2,321 research outputs found
Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7
No full textIn this paper, we use survey data to analyze the accuracy, unbiasedness, and the efficiency of professional macroeconomic forecasts. We analyze a large panel of individual forecasts that has not been analyzed in the literature so far. We provide evidence on the properties of forecasts for all G7 counties and for four diffierent macroeconomic variables. Our results show a high degree of dispersion of forecast accuracy across forecasters. We also find that there are large diffierences in the performance of forecasters not only across countries but also across diffierent macroeconomic variables. In general, forecasts tend to be biased in situations where forecasters have to respond to large structural shocks or gradual changes in the trend of a variable. Furthermore, while a sizable fraction of forecasters seem to smooth their GDP forecasts significantly, this does not apply to forecasts made for other macroeconomic variables.Evaluating forecasts, Macroeconomic Forecasting, Rationality, Survey Data, Fixed-Event Forecasts
Sticky Information Phillips Curves: European Evidence
No full textWe estimate the sticky information Phillips curve model of Mankiw and Reis (2002) using survey expectations of professional forecasters from four major European economies. Our estimates imply that inflation expectations in France, Germany and the United Kingdom are updated about once a year, in Italy about once each six months.Inflation expectations, sticky information, Phillips curve, inflation persistence
Accentuation of Jonas Rėza's Psalter of 1625
No full textStraipsnyje trumpai apžvelgiama dabartinių kalbų kirčio ženklų istorija – nuo Antikos kalbininko Aristofano Bizantiečio žymėtų akūto, gravio ir cirkumflekso iki Mažvydo Katekizme pažymėto į riestinį cirkumfleksą panašaus ženklo, Baltramiejaus Vilento raštų, D. Kleino gramatikos, J. Rėzos psalmyno ,,Psalteras Dowido“ kirčio ženklų. Išsamiau straipsnyje analizuojamas 1625 m. J. Rėzos psalmyno kirčiavimas, iš graikų perimti kirčio ženklai, paties autoriaus įsivestas kirčio ženklas. Straipsnyje taip pat aptariama Rėzos psalmyne vartotų kirčio ženklų funkcijos, kirčio ženklų vartojimo įvairavimas, sąsajos tarp psalmyno kirčiavimo ir D. Kleino gramatikos Reikšminiai žodžiai: Akūtas; Gravis; Cirkumfleksas; Psalmynas; Lietuvių kalbos istorija; KirčiavimasThis article gives a brief overview of the history of the accent marks of languages from Antiquity linguist Aristophanes of Byzantium marked the acute accent, grave accent and circumflex accent until the sign similar to a tilde-shaped circumflex marked in Mažvydas’ Catechism, and accent signs of Baltramiejus Vilentas’ writings, Daniel Klein‘s grammer, and Jonas Rhesa’s Psalter of David. The article gives a comprehensive analysis of the accentuation made by Jonas Rhesa in the psalter, accent marks taken from Greek, and an accent mark developed by the author himself. The article also discusses the functions of the accent marks used in Rhesa’s psalter, the variation of the usage of accent marks and the interaction between the accentuation of the psalter and D. Klein’s grammer
Understanding the Transmission of Macroeconomic Information: The Role of Central Bank Communication and Local Information for the Formation of Macroeconomic Expectations
No full textIn this dissertation, I analyze various aspects of the transmission of macroeconomic information and review methods for testing multiple hypotheses. Chapter 1 investigates the clarity of speeches by the European Central Bank’s (ECB) Executive Board over time. Since its inception, the readability of ECB speeches has improved, especially in those intended for general audiences and delivered by female speakers. The improvement in clarity is gradual and not tied to changes in the board’s composition or major economic events. We also find that complex speeches are associated with negative media sentiment about the ECB. Chapter 2 analyzes how the complexity of ECB speeches affects trading in financial markets. Trading activity rises when speeches contain new monetary policy information but declines when this information is communicated in a complex way. ECB presidents’ speeches primarily drive this effect. The results underscore the crucial role of clear communication for effective monetary policy transmission. Chapter 3 shifts focus to how German firms form expectations about economic growth. Using new survey data, we show that firms rely on local information, including regional economic conditions, industry performance, and their own business situation, especially when the firms are small. Our findings are consistent with theories of rational inattention. Chapter 4 addresses the simultaneous testing of multiple null hypotheses. Parametric tests that incorporate information from all subsidiary null hypotheses perform best. These tests exhibit higher statistical power than the well-known minimum P-value test and are computationally more efficient than a non-parametric approach.
