bank credibility results in an inflationary shock moving the economy to a different point on the contour, so that credibility improvements reduce the response of the long interest rate to a greater degree than they reduce the response of the short rate. In particular, an increase in credibility alternatively could be interpreted as a decrease in the expected inflation target of the central bank, as in Erceg and Levin (2003) and Gürkaynak et al. (2005). Our approach can be viewed as complementary, although it is noteworthy that the pattern of yield curve response to news does not vary substantively with the κ or θ parameters indicating updating of the perceived central bank inflation target, .III. Empirical ApproachA. Testing StrategyThe model presented in the previous section provides a framework interpreting a time-varying response of the immediate effect of economic news on the term structure of interest rates. An empirical application requires a method for testing for instability in this relationship. In this section we discuss the method we use to test for persistent variation in the immediate response of the term structure to news.We use a linear specification linking the surprise component of news to the change in an asset price, as is standard in research on the high-frequency response of asset prices to news (see, e.g., Andersen et al. 2003). The specification for the effect of news on any asset price qt, allowing for the possibility of a time-varying coefficient on the news variable, iswhere is the change in the term structure over the short period of time between t−, just before an announcement, and t+, just after that announcement (i.e., ); represents the announced value of a variable, which is known at time t+; represents the expected value of that variable before the announcement (so is the surprise component of the announcement); and is a white-noise error term. This parsimonious specification is most appropriate when the time horizon between t− and t+ is short, for example, when it is measured in minutes rather than in days, and when news about the variable x does not become available at the same time (i.e., within the span t− to t+) as announcements about some other relevant variable.In our application, we define the term structure as , with L and S denoting long-term and short-term interest rates, respectively. Our theoretical motivation argued that a significant evolution in the response of the difference between 10-year and 2-year European interest rates would be expected for a central bank with changing market perceptions of its policy reaction function priorities.The challenge, in this context, is that there is not a single, widely recognized dramatic change in policy that was clearly a watershed that led to a change in the public's perceptions of the ECB. Thus, we cannot perform a simple Chow test over γi. Moreover, it is unlikely that there was a discrete change in expectations, in response to either a single event or a small number of events. Rather, it is more reasonable to think of perceptions changing gradually as market participants learned about the ECB through its pronouncements and, especially, its actions.15 Thus, we would like to test for persistent change in the estimated parameter γi.16Elliott and Müller (2006) have developed a test for the presence of persistent time variation in one or more regression coefficients. Their quasi local level (qLL) statistic provides asymptotically equivalent tests for a large class of persistent breaking processes against the alternative of structural stability. The test does not require the specification of an exact breaking process, such as breaks that occur in a random fashion, serial correlation in the changes of coefficients, or a clustering of break points.17 This feature of their test makes it well suited for our purposes since we do not need to test for a particular type of updating by market participants of their views on central bank inflation aversion. The qLL statistic takes a negative value, and a value smaller (i.e., more negative) than the critical value implies a failure to reject time variation in one or more coefficients for the entire sample period. This procedure tests for persistent time variation over the entire sample and, as such, does not identify a particular date as the one most likely to represent a discrete break point.18As will be shown below, we do, in fact, find evidence that there has been persistent time variation in the slope coefficient in term spread regressions for Germany, France, and Italy, but not for the United States. We also find that there is significant parameter instability in the response of the bilateral euro-dollar exchange rate to news.19 We interpret this combined finding of parameter instability for European rates and the euro-dollar rate and parameter stability for U.S. rates as reflecting an evolving view of the inflation aversion of the ECB rather than as some structural change common to financial markets across all four of these industrial countries.The Elliott and Müller qLL statistic says nothing about the direction of change of γi. Yet, following from the results presented in Section II, a decrease in γi can be interpreted as an increase in the perceived relative inflation aversion of the central bank. For this purpose, we rely on methods from Müller and Petalas (2010), who show how to calculate the smoothed time path of γi. We present these estimated time paths. For robustness, the results from these smoothed