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Reliance on Science by Inventors : Hybrid Extraction of In-Text Patent-to-Article Citations

Marx, Matt; Fuegi, Aaron - 2022

We curate and characterize a complete set of citations from patents to scientific articles, including nearly 16 million from the full text of USPTO and EPO patents. Combining heuristics and machine learning, we achieve 25% higher performance than machine learning alone. At 99.4% accuracy,...

Persistent link: https://www.econbiz.de/10013291979

Machine Learning and Perceived Age Stereotypes in Job Ads : Evidence from an Experiment

Burn, Ian; Firoozi, Daniel; Ladd, Daniel; Neumark, David - 2022

similarity of job-ad language to ageist stereotypes identified by industrial psychologists. We then conduct an experiment to … evaluate whether this language is perceived as biased against older workers. We find that language classified by the machine … assigned to the language related to ageist stereotypes are larger when responses are incentivized by rewarding participants for …

Persistent link: https://www.econbiz.de/10014241733

Answering the Queen : Machine Learning and Financial Crises

Fouliard, Jeremy; Howell, Michael J; Rey, Hélène - 2022

Financial crises cause economic, social and political havoc. Macroprudential policies are gaining traction but are still severely under-researched compared to monetary and "fiscal policy. We use the general framework of sequential predictions, also called online machine learning, to forecast...

Persistent link: https://www.econbiz.de/10014243066

Machine Learning in Gravity Models : An Application to Agricultural Trade

Gopinath, Munisamy; Batarseh, Feras; Beckman, Jayson - 2022

Predicting agricultural trade patterns is critical to decision making in the public and private domains, especially in the current context of trade disputes among major economies. Focusing on seven major agricultural commodities with a long history of trade, this study employed data-driven and...

Persistent link: https://www.econbiz.de/10013297855

The Allocation of Decision Authority to Human and Artificial Intelligence

Athey, Susan; Bryan, Kevin; Gans, Joshua S. - 2021

The allocation of decision authority by a principal to either a human agent or an artificial intelligence (AI) is examined. The principal trades off an AI’s more aligned choice with the need to motivate the human agent to expend effort in learning choice payoffs. When agent effort is desired,...

Persistent link: https://www.econbiz.de/10013314331

Managing Intelligence : Skilled Experts and Ai in Markets for Complex Products

Gruber, Jonathan; Handel, Benjamin; Kina, Samuel; … - 2021

In numerous high stakes markets skilled experts play a key role in facilitating consumer choice of complex products. New artificial intelligence (AI) technologies are increasingly being used to augment expert decisions. We study the role of technology and expertise in the market for health...

Persistent link: https://www.econbiz.de/10013315315

Man vs. Machine Learning : The Term Structure of Earnings Expectations and Conditional Biases

van Binsbergen, Jules H.; Han, Xiao; Lopez-Lira, Alejandro - 2022

We introduce a real-time measure of conditional biases in firms' earnings forecasts. The measure is defined as the difference between analysts' expectations and a statistically optimal unbiased machine-learning benchmark. Analysts' conditional expectations are, on average, biased upwards, and...

Persistent link: https://www.econbiz.de/10013403894

Are We Approaching an Economic Singularity? Information Technology and the Future of Economic Growth

Nordhaus, William D. - 2015

What are the prospects for long-run economic growth? The present study looks at a recently launched hypothesis, which I label Singularity. The idea here is that rapid growth in computation and artificial intelligence will cross some boundary or Singularity after which economic growth will...

Persistent link: https://www.econbiz.de/10013015557

Spurious Regressions in Financial Economics?

Ferson, Wayne E. - 2010

Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of Yule (1926) and Granger and Newbold (1974). Data mining for predictor variables interacts with spurious regression bias. The...

Persistent link: https://www.econbiz.de/10012762990

Machine Learning for Solar Accessibility : Implications for Low-Income Solar Expansion and Profitability

Davuluri, Sruthi - 2019

The solar industry in the US typically uses a credit score such as the FICO score as an indicator of consumer utility payment performance and credit worthiness to approve customers for new solar installations. Using data on over 800,000 utility payment performance and over 5,000 demographic...

Persistent link: https://www.econbiz.de/10012862419