This paper considers the Bank of England’s density forecasts and its revisions to quantify the effects of information flow on the financial markets and survey forecasters. Central banks increasingly rely on published forecasts to communicate their economic outlook to market participants. Point forecasts and their revisions have been shown to move financial markets. However, the effects of the higher-order moments have not been investigated thoroughly, primarily due to data limitations. The Bank of England, on the other hand, has been publishing information on its density forecasts since the late 1990s, making it useful for our analysis. Using daily information on the financial markets, we find that the updates of higher moments are more important in moving financial markets than the revisions to the first central moment of the density forecasts, making them relevant for monetary policy communication. Information about output matters more than information about inflation, and the effect of information is state-contingent. Finally, we see that the consensus forecast and disagreement among professional forecasters strongly correlate with updates in higher-order forecast moments.

Daily data obtained through web scraping allows for generating high-frequency signals for evaluating the effects of policies and supporting decision-making processes. The reliability of official price data in Russia has been questioned during the ongoing war in Ukraine. This study investigates the influence of this war and related sanctions on Russian official and online prices for different categories of goods before and after the war. A disaggregated analysis of price patterns finds significant differences in price dynamics following Russia's invasion of Ukraine, which may be attributed to the following international economic sanctions. In light of disruptions to traditional channels related to conflicts and political decisions, we contribute to the growing literature using online data to monitor real-time economic activity, price, and quantity evolution. We highlight the importance of political events and economic sanctions on pricing and consumption patterns in times of war and show that sanctions may have contributed to an average excess CPI level for Russia of 11.7%.

Since the Global Financial Crisis, a lively debate has emerged regarding the monetary policy rule the central bank of a small open economy (SOE) follows and should follow. By identifying the monetary policy rule that best fits historical data and minimizes central bank loss functions, this study contributes to this debate. We estimate a medium-scale micro-founded SOE model under various monetary policy rules using Israeli data from 1992 to 2019. Our results show that simple inflation targeting (IT) rules are more appropriate than hybrid rules targeting the exchange rate. Given central bank goals, shock uncertainty, and limited information, nominal income targeting rules may have been more desirable over the last three decades than IT rules.

Every financial crisis raises questions about how the banking market structure affects the real economy. Although low bank concentration may lower markups and foster bank risk-taking, controlled banking concentration systems appear more resilient to financial shocks. We use a nonlinear dynamic stochastic general equilibrium model with financial frictions to compare the transmissions of shocks under different competition and concentration configurations. Oligopolistic competition and concentration amplify the effects of the shocks relative to monopolistic competition. The transmission mechanism works through the markups, which are amplified when banking concentration is increased. According to financial stability and social welfare objectives, the desirable banking market structure is determined. Depending on policymakers' preferences, the banking concentration of five to seven banks balances social welfare and bank stability objectives.

We examine how the Federal Reserve (Fed) communicated during the COVID-19 pandemic and compares it with other periods of stress. This comparison uses novel dictionaries related to COVID-19, unconventional monetary policy (UMP), financial stability, and usual sentiment analysis and topic modeling. We show that Fed communication during the COVID-19 pandemic focused on financial stability, market volatility, social welfare, and UMP, and presented significant contextual uncertainty. We also compare Fed communication during the COVID-19 pandemic with the dot-com and global financial crises regarding content, sentiment, and timing. We find that Fed communication and actions were more reactive to the COVID-19 crisis than to other crises. We also show that declining financial stability sentiment in interest rate announcements and minutes precedes accommodative monetary policy decisions.

