This study analyzes the volatility spillover effects in the US stock market (S&P500) and cryptocurrency market (BGCI) using intraday data during the COVID-19 pandemic. As the potential drivers of portfolio diversification, we measure the asymmetric volatility transmission on both markets. We...

This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude...

Learning-by-doing is a fundamental concept in economics but a challenging one to document in high-skilled settings due to non-random assignment of workers to tasks and lacking performance measures. Our paper overcomes these challenges in the context of heart attack treatments in Sweden, where we...

This paper shows that belief‐driven economic fluctuations are a general feature of many determinate macroeconomic models. In environments with hidden state variables, forecast‐model misspecification can break the link between indeterminacy and sunspots by establishing the existence of...

Historically, exchange rate forecasting models have exhibited poor out-of-sample performances and were inferior to the random walk model. Monthly panel data from 1973 to 2014 for ten currency pairs of OECD countries are used to make out-of sample forecasts with artificial neural networks and...

This paper develops a large-scale application to improve the labour market matching process with model- and algorithm-based statistical methods. We use comprehensive administrative data on employment biographies covering individual and job-related information of workers in Germany. We estimate...

Purpose: Developments in Industry 4.0 technologies and Artificial Intelligence (AI) have enabled data-driven manufacturing. Predictive maintenance (PdM) has therefore become the prominent approach for fault detection and diagnosis (FD/D) of induction motors (IMs). The maintenance and early FD/D...

The development of entrepreneurship competence considering a broad view of entrepreneurship requires a systematic approach to determine the validated content of learning and methodological basis for supporting learners' entrepreneurial attitudes and behaviour. There is still relatively little...

Entrepreneurship is considered a key driver for economic growth. Therefore, more and more studies are investigating the role and effectiveness of entrepreneurship education. In this context, the present study is aimed at investigating the effectiveness of entrepreneurship programs, with a...

This paper argues that the persistence of greenfield foreign direct investment (FDI) comes from information frictions. First, our simple social learning model shows that, through signaling effects, information frictions generate persistent greenfield FDI inflows. Second, we show empirically that...

We study an extended version of a sender-receiver signaling game-a context-signaling (CS) game that involves external contextual cues that provide information about a sender's private information state. A formal evolutionary analysis of the investigated CS game shows that ambiguous signaling...

This paper views teacher quality through the human capital perspective. Teacher quality exhibits substantial growth over teachers' careers, but why it improves is not well understood. I use a human capital production function nesting On-the-Job-Training (OJT) and Learningby- Doing (LBD) and...

This paper views teacher quality through the human capital perspective. Teacher quality exhibits substantial growth over teachers’ careers, but why it improves is not well understood. I use a human capital production function nesting On-the-Job-Training (OJT) and Learning-by-Doing (LBD) and...

This paper analyses the pathways of technology diffusion through social networks, following the experimental introduction of new technologies in Guinea-Bissau. In the context of an agricultural extension project, we document both the direct effects of this intervention and subsequent diffusion...

This paper introduces a new algorithm for exploiting time-series predictability-based patterns to obtain an abnormal return, or alpha, with respect to a given benchmark asset pricing model. The algorithm proposes a deterministic daily market timing strategy that decides between being fully...

The energy transition potentially poses an existential risk for major international oil companies (IOCs) if they fail to adapt to low-carbon business models. Projections of energy futures, however, are met with diverging assumptions on its scale and pace, causing disagreement among IOC...

A heterogeneous expectations model is provided, where private agents facing policy ignorance have to learn about the underlying fundamentals via a signal extraction problem. The model is estimated on a U.S. data set using Bayesian approach. The empirical results imply that the improvement in...

This paper evaluates the predictive performance of machine learning techniques in estimating time-varying betas of US stocks. Compared to established estimators, tree-based models and neural networks outperform from both a statistical and an economic perspective. Random forests perform the best...

While the role of organizational learning in improving firms’ performance is well documented, there are still questions surrounding the dominant forces driving technological learning. This is particularly true in the electricity industry where the growth of renewable technologies has been...

In the context of risk-based portfolio construction and pro-active risk management, finding robust predictors of future realised volatility is paramount to achieving optimal performance. Volatility has been documented in economics literature to exhibit pronounced persistence with clusters of...

The strategic management of knowledge spillovers to employee ventures may provide firms with knowledge spill-ins, or the potential to learn from the ventures they have spun out. However, the mechanisms underlying knowledge spill-ins and their importance for external learning in uncertain...