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Abstract

We construct a new indicator to capture media sentiment about the European Central Bank monetary policy and its relevant environment by analyzing 25,000 articles from five major international newspapers. Using named entity recognition and part-of-speech tagging, we propose a methodology to dissociate the dissemination of official communications of the central bank from the media comments. The resulting (daily) index correlates with some (monthly) standard measures of economic sentiment but reveals idiosyncratic information on monetary policy. Analyzing the determinants of our index, we find that both press conference and inter-meeting communications of the President significantly affect media sentiment. We then show that, controlling for a large range of factors, daily changes in media sentiment have predictive power for financial market inflation expectations.

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... However, the authors of the latter study noticed that in a large sample of 10-Ks documents from 1994 to 2008, almost three-fourths of the words identified as negative by the widely used Harvard Dictionary were typically not considered negative in financial contexts. The study of Picault et al. (2022) confirms those results. The authors used various dictionaries to measure the extent to which the press conference and inter-meeting communications affect media sentiment. ...
Article
In this paper, we sought to investigate the effect of communication by central banks on consumer inflation expectations. To this end, we ran investigations into six European economies that, between 2010 and mid-2019, implemented inflation targeting: the Czech Republic, Hungary, Poland, Romania, Sweden, and the UK. Consumer inflation expectations were derived from qualitative surveys and quantified by probabilistic method. The communication tone of the central banks was derived from their minutes. We applied the textual method and latent Dirichlet allocation technique to derive minutes content that describes decision and underling economic conditions. For the sample collected, we estimated, controlling for past inflation and industrial production index, panel models. As some data proved to be fractionally integrated, we applied double filtering using the autoregressive fractionally integrated moving average method to account for autocorrelation followed by multilevel modelling. We estimated the model for two vectors of controls and four lexicons. The results suggest that the communication tone of a central bank affects consumer inflation expectations. However, the direction of relationship is conditional on dictionary.
... This suggests that, if central banks want to add direct communications to the public as a new policy tool, they will have to find new ways to reach the public without relying on traditional media. Recent work by Picault et al. (2022) suggests that the media channel is important also for financial markets and that many financial market actors do not listen directly to central banks. ...
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Does communication influence trust in the central bank? We examine this question using survey data covering 488,000 Eurozone citizens from 1999 to 2019. We find compelling evidence that more communication, as measured by the number of speeches made by representatives of the Eurosystem, negatively impacts citizens' trust in the ECB. This holds for speeches as a whole and for different groups of speakers. This effect was exacerbated during the global financial and European sovereign debt crises. The estimated long-term effect is substantial. An increase in the number of speeches per year by 100 reduces the share of those expressing trust in the institution by 6-11 percentage points. We do detect a positive result from more speeches in the form of increased informedness on the ECB and the EU. However, the overall negative effect prevails. In addition to individuals' socioeconomic status, macroeconomic conditions influence the trust-building process, albeit less robustly. Specifically, higher unemployment, public debt ratios, financial stress, and policy uncertainty weigh negatively, whereas GDP growth and a higher policy rate tend to enhance trust. JEL Classification: E58, E52, E71, D83, D80.
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We analyze the degree of anchoring of inflation expectations in the euro area during the post-crisis period, with a focus on the time span from 2014 onwards when long-term beliefs have substantially drifted away from the policy target. Using a new estimation technique, we look at tail co-movements between short-and long-term distributions of inflation expectations, estimated from daily quotes of inflation derivatives. We find that, during 2014, average correlations between short-and long-term inflation expectations rose sharply; moreover, negative tail events impacting short-term beliefs have been increasingly channeled to long-term views, triggering both downward revisions in expectations and upward changes in uncertainty. Overall, our results signal a risk of downside de-anchoring of long-term inflation expectations. JEL Codes: C14, C58, E31, E44, G13.
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We develop a field-specific dictionary to measure the stance of the European Central Bank (ECB) monetary policy (dovish, neutral, hawkish) and the state of the Eurozone economy (positive, neutral, negative) through the content of ECB press conferences. In contrast with traditional textual analysis, we propose a novel approach using term-weighting and contiguous sequence of words (n-grams) to better capture the subtlety of central bank communication. We find that quantifying ECB communication using our field-specific weighted lexicon helps to explain future ECB monetary decisions when considering an augmented Taylor rule. Regarding European stock market volatility, we find that markets are more (less) volatile on the day following a conference with a negative (positive) tone about the euro area economic outlook. Our indicators significantly outperform a textual classification based on the Loughran–McDonald or Apel–Blix Grimaldi dictionaries and a media-based measure of economic policy uncertainty.
