Journal of Econometrics最新文献

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Why are replication rates so low? 为什么复制率如此之低？

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-10-01 DOI: 10.1016/j.jeconom.2024.105868

Patrick Vu

Many explanations have been offered for why replication rates are low in the social sciences, including selective publication,

p

-hacking, and treatment effect heterogeneity. This article emphasizes that issues with the most commonly used approach for setting sample sizes in replication studies may also play an important role. Theoretically, I show in a simple model of the publication process that we should expect the replication rate to fall below its nominal target, even when original studies are unbiased. The main mechanism is that the most commonly used approach for setting the replication sample size does not properly account for the fact that original effect sizes are estimated. Specifically, it sets the replication sample size to achieve a nominal power target under the assumption that estimated effect sizes correspond to fixed true effects. However, since there are non-linearities in the replication power function linking original effect sizes to power, ignoring the fact that effect sizes are estimated leads to systematically lower replication rates than intended. Empirically, I find that a parsimonious model accounting only for these issues can fully explain observed replication rates in experimental economics and social science, and two-thirds of the replication gap in psychology. I conclude with practical recommendations for replicators.

对于社会科学领域重复率低的原因，有很多解释，包括选择性发表、P-黑客和治疗效果异质性。本文强调，复制研究中最常用的样本量设定方法的问题可能也是一个重要原因。从理论上讲，我在一个简单的发表过程模型中表明，即使原始研究没有偏倚，我们也应该预期复制率会低于其名义目标。其主要机制在于，最常用的设定复制样本大小的方法并没有正确考虑原始效应大小是估计出来的这一事实。具体来说，这种方法是假设估计的效应大小与固定的真实效应相对应，从而设定复制样本量以达到名义功率目标。然而，由于复制功率函数中存在将原始效应大小与功率联系起来的非线性，忽略效应大小是估计出来的这一事实会导致系统复制率低于预期。根据经验，我发现一个只考虑这些问题的简约模型可以完全解释实验经济学和社会科学中观察到的复制率，以及心理学中三分之二的复制差距。最后，我为复制者提出了切实可行的建议。

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引用次数: 0

Polar amplification in a moist energy balance model: A structural econometric approach to estimation and testing 湿能量平衡模型中的极地放大效应：估算和检验的结构计量经济学方法

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-10-01 DOI: 10.1016/j.jeconom.2024.105885

William A. Brock , J. Isaac Miller

Poleward transport of atmospheric moisture and heat play major roles in the magnification of warming in poleward latitudes per degree of global warming, a phenomenon known as polar amplification (PA). We derive a time series econometric framework using a system of equations that have error-correction mechanisms restricted across equations to estimate and an identification strategy to recover the parameters of a moist energy balance model (MEBM) similar to those in the recent climate science literature. This framework enables the climate econometrician to estimate and forecast temperature rise in latitude belts as cumulative emissions continue to grow as well as account for effects of increases in atmospheric moisture suggested by the Clausius–Clapeyron equation, a driver of spatial non-uniformity in climate change. Non-uniformity is important for two reasons: climate change has unequal economic consequences that need to be better understood and amplification of temperatures in polar latitudes may trigger irreversible climate tipping points, which are disproportionately located in those regions.

大气湿度和热量的极地传输在极地纬度每升高一度全球变暖的放大过程中起着重要作用，这种现象被称为极地放大（PA）。我们推导了一个时间序列计量经济学框架，该框架使用了一个方程系统，该方程系统具有误差修正机制，可限制各方程的估算，并采用了一种识别策略来恢复湿能量平衡模型（MEBM）的参数，该模型与近期气候科学文献中的模型类似。这一框架使气候计量经济学家能够估算和预测纬度带的温度上升，因为累积排放量持续增长，并考虑到克劳修斯-克拉皮隆方程提出的大气湿度增加的影响，这是气候变化空间非均匀性的驱动因素。非均匀性之所以重要，有两个原因：气候变化会带来不平等的经济后果，需要更好地理解；极地纬度温度的放大可能会引发不可逆转的气候临界点，而这些地区的气候临界点不成比例。

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引用次数: 0

Inference in cluster randomized trials with matched pairs 配对分组随机试验中的推论

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-10-01 DOI: 10.1016/j.jeconom.2024.105873