estimates are supported by the sup-Wald tests for parameter stability (see Andrews 1993, 2003), which offer a break date for γi that roughly corresponds to the peak value of the estimated smoothed time path.As will be shown, we find that γi decreases over the sample period for the cases in which there is evidence of a significant persistent change in γi (i.e., for the three European yield curves and for the euro-dollar exchange rate). Even more tellingly, the reduction in γi tends to occur in the wake of monetary tightening by the ECB. It is unlikely that other candidate explanations for changes in the responsiveness of the slope coefficients that are not linked to the perception of the ECB policy stance would map as closely to actual ECB policy changes.B. DataThe three types of data used in our analysis are various asset prices, where the assets are government bonds and foreign exchange, inflation announcements, and related market expectations of inflation. We begin this subsection with a discussion of the five different asset prices used as dependent variables in our estimation. We then describe our construction of inflation surprises.Asset price data. Five different dependent variables are used in the regressions. In each case, the dependent variable, , represents the change in q between 30 minutes before and 30 minutes after each monthly inflation announcement over the period January 1999 to June 2005. The changes in the term spread between 10-year and 2-year interest rates for French, Italian, German, or U.S. government bonds are four of the dependent variables, with a robustness section (Sec. IV.D) considering the 2-year and 10-year rates separately.The fifth dependent variable is the case in which represents the change in the logarithm of the euro-dollar exchange rate 30 minutes before and 30 minutes after the news announcement. Through short-run interest rate parity, the exchange rate move should reflect the relative effects of news on interest rates in the euro area versus in the United States (see the appendix). In this case, a positive value of rather than indicating an increase in the premium of the long rate relative to the short rate indicates a depreciation of the euro. Evidence that γi decreases over the sample period in the exchange rate specification is consistent with a situation of more of an increase in the perceived anti-inflation stance of the ECB, as compared to the U.S. Federal Reserve.Inflationary announcements and expectations. To capture the economic news ηt that lead to asset price updating, we restrict our attention to inflation announcement measures. Candidate data releases for our study potentially include indicators of consumer price inflation for the full euro area, for individual countries in the euro area, and for the United States. The construction of the "news" variable, which is the appropriate variable to be employed in the specification, also requires measures of market expectations for the full sample period. While some earlier studies use vector autoregressions to generate measures of sho

Japan’s encounter with deflation and near‐zero‐interest short‐term interest rates in the 1990s led to a surge in research on the implications of the zero lower bound (ZLB) on nominal interest rates for monetary policy around the end of that decade. Based on model simulations, the literature at that time identified a number of key implications of the ZLB (see Orphanides and Wieland [2000], Reifschneider and Williams [2000, 2002], Eggertsson and Woodford [2003], and references therein). First, with low inflation targets of the kind followed by many central banks, the ZLB will frequently be a binding constraint on monetary policy. That is, Japan’s example is not an outlier but rather a harbinger for the future. Second, at inflation targets of 1% or lower, lowering the inflation target comes at a cost of higher variability of output and inflation, although the effects on inflation variability are relatively small. This analysis provides an argument for maintaining a positive inflation target cushion above 1%. Third, in rare instances of severe prolonged recessions accompanied by deflation, standard open market operations will be insufficient to bring the inflation rate back to target, andalternative sources of stimulus to the economy, such as fiscal policy, will be needed. Fourth, central banks can significantly reduce the effects of the ZLB onmacroeconomic stability by modifying their policy actions and communication to the public when the ZLB threatens to constrain policy. Specifically, policies that cut rates aggressively when deflation is a risk and promise to temporarily target a higher rate of inflation following episodes where the ZLB binds were found to greatly reduce the effects of the ZLB in model simulations. In the decade since this researchwas initiated, the ZLB has gone froma theoretical issue applying to Japan to one that plagues many industrialized economies. Indeed, an era of overwhelming confidence in monetary policy’s power to tame the business cycle while delivering low and stable inflation has been replaced by fears that the global economy could