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We propose a Hawkish-Dovish (HD) indicator that measures the degree of 'hawkishness' or 'dovishness' of the media's perception of the ECB's tone at each press conference. We compare two methods to calculate the indicator: semantic orientation and Support Vector Machines text classification. We show that the latter method tends to provide more stable and accurate measurements of perception on a labelled test set. Furthermore, we demonstrate the potential use of this indicator with several applications: we perform a correlation analysis with a set of interest rates, use Latent Dirichlet Allocation to detect the dominant topics in the news articles, and estimate a set of Taylor rules. The findings provide decisive evidence in favour of using an advanced text mining classification model to measure the medias perception and the Taylor rule application confirms that communication plays a significant role in enhancing the accuracy when trying to estimate the bank's reaction function. JEL codes: C02, C63, E52, E58 In recent years communication became increasingly important in central banks. In particular, after the financial crisis, communication has increasingly qualified as a genuine policy tool able to steer interest rates in financial markets and drive expectations on the course of monetary policy. With official interest rates approaching zero and thereby reducing their effectiveness, various forms of forward guidance (i.e. a verbal commitment on the future course of monetary policy unconditional or conditional to some economic event) were added to the standard monetary policy toolkit existing out of interest rates and refinancing instruments for the banking sector. The growing relevance of communication in the conduct of monetary policy was mirrored by a rising interest of academicians and practitioners. In particular, a branch of economic research increasingly focused on the role of communication in adding valuable information besides what is already contained in macroeconomic variables, and in revealing policy makers preferences on the course of monetary policy with a view to enhance predictability. If the traditional approach consists in analysing how information events impact financial market developments and expectations of future policy moves, more recently analysis shifted towards analysing the language used by the central bank in its statements and how such message is perceived by its stakeholders. This paper contributes to the latter with a numerical indicator, called HD index (after the initials of hawkish and dovish), derived from media reports on the ECB press conference. Combining concepts and techniques developed in the context of computational linguistics and data mining, the indicator extracts relevant information on ECB monetary policy as reported by external observers and may therefore be interpreted as how media perceive the central banks monetary policy messages. For practical reasons, the perception is expressed on a numerical interval between-1 (most dovish) and +1 (most hawkish). In other words, the indicator indicates whether the perceived tone on monetary policy communication is predominantly on the tightening side (hawk-ish perception) or rather on the loosening side (dovish perception). Although the approach to quantify communication is not new, the approach proposed in this paper is original in various dimensions. First, the indicator does not measure directly official central bank communication but how such communication is received and interpreted with the crucial support of data mining techniques. Second, two different techniques are employed to compute the HD index: one based on the semantic orientation (SO) and the second on text classification using Support Vector Machines (SVM). The former, the most commonly used by researchers, measures how often the ECB is mentioned in a news article together with a number of given hawkish and dovish words or expressions, while the latter, computationally more complex, uses a classification model to predict the tone of an article. Both methods are applied to a data set of around 9,000 articles published between January 1999 and March 2016 in order to assess which methodology produces better results. Based on various criteria (event ECB Working Paper 2085, July 2017 2 analysis, correlations with actual interest rates and classification method) the SVM methodology tends to produce better and more reliable results. Third, in addition to its superiority on the SO, the SVM classification model can be used to analyse the terms most frequently employed by media in relation to a likely future course of monetary policy. Finally, an expanded Taylor rule framework including the HD index alongside traditional variables measuring inflation expectations and economic slack, is presented. Results suggest that the significance of the HD index as well as a relatively better fit confirm the positive role of ECB communication in enhancing the accuracy when trying to estimate the bank's reaction function, and thus that, on average, the ECB messages are correctly understood by its media watchers.
