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Optimal monetary policy studies typically rely on a single structural model and identification of model-specific rules that minimize the unconditional volatilities of inflation and real activity. In our proposed approach, we take a large set of structural models and look for the model-robust rules that minimize the volatilities at those frequencies that policymakers are most interested in stabilizing. Compared to the status quo approach, our results suggest that policymakers should be more restrained in their inflation responses when their aim is to stabilize inflation and output growth at specific frequencies. Additional caution is called for due to model uncertainty.

This study examines nonlinear effects of global and country-specific geopolitical risk uncertainty on stock returns of Brazil, India, Indonesia, South Africa, and Turkey, employing a three-regime Markov-switching approach. This study discovers that the Markov-switching model captured the impacts of global and country-specific geopolitical risk uncertainty on stock returns of all fragile emerging economies, while the linear framework does not. Hence, the effects of both risk factors are nonlinear and asymmetric on stock market returns. The empirical results uncover that global geopolitical risk uncertainty can affect stock market performance both positively and negatively, which depend on contemporaneous time, lag time, volatility regimes, and stock market. The results also reveal that the country-specific political unrest adversely influences the stock market performance of four fragile emerging economies throughout the volatility regimes, with exception of the Indian stock market performance. Therefore, investors should follow market volatility behavior before taking risk of global and domestic geopolitical uncertainty.

In the aftermath of the global financial crisis, central banks started being confronted with severe challenges that led to an unprecedented policy response in terms of the size and variety of monetary policy measures. One such measure centred on central banks communicating to the public more explicitly their future policy actions in order to influence expectations. In the case of interest rates, as the standard policy rate approached the effective lower bound, major central banks began providing forward guidance (FG) on interest rates with the intention of lowering expectations of future short-term rates. While FG had been used in certain jurisdictions before the crisis, its prominence in the monetary policy toolkit grew substantially in the aftermath of the crisis. This occasional paper summarises the work carried-out by the Eurosystem Taskforce on the macroeconomic impact of rate forward guidance (FG) in an environment of large central bank balance sheets. The analysis presented covers the period up to February 2020 so the implications of the pandemic as well as the ECB's strategy review are beyond the scope of the Taskforce's mandate. The paper describes the analytical challenges associated with assessing rate FG on account of the relative novelty of these policies, the lack of well-established empirical results and the sensitivity of model predictions to the expectations formation process. To overcome and address these challenges, the Taskforce took stock of all the available infrastructure and analysis within in the Eurosystem, and where needed, developed structural and empirical models and approaches to assess the macroeconomic impact of rate FG in an environment of large central bank balance sheets.

Monitoring and predicting the economy���s short-term dynamics are vital in economic decision making. However, major economic indicators are released with a substantial delay, and policy-makers must therefore rely on sophisticated models to accurately estimate them. Consumers are increasingly adopting electronic payment methods���a trend that accelerated dramatically during the COVID-19 pandemic. The vast amounts of high-frequency data generated by electronic payments are available almost in real time. And thanks to recent advances in artificial intelligence and machine learning, we have sophisticated econometric tools for analyzing non-traditional data and nonlinear relationships. In this paper we aim to show that payments data and machine learning models are useful in predicting short-term macroeconomic dynamics, such as nowcasting gross domestic product and retail and wholesale trade in Canada. We also address the challenges of interpretation and overfitting of machine learning models in order to improve their performance and our understanding of their predictions. We find that payments data that capture a variety of economic transactions are useful for estimating the state of the economy in real time. Moreover, the econometric tools provided by machine learning can capture large and nonlinear effects from a crisis. We also find that a few payment streams in Canada���s retail payment systems become significantly more important during periods of crisis, which substantially improves our model performance during those periods., Il est primordial de suivre et de pr��dire la dynamique �� court terme de l�����conomie pour prendre des d��cisions ��conomiques. Toutefois, les principaux indicateurs ��conomiques sont publi��s avec un long d��calage. Par cons��quent, les autorit��s publiques doivent recourir �� des mod��les sophistiqu��s pour les estimer avec pr��cision. Les consommateurs adoptent de plus en plus les modes de paiement ��lectronique, et cette tendance s���est fortement acc��l��r��e durant la pand��mie de COVID-19. Les gros volumes de donn��es �� haute fr��quence g��n��r��es par les paiements ��lectroniques sont accessibles presque en temps r��el. Gr��ce aux r��cents progr��s de l���intelligence artificielle et de l���apprentissage automatique, nous disposons d���outils ��conom��triques perfectionn��s pour analyser des donn��es non traditionnelles et des relations non lin��aires. Dans cette ��tude, nous avons comme objectif de montrer que les donn��es de paiement et les mod��les d���apprentissage automatique sont utiles pour pr��dire la dynamique macro��conomique �� court terme, y compris les pr��visions du produit int��rieur brut et du commerce de gros et de d��tail au Canada pour la p��riode en cours. Nous examinons aussi les d��fis li��s �� l���interpr��tation et au surajustement des mod��les d���apprentissage automatique afin d���am��liorer leur performance et notre compr��hension de leurs pr��visions. Nous constatons que les donn��es de paiement qui couvrent diverses transactions ��conomiques sont efficaces pour estimer la situation ��conomique en temps r��el. De plus, les outils ��conom��triques issus de l���apprentissage automatique permettent de rendre compte des effets importants et non lin��aires d���une crise. Nous observons aussi que quelques cat��gories de paiements dans les syst��mes de paiement de d��tail du Canada deviennent beaucoup plus importantes en p��riode de crise, ce qui am��liore consid��rablement la performance de notre mod��le durant de telles p��riodes.