Yuehao Bai , Jizhou Liu , Azeem M. Shaikh , Max Tabord-Meehan

This paper studies inference in cluster randomized trials where treatment status is determined according to a “matched pairs” design. Here, by a cluster randomized experiment, we mean one in which treatment is assigned at the level of the cluster; by a “matched pairs” design, we mean that a sample of clusters is paired according to baseline, cluster-level covariates and, within each pair, one cluster is selected at random for treatment. We study the large-sample behavior of a weighted difference-in-means estimator and derive two distinct sets of results depending on if the matching procedure does or does not match on cluster size. We then propose a single variance estimator which is consistent in either regime. Combining these results establishes the asymptotic exactness of tests based on these estimators. Next, we consider the properties of two common testing procedures based on

t

-tests constructed from linear regressions, and argue that both are generally conservative in our framework. We additionally study the behavior of a randomization test which permutes the treatment status for clusters within pairs, and establish its finite-sample and asymptotic validity for testing specific null hypotheses. Finally, we propose a covariate-adjusted estimator which adjusts for additional baseline covariates not used for treatment assignment, and establish conditions under which such an estimator leads to strict improvements in precision. A simulation study confirms the practical relevance of our theoretical results.

本文研究了按照 "配对 "设计确定治疗状态的分组随机试验中的推论。这里所说的分组随机试验，是指在分组水平上分配治疗的试验；这里所说的 "配对 "设计，是指根据基线、分组水平协变量将分组样本配对，并在每对样本中随机选择一个分组进行治疗。我们研究了加权均值差估计器的大样本行为，并得出了两组截然不同的结果，这取决于匹配程序是否与群组规模相匹配。然后，我们提出了一个在两种情况下都一致的单一方差估计器。将这些结果结合起来，就能确定基于这些估计器的检验的渐近精确性。接下来，我们考虑了基于线性回归构建的 t 检验的两种常见检验程序的特性，并认为这两种检验程序在我们的框架中一般都是保守的。此外，我们还研究了一种随机化检验的行为，这种检验会对成对集群的处理状态进行置换，并确定其在检验特定零假设时的有限样本有效性和渐近有效性。最后，我们提出了一种协变量调整估计器，该估计器可对未用于治疗分配的额外基线协变量进行调整，并确定了这种估计器可严格提高精确度的条件。一项模拟研究证实了我们理论结果的实用性。

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引用次数: 0

Testing for strong exogeneity in Proxy-VARs 检验 Proxy-VARs 中的强外生性

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-10-01 DOI: 10.1016/j.jeconom.2024.105876

Martin Bruns , Sascha A. Keweloh

Proxy variables have gained widespread prominence as indispensable tools for identifying structural VAR models. Analogous to instrumental variables, proxies need to be exogenous, i.e. uncorrelated with all non-target shocks. Assessing the exogeneity of proxies has traditionally relied on economic arguments rather than statistical tests. We argue that the economic rationale underlying the construction of commonly used proxy variables aligns with a stronger form of exogeneity. Specifically, proxies are typically constructed as variables not containing any information on the expected value of non-target shocks. We show conditions under which this enhanced concept of proxy exogeneity is testable without additional identifying assumptions.

代理变量作为确定结构性 VAR 模型不可或缺的工具，已得到广泛重视。与工具变量类似，代理变量必须是外生的，即与所有非目标冲击无关。评估代理变量的外生性历来依赖于经济学论据而非统计检验。我们认为，构建常用替代变量的经济学原理与更强的外生性形式是一致的。具体来说，代理变量通常是作为不包含任何非目标冲击预期值信息的变量构建的。我们展示了无需额外识别假设即可检验这种增强的代理外生性概念的条件。

引用次数: 0

Varying-coefficient spatial dynamic panel data models with fixed effects: Theory and application 具有固定效应的可变系数空间动态面板数据模型：理论与应用

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-10-01 DOI: 10.1016/j.jeconom.2024.105883

Han Hong , Gaosheng Ju , Qi Li , Karen X. Yan

This paper considers a varying-coefficient spatial dynamic panel data model with fixed effects. We show that a two-point approximation method poses a potential weak identification problem. We propose a robust modified estimator to address this issue. Our two-step estimation procedure incorporates both linear and quadratic moment conditions. We also extend our analysis to a partially linear varying-coefficient model and develop a consistent test for this specification. We establish the asymptotic properties of the proposed estimators. Simulations indicate that our estimators and the test statistic perform well in finite samples. We apply the partially linear varying-coefficient model to study how the sales of liquor producers respond to those of neighboring competitors in China. We find spatial dependence among liquor producers and show that the spatial effects vary with competition intensity.