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We investigate whether the anchoring properties of longrun inflation expectations in the United States, the euro area, and the United Kingdom have changed around the economic crisis that erupted in mid-2007. We document that surveybased measures of long-run inflation expectations remained fairly stable around 2 percent in the euro area, fluctuated above 2 percent in the United States, and drifted up to about 2.5 percent in the United Kingdom. Expectations measures extracted from inflation-indexed bonds and inflation swaps became much more volatile in 2007. Moreover, structural break tests show that their sensitivity to news about inflation and other domestic macroeconomic variables—a measure of anchoring—increased during the crisis, and in particular during the heightened turmoil triggered by the collapse of Lehman Brothers. While liquidity premia and technical factors have significantly influenced the behavior of inflation-indexed markets since the outburst of the crisis, we show that these factors did not contaminate the relationship between macroeconomic news and financial market-based inflation expectations at the daily frequency. While our evidence is consistent with the idea that long-run inflation expectations may have become less firmly anchored during the crisis, problems in measuring expectations accurately make it difficult to draw definitive conclusions.
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This paper compares the evolution of long-run inflation expectations in the euro area and the United States, using evidence from financial markets and surveys of professional forecasters. Survey data indicate that long-run inflation expectations are reasonably well anchored in both economies but reveal substantially greater dispersion across forecasters' long-horizon projections of US inflation. Analysis of daily data on inflation swaps and nominal-indexed bond spreads, which gauge compensation for expected inflation and inflation risk, also suggests that long-run inflation expectations are more firmly anchored in the euro area than in the United States. (JEL D84, E31, E37, E52, E58)
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Over the last two decades, communication has become an increasingly important aspect of monetary policy. These real-world developments have spawned a huge new scholarly literature on central bank communication—mostly empirical, and almost all of it written in this decade. We survey this ever-growing literature. The evidence suggests that communication can be an important and powerful part of the central bank’s toolkit since it has the ability to move financial markets, to enhance the predictability of monetary policy decisions, and potentially to help achieve central banks’ macroeconomic objectives. However, the large variation in communication strategies across central banks suggests that a consensus has yet to emerge on what constitutes an optimal communication strategy.
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This paper examines the effect of European Central Bank (ECB) communication on the price discovery process in the Euribor futures market using a new tick-by-tick data set. First, we show that two pieces of news systematically hit financial markets on Governing Council meeting days: the ECB policy rate decision and the explanation of its monetary policy stance. Second, we find that the unexpected component of ECB explanations has a significant and sizable impact on futures prices. Third, we investigate how communication interacts with learning by the public about the credibility of the central bank: financial market participants needed around three years, from 1999 through 2001, to learn how to interpret and believe ECB announcements. Finally, our results suggest that the Euribor futures market is efficient.
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We investigate the relationship between media sentiment and international equity prices using a new dataset of 4 million news articles published between 1991 and 2015. Three key results emerge. First, news sentiment robustly predicts (future) daily returns around the world. However, we find a sharp contrast between the effect of local news and that of global news: whereas local news optimism (pessimism) predicts a small and transitory increase (decrease) in local equity returns, global news sentiment has a larger impact on returns that does not reverse in the short run. Second, news sentiment affects local prices mainly through the investment decisions of foreign—rather than local—investors. Third, large variations in global news sentiment predominantly happen in the absence of new information about fundamentals, suggesting that movements in global sentiment capture variations in investors sentiment. Taken together, our findings illustrate the key role played by foreign news and investors sentiment in driving local asset prices.
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This paper demonstrates state-of-the-art text sentiment analysis tools while developing a new time-series measure of economic sentiment derived from economic and financial newspaper articles from January 1980 to April 2015. We compare the predictive accuracy of a large set of sentiment analysis models using a sample of articles that have been rated by humans on a positivity/negativity scale. The results highlight the gains from combining existing lexicons and from accounting for negation. We also generate our own sentiment-scoring model, which includes a new lexicon built specifically to capture the sentiment in economic news articles. This model is shown to have better predictive accuracy than existing “off-the-shelf” models. Lastly, we provide two applications to the economic research on sentiment. First, we show that daily news sentiment is predictive of movements of survey-based measures of consumer sentiment. Second, motivated by Barsky and Sims (2012), we estimate the impulse responses of macroeconomic variables to sentiment shocks, finding that positive sentiment shocks increase consumption, output, and interest rates and dampen inflation.
