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Evidence of Decreasing Internet Entropy : The Lack of Redundancy in DNS Resolution by Major Websites and Services
Bates, Samantha - 2018
This paper analyzes the extent to which the Internet's global domain name resolution (DNS) system has preserved its distributed resilience given the rise of cloud-based hosting and infrastructure. We explore trends in the concentration of the DNS space since at least 2011. In addition, we...
Persistent link: https://www.econbiz.de/10012453397
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Sources of Entropy in Representative Agent Models
Backus, David - 2011
preferences, habits, and jumps. The metrics describe the pricing kernel's dispersion (the entropy of the title) and dynamics (time … dependence, a measure of how entropy varies over different time horizons). We show how each model generates entropy and time … approximations -- clarifies the mechanisms underlying these models. It also reveals, in some cases, tension between entropy, which …
Persistent link: https://www.econbiz.de/10012461438
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Behavioral Implications of Rational Inattention with Shannon Entropy
Caplin, Andrew - 2013
entropy cost functions that better match this feature of the data and that retain key simplifying features of the Shannon …
Persistent link: https://www.econbiz.de/10012459344
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Rationally Inattentive Behavior : Characterizing and Generalizing Shannon Entropy
Caplin, Andrew - 2017
We provide a full behavioral characterization of the standard Shannon model of rational inattention. The key axiom is "Invariance under Compression", which identifies this model as capturing an ideal form of attention-constrained choice. We introduce tractable generalizations that allow for many...
Persistent link: https://www.econbiz.de/10012455030
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Term Structures of Asset Prices and Returns
Backus, David - 2016
We explore the term structures of claims to a variety of cash flows, namely, U.S. government bonds (claims to dollars), foreign government bonds (claims to foreign currency), inflation-adjusted bonds (claims to the price index), and equity (claims to future equity indexes or dividends). The...
Persistent link: https://www.econbiz.de/10012456513
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The economics of artificial intelligence : an agenda
Agrawal, Ajay (ed.); Gans, Joshua (ed.); Goldfarb, Avi (ed.) - NBER Conference on the Economics of Artificial …; … - 2019
Persistent link: https://www.econbiz.de/10011904305
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Refining Public Policies with Machine Learning : The Case of Tax Auditing
Battaglini, Marco; Guiso, Luigi; Lacava, Chiara; … - National Bureau of Economic Research - 2022
We study the extent to which ML techniques can be used to improve tax auditing efficiency using administrative data, without the need of randomized audits. Using Italy's population data on sole proprietorship tax returns, audits and their outcome, we develop a new approach to address the so...
Persistent link: https://www.econbiz.de/10013477269
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Estimating the Impact of the Age of Criminal Majority : Decomposing Multiple Treatments in a Regression Discontinuity Framework
Mueller-Smith, Michael; Pyle, Benjamin; Walker, Caroline - National Bureau of Economic Research - 2023
This paper studies the impact of adult prosecution on recidivism and employment trajectories for adolescent, first-time felony defendants. We use extensive linked Criminal Justice Admin- istrative Record System and socio-economic data from Wayne County, Michigan (Detroit). Using the discrete age...
Persistent link: https://www.econbiz.de/10014337757
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Artificial Intelligence and Scientific Discovery : A Model of Prioritized Search
Agrawal, Ajay; McHale, John; Oettl, Alexander - National Bureau of Economic Research - 2023
We model a key step in the innovation process, hypothesis generation, as the making of predictions over a vast combinatorial space. Traditionally, scientists and innovators use theory or intuition to guide their search. Increasingly, however, they use artificial intelligence (AI) instead. We...
Persistent link: https://www.econbiz.de/10014337792
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Machine Forecast Disagreement
Bali, Turan G.; Kelly, Bryan T.; Mörke, Mathis; … - National Bureau of Economic Research - 2023
We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...
Persistent link: https://www.econbiz.de/10014337816