Collectively, this dissertation provides insights into the importance of clarity in central bank communication, the role of local information in forming expectations, and methods for testing multiple null hypotheses.Diese Dissertation befasst sich mit der Übermittlung makroökonomischer Informationen sowie Methoden zum Testen mehrerer Hypothesen. Kapitel 1 untersucht die Verständlichkeit der Reden des Direktoriums der Europäischen Zentralbank (EZB). Seit der Gründung der EZB hat sich die Verständlichkeit der Reden verbessert, insbesondere derer, die für ein allgemeines Publikum bestimmt sind und die von Rednerinnen gehalten werden. Die Verbesserung ist graduell und nicht von der Zusammensetzung des Direktoriums oder bedeutenden wirtschaftlichen Ereignissen beeinflusst. Die Analyse zeigt außerdem, dass komplexe Reden mit negativer Medienberichterstattung über die EZB in Verbindung stehen. Kapitel 2 analysiert, wie die Komplexität der EZB-Reden den Handel auf Finanzmärkten beeinflusst. Die Handelsaktivität steigt, wenn Reden neue Informationen zur Geldpolitik enthalten, sinkt jedoch, wenn diese Informationen auf komplexe Weise kommuniziert werden. Dieser Effekt wird hauptsächlich durch die Reden der EZB-Präsidenten verursacht und unterstreicht die entscheidende Rolle klarer Kommunikation für eine effektive Übermittlung von Geldpolitik. Kapitel 3 verlagert den Fokus auf die Erwartungsbildung deutscher Firmen. Anhand von Umfragedaten zeigen wir, dass sich die Wachstumserwartungen von Firmen auf lokale Informationen wie regionale wirtschaftliche Bedingungen, die Lage in ihrer Branche und die eigene Geschäftssituation stützen. Dies ist insbesondere bei kleinen Firmen der Fall. Unsere Ergebnisse stützen die Theorie der rationalen Unaufmerksamkeit. Kapitel 4 behandelt Tests von Nullhypothesen, die aus mehreren Teilnullhypothesen bestehen. Parametrische Tests, die Informationen aller Teilnullhypothesen verwenden, haben eine höhere Trennschärfe als der weit verbreitete Minimum-P-Wert-Test und beanspruchen weniger Rechenleistung als ein nicht-parametrischer Test. Zusammen bieten die Kapitel Einblicke in die Bedeutung von Verständlichkeit in der Zentralbankkommunikation, die Rolle lokaler Informationen bei der Bildung von makroökonomischen Erwartungen und Methoden zum Testen von multiplen Nullhypothesen
Disagreement among Forecasters in G7 Countries
No full textUsing the Consensus Economics dataset with individual expert forecasts from G7 countries we investigate determinants of disagreement (crosssectional dispersion of forecasts) about six key economic indicators. Disagreement about real variables (GDP, consumption, investment and unemployment) has a distinct dynamic from disagreement about nominal variables (in
ation and interest rate). Disagreement about real variables intensifes strongly during recessions, including the current one (by about 40 percent in terms of the interquartile range). Disagreement about nominal variables rises with their level, has fallen after 1998 or so (by 30 percent), and is considerably lower under independent central banks (by 35 percent). Cross-sectional dispersion for both groups increases with uncertainty about the underlying actual indicators, though to a lesser extent for nominal series. Countryby- country regressions for inflation and interest rates reveal that both the level of disagreement and its sensitivity to macroeconomic variables tend to be larger in Italy, Japan and the United Kingdom, where central banks became independent only around the mid-1990s. These findings suggest that more credible monetary policy can substantially contribute to anchoring of expectations about nominal variables; its eects on disagreement about real variables are moderate.disagreement, survey expectations, monetary policy, forecasting
Essays on Information Disclosure, Uncertainty Perception, and Expectations in Financial Markets
No full textThis thesis encompasses four self-contained chapters besides the introduction. Each chapter is written so that it can be read independently, however, they are closely related to each other in terms of methods and object of study. The next two chapters, Chapters 2 and 3, are the result of collaborative work with Matthias Schnaubelt and Oleg Seifert. These chapters examine the impact of interactions between analysts and executives on options' implied volatility across various maturities. Chapter 2 analyzes the financial and economic implications of these interactions using an event-study approach. Chapter 3 outlines the text-processing methodology used for topic model evaluation, and selection. Chapter 4 examines the relationship between social media data evaluated at a high-frequency level and stock market uncertainty. Chapter 5 concludes with an analysis of the effect of daily news on inflation expectations and risk-premium at different horizons. This is derived from the term structure of inflation-protected securities. Below, we provide a brief discussion of the motivation and main results for each chapter and the connections among them
