We investigate how optimal attention allocation of green-motivated investors changes information asymmetry in financial markets and thus affects firms‘ financing costs. To guide our empirical analysis, we propose a model where investors with heterogeneous green preferences endogenously allocate limited attention to learn market-level or firm-specific fundamental shocks. We find that a higher fraction of green investors in the market leads to higher aggregate attention to green firms. This reduces the information asymmetry of green firms, leading to higher price informativeness and lower leverage. Moreover, the information asymmetry of brown firms and the market increases with the share of green investors. Therefore, greater green attention is associated with less market efficiency. We provide empirical evidence to support our model predictions using U.S. data. Our paper shows how the growing demand for sustainable investing shifts investors‘ attention and benefits eco-friendly firms.

We examine the effect of sovereign credit impairments on the pricing of syndicated loans following rating downgrades in the borrowing firms' countries of domicile. We find that the sovereign ceiling policies used by credit rating agencies create a disproportionately adverse impact on the bounded firms' borrowing costs relative to other domestic firms following their sovereign's rating downgrade. Rating-based regulatory frictions partially explain our results. On the supply-side, loans carry a higher spread when granted from low-capital banks, non-bank lenders, and banks with high market power. We further document an operating demand-side channel, contingent on borrowers' size, financial constraints, and global diversification. Our results can be attributed to the relative bargaining power between lenders and borrowers: relationship borrowers and non-bank dependent borrowers with alternative financing sources are much less affected.

Using a supervised machine learning framework on a large training set of questions and answers, we identify 1,364 trigrams that signal nonanswers in earnings call questions and answers (Q&A). We show that this glossary has economic relevance by applying it to contemporaneous stock market reactions after earnings calls. Our findings suggest that obstructing the flow of information leads to significantly lower cumulative abnormal stock returns and higher implied volatility. As both our method and glossary are free of financial context, we believe that the measure is applicable to other fields with a Q&A setup outside the contextual domain of financial earnings conference calls.

This paper provides new evidence of herding due to non- and fundamental information in global equity markets. Using quantile regressions applied to daily data for 33 countries, we investigate herding during the Eurozone crisis, China’s market crash in 2015–2016, in the aftermath of the Brexit vote and during the Covid-19 Pandemic. We find significant evidence of herding driven by non-fundamental information in case of negative tail market conditions for most countries. This study also investigates the relationship between herding and systemic risk, suggesting that herding due to fundamentals increases when systemic risk increases more than when driven by non-fundamentals. Granger causality tests and Johansen’s vector error-correction model provide solid empirical evidence of a strong interrelationship between herding and systemic risk, entailing that herding behavior may be an ex-ante aspect of systemic risk, with a more relevant role played by herding based on fundamental information in increasing systemic risk.

Die wirtschaftliche Aktivität und das Ausfallrisiko staatlicher Schulden beeinflussen sich gegenseitig. Sinkt die wirtschaftliche Aktivität einer Volkswirtschaft, steigt wegen fallender Steuereinnahmen das Risiko, dass der Staat Zinszahlungen und Tilgungen auf Staatsanleihen nicht zurückzahlen kann. Umgekehrt kann das staatliche Ausfallrisiko seinerseits die wirtschaftliche Aktivität beeinflussen. Steigt das Ausfallrisiko, geraten Banken unter Druck, die Staatsanleihen in ihren Bilanzen führen, und reduzieren die Kreditvergabe an Unternehmen. In der Konsequenz sinkt die wirtschaftliche Aktivität. Dieser Beitrag nutzt hochfrequente News-Ticker-Daten zur Ableitung politischer Ereignisse und davon ausgelöster Fluktuationen im Staatsschuldenrisiko. Diese allein politisch bedingten Fluktuationen ermöglichen es, den Effekt des Staatsschuldenrisikos auf die wirtschaftliche Aktivität zu messen, ohne dass die Schätzung von der gegenläufigen Beziehung der Variablen beeinträchtigt wird. Das Vorgehen wird am Beispiel Italiens erläutert.

