Will Artificial Intelligence Replace Computational Economists Any Time Soon?

Serguei Maliar and Pablo Winant

No 14024, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: Artificial intelligence (AI) has impressive applications in many fields (speech recognition, computer vision, etc.). This paper demonstrates that AI can be also used to analyze complex and high-dimensional dynamic economic models. We show how to convert three fundamental objects of economic dynamics -- lifetime reward, Bellman equation and Euler equation -- into objective functions suitable for deep learning (DL). We introduce all-in-one integration technique that makes the stochastic gradient unbiased for the constructed objective functions. We show how to use neural networks to deal with multicollinearity and perform model reduction in Krusell and Smith's (1998) model in which decision functions depend on thousands of state variables -- we literally feed distributions into neural networks! In our examples, the DL method was reliable, accurate and linearly scalable. Our ubiquitous Python code, built with Dolo and Google TensorFlow platforms, is designed to accommodate a variety of models and applications.

Keywords: Artificial intelligence; Machine learning; Deep learning; Neural network; Stochastic gradient; Dynamic models; Dynamic programming; Bellman equation; Euler equation; Value function (search for similar items in EconPapers)
Date: 2019-09
New Economics Papers: this item is included in nep-big, nep-cmp, nep-dge, nep-ore and nep-pay
References: View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
https://cepr.org/publications/DP14024 (application/pdf)
CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:14024

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP14024

Access Statistics for this paper

More papers in CEPR Discussion Papers from C.E.P.R. Discussion Papers Centre for Economic Policy Research, 33 Great Sutton Street, London EC1V 0DX.
Bibliographic data for series maintained by ().