Disagreement among forecasters in G7 countries
No full textUsing the Consensus Economics dataset with individual expert forecasts from G7 countries we investigate determinants of disagreement (crosssectional dispersion of forecasts) about six key economic indicators. Disagreement about real variables (GDP, consumption, investment and unemployment) has a distinct dynamic from disagreement about nominal variables (inflation and interest rate). Disagreement about real variables intensifies strongly during recessions, including the current one (by about 40 percent in terms of the interquartile range). Disagreement about nominal variables rises with their level, has fallen after 1998 or so (by 30 percent), and is considerably lower under independent central banks (by 35 percent). Cross-sectional dispersion for both groups increases with uncertainty about the underlying actual indicators, though to a lesser extent for nominal series. Country-by-country regressions for inflation and interest rates reveal that both the level of disagreement and its sensitivity to macroeconomic variables tend to be larger in Italy, Japan and the United Kingdom, where central banks became independent only around the mid-1990s. These findings suggest that more credible monetary policy can substantially contribute to anchoring of expectations about nominal variables; its effects on disagreement about real variables are moderate. JEL Classification: E31, E32, E37, E52, C53disagreement, forecasting, monetary policy, survey expectations
Aufsätze über Zeitreihenprognosen und Maschinelles Lernen
No full textThis dissertation investigates how modern machine learning (ML) methods, with a particular focus on multi-task learning (MTL) frameworks, can enhance forecasts in financial and macroeconomic contexts. Chapter 1 outlines the limitations of traditional econometric approaches in environments characterized by nonlinearity, structural breaks, and mixed-frequency data, and motivates the use of ML models capable of exploiting shared information across related prediction tasks. Chapter 2 evaluates the performance of temporal fusion transformers (TFT) for forecasting realized volatility (RV) of US stocks. It shows that models with sector-level pooling significantly outperform asset-specific or fully pooled models, and that TFT surpasses traditional volatility models and common ML benchmarks, especially in volatile market phases. Chapter 3 extends this approach by introducing a two-dimensional MTL framework to jointly forecast RV across industry portfolios and forecast horizons. Using long short-term memory (LSTM) models with structured parameter sharing, the study finds that sharing information across both dimensions improves forecast accuracy, particularly at short horizons. Chapter 4 applies MTL to macroeconomic nowcasting using disaggregated US labor market and inflation data. Results show that MTL enhances nowcast accuracy compared to single-task and traditional models, with the optimal degree of information sharing depending on task-specific heterogeneity. Chapter 5 embeds MTL into a mixed frequency data sampling (MIDAS) setting by combining it with different MIDAS techniques to nowcast sectoral employment using high-frequency indicators. Nonlinear MTL models, particularly those based on extreme gradient boosting (XGBoost), outperform benchmarks and highlight the value of preserving intra-month dynamics. Overall, the dissertation demonstrates that combining MTL with flexible ML architectures offers a powerful framework for improving forecast quality and stability in complex economic settings
Neuronale Netze für Zeitreihenprognosen: Architekturen, Evaluation und Unsicherheitsquantifizierung für Makroökonomie und Rohstoffpreise
