After two years of recession, Austria's economic output is likely to stagnate in 2025. WIFO expects GDP growth of 1.2 percent in 2026. The upturn in the global economy should then give the Austrian economy some momentum again, driven by both exports and domestic demand.

As investors increasingly use Environmental, Social, and Governance (ESG) criteria, a key challenge remains: ESG data is typically reported annually, while financial markets move much faster. This study investigates whether incorporating annual ESG scores can improve monthly stock return...

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...

German and European migration policy operates in permanent crisis mode. Sudden increases in irregular immigration create a sense of loss of control, which is instrumentalised by populist forces. This has generated great interest in quantitative migration predictions. High expectations are placed...

Word embeddings are vectors of real numbers associated with words, designed to capture semantic and syntactic similarity between the words in a corpus of text. We estimate the word embeddings of the European Central Bank's introductory statements at monetary policy press conferences by using a...

The farm-level economic impacts of the FAPRI 2025 Baseline on representative crop and livestock operations are projected in this report, assuming provisions of the 2018 Farm Bill are in effect and continue throughout the 2025-2030 projection period. The current representative farm analysis...

This study examines the out-of-sample predictability of expected skewness of oil price returns, which serves as a metric for global future risks, as we show statistically through the association with crises of different nature, for stock returns of 10 (8 advanced plus two emerging) countries...

Understanding the developments of atmospheric ethane is essential for better identifying the anthropogenic sources of methane, a major greenhouse gas with high global warming potential. While previous studies have focused on analyzing past trends in ethane and modeling the inter-annual...

Studies show that innovation information disclosed by listed firms affects the decision of non-listed firms and their stakeholders. This paper explores whether innovation information disclosed within a specific list board (i.e., market) also spills over to other list boards. Based on the...

Using a novel and unique panel dataset of individual-level professional forecasts at short, medium, and very-long horizons, we provide new stylized facts about survey forecasts. We present direct evidence that forecasters use multivariate models in an environment with imperfect information about...

This paper introduces a new predictive analytics model for forecasting stock price trends in financial assets traded on major stock exchanges worldwide and the Colombian Stock Exchange. The model is built on a probability space definition that consists of a measurable space derived from...

Under inflation forecast targeting, central banks such as the ECB adjust policy to keep expected inflation on target. We evaluate the ECB’s inflation forecasts: they are unbiased and efficient but contain little information at forecast horizons beyond three quarters. In a New Keynesian model...

To effectively manage natural gas dispatchability, the energy industry needs to precisely analyze the seasonal trends of natural gas production and consumption. However, most predictive models demand data pretreatment and are labor-intensive. To address this, a novel seasonal discrete grey...

In this paper, I examine the value that investors place on analysts who exhibit lower forecast error volatility. Building on prior empirical research, I develop a theoretical model that formalizes the role of error volatility in investment decision-making. I propose an investment strategy that...

We predict earnings for forecast horizons of up to five years by using the entire set of Compustat financial statement data as input and providing it to state-of-the-art machine learning models capable of approximating arbitrary functional forms. Our approach improves prediction one year ahead...