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We construct a new measure of uncertainty about Federal Reserve policy actions and their consequences, a monetary policy uncertainty (MPU) index. We evaluate the information content of our index and document the usefulness of our index in bridging periods of conventional and unconventional policy making. We also estimate the aggregate effects of shocks to MPU on output, credit spreads, and other variables. Finally, we investigate the transmission channels of MPU, finding that heightened MPU leads to protracted declines in firm investment through both real options and financial frictions channels.
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We use daily data on government bond yields and market-based inflation expectations to measure the announcement effects of unconventional monetary policy announcements in the euro area, focusing on their impact on ex-ante real interest rates. We find evidence of statistically significant effects of several announcements on real interest rates at maturities of two, five and ten years that operate partly through nominal interest rates and partly by raising inflation expectations. Announcements that exceeded market expectations significantly reduced nominal and real interest rates while announcements that disappointed expectations had the opposite effect.
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The classic papers by Newey and West (1987) and Andrews (1991) spurred a large body of work on how to improve heteroscedasticity- and autocorrelation-robust (HAR) inference in time series regression. This literature finds that using a larger-than-usual truncation parameter to estimate the long-run variance, combined with Kiefer-Vogelsang (2002, 2005) fixed-b critical values, can substantially reduce size distortions, at only a modest cost in (size-adjusted) power. Empirical practice, however, has not kept up. This article therefore draws on the post-Newey West/Andrews literature to make concrete recommendations for HAR inference. We derive truncation parameter rules that choose a point on the size-power tradeoff to minimize a loss function. If Newey-West tests are used, we recommend the truncation parameter rule S = 1.3T1/2 and (nonstandard) fixed-b critical values. For tests of a single restriction, we find advantages to using the equal-weighted cosine (EWC) test, where the long run variance is estimated by projections onto Type II cosines, using ν = 0.4T2/3 cosine terms; for this test, fixed-b critical values are, conveniently, tν or F. We assess these rules using first an ARMA/GARCH Monte Carlo design, then a dynamic factor model design estimated using a 207 quarterly U.S. macroeconomic time series.
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Media coverage of ECB's policy decisions has an impact on financial market expectations, and thus, on the monetary policy objectives of the ECB. In this article, we use a computational linguistic approach to extract the uncertainty tone emerging from media coverage of ECB's policy decisions during the period 1999M01–2014M08, the Media Uncertainty Index (MUI). We then relate the MUI to the interest rate setting procedure of the ECB. Our results suggest that the monetary institution implements an accommodative (restrictive) monetary policy in response to an increase (decrease) of the degree of uncertainty expressed by the media. Additional extensions show that (i) the ECB is more responsive to the uncertainty captured by the MUI in the pre-crisis era, while in the post-crisis era the ECB is more concerned by the uncertainty of the overall economic environment, as captured by the Economic Policy Uncertainty index (Baker et al., 2016) and that (ii) it (also) reacts to media's expressed uncertainty through its unconventional policy measures. Our findings shed some new light on the decision-making process of the ECB when it has to deal with the uncertainty ensuing from its past policy decision and the uncertainty of the overall economic environment, and thus, address an important issue related to the political economy of central banking.
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We study the effects of the announcements of ECB asset purchases and of financial stability measures in the euro area in the wake of the global financial crisis and the euro area sovereign debt crisis on 10-year government bond term premia in 11 euro area countries. We find that the term premia of euro area countries with higher sovereign risk, as measured by sovereign CDS spreads, decreased more in response to the announcements of asset purchases and financial stability measures. Term premia of countries with lowest sovereign risk either increased as in Germany, or were not significantly affected or fell slightly, as in the Netherlands and Finland.
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This paper examines the financial market impact of intermeeting communication of the members of the European Central Bank's Governing Council (GC) using high frequency data between July 2008 and January 2014. Constructing a rich dataset of GC members’ public statements (speeches, conference discussions and media interviews) between monetary policy meetings allows us to investigate a detailed pattern of market responses to the ad-hoc communication of central bankers. Using least squares and quantile regressions, we document the impact of policymakers’ public statements on interest rates and the stock market with very little or no impact on exchange rates. In general, we find little evidence that the timing, sequencing or content of communication matters in immediate response. On the contrary, the results suggest that the market concentrates on the communication of key members of the committee.