In this article, we investigate the divergence between credit ratings (CRs) and Moody's market-implied ratings (MIRs). Our evidence shows that rating gaps provide incremental information to the market regarding issuers' default risk over CRs alone in the short horizon and outperform CRs over extended horizons. The predictive ability of rating gaps is greater for more opaque and volatile issuers. Such predictability was more pronounced during the 2008 financial crisis but weakened in the post-Dodd-Frank Act period. This finding is consistent with credit rating agencies' efforts to improve their performance when facing regulatory pressure. Moreover, our analysis identifies rating-gap signals that do (do not) lead to subsequent Moody's actions to place issuers on negative outlook and watchlists. We find that negative signals from MIR gaps have a real economic impact on issuers' fundamentals such as profitability, leverage, investment, and default risk, thus supporting the recovery-efforts hypothesis.

The world price of oil is determined by the interactions of multiple producers and consumers who face different constraints and shocks. We show how this feature of the oil market can be used to estimate local and global elasticities of supply and demand and provide a rich set of testable restrictions. We develop a novel approach to estimation based on full-information maximum likelihood that generalizes the insights from granular instrumental variables. We conclude that the supply responses of Saudi Arabia and adjustments of inventories have historically played a key role in stabilizing the price of oil. We illustrate how our structural model can be used to analyze how individual producers and consumers would dynamically adapt to a geopolitical event such as a major disruption in the supply of oil from Russia.

The Halle Institute for Economic Research (IWH) is a member of AIECE (Association d'Instituts Europeens de Conjoncture Economique/Association of European Conjuncture Institutes), an association of independent European institutes involved in surveying economic conditions and developments, and in short-term macroeconomic forecasting. The main objective of the Association is to stimulate the exchanges between its members with a view to improve their insight into international economic developments. This ranges from the exchange of statistical or institutional information to discussions on economic policy Guidelines to common research activities. The AIECE organises between its members an exchange of view, of information and of literature on international economic developments, in particular in Europe. The Association provides the framework for joint activities of its members in areas of common interest. Its structure allows its members to develop common views on the future cyclical development. In order to meet these objectives the Association has half-yearly plenary meetings, centred around a general report on the European conjuncture prepared in turn by one of the members in cooperation with the other member institutes, but also with discussions of the working group reports and of special surveys prepared by member institutes. In Spring 2023, the report was written by the Halle Institute for Economic Research (IWH).

The Halle Institute for Economic Research (IWH) is a member of AIECE (Association d'Instituts Europeens de Conjoncture Economique/Association of European Conjuncture Institutes), an association of independent European institutes involved in surveying economic conditions and developments, and in short-term macroeconomic forecasting. The main objective of the Association is to stimulate the exchanges between its members with a view to improve their insight into international economic developments. This ranges from the exchange of statistical or institutional information to discussions on economic policy Guidelines to common research activities. The AIECE organises between its members an exchange of view, of information and of literature on international economic developments, in particular in Europe. The Association provides the framework for joint activities of its members in areas of common interest. Its structure allows its members to develop common views on the future cyclical development. In order to meet these objectives the Association has half-yearly plenary meetings, centred around a general report on the European conjuncture prepared in turn by one of the members in cooperation with the other member institutes, but also with discussions of the working group reports and of special surveys prepared by member institutes. In Spring 2023, the report was written by the Halle Institute for Economic Research (IWH).

Micro-data on robots have been very sparse in Germany so far. Consequently, a dedicated section has been introduced in the IAB Establishment Panel 2019 that includes questions on the number and type of robots used. This article describes the background and development of the survey questions, provides information on the quality of the data, possible checks and steps of data preparation. The resulting data is aggregated on industry level and compared with the frequently used robot data by the International Federation of Robotics (IFR) which contains robot supplier information on aggregate robot stocks and deliveries.