The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, and machine learning methods, are decidedly within the range of the Journal's interests. The Annals of Econometrics is a supplement to the Journal of Econometrics. Each issue of the Annals is a collection of refereed papers on a topic proposed by the guest editor of the issue.

《計(jì)量經(jīng)濟(jì)學(xué)雜志》是重要的、高質(zhì)量的、新的理論和應(yīng)用計(jì)量學(xué)研究的出口。該期刊的范圍包括有關(guān)經(jīng)濟(jì)研究中遇到的識別、估計(jì)、測試、決策和預(yù)測問題的論文。經(jīng)典的貝葉斯統(tǒng)計(jì)和機(jī)器學(xué)習(xí)方法，無疑是在雜志的興趣范圍內(nèi)。《計(jì)量經(jīng)濟(jì)學(xué)年鑒》是《計(jì)量經(jīng)濟(jì)學(xué)雜志》的補(bǔ)充。《年鑒》的每一期都是關(guān)于該期客座編輯提出的主題的參考論文集。