Journal of Econometrics最新文献

Asymptotic theory of the best-choice rerandomization using the Mahalanobis distance 利用马氏距离的最佳选择再随机化的渐近理论

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-06-25 DOI: 10.1016/j.jeconom.2025.106049

Yuhao Wang , Xinran Li

{"title":"Asymptotic theory of the best-choice rerandomization using the Mahalanobis distance","authors":"Yuhao Wang , Xinran Li","doi":"10.1016/j.jeconom.2025.106049","DOIUrl":"10.1016/j.jeconom.2025.106049","url":null,"abstract":"<div><div>Rerandomization, a design that utilizes pretreatment covariates and improves their balance between different treatment groups, has received attention recently in both theory and practice. From a survey by Bruhn and McKenzie (2009), there are at least two types of rerandomization that are used in practice: the first rerandomizes the treatment assignment until covariate imbalance is below a prespecified threshold; the second randomizes the treatment assignment multiple times and chooses the one with the best covariate balance. In this paper we will consider the second type of rerandomization, namely the best-choice rerandomization, whose theory and inference are still lacking in the literature. In particular, we will focus on the best-choice rerandomization that uses the Mahalanobis distance to measure covariate imbalance, which is one of the most commonly used imbalance measure for multivariate covariates and is invariant to affine transformations of covariates. We will study the large-sample repeatedly sampling properties of the best-choice rerandomization, allowing both the number of covariates and the number of tried complete randomizations to increase with the sample size. We show that the asymptotic distribution of the difference-in-means estimator is more concentrated around the true average treatment effect under rerandomization than under the complete randomization, and propose large-sample accurate confidence intervals for rerandomization that are shorter than that for the completely randomized experiment. We further demonstrate that, with moderate number of covariates and with the number of tried randomizations increasing polynomially with the sample size, the best-choice rerandomization can achieve the ideally optimal precision that one can expect even with perfectly balanced covariates. The developed theory and methods for rerandomization are also illustrated using real field experiments.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"251 ","pages":"Article 106049"},"PeriodicalIF":9.9,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144479985","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 robust residual-based test for structural changes in factor models 一个稳健的残差为基础的测试结构变化的因素模型

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-06-12 DOI: 10.1016/j.jeconom.2025.106042

Bin Peng , Liangjun Su , Yayi Yan

引用次数: 0

Multivariate stochastic volatility models based on generalized Fisher transformation 基于广义Fisher变换的多元随机波动模型

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-06-11 DOI: 10.1016/j.jeconom.2025.106041

Han Chen , Yijie Fei , Jun Yu

引用次数: 0

Time-varying vector error-correction models: Estimation and inference 时变矢量误差校正模型：估计与推断

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-06-05 DOI: 10.1016/j.jeconom.2025.106035

Jiti Gao , Bin Peng , Yayi Yan

引用次数: 0

Distribution regression with censored selection 带有删节选择的分布回归

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-06-03 DOI: 10.1016/j.jeconom.2025.106030

Songnian Chen , Nianqing Liu , Hanghui Zhang

{"title":"Distribution regression with censored selection","authors":"Songnian Chen , Nianqing Liu , Hanghui Zhang","doi":"10.1016/j.jeconom.2025.106030","DOIUrl":"10.1016/j.jeconom.2025.106030","url":null,"abstract":"<div><div>Chernozhukov, Fernández-Val, and Luo (2023, CFL (2023) hereafter) considered a distribution regression model subject to sample selection with a binary selection mechanism. In this paper, we show how to identify and estimate a semi-parametric distribution regression model subject to a censored selection rule. With censored selection, we do not need to impose the usual outcome exclusion restriction or exclusion of the level of the latent selection variable from the selection sorting function for model identification, unlike CFL (2023). We propose new semiparametric estimators and corresponding inference procedures for model parameters and related functional parameters. We apply our method to investigate wage inequality in the UK for the period 1978–2000 using the Family Expenditure Survey (FES) data. Our findings reveal that (i) the selection sorting exclusion and outcome exclusion restrictions imposed by CFL (2023) are rejected; (ii) there is negative selection into work at most quantile levels for females, but not for males; (iii) in contrast to CFL (2023), our selection sorting effect pattern does not offer clear evidence on assortative matching or glass ceiling in the UK labor market; (iv) the latent gender wage gaps after correcting for selection bias are about 25%–50% of CFL (2023)’s estimates, and are also significantly smaller than the observed wage gaps; (v) similar to CFL (2023), there exists some strong evidence on gender discrimination in the UK labor market.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"251 ","pages":"Article 106030"},"PeriodicalIF":9.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195267","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

Multilevel matrix factor model 多层矩阵因子模型

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-31 DOI: 10.1016/j.jeconom.2025.106033

Yuteng Zhang , Yongchang Hui , Junrong Song , Shurong Zheng

引用次数: 0

Realized candlestick wicks 实现烛台灯芯

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-27 DOI: 10.1016/j.jeconom.2025.106014

Yifan Li , Ingmar Nolte , Sandra Nolte , Shifan Yu

引用次数: 0

Inference for large dimensional factor models under general missing data patterns 一般缺失数据模式下大维度因子模型的推理

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-26 DOI: 10.1016/j.jeconom.2025.106022

Liangjun Su , Fa Wang

引用次数: 0

On changepoint detection in functional data using empirical energy distance 基于经验能量距离的函数数据变化点检测

IF 9.9 3区经济学

Journal of Econometrics Pub Date : 2025-05-23 DOI: 10.1016/j.jeconom.2025.106023

B. Cooper Boniece , Lajos Horváth , Lorenzo Trapani

{"title":"On changepoint detection in functional data using empirical energy distance","authors":"B. Cooper Boniece , Lajos Horváth , Lorenzo Trapani","doi":"10.1016/j.jeconom.2025.106023","DOIUrl":"10.1016/j.jeconom.2025.106023","url":null,"abstract":"<div><div>We propose a novel family of test statistics to detect the presence of changepoints in a sequence of dependent, possibly multivariate, functional-valued observations. Our approach allows to test for a very general class of changepoints, including the “classical” case of changes in the mean, and even changes in the whole distribution. Our statistics are based on a generalisation of the empirical energy distance; we propose weighted functionals of the energy distance process, which are designed in order to enhance the ability to detect breaks occurring at sample endpoints. The limiting distribution of the maximally selected version of our statistics requires only the computation of the eigenvalues of the covariance function, thus being readily implementable in the most commonly employed packages, e.g. <span>R</span>. We show that, under the alternative, our statistics are able to detect changepoints occurring even very close to the beginning/end of the sample. In the presence of multiple changepoints, we propose a binary segmentation algorithm to estimate the number of breaks and the locations thereof. Simulations show that our procedures work very well in finite samples. We complement our theory with applications to financial and temperature data.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"250 ","pages":"Article 106023"},"PeriodicalIF":9.9,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144124770","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

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