Journal of Econometrics最新文献_第7页

Covariate adjustment in experiments with matched pairs 配对实验中的协变量调整

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105740

Yuehao Bai , Liang Jiang , Joseph P. Romano , Azeem M. Shaikh , Yichong Zhang

{"title":"Covariate adjustment in experiments with matched pairs","authors":"Yuehao Bai , Liang Jiang , Joseph P. Romano , Azeem M. Shaikh , Yichong Zhang","doi":"10.1016/j.jeconom.2024.105740","DOIUrl":"https://doi.org/10.1016/j.jeconom.2024.105740","url":null,"abstract":"<div><p>This paper studies inference for the average treatment effect (ATE) in experiments in which treatment status is determined according to “matched pairs” and it is additionally desired to adjust for observed, baseline covariates to gain further precision. By a “matched pairs” design, we mean that units are sampled i.i.d. from the population of interest, paired according to observed, baseline covariates, and finally, within each pair, one unit is selected at random for treatment. Importantly, we presume that not all observed, baseline covariates are used in determining treatment assignment. We study a broad class of estimators based on a “doubly robust” moment condition that permits us to study estimators with both finite-dimensional and high-dimensional forms of covariate adjustment. We find that estimators with finite-dimensional, linear adjustments need not lead to improvements in precision relative to the unadjusted difference-in-means estimator. This phenomenon persists even if the adjustments interact with treatment; in fact, doing so leads to no changes in precision. However, gains in precision can be ensured by including fixed effects for each of the pairs. Indeed, we show that this adjustment leads to the minimum asymptotic variance of the corresponding ATE estimator among all finite-dimensional, linear adjustments. We additionally study an estimator with a regularized adjustment, which can accommodate high-dimensional covariates. We show that this estimator leads to improvements in precision relative to the unadjusted difference-in-means estimator and also provides conditions under which it leads to the “optimal” nonparametric, covariate adjustment. A simulation study confirms the practical relevance of our theoretical analysis, and the methods are employed to reanalyze data from an experiment using a “matched pairs” design to study the effect of macroinsurance on microenterprise.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"241 1","pages":"Article 105740"},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140621415","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

Parametric risk-neutral density estimation via finite lognormal-Weibull mixtures 通过有限对数正态-威布尔混合物进行参数风险中性密度估计

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105748

Yifan Li , Ingmar Nolte , Manh Cuong Pham

{"title":"Parametric risk-neutral density estimation via finite lognormal-Weibull mixtures","authors":"Yifan Li , Ingmar Nolte , Manh Cuong Pham","doi":"10.1016/j.jeconom.2024.105748","DOIUrl":"https://doi.org/10.1016/j.jeconom.2024.105748","url":null,"abstract":"<div><p>This paper proposes a new parametric risk-neutral density (RND) estimator based on a finite lognormal-Weibull mixture (LWM) density. We establish the consistency and asymptotic normality of the LWM method in a general misspecified parametric framework. Based on the theoretical results, we propose a sequential test procedure to evaluate the goodness-of-fit of the LWM model, which leads to an adaptive choice for the number and type of mixture components. Our simulation results show that, in finite samples with various observation error specifications, the LWM method can approximate complex RNDs generated by state-of-the-art multi-factor stochastic volatility models with a few (typically less than 4) mixtures. Application of the LWM model on index options confirms its reliability in recovering empirical RNDs with a heavy left tail or bimodality, which can be incorrectly identified as bimodality or a heavy left tail by existing (semi)-nonparametric methods if the goodness-of-fit to the observed data is ignored.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"241 2","pages":"Article 105748"},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0304407624000940/pdfft?md5=f465fdac6f8ce04ea8c1db064b06c8cc&pid=1-s2.0-S0304407624000940-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140813191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust inference of panel data models with interactive fixed effects under long memory: A frequency domain approach 长记忆下具有交互固定效应的面板数据模型的稳健推断：频域方法

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105761

Shuyao Ke , Peter C.B. Phillips , Liangjun Su

{"title":"Robust inference of panel data models with interactive fixed effects under long memory: A frequency domain approach","authors":"Shuyao Ke , Peter C.B. Phillips , Liangjun Su","doi":"10.1016/j.jeconom.2024.105761","DOIUrl":"https://doi.org/10.1016/j.jeconom.2024.105761","url":null,"abstract":"<div><p>This paper studies a linear panel data model with interactive fixed effects wherein regressors, factors and idiosyncratic error terms are all stationary but with potential long memory. The setup involves a new formulation of panel data models, where weakly dependent regressors, factors and idiosyncratic errors are embedded as a special case. Standard methods based on principal component decomposition and least squares estimation, as in Bai (2009), are found to be biased and distorted in inference. To cope with this failure and to provide a simple implementable estimation procedure, a frequency domain least squares estimation is proposed. The limit distribution of the frequency domain estimator is established and a self-normalized approach to inference without the need for plug-in estimation of memory parameters is developed. Simulations show that the frequency domain estimator performs robustly under short memory and outperforms the time domain estimator when long range dependence is present. An empirical illustration is provided, examining the long-run relationship between stock returns and realized volatility.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"241 2","pages":"Article 105761"},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140818618","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