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Previous article FreeCosts and Benefits to Phasing out Paper CurrencyKenneth RogoffKenneth RogoffHarvard University and NBER Search for more articles by this author Harvard University and NBERPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreThis paper explores the costs and benefits to phasing out paper currency, beginning with large-denomination notes, later extending to all but small coins and bills, and eventually those as well. It is hardly a simple issue; paper currency is deeply ingrained in the public’s image of government and country, and any attempt to change long-standing monetary conventions raises a host of complex issues. The symbolic value of the euro, for example, as a flag for nascent European institutions, is hard to overstate. Nevertheless, it is important to ask whether currency in paper form has outlived its usefulness. Today, credit and debit cards are increasingly being used for even small transactions. And although today’s cryptocurrencies fall far short of being true currencies—for one thing their prices are simply too volatile—the underlying technologies may ultimately strengthen the menu of electronic payments options.1Zero-Interest Negotiable Bonds as an Obstacle to Negative Policy Interest RatesPaper currency has two very distinct properties that should draw our attention. First, it is precisely the existence of paper currency that makes it difficult for central banks to take policy interest rates much below zero, a limitation that seems to have become increasingly relevant during this century. As Blanchard, Dell’Ariccia, and Mauro (2010) point out, today’s environment of low and stable inflation rates has drastically pushed down the general level of interest rates. The low overall level, combined with the zero bound, means that central banks cannot cut interest rates nearly as much as they might like in response to large deflationary shocks.If all central bank liabilities were electronic, paying a negative interest on reserves (basically charging a fee) would be trivial. But as long as central banks stand ready to convert electronic deposits to zero-interest paper currency in unlimited amounts, it suddenly becomes very hard to push interest rates below levels of, say, −0.25 to −0.50%, certainly not on a sustained basis. Hoarding cash may be inconvenient and risky, but if rates become too negative, it becomes worth it.2In a series of insightful papers, Willem Buiter ([2009], and citations therein) has discussed whether it might be possible to find devices for paying negative interest rates on currency.3 Buiter notes that there were experiments with stamp taxes during the Great Depression (currency would remain valid only if it were regularly stamped to reflect tax payment). There are a variety of other ideas. For example, Mankiw (2009) points out that the central bank could effectively tax currency by holding lotteries based on serial numbers, and making the “winners” worthless.Paying a negative interest rate on currency, or on electronic reserves at the central bank, may seem barbaric to some, but it is arguably no more barbaric than inflation, which similarly reduces the real purchasing power of currency. The idea of raising target inflation to reduce the likelihood of hitting the zero bound is indeed an alternative approach. Blanchard et al. point out that if central banks permanently raised their target inflation rates from 2% to 4%, it would leave them scope to make deeper cuts to real interest rates in severe downturns. Arguably, paying negative interest rates is a better approach if, as many believe, inflation becomes more unstable as the general level of inflation rises. Robert Hall (1983) argues forcefully that the central role of monetary policy should be to provide a stable unit of account, and in principle the ability to pay negative interest rates facilitates its ability to achieve this in today’s low inflation environment (Hall 2002, 2013).Even if there is a good case for allowing the central bank to pay a significant negative interest rate to fight a large deflationary shock, what is to stop a government from using negative interest rates as a wealth tax in normal times? This is a complex issue that parallels many of the problems in trying to design central bank institutions that will resist the temptation to inflate. Nevertheless, the challenges of conducting monetary policy at the zero bound force consideration of alternatives to the status quo. If, as Reinhart and Rogoff (2014) conjecture, business and financial cycles in the twenty-first century may produce larger fluctuations than they did in the last part of the twentieth century, the issue of hitting the zero bound may indeed remain a recurrent one.Anonymous Money as a Vehicle for Facilitating Tax Evasion and Illegal ActivityWe now turn to a second drawback to paper currency. Paper currency facilitates making transactions anonymous, helping conceal activities from the government in a way that might help agents avoid laws, regulations, and taxes. This is a big difference from most forms of electronic money that, in principle, can be traced by the government. (The issue of substitute anonymous transactions vehicles, such as Bitcoin, is discussed later on.)Standard monetary theory (e.g., Kiyotaki and Wright 1989) suggests that an essential property of money is that neither buyer nor seller requires knowledge of its history, giving it a certain form of anonymity. (A slight caveat is that the identity of the buyer might be correlated with the probability of the currency being counterfeit, but until now this is a problem that governments have been able to contain.) There is nothing, however, in standard theories of money that requires transactions to be anonymous from tax-or law-enforcement authorities. And yet there is a significant