The stability of global energy markets is fundamental to effective energy strategy, influencing national policy and corporate investment decisions. Extreme volatility, such as during the COVID-19 pandemic, exposes the limitations of conventional risk assessment tools and undermines strategic...

Forecasts that minimize mean squared forecast error (MSE) often exhibit excessive volatility, limiting their practical applicability. We address this accuracy smoothness trade-off by introducing a Multivariate Smooth Sign Accuracy (M-SSA) framework, which extracts smoothed components from...

Inflation dynamics reflect forces operating at different cycles, from short-lived shocks to longterm structural trends. We introduce the sum-of-the-cycles (SOC) method, which exploits this multifrequency structure of inflation for forecasting. SOC decomposes inflation into cyclical components,...

Die Weltwirtschaft wird im Jahr 2026 durch den Iran-Krieg und den damit einhergehenden sprunghaften Anstieg der Energiepreise spürbar belastet. Eine anhaltende Blockade der für den globalen Rohöl- und Gashandel wichtigen Straße von Hormus und die Zerstörung von Förderkapazitäten...

Public support for policy interventions depends on citizens' beliefs about their likely effects. We examine how individuals form such beliefs by studying their predictions of experimental outcomes in a policy-relevant setting, and why their predictions differ from expert benchmarks. We elicit...

Professional inflation forecasts contain valuable information but exhibit information frictions. We extract improved forecasts by explicitly modeling these frictions using the US Survey of Professional Forecasters data, and find that forecast rigidity increases systematically with horizon,...

We introduce a simple yet powerful method for enhancing mutual fund performance prediction by combining individual predictors into a composite predictor. This composite approach integrates information from 19 well-established return-based and portfolio holdings-based predictors from the...

We study the determinants of US dollar demand across market participants and traded instruments using survey-based exchange rate and macroeconomic expectations. Leveraging granular FX trading data and forward looking expectations, we present three results. First, currency investors increase...

We test whether forecast bias affects individual investors' stock trading by combining bias measures from laboratory experiments with administrative trade data. Forecast bias is positively associated with past excess returns of purchased stocks: Compared to contrarians, extrapolators purchase...

For many decades, time-series forecasting has been applied to different problems by scientists and industries. Many models have been introduced for the purpose of forecasting. These advancements have significantly improved the accuracy and reliability of predictions, especially in complex...

This paper analyzes three forecasting methods for commodity spot prices and applies them to copper prices. The first method uses futures prices from either LME or COMEX. The second method uses analysts' consensus expectations, reported by Bloomberg. The third method jointly uses futures and...

Public support for policy interventions depends on citizens' beliefs about their likely ef-fects. We examine how individuals form such beliefs by studying their predictions of experimental outcomes in a policy-relevant setting, and why their predictions differ from expert benchmarks. We elicit...

The Agricultural and Food Policy Center (AFPC) at Texas A&M University develops and maintains data to simulate 91 representative crop, dairy, and livestock operations in major production areas of 30 states. The chief purpose of this analysis is to project the economic viability of those farms by...

We examine whether aggregate "music mood" derived from globally popular songs can help forecast primary equity issuance. We build a Friday-anchored weekly panel that merges SEC EDGAR counts of priced Initial Public Offerings (IPOs) with features from the Spotify Daily Top 200 (audio descriptors...

This study forecasts inbound tourism demand for the United Kingdom, using monthly data from February 1989 to February 2020. In the empirical analysis, we evaluate and compare the performance of five machine learning models (decision trees, random forests, XGBoost, and support vector regression...

Stock price forecasting remains challenging due to the non-linear, noisy, and non-stationary nature of financial time series. Although LSTMs and Transformer-based models have improved sequential modeling, their ability to scale efficiently to long financial sequences remains limited. Recently,...

Klimawandel gilt seit geraumer Zeit als ein globaler Megatrend mit weitreichenden Folgen für das gesellschaftliche und wirtschaftliche Leben. Klimatische Veränderungen führen zu direkten Beeinträchtigungen der Natur. Daraus können vielfältige ökonomische Anpassungslasten entstehen. Im...

Planning for future healthcare needs is essential for ensuring the safe and effective delivery of healthcare services in the coming years. A number of studies have shown that demand for health and social care services will increase in Ireland in the coming years due to a growing and ageing...

Der Arbeitsmarkt in Deutschland ist weiterhin durch Stagnation gekennzeichnet. Bundesweit bleiben Beschäftigung und Arbeitslosigkeit 2026 im Vergleich zu 2025 nahezu unverändert. Auf Ebene der Bundesländer und der Agenturbezirke zeigen sich teilweise positive Entwicklungen, die jedoch bisher...

A growth mindset-a belief that intelligence is malleable rather than a fixed trait-is a crucial factor for educational success. I investigate whether a growth mindset also plays a role in students' post-graduation life outcomes, specifically, in the pursuit of higher education in a nationwide...

This work highlights a previously overlooked factor that contributes to bias in private inflation forecasts-ignorance of confidential monetary rules. Additionally, it examines how this ignorance indirectly affects policy rate settings. The model proposed reconciles biases in two key forecast...

Austria's economy is recovering over the projection period from a recession that, according to the revised National Accounts, proved comparably severe to Germany's. The rebound is driven by private consumption, while foreign trade in goods continues to contract for the time being. Residential...

We provide a parsimonious setup for forecasting U.S. GDP growth and the unemployment rate based on a few fundamental drivers. This setup yields forecasts that are reasonably accurate compared with private-sector and Federal Reserve forecasts over the 1984-2019 and post-COVID-19 pandemic periods....