A consensus has emerged among economists that central banks cannot ignore employment and how monetary policies affect workers and employers. However, there is no agreement on the extent to which labour issues should be incorporated into operational frameworks or whether central banks should support structural reforms. In fact, more than 80% of the world’s central banks have no explicit employment objective. That said, given that labour issues can directly cause macroeconomic imbalances, many central banks, even those without explicit dual objectives, have incorporated labour indicators into their core policy frameworks. We assess the implicit mandate of the Bank of Canada and the European Central Bank, which, unlike the Federal Reserve, do not have an express labour mandate. To scrutinize modern central banking practices, we investigate the historical, legal, and extra-statutory data with regard to the primary objectives of central banks and how they interact with secondary objectives in practice. Our analysis shows that both the Global Financial Crisis and the recession triggered by COVID-19 have had tremendous impacts on the workforce, requiring immediate action and eventually changing the policy environment in which central banks operate. However, while neither the Bank of Canada nor the European Central Bank have an explicit dual mandate, the latter has been much more aggressive in pursuing labour objectives. We discuss the legality of this mandate transformation in light of the Bank of Canada Act and the European Union Treaty. Finally, we make a legal case for a more human-developmental approach to central banking, one that involves greater social and labour dimensions.

We present a hierarchical architecture based on recurrent neural networks for predicting disaggregated inflation components of the Consumer Price Index (CPI). While the majority of existing research is focused on predicting headline inflation, many economic and financial institutions are interested in its partial disaggregated components. To this end, we developed the novel Hierarchical Recurrent Neural Network (HRNN) model, which utilizes information from higher levels in the CPI hierarchy to improve predictions at the more volatile lower levels. Based on a large dataset from the US CPI-U index, our evaluations indicate that the HRNN model significantly outperforms a vast array of well-known inflation prediction baselines. Our methodology and results provide additional forecasting measures and possibilities to policy and market makers on sectoral and component-specific price changes.

We use text-mining techniques to measure the accessibility and quality of information within the texts of interest rate announcements published by the Bank of Israel over the past decade. We find that comprehension of interest rate announcements published by the Bank of Israel requires fewer years of education than interest rate announcements published by the Federal Reserve and the European Central Bank. In addition, we show that the sentiment within these announcements is aligned with economic fluctuations. We also find that textual uncertainty is correlated with the volatility of the domestic financial market.

We develop a behavioral New Keynesian model to analyze optimal monetary policy with heterogeneously myopic households and firms. Five key results are derived. First, our model reflects coherent microeconomic and aggregate myopia due to the consistent transition from subjective to objective expectations. Second, the optimal monetary policy entails implementing inflation targeting in a framework where myopia distorts agents’ inflation expectations. Third, price level targeting emerges as the optimal policy under output gap, revenue, or interest rate myopia. Under price level targeting, rational inflation expectations are a minimal condition for optimality under bounded rationality. Fourth, bounded rationality is not necessarily welfare-decreasing and is even associated with welfare gains for extreme cognitive discounting. Finally, our empirical results point to the behavioral model’s superiority over the rational model.

 

This article investigates how uncertainty impacts the effect of monetary policy surprises on stock returns. Using high-frequency US data, we demonstrate that stock markets respond more aggressively to monetary policy surprises during periods of high uncertainty. We also show that uncertainty asymmetrically influences the transmission of positive and negative monetary policy surprises to stock market prices. The amplifying effect of uncertainty is found to be stronger for expansionary shocks than for contractionary shocks. Our robustness analysis confirms that financial uncertainty has a significant role in shaping the influence of monetary policy on the stock market.

Significant shifts in the composition of consumer spending as a result of the COVID-19 crisis can complicate the interpretation of official inflation data, which are calculated by the Central Bureau of Statistics (CBS) based on a fixed basket of goods. We focus on Israel as a country that experienced three lockdowns, additional restrictions that significantly changed consumer behavior, and a successful vaccination campaign that has led to the lifting of most of these restrictions. We use credit card spending data to construct a consumption basket of goods representing the composition of household consumption during the COVID-19 period. We use this synthetic COVID-19 basket to calculate the adjusted inflation rate that should prevail during the pandemic period. We find that the differences between COVID-19-adjusted and CBS (unadjusted) inflation measures are transitory. Only the contribution of certain goods and services, particularly housing and transportation, to inflation changed significantly, especially during the first and second lockdowns. Although lockdowns and restrictions in developed countries created a significant bias in inflation weighting, the inflation bias remained unexpectedly small and transitory during the COVID-19 period in Israel.