body of evidence that a large percentage of currency in most countries, generally well over 50%, is used precisely to hide transactions. I have summarized the international evidence in earlier research (Rogoff 1998, 2002). Other than the introduction of the euro, rather little has changed except that, if anything, anonymous currencies have continued to grow at a faster rate than nominal gross domestic product (GDP).Given that banks and businesses are typically quite efficient in their cash management (as evidenced by several central bank surveys), the most surprising fact about currency is the sheer extant amount that most Organisation for Economic Co-operation and Development (OECD) countries have in circulation, far in excess of anything that can be traced to legal use in the domestic economy. Table 1 gives data on currency by denomination and as a share of GDP for the United States, the Eurozone, Japan, and Hong Kong. For example, as of December 2013, there was roughly 1.2 trillion dollars in US currency in circulation, or roughly $4,000 for every man, woman, and child living in the United States. Moreover, 77% of the total value is in $100 bills, meaning more than thirty $100 bills per person. By contrast, denominations of $10 and under accounted for less than 4% of the total value of currency in use.Table 1. A. Europe: Currency in Circulation (February 20, 2014)Denomination (€)Value (In Thousands of Euros)Value (% of Total Currency)Value (% of 2013 GDP)58,028,790.80.8380.0841020,115,075.42.1000.2102057,254,121.05.9780.59850335,791,854.335.0633.507100183,322,233.019.1421.91520039,428,190.44.1170.412500289,720,996.030.2523.026Total (banknotes)933,661,260.8997.4919.752All coins24,029,083.22.5090.251Total (incl. coins)957,690,344.010010.003B. Hong Kong, Currency in Circulation (end of 2012)Denomination (HK$)Value (in Billions of HKD)Value (% of Total Currency)Value (% of 2012 GDP)102.920.9670.1432011.383.7730.558507.002.3220.34410027.138.9981.33250074.0924.5743.6371,000169.1956.1158.305Total (banknotes)291.7096.75014.319All coins9.803.2500.481Total (incl. coins)301.5010014.800C. Japan, Currency in Circulation (February 2014)Denomination (¥)Value (in 100 Millions of Yen)Value (% of Total Currency)Value (% of 2013 GDP)5001,0660.1180.0221,00038,0364.1930.7952,0001,9950.2200.0425,00029,5953.2620.61910,000790,19687.10116.519Total (banknotes)861,33594.94218.006All coins45,8845.0580.959Total (incl. coins)907,22010018.965D. United States, Currency in Circulation (December 31, 2013)Denomination ($)Value (in Billions of Dollars)Value (% of Total Currency)Value (% of 2013 GDP)110.60.8850.06322.10.1750.013512.71.0600.0761018.51.5440.11020155.012.9350.9235074.56.2170.443100924.777.1685.504500 to 10,0000.30.0250.002Total1,198.31007.133Source Panel A: European Central Bank; Panel B: Hong Kong Monetary Authority; Panel C: Bank of Japan; Panel D: Board of Governors of the Federal Reserve Sytem.View Table ImageThe size of dollar currency holdings, relative to GDP or per capita, is hardly unique. Indeed, in the United States the currency supply is 7% of GDP, in the Eurozone 10%, and in Japan 18%. Despite having lower per-capita income, the Eurozone also has roughly $4,000 in euros for every one of its citizen (valued at the April 2014 euro-dollar exchange rate). The euro has a much greater range of high denominations, so the value is not as concentrated in a single denomination as in the United States. Nevertheless, the same basic phenomenon holds, with roughly a third of the value of euro currency held in 50 euro notes (roughly $70), and another third in 500 euro notes (roughly $700). Adding in 100 and 200 euro notes brings the percent of high-denomination notes above that of the United States. In Japan, the total amount of currency outstanding is similar to that in the United States and Europe, despite having a population size only 40% as large. The concentration in the highest denomination is even more acute, with 87% of the value of notes being in 10,000 yen notes, the largest denomination, roughly $100 at April 2014 exchange rates.4It is true that in the case of the United States and the euro area, there is fairly convincing evidence that a large share is held abroad. Porter and Judson (1996) use seasonal comparisons with Canada and biometric techniques to infer that roughly 70% of US currency is held abroad. It should be noted that Canada is a country that has relatively low currency use compared to many other advanced countries. However, the fact that currency outstanding is comparable to the United States in so many other OECD countries, most of whose currencies are used only domestically, suggests that perhaps the size of currency holdings in the United States is similarly quite large; Rogoff (1998) speculates that the ratio of US currency held internationally may be closer to 50%. Of course, as interest rates have fallen to near zero in recent years, it is not surprising that the demand for currency in the domestic US economy appears to have risen; using similar techniques to her earlier work, Judson (2012) estimates around 50% of US dollars are held domestically postfinancial crisis. Even if foreign holdings of currency are important for a few countries (including also Hong Kong and Switzerland), this is not thought to be the case for most OECD countries. The Japanese yen does not appear to be a significant international currency.In any event, it is clear that the long-term trend domestic demand for currency in the legal economy is dwindling, due