Estimation and inference of seller’s expected revenue in first-price auctions 第一价格拍卖中卖方预期收益的估计和推论

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105734

Federico Zincenko

引用次数: 0

Identifiability and estimation of possibly non-invertible SVARMA Models: The normalised canonical WHF parametrisation 可能不可逆 SVARMA 模型的可识别性和估计：归一化典范 WHF 参数化

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105766

Bernd Funovits

{"title":"Identifiability and estimation of possibly non-invertible SVARMA Models: The normalised canonical WHF parametrisation","authors":"Bernd Funovits","doi":"10.1016/j.jeconom.2024.105766","DOIUrl":"https://doi.org/10.1016/j.jeconom.2024.105766","url":null,"abstract":"<div><p>This article focuses on the parametrisation, identifiability, and (quasi-) maximum likelihood (QML) estimation of possibly non-invertible structural vector autoregressive moving average (SVARMA) models. SVAR models are routinely adopted due to their well-known implementation strategy. However, for various economic and statistical reasons, multivariate SVARMA settings are often more suitable. These settings introduce complexity in the analysis, primarily due to the presence of the moving average (MA) polynomial. We propose a novel representation of the MA polynomial matrix using the Wiener–Hopf factorization (WHF). A significant advantage of the WHF is its ability to handle possible non-invertibility and thus models with informational asymmetry between economic agents and outside observers. Since solutions of Dynamic Stochastic General Equilibrium (DSGE) models often involve this informational asymmetry, SVARMA models in WHF parametrisation can be considered data-driven alternatives to DSGE models and used for their evaluation. Furthermore, we provide low-level conditions for the asymptotic normality of the (Q)ML estimator and analytic expressions for the score and information matrix. As application, we estimate the Blanchard and Quah model, and compare our results and implied impulse response function with the ones in the SVAR model by Blanchard and Quah and a non-invertible SVARMA model by Gouriéroux and co-authors. Importantly, we have implemented this novel method in a well-documented R-package, making it readily accessible for researchers and practitioners.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"241 2","pages":"Article 105766"},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S030440762400112X/pdfft?md5=31d8eea116ae38418b22b6b324439bd8&pid=1-s2.0-S030440762400112X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141068097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid unadjusted Langevin methods for high-dimensional latent variable models 高维潜变量模型的混合非调整朗文方法

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105741

Rubén Loaiza-Maya , Didier Nibbering, Dan Zhu

引用次数: 0

Testing identification conditions of LATE in fuzzy regression discontinuity designs 测试模糊回归不连续设计中 LATE 的识别条件

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105738

Yu-Chin Hsu , Ji-Liang Shiu , Yuanyuan Wan

引用次数: 0

Dynamic partial correlation models 动态部分相关模型

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105747

Enzo D’Innocenzo , Andre Lucas

引用次数: 0

Extreme expectile estimation for short-tailed data 短尾数据的极值期望值估计

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105770

Abdelaati Daouia , Simone A. Padoan , Gilles Stupfler

{"title":"Extreme expectile estimation for short-tailed data","authors":"Abdelaati Daouia , Simone A. Padoan , Gilles Stupfler","doi":"10.1016/j.jeconom.2024.105770","DOIUrl":"https://doi.org/10.1016/j.jeconom.2024.105770","url":null,"abstract":"<div><p>The use of expectiles in risk management has recently gathered remarkable momentum due to their excellent axiomatic and probabilistic properties. In particular, the class of elicitable law-invariant coherent risk measures only consists of expectiles. While the theory of expectile estimation at central levels is substantial, tail estimation at extreme levels has so far only been considered when the tail of the underlying distribution is heavy. This article is the first work to handle the short-tailed setting where the loss (<em>e.g.</em> negative log-returns) distribution of interest is bounded to the right and the corresponding extreme value index is negative. This is motivated by the assessment of long-term market risk carried by low-frequency (<em>e.g.</em> weekly) returns of equities that show evidence of being generated from short-tailed distributions. We derive an asymptotic expansion of tail expectiles in this challenging context under a general second-order extreme value condition, which allows to come up with two semiparametric estimators of extreme expectiles, and with their asymptotic properties in a general model of strictly stationary but weakly dependent observations. We also extend the applicability of the proposed method to the regression setting. A simulation study and a real data analysis from a forecasting perspective are performed to compare the proposed competing estimation procedures.</p></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"241 2","pages":"Article 105770"},"PeriodicalIF":6.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141072886","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

Measuring tail risk 衡量尾端风险

IF 6.3 3区经济学

Journal of Econometrics Pub Date : 2024-04-01 DOI: 10.1016/j.jeconom.2024.105769

Maik Dierkes , Fabian Hollstein , Marcel Prokopczuk , Christoph Matthias Würsig

引用次数: 0