Narrow search
Showing 1 - 10 of 549
Cover Image
Merging Simulation and Projection Approaches to Solve High-Dimensional Problems
Judd, Kenneth L. - 2012
We introduce an algorithm for solving dynamic economic models that merges stochastic simulation and projection … approaches: we use simulation to approximate the ergodic measure of the solution, we construct a fixed grid covering the support … support of the ergodic measure roughly uniformly. The proposed algorithm is tractable in problems with high dimensionality …
Persistent link: https://www.econbiz.de/10012460159
Cover Image
Selecting Directors Using Machine Learning
Erel, Isil - 2018
Can an algorithm assist firms in their hiring decisions of corporate directors? This paper proposes a method of …
Persistent link: https://www.econbiz.de/10012453279
Cover Image
Polanyi's Paradox and the Shape of Employment Growth
Autor, David - 2014
In 1966, the philosopher Michael Polanyi observed, "We can know more than we can tell... The skill of a driver cannot be replaced by a thorough schooling in the theory of the motorcar; the knowledge I have of my own body differs altogether from the knowledge of its physiology." Polanyi's...
Persistent link: https://www.econbiz.de/10012458183
Cover Image
Are Software Automation and Teleworkers Substitutes? Preliminary Evidence from Japan
Baldwin, Richard E.; Okubo, Toshihiro - National Bureau of Economic Research - 2023
Digital technology is reshaping workplaces by enabling spatial separation of offices, known as telework, or remote intelligence (RI), and by facilitating automation of service sector tasks via artificial intelligence (AI). This paper is a first attempt to empirically investigate whether AI and...
Persistent link: https://www.econbiz.de/10014337859
Cover Image
Artificial Intelligence and Pricing : The Impact of Algorithm Design
Asker, John; Fershtman, Chaim; Pakes, Ariel - National Bureau of Economic Research - 2021
The behavior of artificial intelligences algorithms (AIAs) is shaped by how they learn about their environment. We compare the prices generated by AIAs that use different learning protocols when there is market interaction. Asynchronous learning occurs when the AIA only learns about the return...
Persistent link: https://www.econbiz.de/10012496088
Cover Image
Spooky Boundaries at a Distance : Inductive Bias, Dynamic Models, and Behavioral Macro
Kahou, Mahdi Ebrahimi; Fernández-Villaverde, Jesús; … - National Bureau of Economic Research - 2024
In the long run, we are all dead. Nonetheless, when studying the short-run dynamics of economic models, it is crucial to consider boundary conditions that govern long-run, forward-looking behavior, such as transversality conditions. We demonstrate that machine learning (ML) can automatically...
Persistent link: https://www.econbiz.de/10015056176
Cover Image
The Promise and Pitfalls of Conflict Prediction : Evidence from Colombia and Indonesia
Bazzi, Samuel - 2019
Policymakers can take actions to prevent local conflict before it begins, if such violence can be accurately predicted. We examine the two countries with the richest available sub-national data: Colombia and Indonesia. We assemble two decades of fine-grained violence data by type, alongside...
Persistent link: https://www.econbiz.de/10012479929
Cover Image
Machine Learning for Regularized Survey Forecast Combination : Partially-Egalitarian Lasso and its Derivatives
Diebold, Francis X. - 2018
Despite the clear success of forecast combination in many economic environments, several important issues remain incompletely resolved. The issues relate to selection of the set of forecasts to combine, and whether some form of additional regularization (e.g., shrinkage) is desirable. Against...
Persistent link: https://www.econbiz.de/10012480620
Cover Image
Answering the Queen : Machine Learning and Financial Crises
Fouliard, Jeremy - 2020
Financial crises cause economic, social and political havoc. Macroprudential policies are gaining traction but are still severely under-researched compared to monetary policy and fiscal policy. We use the general framework of sequential predictions also called online machine learning to forecast...
Persistent link: https://www.econbiz.de/10012482520
Cover Image
Demand Estimation with Machine Learning and Model Combination
Bajari, Patrick - 2015
We survey and apply several techniques from the statistical and computer science literature to the problem of demand estimation. We derive novel asymptotic properties for several of these models. To improve out-of-sample prediction accuracy and obtain parametric rates of convergence, we propose...
Persistent link: https://www.econbiz.de/10012457711