in part to advances in cashless payments.5 As already noted, the small number of central bank surveys that have been performed to measure domestic use of currency in the legal economy typically find very low percentages, on the order of 10–15% of total extant currency in the case of the United States (see also Feige 2012a, 2012b). Cash is used more intensively in some Eurozone countries. Fischer, Köhler, and Seitz (2004) use a wide range of methods to estimate the transactions demand for currency within the euro area to be 25–35% of total euro currency in circulation. This estimate is broadly in accord with European Central Bank surveys taken after the financial crisis (ECB 2011) that reported holdings and demand for euro in the legal domestic economy of roughly one-third of total euros outstanding. Of the remainder, Bartzsch, Rösl, and Seitz (2011) look at euro notes issued by the Bundesbank and find that between 40 and 55% are held outside of Eurozone countries. (It is quite possible that the overall level of euro notes held outside the Eurozone is lower, since Bundesbank-issued notes are particularly popular, even if in principle all the Eurozone central bank notes should be perfect substitutes.)Presumably, currency that is not held in the domestic legal economy or in the global economy (legal and underground) is mainly held in the domestic underground economy.6 The underground economy includes agents evading taxes, laws, and regulation. The size of the underground economy is not known within any precision, though estimates for the United States are on the order of 7–10% of GDP (e.g., IRS 2012, Feige 2012a, b). The IRS estimates that for the benchmark year 2006, the tax gap (tax not paid voluntarily) is over $450 billion, with a gap of $385 billion still remaining after tax collection efforts. Importantly, this estimate does not include the informal economy (US Treasury Inspector General 2013). In Europe, where taxes are higher and regulation is often more onerous, most estimates suggest that the size of the underground economy is considerably larger than in the United States (see Schneider, Buehn, and Montenegro 2010).Summing up, currency should be becoming technologically obsolete. However, in no small part due to its association with the underground economy, it is not.Arguments against Phasing out Paper CurrencyThe arguments for eliminating paper currency are impressive, but there are important points on the other side of the equation. The most straightforward is seigniorage. The United States’ money supply increased by an average of roughly $30 billion per year from 2002–2007, and averaged roughly $70 billion per year in the years immediately following the financial crisis. The magnitudes are similar in many other large advanced countries. If a phase-out of paper currency were simply met by an increased demand for electronic central bank reserves, there would, of course, be no significant loss. However, precisely because paper currency is anonymous, replacing it with nonanonymous electronic money would likely lead to a large shrinkage in demand, and treasuries would have to absorb the loss. Rogoff (1998) conjectures that this cost might be fully compensated if a modest fraction of the underground economy is induced to pay taxes and, of course, there are also potential gains from reduced law-enforcement costs. It is unclear how easily these activities could substitute into other transactions media, but presumably this could be made difficult by restricting other potential anonymous transactions vehicles.Of course, if the government simply replaced paper currency with electronic currency that it could somehow credibly make anonymous, there would not necessarily be any long-run shrinkage in demand. The government would continue to garner seigniorage revenues from the underground economy and the problem of the zero bound on nominal interest rates would be effectively eliminated. That said, it is far from clear that the government can credibly issue a fully anonymous electronic currency and even if it could, anonymous electronic fiat money has all the drawbacks of an anonymous paper currency in facilitating tax evasion and illegal activity.There is also a question of how forcing a more rapid shift to cashless payments would affect transactions costs. Retailers are typically forced to pay a pro-rata fee to companies such as MasterCard and Visa for credit card services, but handling paper currency also entails substantial costs to protect against theft and pilferage. Also, in principle, the federal government could allow individuals to maintain ATMs and debit cards at the Federal Reserve, and arguably these could be serviced by private subcontractors at lower cost than conventional bank services.Another important argument for maintaining the status quo is that eliminating a core symbol of the monetary regime could disrupt common social conventions for using money, possibly in unexpected ways. For example, it could lead to a precipitous decline in demand for debt and not just for fiat money. This need not happen. In his hugely influential book on monetary policy, Woodford (2003) shows that central bank stabilization policy can work perfectly well in the limit as money’s role in transactions goes to zero. As long as social price-setting convention remains, and as long as the central bank can manipulate banks’ reserves to set the price level, monetary stabilization policy can still operate with full force. However, one must be careful