Why does the short-term slope of the yield curve predict recessions? We explore the economic forces underlying Treasury yields' fluctuations and highlight the roles of a tight monetary policy stance and expectations of lower inflation in predicting downturns. While the monetary policy stance is still accommodative, indicating a low recession probability, the negative inflation slope points to higher odds of a recession within a year. An aggressive removal of policy accommodation increases the recession probability to 60%.

This paper summarises the findings of the Eurosystem's Expert Group on Inflation Expectations (EGIE), which was one of the 13 work streams conducting analysis that fed into the ECB's monetary policy strategy review. The EGIE was tasked with (i) reviewing the nature and behaviour of inflation expectations, with a focus on the degree of anchoring, and (ii) exploring the role that measures of expectations can play in forecasting inflation. While it is households' and firms' inflation expectations that ultimately matter in the expectations channel, data limitations have meant that in practice the focus of analysis has been on surveys of professional forecasters and on market-based indicators.Regarding the anchoring of inflation expectations, this paper considers a number of metrics: the level of inflation expectations, the responsiveness of longer-term inflation expectations to shorter-term developments, and the degree of uncertainty. Different metrics can provide conflicting signals about the scale and timing of potential unanchoring, which underscores the importance of considering all of them. Overall, however, these metrics suggest that in the period since the global financial and European debt crises, longer-term inflation expectations in the euro area have become less well anchored. Regarding the role measures of inflation expectations can play in forecasting inflation, this paper finds that they are indicative for future inflationary developments. When it comes to their predictive power, both market-based and survey-based measures are found to be more accurate than statistical benchmarks, but do not systematically outperform each other. Beyond their role as standalone forecasts, inflation expectations bring forecast gains when included in forecasting models and can also inform scenario and risk analysis in projection exercises performed using structural models. In terms of the implications for the ECB's economic and monetary analysis going forward, the work of the EGIE essentially highlights the need for (i) more data on households' and firms' inflation expectations, (ii) a comprehensive framework for assessing (un)anchoring and (iii) further considerations regarding the use of observed expectation measures in forecasting models.

The secular decline in the equilibrium real interest rate observed over the past decades has materially limited the room for policy-rate reductions in recessions, and has led to a marked increase in the incidence of episodes where policy rates are likely to be at, or near, the effective lower bound on nominal interest rates. Using the ECB's New Area-Wide Model, we show that, if unaddressed, the effective lower bound can cause substantial costs in terms of worsened macroeconomic performance, as rejected in negative biases in inflation and economic activity, as well as heightened macroeconomic volatility. These costs can be mitigated by the use of nonstandard instruments, notably the joint use of interest-rate forward guidance and large-scale asset purchases. When considering alternatives to inflation targeting, we find that make-up strategies such as price-level targeting and average-inflation targeting can, if they are well-understood by the private sector, largely undo the negative biases and heightened volatility induced by the effective lower bound.