本文研究了一个具有固定效应的变化系数空间动态面板数据模型。我们的研究表明，两点近似法存在潜在的弱识别问题。我们提出了一个稳健的修正估计器来解决这个问题。我们的两步估计程序包含线性和二次矩条件。我们还将分析扩展到了部分线性变化系数模型，并开发了针对该模型的一致检验方法。我们建立了所提出的估计器的渐近特性。模拟表明，我们的估计值和检验统计量在有限样本中表现良好。我们运用部分线性变化系数模型研究了中国白酒生产商的销售额如何对周边竞争者的销售额做出反应。我们发现白酒生产商之间存在空间依赖性，并表明空间效应随竞争强度而变化。

引用次数: 0

Local projections vs. VARs: Lessons from thousands of DGPs 本地预测与 VAR：成千上万 DGP 的经验教训

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-09-01 DOI: 10.1016/j.jeconom.2024.105722

Dake Li , Mikkel Plagborg-Møller , Christian K. Wolf

We conduct a simulation study of Local Projection (LP) and Vector Autoregression (VAR) estimators of structural impulse responses across thousands of data generating processes, designed to mimic the properties of the universe of U.S. macroeconomic data. Our analysis considers various identification schemes and several variants of LP and VAR estimators, employing bias correction, shrinkage, or model averaging. A clear bias–variance trade-off emerges: LP estimators have lower bias than VAR estimators, but they also have substantially higher variance at intermediate and long horizons. Bias-corrected LP is the preferred method if and only if the researcher overwhelmingly prioritizes bias. For researchers who also care about precision, VAR methods are the most attractive—Bayesian VARs at short and long horizons, and least-squares VARs at intermediate and long horizons.

我们对数千个数据生成过程的结构脉冲响应的局部投影（LP）和向量自回归（VAR）估计器进行了模拟研究，旨在模拟美国宏观经济数据的整体特性。我们的分析考虑了各种识别方案以及 LP 和 VAR 估计器的几种变体，采用了偏差校正、收缩或模型平均等方法。在偏差与方差之间出现了明显的权衡：LP 估计器的偏差低于 VAR 估计器，但它们在中长期的方差也要大得多。只有当研究人员优先考虑偏差时，偏差校正 LP 才是首选方法。对于同时关注精确度的研究人员来说，VAR 方法最具吸引力--在短跨度和长跨度上采用贝叶斯 VAR 方法，在中跨度和长跨度上采用最小二乘 VAR 方法。

引用次数: 0

State-dependent local projections 取决于州的地方预测

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-09-01 DOI: 10.1016/j.jeconom.2024.105702

Sílvia Gonçalves , Ana María Herrera , Lutz Kilian , Elena Pesavento

Do state-dependent local projections asymptotically recover the population responses of macroeconomic aggregates to structural shocks? The answer to this question depends on how the state of the economy is determined and on the magnitude of the shocks. When the state is exogenous, the local projection estimator recovers the population response regardless of the shock size. When the state depends on macroeconomic shocks, as is common in empirical work, local projections only recover the conditional response to an infinitesimal shock, but not the responses to larger shocks of interest in many applications. Simulations suggest that impulse responses may be off by as much as 82 percent and fiscal multipliers by as much as 40 percent.