that just because a similar equilibrium can be obtained with or without a significant transactions role for money, it does not necessarily mean that private agents will focus on the same equilibrium as they would when there exists paper currency. Yes, the government can help coordinate expectations by insisting that taxes are paid in the electronic fiat currency and that all state contracts be denominated in this currency, but it is important to acknowledge that there is at least an outside risk that if the government is too abrupt in abandoning a century-old social convention, it will destabilize inflation expectations, introduce a risk premium into bond pricing, and generally induce unexpected macroeconomic instabilities.There is also a potential risk to central bank independence. Even if eliminating currency is at least revenue neutral for the government as a whole, the central bank is the one that will lose seigniorage revenue. The Treasury is the one that will correspondingly gain through higher tax revenues and lower law-enforcement costs. Under longstanding institutional relationships, the ability to self-finance has put central banks in a privileged position. Although governments typically maintain oversight of central bank budgets, the fact that the central bank nominally appears to be a “profit center” considerably strengthens its hand in maintaining operational independence. In recent years, quantitative easing has been a massive money maker, but this is not the normal state of affairs when currency provision is a key source of revenue.Another argument for maintaining paper currency is that it pays to have a diversity of technologies and not to become overly dependent on an electronic grid that may one day turn out to be very vulnerable. Paper currency diversifies the transactions system and hardens it against cyber attack, electromagnetic pulse (EMP) blasts, and so forth. This argument, however, seems increasingly less relevant because economies are so totally exposed to these problems anyway. With paper currency being so marginalized already in the legal economy in many countries, it is hard to see how it could be brought back quickly, particularly if ATM machines were compromised at the same time as other electronic systems.7A different type of argument against eliminating currency relates to civil liberties. In a world where society’s mores and customs evolve, it is important to tolerate experimentation at the fringes. This is potentially a very important argument, though the problem might be mitigated if controls are placed on the government’s use of information (as is done, say, with tax information), and the problem might also be ameliorated if small bills continue to but not if any country to reduce the use of its currency, there is a risk that another currency would be used within domestic Even if that risk is not for a country like the United States, there is still the of revenue from foreign of currency of may be in underground or illegal activities within their even if not within US any attempt to large-denomination currency would be taken in a that at the very least the global currency into use at the time of and has a role in the global of the last 100 Despite and advances in electronic transactions it has even if its seem to be in the world underground and illegal economy. With many central banks now near or at the zero interest rate bound, there are increasingly arguments for how it might be out of there are many arguments for not the status from the of seigniorage revenues to civil in from to may already in the of the paper currency anyway. Nevertheless, the role of paper currency large-denomination in facilitating tax evasion and illegal and the and perhaps problem of the zero bound on nominal interest it is to the costs and benefits to a more for phasing out the use of paper earlier of this paper the for a at the April NBER in The author is to Judson and as well as to NBER for and to and for research For of research and of the financial relationships, if see may use the and but central banks typically several of money, from a one that includes only currency and bank reserves at the central bank, to increasingly that for example, transactions deposits at financial institutions (e.g., time and holdings of at money Currency in the United States for roughly of the Federal monetary course, central banks can and reserves at interest rates as a tax on The problem is when the interest rates for turn (2009) as the to the idea of currency. also Buiter and at a wide range of OECD countries, and indeed the United States does not particularly stand out as having high per-capita GDP currency and (2014) use data from a large to that the cash share of in the United States will decline by per is possible that even those cash holdings that are for for by individuals simply not I this is not nearly as important as cash holdings used to avoid taxes or to in illegal is true that nearly all holding though individuals are following this there would still need to be a for currency after a that if only small bills remain in circulation, the central bank would still have the to lower interest rates to more negative levels than if large bills continue to since costs are much greater for any large some foreign use of dollar and euro currency is to the even if a significant share goes to facilitating illegal and underground some countries may it to their to see phasing out of dollar and euro paper currency. However, in an where