No full textThe dissertation addresses forecasting with recurrent neural networks (RNNs) specifically designed for macroeconomic time series. Chapter 1 introduces the topic of the dissertation and relates the individual chapters. Chapter 2 presents the open-source software package ProsperNN, where neural network architectures specifically designed to handle settings found in macroeconomic forecasting are implemented, along with analysis tools for the models and their forecast. A case study demonstrates the competitiveness of the neural networks and adapt the analysis tools accordingly. Chapter 3 highlights the importance of a rigorous evaluation setup for time series with low predictability that are commonly observed in exchange rates or stock prices. Various machine learning and statistical methods fail to outperform the naive forecast, which underscores the relevance of this baseline in benchmarking settings, especially for complex forecasting methods. Chapter 4 employs a Historical Consistent Neural Network (HCNN) on a steel price dataset. The model is explained in detail and the employed concepts are related to the literature, among others, by deriving an equivalent representation as a basic RNN. Compared to statistical models and a standard RNN, HCNNs achieve the highest forecast accuracy and deliver the largest reduction in procurement costs in a simulation setting. Chapter 5 evaluates the uncertainty quantification of sample-based forecasts created with RNNs. It shows that computational-demanding approaches can be well approximated by approaches with fewer trainable parameters, while incurring only a slight loss in forecast performance. Overall, the dissertation contributes to the application of RNNs to macroeconomic time series, with a focus on neural network architectures, evaluation strategies, and uncertainty quantification.Die Dissertation beschäftigt sich mit rekurrenten neuronalen Netzwerken (RNN), die speziell für makroökonomische Zeitreihen entwickelt wurden. Kapitel 1 erläutert das Thema der Dissertation und zeigt die Zusammenhänge zwischen den Kapiteln auf. Kapitel 2 stellt das frei verfügbare Softwarepaket ProsperNN vor, das Architekturen neuronaler Netzwerke sowie Analyse-Methoden für die Modelle und deren Prognosen bereitstellt. Die Implementierungen sind speziell auf die Anforderungen von makroökonomischen Prognosen zugeschnitten. In einer Beispielstudie wird die Konkurrenzfähigkeit der neuronalen Netzwerk Architekturen gezeigt und die Analyse-Methoden angewandt. Kapitel 3 stellt die Bedeutung einer rigorosen Evaluationsstrategie für Zeitreihen mit geringer Prognostizierbarkeit dar, die zum Beispiel bei Wechseloder Aktienkursen vorliegt. Zahlreiche Methoden aus den Bereichen des maschinellen Lernens und der Statistik erreichen eine gerringere Prognosegüte als die naive Prognose. Dies hebt die Relevanz dieser einfachen Methode in Vergleichsstudien hervor, besonders wenn komplexe Prognosemethoden untersucht werden. Kapitel 4 wendet ein Historical Consistent Neural Network (HCNN) zur Prognose von Stahlpreisen an. Das Modell wird detailliert beschrieben und die eingebauten Konzepte werden in Bezug zur Fachliteratur gesetzt, unter anderem durch das Herleiten einer äquivalenten Darstellung als klassisches RNN. Verglichen mit statistischen Methoden und einem RNN haben HCNNs die höchste Prognosegenauigkeit und können in einer Simulation die Beschaffungskosten am stärksten reduzieren. Kapitel 5 bewertet die Unsicherheitsdarstellung von Prognosen, die auf Basis verschiedener Szenarien mit RNNs erstellt werden. Es zeigt, dass Methoden mit hohem Ressourcenbedarf ohne großen Verlust in der Prognosegenauigkeit gut mit Methoden mit weniger trainierbaren Parametern angenähert werden können. Insgesamt trägt die Dissertation dazu bei, wie RNNs auf makroökonomische Zeitreihen angewendet werden. Dabei liegt der Fokus auf den Architekturen der neuronalen Netze, der Evaluationsstrategie und der Unsicherheitsdarstellung
What macroeconomic shocks affect the German banking system? Analysis in an integrated micro-macro model
No full textWe analyze what macroeconomic shocks affect the soundness of the German banking system and how this, in turn, feeds back into the macroeconomic environment. Recent turmoils on the international financial markets have shown very clearly that assessing the degree to which banks are vulnerable to macroeconomic shocks is of utmost importance to investors and policy makers. We propose to use a VAR framework that takes feedback effects between the financial sector and the macroeconomic environment into account. We identify responses of a distress indicator for the German banking system to a battery of different structural shocks. We find that monetary policy shocks, fiscal policy shocks, and real estate price shocks have a significant impact on the probability of distress in the banking system. We identify some differences across type of banks and different distress categories, though these differences are often small and do not show any systematic patterns. --VAR,banking sector stability,sign restriction approach
- …