This paper proposes an econometric framework for nowcasting the monetary policy stance and decisions of the European Central Bank (ECB) exploiting the ow of conventional and textual data that become available between two consecutive press conferences. Decompositions of the updated nowcasts into variables' marginal contribution are also provided to shed light on the main drivers of the ECB's reaction function at every point in time. In out-of-sample nowcasting experiments, the model provides an accurate tracking of the ECB monetary policy stance and decisions. The inclusion of textual variables contributes signifi- cantly to the gradual improvement of the model performance.

"The spread of COVID-19 has caused large-scale loss of life and economic damage. This pandemic has had a swift effect on the macroeconomy, posing a new and different shock to the Canadian economy. Governments have responded in many ways, including through public health measures, fiscal stimulus and monetary policy. Policy-makers seek to understand the current state of the economy for their COVID-19 support to be effective. However, major economic indicators are released with a substantial delay. This problem is usually dealt with by using a linear model of past economic variables. But this is not the best approach presently, given the large and nonlinear effects of COVID-19 on the economy. In this paper, we develop a model to predict the current state of the economy—known as nowcasting—using retail payments system data and machine learning. The Canadian retail payments data aid in understanding the current state of the economy because they include many types of transactions and are available daily. These data features are ideal for macroeconomic nowcasting during a crisis. The flexibility of machine learning can help capture the large and nonlinear effects of the COVID-19 shock. We find that our model—compared with a benchmark model—has a significant increase in prediction accuracy, measured as a 15 to 45 percent reduction in forecast error.", "La propagation de la COVID-19 a causé des pertes de vie et des dégâts économiques à grande échelle. La pandémie a rapidement eu des répercussions sur la macroéconomie, ce qui a provoqué un choc nouveau et différent pour l’économie canadienne. Les gouvernements ont réagi de nombreuses façons, notamment au moyen de mesures sanitaires, de programmes de relance budgétaire et de la politique monétaire. Les autorités publiques cherchent à comprendre l’état actuel de l’économie afin de fournir un soutien efficace en réponse à la COVID-19. Toutefois, les principaux indicateurs économiques sont publiés avec un long décalage. On contourne souvent ce problème en utilisant un modèle linéaire qui comprend des variables économiques passées. Actuellement, ce n’est pas la meilleure approche, compte tenu des effets importants et non linéaires de la pandémie sur l’économie. Dans notre étude, nous élaborons un modèle servant à prévoir l’état actuel de l’économie – soit un modèle de prévision immédiate – en utilisant les données du système de paiement de détail et l’apprentissage automatique. Les données sur les paiements de détail au Canada facilitent la compréhension de la situation économique actuelle, puisqu’elles comprennent différents types de transactions et sont disponibles quotidiennement. Ces données sont idéales pour faire des prévisions macroéconomiques immédiates lors d’une crise. La flexibilité de l’apprentissage automatique peut aider à rendre compte des effets importants et non linéaires du choc de la COVID-19. Nous constatons que, comparativement à un modèle de référence, notre modèle améliore de façon considérable la précision des prévisions, entraînant une diminution de 15 à 45 % des erreurs de prévision."

From 2013 up to the launch of the ECB's strategy review in January 2020, inflation in the euro area was low and over-predicted. This low inflation during the years 2013-19 can be attributed to a combination of interconnected factors. Cyclical developments account for a substantial share of the fall in underlying inflation, mainly in the first part of the low inflation period. Additionally, there is evidence that an underestimation of the amount of economic slack and less well-anchored longer-term inflation expectations, in combination with monetary policy in the euro area being constrained by the effective lower bound, have played an important role in the long period of subdued inflation. Ongoing disinflationary structural trends (such as globalisation, digitalisation and demographic factors) are likely to have had a dampening effect on inflation over the last few decades, but were in themselves not the main drivers of low inflation in the euro area from 2013 to 2019. However, as they could not have been easily offset by interest rate policy in an effective lower bound environment, they might also have contributed to the more subdued inflation dynamics in the euro area from 2013 to 2019.