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Lagged dependent variables (LDVs) have been used in regression analysis to provide robust estimates of the effects of independent variables, but some research argues that using LDVs in regressions produces negatively biased coefficient estimates, even if the LDV is part of the data-generating process. I demonstrate that these concerns are easily resolved by specifying a regression model that accounts for autocorrelation in the error term. This actually implies that more LDV and lagged independent variables should be included in the specification, not fewer. Including the additional lags yields more accurate parameter estimates, which I demonstrate using the same data-generating process scholars had previously used to argue against including LDVs. I use Monte Carlo simulations to show that this specification returns much more accurate coefficient estimates for independent variables (across a wide range of parameter values) than alternatives considered in earlier research. The simulation results also indicate that improper exclusion of LDVs can lead to severe bias in coefficient estimates. While no panacea, scholars should continue to confidently include LDVs as part of a robust estimation strategy.
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We explore whether the tone of central bank communication matters for asset prices and find that tone changes have a significant effect on equity returns. Stock prices increase when tone becomes more positive and vice versa. Moreover, we find that positive tone changes are associated with increasing bond yields, lower implied equity volatility, lower variance risk premia, and lower credit spreads. Since we also show that tone changes are largely unrelated to current and future economic fundamentals, our results suggest that central bank tone matters for asset prices through a risk-based channel.
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This paper provides new evidence on the importance of inflation expectations for variation in nominal interest rates, based on both market-based and survey-based measures of inflation expectations. Using the information in TIPS break-even rates and inflation swap rates, I document that movements in inflation compensation are important for explaining variation in long-term nominal interest rates, unconditionally as well as conditionally on macroeconomic data surprises. Daily changes in inflation compensation and changes in long-term nominal rates generally display a close statistical relationship. The sensitivity of inflation compensation to macroeconomic data surprises is substantial, and it explains a sizable share of the macro response of nominal rates. The paper also documents that survey expectations of inflation exhibit significant co-movement with variation in nominal interest rates, as well as significant responses to macroeconomic news.
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We study how financial market participants process news from four major central banks — the Bank of England (BoE), the Bank of Japan (BoJ), the European Central Bank (ECB), and the Federal Reserve (Fed) — using a novel survey of 195 financial market participants from around the world. Our results indicate that, first, respondents rely more on media reports of central bank events than they do on self-monitoring. The only exceptions are interest rate decisions in the respondent’s home region. In general, the Fed is watched most closely, followed by the ECB, the BoJ, and the BoE. Second, ordered probit estimations reveal that the perceived reliability of media coverage is negatively associated with degree of self-monitoring and positively related to the probability of using media reports, particularly in the case of asset managers. The perceived importance of central bank events is positively related to the degree of self-monitoring in the case of traders. Finally, portfolio managers tend to self-monitor their home central bank more often than do respondents from other parts of the world.
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This is an analysis of the favorableness and extent of the media coverage of the Czech National Bank's (CNB) monetary policy decisions in the period of 2002–2007. An extensive set of articles published in the four most relevant Czech daily broadsheets is used along with parameters of the CNB's actual monetary policy decisions, related communication and variables characterizing the economic environment. The most appealing results are that those CNB decisions that surprised financial markets were not negatively perceived by the media and that interest rate changes increased both favorableness and extent of media coverage. Therefore, from the media coverage point of view, there was no need for too much smoothing when setting the interest rates.
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We survey the textual sentiment literature, comparing and contrasting the various information sources, content analysis methods, and empirical models that have been used to date. We summarize the important and influential findings about how textual sentiment impacts on individual, firm-level and market-level behavior and performance, and vice versa. We point to what is agreed and what remains controversial. Promising directions for future research are emerging from the availability of more accurate and efficient sentiment measures resulting from increasingly sophisticated textual content analysis coupled with more extensive field-specific dictionaries. This is enabling more wide-ranging studies that use increasingly sophisticated models to help us better understand behavioral finance patterns across individuals, institutions and markets.
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This paper studies the effect of sentiment on asset prices during the 20th century (1905 to 2005). As a proxy for sentiment, we use the fraction of positive and negative words in two columns of financial news from the New York Times. The main contribution of the paper is to show that, controlling for other well-known time-series patterns, the predictability of stock returns using news' content is concentrated in recessions. A one standard deviation shock to our news measure during recessions predicts a change in the conditional average return on the DJIA of twelve basis points over one day.