依赖于状态的局部预测是否能近似地恢复宏观经济总量对结构性冲击的人口响应？这个问题的答案取决于经济状态是如何确定的以及冲击的大小。如果状态是外生的，那么无论冲击大小如何，局部预测估算器都能恢复人口响应。当经济状态取决于宏观经济冲击时（这在实证研究中很常见），局部预测只能恢复对无限小冲击的条件响应，而不能恢复对较大冲击的响应，这在许多应用中都很重要。模拟结果表明，脉冲响应的偏差可能高达 82%，财政乘数的偏差可能高达 40%。

引用次数: 0

Local projections in unstable environments 不稳定环境中的局部投影

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-09-01 DOI: 10.1016/j.jeconom.2024.105726

Atsushi Inoue , Barbara Rossi , Yiru Wang

This paper develops a local projection estimator for estimating impulse responses in the presence of time variation. Importantly, we allow local instabilities in both slope coefficients and variances. Monte Carlo simulations illustrate that the method performs well in practice. Using our proposed estimator, we shed new light on the effects of fiscal policy shocks and the size of government spending multipliers. Our analysis uncovers the existence of instabilities that were unaccounted for in previous studies, and links time variation in the multipliers to the size of government debt.

本文开发了一种局部投影估计器，用于估计存在时间变化的脉冲响应。重要的是，我们允许斜率系数和方差都存在局部不稳定性。蒙特卡罗模拟表明，该方法在实践中表现良好。利用我们提出的估计方法，我们对财政政策冲击的影响和政府支出乘数的大小有了新的认识。我们的分析揭示了以往研究中没有考虑到的不稳定性的存在，并将乘数的时间变化与政府债务规模联系起来。

引用次数: 0

Functional quantile autoregression 功能量子自回归

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-09-01 DOI: 10.1016/j.jeconom.2024.105765

Chaohua Dong , Rong Chen , Zhijie Xiao , Weiyi Liu

This paper proposes a new class of time series models, the functional quantile autoregression (FQAR) models, in which the conditional distribution of the observation at the current time point is affected by its past distributional information, and is expressed as a functional of the past conditional quantile functions. Different from the conventional functional time series models which are based on functionally observed data, the proposed FQAR method studies functional dynamics in traditional time series data. We propose a sieve estimator for the model. Asymptotic properties of the estimators are derived. Numerical investigations are conducted to highlight the proposed method.

本文提出了一类新的时间序列模型--函数量子自回归（FQAR）模型，其中观测值在当前时间点的条件分布受其过去分布信息的影响，并表示为过去条件量子函数的函数。与基于函数观测数据的传统函数时间序列模型不同，所提出的 FQAR 方法研究的是传统时间序列数据中的函数动态。我们提出了该模型的筛子估计器。得出了估计器的渐近特性。我们还进行了数值研究，以突出所提议的方法。

引用次数: 0

Reprint of: Out-of-sample tests for conditional quantile coverage: An application to Growth-at-Risk 重印本：条件量子覆盖的样本外测试：风险增长的应用

IF 9.9 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2024-09-01 DOI: 10.1016/j.jeconom.2024.105746

Valentina Corradi , Jack Fosten , Daniel Gutknecht

This paper proposes tests for out-of-sample comparisons of interval forecasts based on parametric conditional quantile models. The tests rank the distance between actual and nominal conditional coverage with respect to the set of conditioning variables from all models, for a given loss function. We propose a pairwise test to compare two models for a single predictive interval. The set-up is then extended to a comparison across multiple models and/or intervals. The limiting distribution varies depending on whether models are strictly non-nested or overlapping. In the latter case, degeneracy may occur. We establish the asymptotic validity of wild bootstrap based critical values across all cases. An empirical application to Growth-at-Risk (GaR) uncovers situations in which a richer set of financial indicators are found to outperform a commonly-used benchmark model when predicting downside risk to economic activity.

本文提出了基于参数条件量子模型的区间预测样本外比较检验。在给定的损失函数下，这些检验对所有模型的条件变量集的实际条件覆盖率与名义条件覆盖率之间的距离进行排序。我们提出了一种成对测试，用于比较单个预测区间的两个模型。然后，我们将这一设置扩展到多个模型和/或区间的比较。极限分布因模型是严格非嵌套还是重叠而异。在后一种情况下，可能会出现退化。我们在所有情况下都确定了基于野生自举法的临界值的渐近有效性。通过对风险增长（GaR）的实证应用，我们发现在预测经济活动下行风险时，一组更丰富的金融指标优于常用的基准模型。

引用次数: 0

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Journal of Econometrics

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