The paper compares price level targeting and inflation targeting regimes in a New Keynesian model with bounded rationality. Economic agents form their expectations using heuristics - they choose between a few simple rules based on their past forecasting performance. Two main specifications of the price level targeting model are examined - the agents form expectations either about price level or about inflation, which is ex ante not equivalent because of sequential nature of the model. In addition, several formulations of the forecasting rules are considered. Both regimes are assessed by loss function comparison. According to the results, price level targeting is preferred in the case with expectations created about price level under the baseline calibration; but it is sensitive to some model parameters. Furthermore, when expectations are created about inflation, price level targeting over time loses credibility and leads to divergence of the economy. On the other hand, inflation targeting model functions stably. Therefore, while potential benefits of price level targeting have been confirmed under certain assumptions, the results suggest that inflation targeting constitutes more robust choice for monetary policy.

This paper discusses the role of economic and monetary analysis in the monetary policy strategy of the European Central Bank (ECB). Both areas of analysis have evolved since the 2003 strategy review. Economic analysis has assigned an increasingly relevant role to the Eurosystem and ECB staff macroeconomic projections in forming a view on the medium-term outlook for economic activity and inflation. Furthermore, its focus has strengthened with regard to structural trends in shaping key economic relationships. Similarly, monetary analysis has shifted in focus: while the 2003 review emphasised the information value of monetary dynamics for detecting risks to price stability over medium-term to longer-term horizons, the focus of monetary analysis has increasingly been redirected to the assessment of monetary policy transmission. This evolution has opened a gap between the formal description of the strategy following the 2003 review and the practice of economic and monetary analysis in informing the ECB's policy deliberations. This paper concludes by presenting options for closing this gap and aligning the strategy formulation with the evolved role of economic and monetary analysis.

Many central banks conduct economic field research involving in-depth interviews with external parties. But very little is known about how this information is used and its importance in the formation of monetary policy. We address this gap in the literature through a thematic analysis of open-ended interviews with senior central bank economic and policy staff who work closely with policy decision-makers. We find that these central bankers consider information from field research programs not just useful but also an essential input for monetary policy making. They use this information in conjunction with quantitative tools primarily to inform their near-term forecasts. The information is considered most valuable at potential turning points in the economy when uncertainty about the pace of economic growth is heightened (in the advent of large shocks to the economy) and when timely official data are not available or are viewed as unreliable. Senior staff also place a high value on maintaining a reliable and credible sample of representative economic agents that can be accessed on an ongoing basis and very quickly when required., Beaucoup de banques centrales mènent des recherches sur le terrain au cours desquelles elles effectuent des entretiens approfondis avec des acteurs du tissu économique de leur pays. Cependant, on en sait très peu sur la manière dont les renseignements ainsi recueillis sont utilisés et sur l’importance qu’ils revêtent dans la conduite de la politique monétaire. Pour remédier à cette lacune, nous réalisons une analyse thématique d’entretiens à questions ouvertes menés auprès de cadres supérieurs de banques centrales chargés des questions d’analyse et de politique économiques et qui travaillent de près avec les décideurs de leur institution. Nous constatons que, pour ces cadres, les renseignements obtenus lors des recherches sur le terrain sont non seulement utiles, mais aussi essentiels pour la formulation de la politique monétaire. Les cadres se servent de ces renseignements conjointement avec des outils quantitatifs, principalement pour éclairer leurs prévisions à court terme. Ces renseignements s’avèrent très précieux dans deux cas : quand l’économie pourrait se trouver à un point de retournement compte tenu de l’incertitude élevée entourant le rythme de croissance économique (lorsque l’économie subit des chocs importants); et quand des données officielles à jour ne sont pas disponibles ou qu’elles ne sont pas considérées comme fiables. Les cadres supérieurs accordent aussi une grande importance au maintien d’un échantillon fiable et crédible d’agents économiques représentatifs qu’ils peuvent consulter régulièrement et très rapidement, au besoin.

An increasing number of emerging and developing countries have adopted or are transitioning towards full-fledged inflation targeting (FFIT) as the main monetary policy framework to anchor inflation. In this paper, we explore the FFIT regime as a means for Mauritius to achieve stable inflation, anchor inflationary expectations and establish credibility in committing monetary policy towards price stability as its primary goal. This paper reviews and highlights issues experienced with the current monetary policy framework and the challenges in transitioning towards FFIT. Given that forecasting is central to FFIT, we develop a practical model-based forecasting and policy analysis system (FPAS) to support transition to FFIT, taking into account structural features and shocks that are specific to the Mauritius economy.

