Journal of Econometrics最新文献

Finite- and large-sample inference for ranks using multinomial data with an application to ranking political parties 利用多项数据进行有限样本和大样本的排名推断，并应用于政党排名

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-13 DOI: 10.1016/j.jeconom.2025.106010

Sergei Bazylik , Magne Mogstad , Joseph P. Romano , Azeem M. Shaikh , Daniel Wilhelm

{"title":"Finite- and large-sample inference for ranks using multinomial data with an application to ranking political parties","authors":"Sergei Bazylik , Magne Mogstad , Joseph P. Romano , Azeem M. Shaikh , Daniel Wilhelm","doi":"10.1016/j.jeconom.2025.106010","DOIUrl":"10.1016/j.jeconom.2025.106010","url":null,"abstract":"<div><div>It is common to rank different categories by means of preferences that are revealed through data on choices. A prominent example is the ranking of political candidates or parties using the estimated share of support each one receives in surveys or polls about political attitudes. Since these rankings are computed using estimates of the share of support rather than the true share of support, there may be considerable uncertainty concerning the true ranking of the political candidates or parties. In this paper, we consider the problem of accounting for such uncertainty by constructing confidence sets for the rank of each category. We consider both the problem of constructing marginal confidence sets for the rank of a particular category as well as simultaneous confidence sets for the ranks of all categories. A distinguishing feature of our analysis is that we exploit the multinomial structure of the data to develop confidence sets that are valid in finite samples. We additionally develop confidence sets using the bootstrap that are valid only approximately in large samples. We use our methodology to rank political parties in Australia using data from the 2019 Australian Election Survey. We find that our finite-sample confidence sets are informative across the entire ranking of political parties, even in Australian territories with few survey respondents and/or with parties that are chosen by only a small share of the survey respondents. In contrast, the bootstrap-based confidence sets may sometimes be considerably less informative. These findings motivate us to compare these methods in an empirically-driven simulation study, in which we conclude that our finite-sample confidence sets often perform better than their large-sample, bootstrap-based counterparts, especially in settings that resemble our empirical application.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"250 ","pages":"Article 106010"},"PeriodicalIF":9.9,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic treatment effect estimation with interactive fixed effects and short panels 基于交互式固定效应和短面板的动态治疗效果估计

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-10 DOI: 10.1016/j.jeconom.2025.106013

Nicholas L. Brown , Kyle Butts

{"title":"Dynamic treatment effect estimation with interactive fixed effects and short panels","authors":"Nicholas L. Brown , Kyle Butts","doi":"10.1016/j.jeconom.2025.106013","DOIUrl":"10.1016/j.jeconom.2025.106013","url":null,"abstract":"<div><div>We study the estimation and inference of dynamic average treatment effect parameters when parallel trends holds conditional on interactive fixed effects and where units enter into treatment at different time periods. Our proposed generalized method of moments estimator consists of two parts: first, we estimate the unobserved time effects by applying the fixed-<span><math><mi>T</mi></math></span> consistent quasi-long-differencing estimator of Ahn et al., (2013) to the never-treated group. Second, we estimate the interactive fixed effects for treated groups post-treatment to recover their unobserved counterfactual outcomes then subtract this quantity from the observed outcomes and average over group membership to estimate the Average Treatment Effect on the Treated. We also demonstrate the robustness of two-way fixed effects to certain parallel trends violations and describe how to test for consistency. We investigate the effect of Walmart openings on local economic conditions and demonstrate that our methods ameliorate pre-trend violations commonly found in the literature. We also provide statistical software to implement our estimator in <span>Julia</span> and <span>R</span>.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"250 ","pages":"Article 106013"},"PeriodicalIF":9.9,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143927528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A simple and computationally trivial estimator for grouped fixed effects models 对于分组固定效应模型的一个简单且计算微不足道的估计器

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-09 DOI: 10.1016/j.jeconom.2025.106011

Martin Mugnier

引用次数: 0

Faster estimation of dynamic discrete choice models using index invertibility 基于指标可逆性的动态离散选择模型的快速估计

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-09 DOI: 10.1016/j.jeconom.2025.106004

