Journal of Econometric Methods最新文献_第4页

Identification of Non-Equilibrium Beliefs in Games of Incomplete Information Using Experimental Data 利用实验数据识别不完全信息博弈中的非均衡信念

Journal of Econometric Methods Pub Date : 2020-03-27 DOI: 10.1515/jem-2019-0029

Victor Aguirregabiria, Erhao Xie

引用次数: 7

Entropy Balancing for Continuous Treatments 连续处理的熵平衡

Journal of Econometric Methods Pub Date : 2020-01-17 DOI: 10.25932/PUBLISHUP-47895

Stefan Tübbicke

{"title":"Entropy Balancing for Continuous Treatments","authors":"Stefan Tübbicke","doi":"10.25932/PUBLISHUP-47895","DOIUrl":"https://doi.org/10.25932/PUBLISHUP-47895","url":null,"abstract":"Abstract Interest in evaluating the effects of continuous treatments has been on the rise recently. To facilitate the estimation of causal effects in this setting, the present paper introduces entropy balancing for continuous treatments (EBCT) – an intuitive and user-friendly automated covariate balancing scheme – by extending the original entropy balancing methodology of Hainmueller, J. 2012. “Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies.” Political Analysis 20 (1): 25–46. In order to estimate balancing weights, the proposed approach solves a globally convex constrained optimization problem, allowing for computationally efficient software implementation. EBCT weights reliably eradicate Pearson correlations between covariates (and their transformations) and the continuous treatment variable. As uncorrelatedness may not be sufficient to guarantee consistent estimates of dose–response functions, EBCT also allows to render higher moments of the treatment variable uncorrelated with covariates to mitigate this issue. Empirical Monte-Carlo simulations suggest that treatment effect estimates using EBCT display favorable properties in terms of bias and root mean squared error, especially when balance on higher moments of the treatment variable is sought. These properties make EBCT an attractive method for the evaluation of continuous treatments. Software implementation is available for Stata and R.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"11 1","pages":"71 - 89"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44146659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Regression-Based Causal Analysis from the Potential Outcomes Perspective. 从潜在结果的角度进行基于回归的因果分析。

Journal of Econometric Methods Pub Date : 2020-01-01 Epub Date: 2019-06-20 DOI: 10.1515/jem-2018-0030

Joseph V Terza

{"title":"Regression-Based Causal Analysis from the Potential Outcomes Perspective.","authors":"Joseph V Terza","doi":"10.1515/jem-2018-0030","DOIUrl":"10.1515/jem-2018-0030","url":null,"abstract":"<p><p>Most empirical economic research is conducted with the goal of providing scientific evidence that will be informative in assessing causal relationships of interest based on relevant counterfactuals. The implementation of regression methods in this context is ubiquitous. With this as motivation, we detail a comprehensive regression-based potential outcomes framework for causal modeling, estimation and inference. This framework facilitates rigorous specification of the effect parameter of interest and makes clear the sense in which it is causally interpretable, when appropriately defined in a potential outcomes setting. It also serves to crystallize the conditions under which the effect parameter and the underlying regression parameters are identified. The consistent sample analog estimator of the effect parameter is discussed. Juxtaposing this framework with a stylized version of a commonly implemented and routinely applied modeling and estimation protocol reveals how the latter is deficient in recognizing, and fully accounting for, conditions required for identification of the relevant effect parameter and the causal interpretability of estimation results. In the context of an example, we demonstrate the conceptual advantages of this general potential outcomes framework for regression modeling by showing how it resolves fundamental shortcomings in the conventional approach to characterizing and remedying omitted variable bias.</p>","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7051001/pdf/nihms-1048487.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37697420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Measuring Benchmark Damages in Antitrust Litigation: Extensions and Practical Implications 衡量反垄断诉讼中的基准损害赔偿：延伸及其现实意义

Journal of Econometric Methods Pub Date : 2019-09-07 DOI: 10.1515/jem-2019-0010

Ai Deng

引用次数: 2

Instrumental Variables Estimation in Large Heterogeneous Panels with Multifactor Structure 具有多因素结构的大型异质面板的工具变量估计

Journal of Econometric Methods Pub Date : 2019-08-30 DOI: 10.1515/jem-2018-0003

G. Forchini, Bin Jiang, B. Peng

引用次数: 0

Level-Based Estimation of Dynamic Panel Models 基于水平的动态面板模型估计

Journal of Econometric Methods Pub Date : 2019-08-01 DOI: 10.1515/jem-2018-0015

Gabriel Montes-Rojas, W. Sosa-Escudero, Federico Zincenko

引用次数: 1

An Empirical Undergraduate Introduction to Estimating Consumer Preferences Using Ride Choices at Disneyland 利用迪士尼乐园游乐设施选择估算消费者偏好的大学生实证介绍

Journal of Econometric Methods Pub Date : 2019-06-14 DOI: 10.1515/JEM-2018-0026

J. Jonathan

引用次数: 0

Adjustments of Rao’s Score Test for Distributional and Local Parametric Misspecifications Rao分数测验对分布和局部参数不规范的调整

Journal of Econometric Methods Pub Date : 2019-04-17 DOI: 10.1515/jem-2017-0022

Anil K. Bera, Yannis Bilias, M. Yoon, Suleyman Taspinar, Osman Doğan

{"title":"Adjustments of Rao’s Score Test for Distributional and Local Parametric Misspecifications","authors":"Anil K. Bera, Yannis Bilias, M. Yoon, Suleyman Taspinar, Osman Doğan","doi":"10.1515/jem-2017-0022","DOIUrl":"https://doi.org/10.1515/jem-2017-0022","url":null,"abstract":"Abstract Rao’s (1948) seminal paper introduced a fundamental principle of testing based on the score function and the score test has local optimal properties. When the assumed model is misspecified, it is well known that Rao’s score (RS) test loses its optimality. A model could be misspecified in a variety of ways. In this paper, we consider two kinds: distributional and parametric. In the former case, the assumed probability density function differs from the data generating process. Kent (1982) and White (1982) analyzed this case and suggested a modified version of the RS test that involves adjustment of the variance. In the latter case, the dimension of the parameter space of the assumed model does not match with that of the true one. Using the distribution of the RS test under this situation, Bera and Yoon (1993) developed a modified RS test that is valid under the local parametric misspecification. This involves adjusting both the mean and variance of the standard RS test. This paper considers the joint presence of the distributional and parametric misspecifications and develops a modified RS test that is valid under both types of misspecification. Earlier modified tests under either type of misspecification can be obtained as the special cases of the proposed test. We provide three examples to illustrate the usefulness of the suggested test procedure. In a Monte Carlo study, we demonstrate that the modified test statistics have good finite sample properties.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2017-0022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45943182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Misspecified Discrete Choice Models and Huber-White Standard Errors 错误指定的离散选择模型和Huber-White标准误差

Journal of Econometric Methods Pub Date : 2019-01-28 DOI: 10.1515/JEM-2016-0002

G. Michael

引用次数: 1

Local Average and Quantile Treatment Effects Under Endogeneity: A Review 内生性条件下局部平均和分位数处理效果综述

Journal of Econometric Methods Pub Date : 2018-10-09 DOI: 10.1515/JEM-2017-0007

M. Huber, Kaspar Wüthrich

引用次数: 14