Econometric Reviews

Econometric Reviews publishes original research articles in both econometric theory and its applications. Edited by @YuyaSasaki12 Published by @tandfSTEM

[Econometric Reviews @MetricReviews]

Guangjie Li and Roberto Leon-Gonzalez propose a novel method for reducing the bias of the maximum likelihood estimator in the presence of nuisance parameters. https://t.co/r51ndImjrJ

[Econometric Reviews @MetricReviews]

Andrés Ramírez–Hassan & Tatiana Caly-Amador propose a novel Bayesian inferential framework for a multi-outcome, endogenous three-stage model that jointly accounts for intensive margin, selection into participation extensive margin, and access restrictions. https://t.co/XDqaMM0sl9

[Econometric Reviews @MetricReviews]

In this article, Zihan Zhang, Lianyan Fu, and Dehui Wang propose a novel causal inference method for high-dimensional settings in which the parallel trends assumption is violated. https://t.co/dJw9ycfsnE

[Econometric Reviews @MetricReviews]

Jonas Meier introduces a multivariate distributional regression framework for dependence and counterfactual analysis, and applies it to study how spousal labor supply responds to the receipt of disability insurance benefits. https://t.co/Sbivp6nxEw

[Econometric Reviews @MetricReviews]

Mohamed Doukali, Taoufik Bouezmarni, & Karim Oualkacha propose a novel copula-based expectile regression approach and find that the intercorrelation among financial time series plays a more important role in improving prediction accuracy for stock returns. https://t.co/A1rpwz8lhk

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Using the BEGE model, Sulkhan Chavleishvili uncovers pronounced time-varying covariances in both bad and good environments across North American and European equity markets, pointing to the presence of a common underlying risk factor. https://t.co/mvweSYenEb

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In causal inference with choice-based samples, Kentaro Akashi and Tetsushi Horie show that the average treatment effect can be consistently estimated using only biased subsamples, without requiring any external information about the original population. https://t.co/kly63IwOQN

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Xinglei Deng and Junjian Zhang propose using the Box–Cox transformation to model nonlinear sample selection. Applying this method, they document a notable gender wage disparity in the labor market. https://t.co/OPomnozhLX

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Xiaojun Song & Zhenting Sun propose a general framework for inference on general notions of almost dominance (almost Lorenz dominance, almost inverse stochastic dominance, and almost stochastic dominance), and analyze the inequality growth in the U.K. https://t.co/fh4YSEUG1n

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Liheng Lei, Xuhui Wang, Zaichao Du, and Xin Zhou propose an easy-to-implement and robust approach to modeling and backtesting systematic risk measures. https://t.co/uY9V767FIA

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Zongwu Cai, Meng Shi, Wuqing Wu, and Yue Zhao propose a novel panel quantile regression model with correlated random effects, developing its estimation procedure and large-sample theory, and apply it to test the pecking order theory among U.S. firms. https://t.co/pzrou0qPKU

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Jen-Che Liao, Xiaojun Song, and Hung-Jen Wang propose a novel testing procedure to identify the determinants of inefficiency in a semiparametric stochastic frontier model. They apply the method to analyze Taiwanese manufacturing and Indian rice production. https://t.co/UbYpTqnJhR

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Xin Miao, Fang Fang, Xuening Zhu, and Hansheng Wang develop model selection and averaging methods for multivariate spatial autoregressive models, applying them to investigate the influence of social media posts. https://t.co/4vyTvjfRGY

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Liyao Li, Ke Miao, and Zhenlin Yang develop a novel estimation method for dynamic spatial panel models with interactive fixed effects. Using this approach, they uncover significant spillover effects in R&D investments. https://t.co/BjWLDIJ6DU

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Georg Keilbar, Juan M. Rodrigues-Poo, Alexandra Soberon, and Weining Wang (@WeiningWan19218) propose a novel and straightforward sieve-based method for estimation and bootstrap inference of panel regression parameters with interactive fixed effects. https://t.co/OGrpjxfAvZ

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Rubing Liang, Yitian Liu, Pengyue Sun, and Qiang Xia propose a novel method for estimating the number of factors in constrained approximate factor models and apply it to investigate the determinants of housing prices. https://t.co/9uV5nqpmSE

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Yanli Lin & Yichun Song develop a novel copula-based method that corrects endogeneity in spatial weights and other factors in spatial dynamic panels, without IVs or control variables. https://t.co/cXfHgI1Q8w

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Yundong Tu and Baiqing Wang develop novel econometric methods for large-dimensional approximate factor models with group structures. Their approach achieves improved convergence rates in theory and enhanced prediction accuracy in practice. https://t.co/JTzhnyJHei

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T. Oka, S. Yasui (@housecat442), Y. Hayakawa (@qiringji), & U. Byambadalai (@undara21) propose a regression-adjustment method for distributional treatment effects in randomized experiments, with applications to environmental and health policy evaluations. https://t.co/z5hznvwM9F

[Econometric Reviews @MetricReviews]

Takamitsu Kurita and Mototsugu Shintani propose a novel method for testing cointegrating relations in VAR models with smooth nonlinear trends. https://t.co/s05TmPWLBS