Around three quarters of Bitcoin transactions take place off-chain. Despite their significance, the vast majority of the empirical literature on cryptocurrencies focuses on on-chain transactions. This paper presents one of the first analysis of both on- and off-chain demand- and supply-side...

Background: In the current context of increasing competitiveness and complexity in markets, accurate demand forecasting has become a key element for efficient production planning. Methods: This study implements recurrent neural networks (RNNs) to predict raw material demand using historical...

This paper studies the relationship between market concentration and aggregate productivity when firmlevel demand emerges from past marketing investments. Granular firms may invest in demand both to complement their productivity and to amplify market power-this second force can create persistent...

The empirical migration literature often identifies the labor market effects of immigration using exogenous variation of migration concentration across sectors. However, this approach differences out macroeconomic effects which occur in all sectors. We apply macroeconomic time series methods to...

We study why free public health insurance in India exhibits persistently low utilisation despite high out of pocket health expenses. Using panel data from the Young Lives Survey and the rollout of the Arogyasri scheme in Andhra Pradesh, we distinguish the roles of informal financial and...

We study why free public health insurance in India exhibits persistently low utilisation despite high out of pocket health expenses. In the context of the Arogyasri program in Andhra Pradesh, we distinguish the roles of informal financial and information networks in shaping adoption....

This study leverages high-frequency foot-traffic data from SafeGraph to estimate demand shocks in customer-facing establishments across New York City's retail, service, and health sectors. Recognizing that variations in foot traffic can arise from both unpredictable demand shocks and firm-driven...

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...

Der Beitrag liefert einen systematischen Überblick zur außerklinischen Intensivpflege (AKI) in Deutschland im Zeitraum von 2018 bis 2022. Auf Basis von AOK-Daten von 18.363 AOK-Versicherten mit AKI werden erstmals umfassende deskriptive Ergebnisse zu den demografischen und...

We propose a demand estimation approach that leverages unstructured data to infer substitution patterns. Using pre-trained deep learning models, we extract embeddings from product images and textual descriptions and incorporate them into a mixed logit demand model. This approach enables demand...

Around three quarters of Bitcoin transactions take place off-chain. Despite their significance, the vast majority of the empirical literature on cryptocurrencies focuses on on-chain transactions. This paper presents one of the first analysis of both on- and off-chain demand- and supply-side...

There is limited theoretical understanding of cost pass-through in markets where prices are dispersed. This paper analyzes cost pass-through within a framework that encompasses many models in the price dispersion literature where consumers vary in the number of firms they consider. We...

We study identification of differentiated product demand from marketlevel data when product characteristics can be endogenous. Past work suggests nonparametric identification may be impossible: that is, in addition to standard price instruments, exogenous characteristic-based instruments are...

Products produced by multiproduct firms can be linked through demand linkages (cannibalization), supply linkages (joint production), or both. We analyze how these within-firm linkages shape the propagation of shocks - such as tariffs - across products and markets and affect firm performance...

We test whether AI-generated news images affect outlet demand and trust. In a preregistered experiment with 2,870 UK adults, the same article was paired with a wireservice photo (with/without credit) or a matched AI image (with/without label). Average newsletter demand changes little. Ex-post...

This study proposes a new deep learning (DL)-based approach for multi-item demand forecasting in multi-wave distribution networks. In modern merchandising supply systems, traditional forecasting techniques such as moving averages and autoregressive integrated moving average (ARIMA) models are...

This paper examines how shifts in investor demand influence firm financing and investment decisions. For identification, the paper exploits a large-scale MSCI methodo logical reform that mechanically redefined the stock weights in major international equity benchmark indexes, changing the...

We estimate demand for five conversational AI use cases - administrative assistance, studying, wellness, friendship, and romance - using a preregistered, within-respondent conjoint experiment in a U.S. online sample (N=1,989). Purpose dominates interest: instrumental uses rank highest, romance...

The research aims to analyse the influence of selected factors on the demand for urban public transport in the Czech Republic. Urban public transport is important publicly provided service worldwide. In the Czech Republic this means public ownership of transport companies and massive subsidies...

Marginal utility (MU) theories of consumer demand assume that consumers try to maximise a generic benefit ('utility') by selecting purchases giving equal MU per unit of cost, from which are predicted the observed relationships between price changes and quantities of demanded consumer goods....