Econometrics Journal最新文献

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Accelerated failure time models with log-concave errors 具有对数凹误差的加速失效时间模型

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2020-05-01 DOI: 10.1093/ectj/utz024

Ruixuan Liu, Zhengfei Yu

We study accelerated failure time (AFT) models in which the survivor function of the additive error term is log-concave. The log-concavity assumption covers large families of commonly-used distributions and also represents the aging or wear-out phenomenon of the baseline duration. For right-censored failure time data, we construct semi-parametric maximum likelihood estimates of the finite dimensional parameter and establish the large sample properties. The shape restriction is incorporated via a nonparametric maximum likelihood estimator (NPMLE) of the hazard function. Our approach guarantees the uniqueness of a global solution for the estimating equations and delivers semiparametric efficient estimates. Simulation studies and empirical applications demonstrate the usefulness of our method.

我们研究了加速失效时间（AFT）模型，其中加性误差项的幸存函数是对数凹的。对数凹度假设涵盖了常用分布的大家族，也代表了基线持续时间的老化或磨损现象。对于右删失失效时间数据，我们构造了有限维参数的半参数最大似然估计，并建立了大样本性质。形状限制是通过危险函数的非参数最大似然估计量（NPMLE）合并的。我们的方法保证了估计方程全局解的唯一性，并提供了半参数有效估计。仿真研究和实证应用证明了我们方法的有效性。

引用次数: 2

Generalized Forecast Averaging in Autoregressions with a Near Unit Root 近单位根自回归的广义预测平均

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2020-04-01 DOI: 10.1093/ECTJ/UTAA006

Mohitosh Kejriwal, Xuewen Yu

This paper develops a new approach to forecasting a highly persistent time series that employs feasible generalized least squares (FGLS) estimation of the deterministic components in conjunction with Mallows model averaging.

本文提出了一种预测高度持续时间序列的新方法，该方法采用确定性分量的可行广义最小二乘(FGLS)估计与Mallows模型平均相结合。

引用次数: 1

Probabilistic forecasting of bubbles and flash crashes 泡沫和闪电崩盘的概率预测

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2020-02-14 DOI: 10.1093/ectj/utaa004

A. Banerjee, Guillaume Chevillon, M. Kratz

We propose a near explosive random coefficient autoregressive model (NERC) to obtain predictive probabilities of the apparition and devolution of bubbles. The distribution of the autoregressive coefficient of this model is allowed to be centred at an O(T−α) distance of unity, with α ∈ (0, 1). When the expectation of the autoregressive coefficient lies on the explosive side of unity, the NERC helps to model the temporary explosiveness of time series and obtain related predictive probabilities. We study the asymptotic properties of the NERC and provide a procedure for inference on the parameters. In empirical illustrations, we estimate predictive probabilities of bubbles or flash crashes in financial asset prices.

我们提出了一个近爆炸随机系数自回归模型（NERC）来获得气泡出现和转移的预测概率。允许该模型的自回归系数的分布以O（T-α）距离为中心，其中α∈（0，1）。当自回归系数的期望值位于单位的爆炸性一侧时，NERC有助于对时间序列的暂时爆炸性进行建模，并获得相关的预测概率。我们研究了NERC的渐近性质，并提供了一个参数推断程序。在实证说明中，我们估计了金融资产价格泡沫或闪电崩盘的预测概率。

引用次数: 5

Wild Bootstrap for Fuzzy Regression Discontinuity Designs: Obtaining Robust Bias-Corrected Confidence Intervals 模糊回归不连续性设计的Wild Bootstrap：获得稳健的偏差校正置信区间

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2020-01-25 DOI: 10.1093/ECTJ/UTAA002

Yang He, Otávio Bartalotti

This paper develops a novel wild bootstrap procedure to construct robust bias-corrected valid confidence intervals for fuzzy regression discontinuity designs, providing an intuitive complement to existing robust bias-corrected methods. The confidence intervals generated by this procedure are valid under conditions similar to the procedures proposed by Calonico et al. (2014) and related literature. Simulations provide evidence that this new method is at least as accurate as the plug-in analytical corrections when applied to a variety of data-generating processes featuring endogeneity and clustering. Finally, we demonstrate its empirical relevance by revisiting Angrist and Lavy (1999) analysis of class size on student outcomes.

本文提出了一种新的野自举方法来构造模糊回归不连续设计的鲁棒偏差校正有效置信区间，为现有的鲁棒偏差校正方法提供了一种直观的补充。该程序生成的置信区间在类似Calonico等(2014)及相关文献提出的程序的条件下是有效的。模拟证明，当应用于各种具有内生性和聚类特征的数据生成过程时，这种新方法至少与插入式分析修正一样准确。最后，我们通过回顾Angrist和Lavy(1999)对班级规模对学生成绩的分析来证明其实证相关性。

引用次数: 9

Erratum to: Semi-parametric analysis of efficiency and productivity using Gaussian processes 勘误表：使用高斯过程对效率和生产率进行半参数分析

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2019-11-07 DOI: 10.1093/ectj/utz021

G. Emvalomatis

引用次数: 0

Index to The Econometrics Journal Volume 21 《计量经济学杂志》第21卷索引

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2018-10-01 DOI: 10.1111/ectj.12119

引用次数: 0

Identification of treatment effects with selective participation in a randomized trial 随机试验中选择性参与的治疗效果鉴定