inflation rates in most countries have fallen over the two currencies more the benefits of being able to use dollar and euro paper currency in the legal economy has presumably been and will continue to Rösl, and for in Economic in Dell’Ariccia, and Monetary in Willem Interest to the Paper in Willem and the on Interest with Negative Interest on Economic in Central of of and in of the of Currency is paper University of in of US Currency the Money and the and in Köhler, and for and Paper European Central in in as The Economic in Robert Monetary of Monetary in the to in into and out of the Paper at the Federal Reserve Economic Policy on of Monetary in Tax from Previous in and for US Currency at and from the of the to Paper Board of Governors of the Federal Reserve in for the to April in and Money as a of of in and of US Federal Reserve in and from from 100 Economic in and for or Economic Policy in of Paper and Development in Buehn, and for the all over the Economic in Inspector General for Tax to the and of the Tax in and and the of from Paper Federal Reserve Bank of in Interest and of a of Monetary University in Previous article by NBER

Comment

Interest rate is the most popular instrument of monetary policy to control inflation around the globe. It is assumed that the tight monetary policy, such as an increase in interest rate, will reduce inflation by reducing aggregate demand in the economy. However, in reality, the use of monetary tightening could be counterproductive. The monetary tightening may increase inflation dates back to 1923 when Gibson (1923) observed that correlation between interest rate and inflation is positive. There are different opinions about how the interest rate affects inflation. The most famous is called Monetary Transmission Mechanism (MTM). According to the demand side channel of MTM, increase an interest rate, therefore the aggregate demand will decrease and finally, the price level will decrease. However, the supply side channel of MTM, states that the rise of interest rate will increase the cost of production, shifting up the aggregate supply curve. This will create a rise in the general prices level. The problem in that, there are many channels of MTM which can be categorized into demand side and supply side. Many researchers take one channel and make single equation, this leads to missing variable bias. Therefore there is need to take them simultaneously which can be done by (SEM) Structural equation modeling. This research study is very significant, because this research combines both demand and supply channel simultaneously, and removes biasedness through (SEM) structural equation modeling. The Augmented Dickey-Fuller (ADF) test finds that all the variables are stationary at first difference i.e. I (1), except inflation and investment. Firstly, unrestricted structural equation model (USEM) has estimated. The mostly coefficient of USEM has found to insignificant i.e. their probability value more than 50 percent. To remove the insignificant coefficient, we are given these unnecessary coefficients the regression weight is zero for the purpose of getting significant results. Secondly, the restricted structural equation model (RSEM) is estimated. The estimated results reveal that; interest rate has a positive relation with exchange rate and industrial inputs prices, while negative relation with the price of equity and investment. Therefore, the exchange rate, price of imports, price of exports and consumption have a positive relation with inflation while investment, loan, and output have a negative relationship with inflation. Finally, the interest rate is not a significant determinant of inflation. Therefore, the exchange rate and cost channel are responsible for the transmission mechanism of interest rate to inflation in Pakistan. This study can be extended in several ways. First, this study focus on how monetary policy effect inflation, further includes in this study fiscal policy. Lastly, a regional analysis can serve as the best extension of this research. Our work was focused on Pakistan only, however a regional comparison can be appropriate.

Monetary policy tools, including money supply and interest rate, are the most popular instruments to control inflation around the globe. It is assumed that a tight monetary policy, either in form of reduction in money supply or an increase in interest rate, will reduce inflation by reducing aggregate demand in an economy. However, monetary policy could be counterproductive if cost side effects of monetary tightening prevail. High energy prices may increase the cost of production by reducing aggregate supply in the economy. If tight monetary policy is used to reduce this cost push inflation, the cost side effect of energy prices will add to cost side effects of monetary tightening and will become dominant. In this case, the monetary policy could be counterproductive. Furthermore, simultaneous reduction in aggregate supply and aggregate demand will bring twofold reduction in output. Therefore greater care is needed in the use of monetary policy in the situation of cost push inflation. This article investigates the presence of cost side effect of monetary transmission mechanism, the role of international oil prices in domestic inflation, and implications for monetary policy. The findings suggest that both monetary policy and oil prices have cost side effects on inflation and monetary tightening could be counterproductive if used to reduce energy pushed inflationary trend.