结构估算的对抗方法

IF 6.6 1区 经济学 Q1 ECONOMICS
Econometrica Pub Date : 2023-12-07 DOI:10.3982/ECTA18707
Tetsuya Kaji, Elena Manresa, Guillaume Pouliot
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引用次数: 0

摘要

我们为结构模型提出了一种新的基于模拟的估计方法--对抗估计。该估计方法是生成器(利用结构模型生成模拟观测数据)和判别器(对观测数据是否为模拟数据进行分类)之间最小问题的解决方案。判别器最大限度地提高分类的准确性,而生成器则最小化分类的准确性。我们的研究表明,在判别器足够丰富的情况下,对抗估计器在正确规范下能达到参数效率,在错误规范下能达到参数率。我们主张使用神经网络作为判别器,它可以利用自适应特性并达到快速收敛率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An Adversarial Approach to Structural Estimation

An Adversarial Approach to Structural Estimation

We propose a new simulation-based estimation method, adversarial estimation, for structural models. The estimator is formulated as the solution to a minimax problem between a generator (which generates simulated observations using the structural model) and a discriminator (which classifies whether an observation is simulated). The discriminator maximizes the accuracy of its classification while the generator minimizes it. We show that, with a sufficiently rich discriminator, the adversarial estimator attains parametric efficiency under correct specification and the parametric rate under misspecification. We advocate the use of a neural network as a discriminator that can exploit adaptivity properties and attain fast rates of convergence.

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来源期刊
Econometrica
Econometrica 社会科学-数学跨学科应用
CiteScore
11.00
自引率
3.30%
发文量
75
审稿时长
6-12 weeks
期刊介绍: Econometrica publishes original articles in all branches of economics - theoretical and empirical, abstract and applied, providing wide-ranging coverage across the subject area. It promotes studies that aim at the unification of the theoretical-quantitative and the empirical-quantitative approach to economic problems and that are penetrated by constructive and rigorous thinking. It explores a unique range of topics each year - from the frontier of theoretical developments in many new and important areas, to research on current and applied economic problems, to methodologically innovative, theoretical and applied studies in econometrics. Econometrica maintains a long tradition that submitted articles are refereed carefully and that detailed and thoughtful referee reports are provided to the author as an aid to scientific research, thus ensuring the high calibre of papers found in Econometrica. An international board of editors, together with the referees it has selected, has succeeded in substantially reducing editorial turnaround time, thereby encouraging submissions of the highest quality. We strongly encourage recent Ph. D. graduates to submit their work to Econometrica. Our policy is to take into account the fact that recent graduates are less experienced in the process of writing and submitting papers.
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