Jackson Bunting , Takuya Ura

{"title":"Faster estimation of dynamic discrete choice models using index invertibility","authors":"Jackson Bunting , Takuya Ura","doi":"10.1016/j.jeconom.2025.106004","DOIUrl":"10.1016/j.jeconom.2025.106004","url":null,"abstract":"<div><div>Many estimators of dynamic discrete choice models with persistent unobserved heterogeneity have desirable statistical properties but are computationally intensive. In this paper we propose a method to quicken estimation for a broad class of dynamic discrete choice problems by exploiting semiparametric index restrictions. Specifically, we propose an estimator for models whose reduced form parameters are invertible functions of one or more linear indices (Ahn et al., 2018) , a property we term index invertibility. We establish that index invertibility implies a set of equality constraints on the model parameters. Our proposed estimator uses the equality constraints to decrease the dimension of the optimization problem, thereby generating computational gains. Our main result shows that the proposed estimator is asymptotically equivalent to the unconstrained, computationally heavy estimator. In addition, we provide a series of results on the number of independent index restrictions on the model parameters, providing theoretical guidance on the extent of computational gains. Finally, we demonstrate the advantages of our approach via Monte Carlo simulations.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"250 ","pages":"Article 106004"},"PeriodicalIF":9.9,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143923089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dimension-agnostic change point detection 与尺寸无关的变化点检测

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-08 DOI: 10.1016/j.jeconom.2025.106012

Hanjia Gao , Runmin Wang , Xiaofeng Shao

{"title":"Dimension-agnostic change point detection","authors":"Hanjia Gao , Runmin Wang , Xiaofeng Shao","doi":"10.1016/j.jeconom.2025.106012","DOIUrl":"10.1016/j.jeconom.2025.106012","url":null,"abstract":"<div><div>Change point testing for high-dimensional data has attracted a lot of attention in statistics, econometrics and machine learning owing to the emergence of high-dimensional data with structural breaks from many fields. In practice, when the dimension is less than the sample size but is not small, it is often unclear whether a method that is tailored to high-dimensional data or simply a classical method that is developed and justified for low-dimensional data is preferred. In addition, the methods designed for low-dimensional data may not work well in the high-dimensional environment and vice versa. In this paper, we propose a dimension-agnostic testing procedure targeting a single change point in the mean of a multivariate weakly dependent time series. Specifically, we can show that the limiting null distribution for our test statistic is the same regardless of the dimensionality and the magnitude of cross-sectional dependence. The power analysis is also conducted to understand the large sample behavior of the proposed test. Through Monte Carlo simulations and a real data illustration, we demonstrate that the finite sample results strongly corroborate the theory and suggest that the proposed test can be used as a benchmark for change-point detection of time series of low, medium, and high dimensions with complex cross-sectional and temporal dependence.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"250 ","pages":"Article 106012"},"PeriodicalIF":9.9,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143923088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pairwise valid instruments 成对有效的仪器

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-07 DOI: 10.1016/j.jeconom.2025.106009

Zhenting Sun , Kaspar Wüthrich

引用次数: 0

Inference on quantile processes with a finite number of clusters 有限集群数量的量化过程推理

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-01 DOI: 10.1016/j.jeconom.2024.105672

Andreas Hagemann

引用次数: 0

Semiparametric approach to estimation of marginal mean effects and marginal quantile effects 估计边际均值效应和边际分位数效应的半参数方法

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-01 DOI: 10.1016/j.jeconom.2023.05.002

Seong-ho Lee , Yanyuan Ma , Elvezio Ronchetti

引用次数: 0

Simultaneous estimation and group identification for network vector autoregressive model with heterogeneous nodes 异构节点网络向量自回归模型的同时估计与组识别

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-01 DOI: 10.1016/j.jeconom.2023.105564

Xuening Zhu , Ganggang Xu , Jianqing Fan

{"title":"Simultaneous estimation and group identification for network vector autoregressive model with heterogeneous nodes","authors":"Xuening Zhu , Ganggang Xu , Jianqing Fan","doi":"10.1016/j.jeconom.2023.105564","DOIUrl":"10.1016/j.jeconom.2023.105564","url":null,"abstract":"<div><div>Individuals or companies in a large social or financial network often display rather heterogeneous behaviors for various reasons. In this work, we propose a network vector autoregressive model with a latent group structure to model heterogeneous dynamic patterns observed from network nodes, for which group-wise network effects and time-invariant fixed-effects can be naturally incorporated. In our framework, the model parameters and network node memberships can be simultaneously estimated by minimizing a least-squares type objective function. In particular, our theoretical investigation allows the number of latent groups <span><math><mi>G</mi></math></span> to be over-specified when achieving the estimation consistency of the model parameters and group memberships, which significantly improves the robustness of the proposed approach. When <span><math><mi>G</mi></math></span> is correctly specified, valid statistical inference can be made for model parameters based on the asymptotic normality of the estimators. A data-driven criterion is developed to consistently identify the true group number for practical use. Extensive simulation studies and two real data examples are used to demonstrate the effectiveness of the proposed methodology.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"249 ","pages":"Article 105564"},"PeriodicalIF":9.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135455296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiway empirical likelihood 多元经验似然

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-01 DOI: 10.1016/j.jeconom.2024.105861

Harold D. Chiang , Yukitoshi Matsushita , Taisuke Otsu

引用次数: 0