The present paper studies the effect of monetary policy on inflation and output within a New Keynesian model with Experience-Based Learning (EBL) that renders expectations heterogeneous across age groups. Under EBL, the age-distribution directly affects the composition of aggregate expectations which gives rise to a novel channel by which the demographic structure of an economy affects monetary policy: the Experience Channel. Relative to models with homogeneous and age-independent expectations, we show that EBL weakens the pass-through of monetary policy on aggregate demand. This affects monetary policy transmission in two ways. First, the impact response of inflation and output to monetary policy shocks is less pronounced since the response of expectations under EBL is muted. Second, the response of inflation is more persistent, since the interest rate sensitivity of aggregate demand is weaker. Moreover, EBL changes the classical monetary policy trade-off between output and inflation stabilisation under supply shocks relative to models with ageindependent expectations. First, for a given inflation volatility, output is always less volatile due to the reduced sensitivity of expectations to monetary policy. Second, under EBL, the trade-off becomes more severe in ageing economies. We show that this effect is largely driven by the Experience Channel.

The Swedish economy is strongly dependent on global economic developments, which is re‡ected in generally strong empirical relationships between Swedish and foreign macroeconomic variables. It is, however, diffi cult for standard open-economy dynamic stochastic general equilibrium (DSGE) models to generate substantial cross-country spillovers; see e.g. the seminal paper of Justiniano and Preston (2010). We present a two-region DSGE model that better captures the dependence on global economic developments than previous models. It is estimated on data for Sweden and an aggregate of its main trading partners, the euro area and the United States, for the period 1995Q2-2018Q4. To capture the strong empirical relationships between Sweden and the foreign economy, we assume that global shocks to e.g. technology, real interest rates, financial risk, and firm and consumer sentiment directly affect both economies, while their impact on each economy may differ. We also allow for a ‡exible specification of the demand for Swedish exports to better account for the ‡uctuations in Swedish trade. Finally, headline and core in‡ation are distinguished by the introduction of consumption of energy goods, which allows for a more detailed and realistic analysis of in‡ation developments. This new model, named MAJA (Modell för Allmän JämviktsAnalys), is used by the Riksbank for interpretation of economic developments, forecasting, scenarios, and policy analysis. It builds on the work of Christiano, Eichenbaum, and Evans (2005) and Smets and Wouters (2003) and the Riksbank's previous models, Ramses I and Ramses II (see Adolfson et al. (2007) and Adolfson et al. (2013), respectively).

The business cycle is alive and well, and real variables respond to it more or less as they always did. Witness the Great Recession. In ation, in contrast, has gone quiescent. This paper studies the sources of this disconnect using VARs and an estimated DSGE model. It finds that the disconnect is due primarily to the muted reaction of inflation to cost pressures, regardless of how they are measured - a flat aggregate supply curve. A shift in policy towards more forceful inflation stabilization also appears to have played some role by reducing the impact of demand shocks on the real economy. The evidence rules out stories centered around changes in the structure of the labor market or in how we should measure its tightness.

We analyze the performance of a broad range of nowcasting and short-term forecasting models for a representative set of twelve old and six new member countries of the European Union (EU) that are characterized by substantial differences in aggregate output variability. In our analysis, we generate ex-post out-of-sample nowcasts and forecasts based on hard and soft indicators that come from a comparable set of identical data. We show that nowcasting works well for the new EU countries because, although that variability in their GDP growth data is larger than that of the old EU economies, the economic significance of nowcasting is on average somewhat larger.

We study the incidence and severity of lower-bound episodes and the efficacy of three types of state-dependent policies - forward guidance about the future path of interest rates, large-scale asset purchases and spending-based fiscal stimulus - in ameliorating the adverse consequences stemming from the effective lower bound on nominal interest rates. In particular, we focus on the euro area economy and examine, using the ECB's New Area-Wide Model, the consequences of the lower bound both for the near-term economic outlook, characterised by persistently low nominal interest rates and inflation, and in a lasting low-real-interest-rate world. Our findings suggest that, if unaddressed, the lower bound can have very substantial costs in terms of worsened macroeconomic performance. Forward guidance, if fully credible, is most powerful and can largely undo the distortionary effects due to the lower bound. A combination of imperfectly credible forward guidance, asset purchases and fiscal stimulus is almost equally effective, in particular when asset purchases enhance the credibility of the forward guidance policy via a signalling effect.