Each person’s characteristics may influence that person’s behaviors and outcomes. This study builds and uses a new database to estimate experts’ performance and boldness based on their experience and characteristics. Our study classifies experts providing inflation forecasts based on their education, experience, gender, and environment. We provide alternative interpretations of factors affecting experts’ inflation forecasting performance, boldness, and pessimism by linking behavioral economics, the economics of education, and forecasting literature. The study finds that an expert with previous experience at a central bank appears to have a lower propensity for predicting deflation.

The global financial crisis (GFC) triggered the use of macroprudential policies imposed on the banking sector. Using bank-level panel data for Israel for the period 2004–2019, we find that domestic macroprudential measures changed the composition of bank credit growth but did not affect the total credit growth rate. Specifically, we show that macroprudential measures targeted at the housing sector moderated housing credit growth but tended to increase business credit growth. We also find that accommodative monetary policy surprises tended to increase bank credit growth before the GFC. We show that accommodative monetary policy surprises increased consumer credit when interacting with macroprudential policies targeting the housing market. Accommodative monetary policy interacted with nonhousing macroprudential measures to increase total credit.

Non-Technical Summary
 

We review several existing text analysis methodologies and explain their formal application processes using the open-source software R and relevant packages. Several text mining applications to analyze central bank texts are presented.

Uncertainty about an economy's regime can change drastically around a crisis. An imported crisis such as the global financial crisis in the euro area highlights the effect of foreign shocks. Estimating an open-economy nonlinear dynamic stochastic general equilibrium model for the euro area and the United States including Markov-switching volatility shocks, we show that these shocks were significant during the global financial crisis compared with periods of calm. We describe how US shocks from both the real economy and financial markets affected the euro area economy and how bond reallocation occurred between short- and long-term maturities during the global financial crisis. Importantly, the estimated nonlinearities when domestic and foreign financial markets influence the economy, should not be neglected. The nonlinear behavior of market-related variables highlights the importance of higher-order estimation for providing additional interpretations to policymakers.

Governments, central banks, and private companies make extensive use of expert and market-based forecasts in their decision-making processes. These forecasts can be affected by terrorism, a factor that should be considered by decision-makers. We focus on terrorism as a mostly endogenously driven form of political uncertainty and assess the forecasting performance of market-based and professional inflation and exchange rate forecasts in Israel. We show that expert forecasts are better than market-based forecasts, particularly during periods of terrorism. However, the performance of both market-based and expert forecasts is significantly worse during such periods. Thus, policymakers should be particularly attentive to terrorism when considering inflation and exchange rate forecasts.

This paper presents an analysis of the stimulants and consequences of money demand dynamics. By assuming that household's money holdings and consumption preferences are not separable, we demonstrate that the interest-elasticity of demand for money is a function of the household's preference to hold real balances, the extent to which these preferences are not separable in consumption and real balances, and trend inflation. An empirical study of U.S. data revealed that there was a gradual fall in the interest elasticity of money demand of approximately one-third during the 1970s due to high trend inflation. A further decline in the interest-elasticity of the demand for money was observed in the 1980s due to the changing household preferences that emerged in response to financial innovation. These developments led to a reduction in the welfare cost of inflation that subsequently explains the rise in monetary neutrality observed in the data.

Central banks' monetary policy rules being consistent with policy objectives are a fundamental of applied monetary economics. We seek to determine, first, which of the central bank's rules are most in line with the historical data for the US economy and, second, what policy rule would work best to assist the central bank in reaching its objectives via several loss function measures. We use Bayesian estimations to evaluate twelve monetary policy rules from 1955 to 2017 and over three different sub-periods. We find that when considering the central bank's loss functions, the estimates often indicate the superiority of NGDP level targeting rules, though Taylor-type rules lead to nearly identical implications. However, the results suggest that various central bank empirical rules, be they NGDP or Taylor type, are more appropriate to achieve the central bank's objectives for each type of period (stable, crisis, recovery).