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Demand estimation using managerial responses to automated price recommendations

García, Daniel; Tolvanen, Juha; Wagner, Alexander K. - 2021

We provide a new framework to identify demand elasticities in markets where managers rely on algorithmic … identify demand elasticities across hotel room types and over time. We confirm these elasticity estimates with a difference …-function approach to two classic questions in the dynamic pricing literature: the evolution of price elasticity of demand over time as …

Persistent link: https://www.econbiz.de/10012534709

Machine predictions and human decisions with variation in payoffs and skill

Ribers, Michael; Ullrich, Hannes - 2020

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...

Persistent link: https://www.econbiz.de/10012315943

News media vs. FRED-MD for macroeconomic forecasting

Ellingsen, Jon; Larsen, Vegard Høghaug; Thorsrud, Leif … - 2020

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP,...

Persistent link: https://www.econbiz.de/10012304069

Boosting tax revenues with mixed-frequency data in the aftermath of Covid-19 : the case of New York

Lahiri, Kajal; Cheng, Yang - 2021

We forecast New York state tax revenues with a mixed-frequency model using a number of machine learning techniques. We …

Persistent link: https://www.econbiz.de/10012649777

Redrawing of a housing market : insurance payouts and housing market recovery in the wake of the Christchurch earthquake of 2011

Nguyen, Cuong; Noy, Ilan; Sommervoll, Dag Einar; Yao, Fang - 2020

On the 22nd of February 2011, much of the residential housing stock in the city of Christchurch, New Zealand, was damaged by an unusually destructive earthquake. Almost all of the houses were insured. We ask whether insurance was able to mitigate the damage adequately, or whether the damage from...

Persistent link: https://www.econbiz.de/10012288010

Uncertainty and monetary policy during extreme events

Pellegrino, Giovanni; Castelnuovo, Efrem; Caggiano, Giovanni - 2020

How damaging are uncertainty shocks during extreme events such as the great recession and the Covid-19 outbreak? Can monetary policy limit output losses in such situations? We use a nonlinear VAR framework to document the large response of real activity to a financial uncertainty shock during...

Persistent link: https://www.econbiz.de/10012288020

Battling antibiotic resistance : can machine learning improve prescribing?

Ribers, Michael Allan; Ullrich, Hannes - 2019

Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and microbiological laboratory data from Denmark to predict...

Persistent link: https://www.econbiz.de/10012022285

Nowcasting German GDP with text data

Okuneva, Mariia; Hauber, Philipp; Carstensen, Kai; … - 2024

This paper investigates the impact of news media information on improving short-term GDP growth forecasts by analyzing a large and unique corpus of 12.4 million news articles spanning from 1991 to 2018. We extract business cycle-related sentiment from each article using an annotated dataset from...

Persistent link: https://www.econbiz.de/10015178446

The perks and perils of machine learning in business and economic research

Dudda, Tom L.; Hornuf, Lars - 2025

We examine predictive machine learning studies from 50 top business and economic journals published between 2010 and 2023. We investigate their transparency regarding the predictive performance of machine learning models compared to less complex traditional statistical models that require fewer...

Persistent link: https://www.econbiz.de/10015326239

Who is AI replacing? : the impact of generative AI on online freelancing platforms

Demirci, Ozge; Hannane, Jonas; Zhu, Xinrong - 2024

This paper studies the impact of Generative AI technologies on the demand for online freelancers using a large dataset … Google Trends to show that the more pronounced decline in the demand for freelancers within automation-prone jobs correlates …

Persistent link: https://www.econbiz.de/10015048322