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2018-05-09 DOI: 10.1111/ectj.12114

Brendan Kline, Elie Tamer

Randomized trials (RTs) are used to learn about treatment effects. This paper studies identification of average treatment response (ATR) and average treatment effect (ATE) from RT data under various assumptions. The focus is the problem of external validity of the RT. RT data need not point identify the ATR or ATE because of selective participation in the RT. The paper reports partial-identification and point-identification results for the ATR and ATE based on RT data under a variety of assumptions. The results include assumptions sufficient to point identify the ATR or ATE from RT data. Under weaker assumptions, the ATR or ATE is partially identified. Further, attention is given to identification of the sign of the ATE and identification of whether participation in the RT is selective. Finally, identification from RT data is compared to identification from observational data.

随机试验（RT）用于了解治疗效果。本文研究了在各种假设下，从RT数据中识别平均治疗反应（ATR）和平均治疗效果（ATE）。重点是RT的外部有效性问题。由于RT的选择性参与，RT数据不需要对ATR或ATE进行点识别。本文报告了在各种假设下，基于RT数据对ATR和ATE的部分识别和点识别结果。结果包括足以从RT数据中点识别ATR或ATE的假设。在较弱的假设下，ATR或ATE被部分识别。此外，注意ATE的符号的识别和参与RT是否是选择性的识别。最后，将来自RT数据的识别与来自观测数据的识别进行比较。

引用次数: 2

Beyond plausibly exogenous 超越看似外源的

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2018-05-04 DOI: 10.1111/ectj.12113

Hans van Kippersluis, Cornelius A. Rietveld

We synthesize two recent advances in the literature on instrumental variable (IV) estimation that test and relax the exclusion restriction. Our approach first estimates the direct effect of the IV on the outcome in a subsample for which the IV does not affect the treatment variable. Subsequently, this estimate for the direct effect is used as input for the plausibly exogenous method developed by Conley, Hansen and Rossi. This two-step procedure provides a novel and informed sensitivity analysis for IV estimation. We illustrate the practical use by estimating the causal effect of (a) attending Catholic high school on schooling outcomes and (b) the number of children on female labour supply.

我们综合了文献中关于工具变量（IV）估计的两个最新进展，这两个进展检验并放宽了排除限制。我们的方法首先估计静脉注射对子样本结果的直接影响，而静脉注射不会影响治疗变量。随后，这种直接效应的估计被用作Conley、Hansen和Rossi开发的看似外生的方法的输入。这两步程序为IV估计提供了一种新颖且知情的灵敏度分析。我们通过估计（a）上天主教高中对学业成绩的因果影响和（b）儿童数量对女性劳动力供应的因果影响来说明实际用途。

引用次数: 62

Non-parametric Bayesian inference of strategies in repeated games 重复博弈策略的非参数贝叶斯推理

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2018-04-06 DOI: 10.1111/ectj.12112

Max Kleiman-Weiner, Joshua B. Tenenbaum, Penghui Zhou

Inferring underlying cooperative and competitive strategies from human behaviour in repeated games is important for accurately characterizing human behaviour and understanding how people reason strategically. Finite automata, a bounded model of computation, have been extensively used to compactly represent strategies for these games and are a standard tool in game theoretic analyses. However, inference over these strategies in repeated games is challenging since the number of possible strategies grows exponentially with the number of repetitions yet behavioural data are often sparse and noisy. As a result, previous approaches start by specifying a finite hypothesis space of automata that does not allow for flexibility. This limitation hinders the discovery of novel strategies that may be used by humans but are not anticipated a priori by current theory. Here we present a new probabilistic model for strategy inference in repeated games by exploiting non‐parametric Bayesian modelling. With simulated data, we show that the model is effective at inferring the true strategy rapidly and from limited data, which leads to accurate predictions of future behaviour. When applied to experimental data of human behaviour in a repeated prisoner's dilemma, we uncover strategies of varying complexity and diversity.

从重复游戏中的人类行为推断出潜在的合作和竞争策略，对于准确描述人类行为和理解人们如何进行战略推理非常重要。有限自动机是一种有界计算模型，已被广泛用于紧凑地表示这些博弈的策略，并且是博弈论分析的标准工具。然而，在重复游戏中对这些策略的推理是具有挑战性的，因为可能策略的数量随着重复次数呈指数级增长，但行为数据往往稀疏且嘈杂。因此，以前的方法从指定自动机的有限假设空间开始，这不允许灵活性。这种限制阻碍了人类可能使用但当前理论无法先验预期的新策略的发现。在这里，我们利用非参数贝叶斯模型，提出了一个新的概率模型，用于重复游戏中的策略推理。通过模拟数据，我们表明该模型能够有效地从有限的数据中快速推断出真正的策略，从而准确预测未来的行为。当应用于反复囚犯困境中人类行为的实验数据时，我们发现了不同复杂性和多样性的策略。

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引用次数: 1

Royal Economic Society Annual Conference 2016 Special Issue on Model Selection and Inference 英国皇家经济学会2016年年会模型选择与推理特刊

IF 1.9 4区经济学 Q2 Economics, Econometrics and Finance

Econometrics Journal

Pub Date : 2018-02-09 DOI: 10.1111/ectj.12098

Richard J. Smith

引用次数: 0

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