Article
Previous research uses negative word counts to measure the tone of a text. We show that word lists developed for other disciplines misclassify common words in financial text. In a large sample of 10-Ks during 1994 to 2008, almost three-fourths of the words identified as negative by the widely used Harvard Dictionary are words typically not considered negative in financial contexts. We develop an alternative negative word list, along with five other word lists, that better reflect tone in financial text. We link the word lists to 10-K filing returns, trading volume, return volatility, fraud, material weakness, and unexpected earnings.
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Using high-frequency euro–dollar exchange rates, we examine the effects of efforts by euro area central bankers to verbally support the euro. Based on a direction, a smoothing and a volatility criterion, we find little evidence that ECB verbal interventions were effective. The most important determinant of effectiveness is whether or not the verbal intervention is captured in the news report headline. Verbal interventions that coincide with releases of macroeconomic data are followed by lower exchange rate volatility. There is no difference in the effects of comments by ECB Executive Board members and NCB presidents.
Article
This paper studies the reaction of the conditional mean and volatility of the euro–dollar exchange rate to statements by European Central Bank and national central bank officials. We focus on comments on monetary policy and the external value of the euro. We find that the Bundesbank has dominated the news coverage. We conclude that ECB statements have mainly influenced conditional volatility. In some cases there are effects of statements on the conditional mean of the euro–dollar exchange rate. Efforts to talk up the euro have generally not been successful. There is also evidence of asymmetric reactions to news.
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The paper assesses the communication strategies of the Federal Reserve, the Bank of England, and the European Central Bank and their effectiveness. We find that the effectiveness of communication is not independent from the decision-making process. The paper shows that the Federal Reserve has been pursuing a highly individualistic communication strategy amid a collegial approach to decision making, while the Bank of England is using a collegial communication strategy and highly individualistic decision making. The European Central Bank (ECB) has chosen a collegial approach both in its communication and in its decision making. Assessing these strategies, we find that predictability of policy decisions and the responsiveness of financial markets to communication are equally good for the Federal Reserve and the ECB. This suggests that there may not be a single best approach to designing a central bank communication strategy. Copyright 2007 The Ohio State University.
Article
This paper introduces methods to compute impulse responses without specification and estimation of the underlying multivariate dynamic system. The central idea consists in estimating local projections at each period of interest rather than extrapolating into increasingly distant horizons from a given model, as it is done with vector autoregressions (VAR). The advantages of local projections are numerous: (1) they can be estimated by simple regression techniques with standard regression packages; (2) they are more robust to misspecification; (3) joint or point-wise analytic inference is simple; and (4) they easily accommodate experimentation with highly nonlinear and flexible specifications that may be impractical in a multivariate context. Therefore, these methods are a natural alternative to estimating impulse responses from VARs. Monte Carlo evidence and an application to a simple, closed-economy, new-Keynesian model clarify these numerous advantages.
Article
This paper explores whether there are systematic patterns as to when members of the decision-making committees of the Federal Reserve, the Bank of England and the European Central Bank communicate with the public, and under what circumstances such communication has the ability to move financial markets. The findings suggest that communication is generally seen as a tool to prepare markets for upcoming decisions, as it becomes more intense before committee meetings, and particularly so prior to interest rate changes. At the same time, markets react more strongly to communication prior to policy changes. Other instances where communication becomes more intense, or where financial markets become more responsive are also identified; even though these are more specific to the individual central banks, they are consistent with differences in the central banks' monetary policy strategies and communication policies.
Article
We study how investor sentiment affects the cross-section of stock returns. We predict that a wave of investor sentiment has larger effects on securities whose valuations are highly subjective and difficult to arbitrage. Consistent with this prediction, we find that when beginning-of-period proxies for sentiment are low, subsequent returns are relatively high for small stocks, young stocks, high volatility stocks, unprofitable stocks, non-dividend-paying stocks, extreme growth stocks, and distressed stocks. When sentiment is high, on the other hand, these categories of stock earn relatively low subsequent returns. Copyright 2006 by The American Finance Association.
Central Bank Tone and the Dispersion of Views within Monetary Policy Committees. Documents de Travail de l'OFCE 2020-02
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Giving content to investor sentiment: The role of media in the stock market
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Giving content to investor sentiment: The role of media in the stock market
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